Độ biến động là gì? Các bài nghiên cứu khoa học liên quan

Giới thiệu

Độ biến động (volatility) là chỉ báo đo lường mức độ thay đổi về giá hoặc tỷ suất sinh lợi của tài sản tài chính trong một khoảng thời gian nhất định. Trong thị trường tài chính, biến động càng cao đồng nghĩa với rủi ro càng lớn do giá tài sản dao động mạnh, nhưng cũng tạo cơ hội lợi nhuận từ các biến động giá ngắn hạn. Trái lại, độ biến động thấp cho thấy giá ổn định hơn, thích hợp với danh mục bảo toàn vốn.

Trong kinh tế vĩ mô, biến động không chỉ xuất hiện ở thị trường cổ phiếu mà còn lan tỏa đến hàng hóa, trái phiếu, tỷ giá và lãi suất. Các sự kiện như khủng hoảng tài chính, thay đổi chính sách tiền tệ hoặc tin tức địa chính trị có thể kích hoạt làn sóng biến động mạnh mẽ. Theo CBOE, chỉ số VIX – được gọi là “chỉ số nỗi sợ hãi” – phản ánh biến động ngụ ý của hợp đồng quyền chọn chỉ số S&P 500, cho thấy kỳ vọng thị trường về dao động giá trong 30 ngày tới.

Trong khoa học dữ liệu và quản trị rủi ro, độ biến động còn là cơ sở để xây dựng mô hình dự báo, định giá quyền chọn và xác định giới hạn tổn thất (VaR, CVaR). Mô hình phân tích chuỗi thời gian như ARCH/GARCH tận dụng tính phân cụm của biến động để dự báo, giúp nhà đầu tư và quản lý danh mục đưa ra quyết định tối ưu. Các công cụ phần mềm tài chính hàng đầu như Bloomberg Terminal hay Reuters Eikon tích hợp phân tích biến động lịch sử và ngụ ý, cung cấp dữ liệu theo thời gian thực.

Định nghĩa độ biến động

Độ biến động (volatility) được định nghĩa là thước đo mức độ dao động của giá tài sản hoặc tỷ suất sinh lợi quanh một giá trị trung bình. Biến động phản ánh sự không chắc chắn về giá tương lai: dao động càng lớn thì biến động càng cao. Trong thực tế, biến động được hiểu theo hai khái niệm chính là biến động lịch sử và biến động ngụ ý.

Biến động lịch sử (historical volatility) được tính toán từ dữ liệu giá trong quá khứ bằng cách đo độ lệch chuẩn của tỷ suất sinh lợi trên một khoảng thời gian xác định, thường là 30, 60 hoặc 90 ngày. Phương pháp này dựa trên giả định rằng mô hình biến động trong quá khứ có thể phản ánh phần nào xu hướng trong tương lai, mặc dù không luôn đúng trong điều kiện thị trường thay đổi đột ngột.

Biến động ngụ ý (implied volatility) là biến động tiềm tàng mà thị trường kỳ vọng, được suy ngẫm từ giá hợp đồng quyền chọn thông qua công thức định giá Black–Scholes hoặc các mô hình tương tự. Khi giá quyền chọn tăng, biến động ngụ ý tăng, cho thấy nhà đầu tư đánh giá khả năng dao động giá trong tương lai cao hơn. CBOE VIX là thước đo biến động ngụ ý của S&P 500 options.

Công thức và chỉ số đo lường

Độ biến động lịch sử thường được tính bằng độ lệch chuẩn của tỷ suất sinh lợi. Giả sử có N ngày giao dịch và tỷ suất sinh lợi ngày i là ri, trung bình là \( \bar r \), độ lệch chuẩn σ được xác định:

$\sigma = \sqrt{\frac{1}{N-1} \sum_{i=1}^{N} (r_i - \bar r)^2}$

Phương sai (variance) là bình phương của độ lệch chuẩn, cho biết sự phân tán bình phương của tỷ suất sinh lợi quanh giá trị trung bình. Hệ số biến động (coefficient of variation, CV) là tỷ lệ giữa độ lệch chuẩn và giá trị trung bình, giúp so sánh độ biến động tương đối giữa các tài sản có mức sinh lợi khác nhau:

$\mathrm{CV} = \frac{\sigma}{\bar r}$

• Biến động hàng ngày: σdaily tính trên dữ liệu ngày giao dịch.
• Biến động hàng năm: σannual = σdaily × √252 (252 ngày giao dịch).
• Biến động hàng tháng: σmonthly = σdaily × √21 (21 ngày giao dịch).

Các loại biến động

Biến động lịch sử (historical volatility) sử dụng dữ liệu giá quá khứ. Mặc dù dễ tính toán và minh bạch, biến động lịch sử không phản ánh tâm lý thị trường hiện tại hay các yếu tố sự kiện sắp tới. Do đó, nó thường được kết hợp với biến động ngụ ý để phân tích toàn diện hơn.

Biến động ngụ ý (implied volatility) được tính từ giá hợp đồng quyền chọn. Nếu ký hiệu σimpl là biến động ngụ ý, giá quyền chọn C được định giá theo công thức Black–Scholes:

C = S_0 N(d_1) - K e^{-rT} N(d_2) \end{script> $d_{1,2} = \frac{\ln(S_0/K) + (r \pm \frac{1}{2}\sigma_{impl}^2)T}{\sigma_{impl}\sqrt{T}}</span></p><p>Biến động thực tế (realized volatility) đo lường biến động diễn ra thực sự trong tương lai, tính khi kỳ hạn quyền chọn kết thúc. Trong khi đó, biến động ước tính (model-implied volatility) là biến động được dự báo từ mô hình như GARCH.</p><figure class="table"><table><thead><tr><th>Loại biến động</th><th>Cơ sở dữ liệu</th><th>Ưu điểm</th><th>Nhược điểm</th></tr></thead><tbody><tr><td>Lịch sử</td><td>Giá quá khứ</td><td>Dễ tính, minh bạch</td><td>Không phản ánh kỳ vọng</td></tr><tr><td>Ngụ ý</td><td>Giá quyền chọn</td><td>Phản ánh tâm lý thị trường</td><td>Phụ thuộc mô hình định giá</td></tr><tr><td>Thực tế</td><td>Giá tương lai</td><td>Đo chính xác biến động đã xảy ra</td><td>Không dự báo trước được</td></tr><tr><td>Ước tính</td><td>Mô hình (GARCH,…)</td><td>Dự báo được</td><td>Phải chọn tham số, giả định</td></tr></tbody></table></figure><h2>Mô hình dự báo biến động</h2><p>Các mô hình ARCH (Autoregressive Conditional Heteroskedasticity) và GARCH (Generalized ARCH) là phương pháp phổ biến để mô phỏng và dự báo độ biến động theo chuỗi thời gian, được giới thiệu bởi Engle (1982) và Bollerslev (1986). Mô hình GARCH(p,q) mô tả phương sai điều kiện σt2 tại thời điểm t bằng tổ hợp của nhiễu bình phương và phương sai quá khứ:</p><p><span class="inline-equation"><span class="katex"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><msubsup><mi>σ</mi><mi>t</mi><mn>2</mn></msubsup><mo>=</mo><msub><mi>α</mi><mn>0</mn></msub><mo>+</mo><msubsup><mo>∑</mo><mrow><mi>i</mi><mo>=</mo><mn>1</mn></mrow><mi>p</mi></msubsup><msub><mi>α</mi><mi>i</mi></msub><msubsup><mi>ϵ</mi><mrow><mi>t</mi><mo>−</mo><mi>i</mi></mrow><mn>2</mn></msubsup><mo>+</mo><msubsup><mo>∑</mo><mrow><mi>j</mi><mo>=</mo><mn>1</mn></mrow><mi>q</mi></msubsup><msub><mi>β</mi><mi>j</mi></msub><msubsup><mi>σ</mi><mrow><mi>t</mi><mo>−</mo><mi>j</mi></mrow><mn>2</mn></msubsup></mrow><annotation encoding="application/x-tex">\sigma_t^2 = \alpha_0 + \sum_{i=1}^p \alpha_i \epsilon_{t-i}^2 + \sum_{j=1}^q \beta_j \sigma_{t-j}^2</annotation></semantics></math></span></span></p><p>Trong đó εt là nhiễu (residual) của tỷ suất sinh lợi, αi và βj là hệ số ước lượng. Mô hình EGARCH và GJR–GARCH mở rộng GARCH để bắt các hiệu ứng bất đối xứng (asymmetric leverage effect) khi biến động tăng mạnh hơn khi thị trường giảm (<a href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1234760">Bollerslev, 1986</a>).</p><p>Phương pháp EWMA (Exponentially Weighted Moving Average) đề xuất bởi RiskMetrics Group sử dụng hàm mũ suy giảm trọng số để ưu tiên dữ liệu gần nhất, tính biến động như sau:</p><p><span class="inline-equation"><span class="katex"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><msubsup><mi>σ</mi><mi>t</mi><mn>2</mn></msubsup><mo>=</mo><mi>λ</mi><msubsup><mi>σ</mi><mrow><mi>t</mi><mo>−</mo><mn>1</mn></mrow><mn>2</mn></msubsup><mo>+</mo><mo stretchy="false">(</mo><mn>1</mn><mo>−</mo><mi>λ</mi><mo stretchy="false">)</mo><msubsup><mi>r</mi><mrow><mi>t</mi><mo>−</mo><mn>1</mn></mrow><mn>2</mn></msubsup></mrow><annotation encoding="application/x-tex">\sigma_t^2 = \lambda \sigma_{t-1}^2 + (1 - \lambda) r_{t-1}^2</annotation></semantics></math></span></span></p><p>Trong đó λ (thường đặt ≈0.94) là hệ số suy giảm. EWMA đơn giản, dễ triển khai trong thực tế nhưng không bắt được tính phân cụm dài hạn của biến động như GARCH.</p><h2>Yếu tố ảnh hưởng đến độ biến động</h2><p>Tình trạng thị trường tài chính và kinh tế vĩ mô là nhân tố chủ đạo định hình biến động. Khủng hoảng tài chính như sự kiện “Thứ Sáu Đen” 1987 hay khủng hoảng tiền tệ châu Á 1997 đã tạo ra các đợt dao động giá dữ dội. Chính sách tiền tệ của Ngân hàng Trung ương (lãi suất, chương trình nới lỏng định lượng) cũng tác động mạnh đến kỳ vọng rủi ro và do đó độ biến động.</p><p>Sự kiện địa chính trị như xung đột, bầu cử hoặc thỏa thuận thương mại quốc tế có thể làm thay đổi kỳ vọng lợi nhuận và rủi ro nhanh chóng. Tin tức kinh tế – tài chính (lãi suất, GDP, CPI) công bố định kỳ thường gây “giật” biến động ngắn hạn khi kết quả lệch xa dự báo.</p><ul><li><strong>Tâm lý nhà đầu tư:</strong> hiệu ứng bầy đàn (herding) làm tăng biến động trong giai đoạn hoảng loạn.</li><li><strong>Đòn bẩy tài chính:</strong> sử dụng margin hoặc phái sinh khuếch đại dao động giá.</li><li><strong>Tính thanh khoản:</strong> thị trường kém thanh khoản thường biến động mạnh hơn cho cùng khối lượng giao dịch.</li></ul><h2>Hiện tượng phân cụm biến động</h2><p>Phân cụm biến động (volatility clustering) là đặc tính chuỗi thời gian cho thấy các giai đoạn biến động lớn thường kéo dài, theo sau bởi các giai đoạn biến động thấp. Hiện tượng này lý giải tại sao những thời điểm thị trường hỗn loạn có xu hướng duy trì độ biến động cao trong một khoảng thời gian nhất định.</p><p>Đặc tính này là cơ sở cho mô hình ARCH/GARCH, khi các hệ số α và β phản ánh tính phụ thuộc vào biến động quá khứ. Mô hình Harvey’s Heterogeneous Autoregressive Realized Volatility (HAR–RV) còn phân chia biến động thực tế theo nhiều khung thời gian (ngày, tuần, tháng) để nâng cao độ chính xác dự báo (<a href="https://www.sciencedirect.com/science/article/pii/S0304405X04001207">Corsi, 2004</a>).</p><h2>Ứng dụng trong quản trị rủi ro</h2><p>Biến động là thành phần mấu chốt trong đo lường VaR (Value at Risk) và CVaR (Conditional VaR), cho phép đánh giá tổn thất tối đa trong một khoảng thời gian xác định với mức độ tin cậy. VaR được tính theo biến động dự báo và phân phối lợi nhuận giả định:</p><p><span class="inline-equation"><span class="katex"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><msub><mrow><mi mathvariant="normal">V</mi><mi mathvariant="normal">a</mi><mi mathvariant="normal">R</mi></mrow><mi>α</mi></msub><mo>=</mo><mi>μ</mi><mo>+</mo><mi>σ</mi><msup><mi mathvariant="normal">Φ</mi><mrow><mo>−</mo><mn>1</mn></mrow></msup><mo stretchy="false">(</mo><mi>α</mi><mo stretchy="false">)</mo></mrow><annotation encoding="application/x-tex">\mathrm{VaR}_{\alpha} = \mu + \sigma \Phi^{-1}(\alpha)</annotation></semantics></math></span></span></p><p>Với μ là kỳ vọng lợi nhuận, σ biến động, Φ−1 hàm ngược phân phối chuẩn và α mức tin cậy. CVaR cung cấp giá trị kỳ vọng của tổn thất vượt quá VaR, đánh giá rủi ro ở phần đuôi phân phối (<a href="https://www.investopedia.com/terms/c/conditional_value_at_risk.asp">Investopedia</a>).</p><p>Hedging danh mục với công cụ phái sinh (futures, options) dựa trên biến động ước tính giúp giảm thiểu rủi ro thị trường. Chiến lược delta-hedging sử dụng biến động ngụ ý để điều chỉnh tỷ trọng quyền chọn – cơ sở, hạn chế rủi ro giá trong thời gian thực (<a href="https://www.investopedia.com/terms/d/deltahedging.asp">Investopedia</a>).</p><h2>Giám sát và công cụ phân tích</h2><p>Bloomberg Terminal và Refinitiv Eikon cung cấp chỉ số biến động lịch sử và ngụ ý thời gian thực, bản đồ nhiệt (heatmap) theo ngành, theo region và chức năng cảnh báo tự động khi biến động vượt ngưỡng cài đặt. Bộ công cụ này tích hợp mô-đun GARCH, EWMA và Monte Carlo simulation nhằm hỗ trợ phân tích sâu.</p><p>Các thư viện mã nguồn mở Python như “arch” (Kevin Sheppard) và “statsmodels” cho phép xây dựng mô hình GARCH, tính biến động lịch sử và phân cụm. Trong R, gói “rugarch” cung cấp giao diện trực quan để ước lượng đa dạng cấu hình GARCH và kiểm tra hiệu năng dự báo.</p><ul><li>Python “arch”: <a href="https://pypi.org/project/arch">https://pypi.org/project/arch</a></li><li>R “rugarch”: <a href="https://cran.r-project.org/web/packages/rugarch">https://cran.r-project.org/web/packages/rugarch</a></li><li>Bloomberg VIX: <a href="https://www.bloomberg.com/quote/VIX:IND">https://www.bloomberg.com/quote/VIX:IND</a></li></ul><h2>Tài liệu tham khảo</h2><ul><li>Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. <i>Econometrica</i>, 50(4), 987–1007.</li><li>Bollerslev, T. (1986). Generalized autoregressive conditional heteroscedasticity. <i>Journal of Econometrics</i>, 31(3), 307–327.</li><li>Corsi, F. (2004). A simple approximate long-memory model of realized volatility. <i>Journal of Financial Econometrics</i>, 2(1), 67–101.</li><li>RiskMetrics Group. (1996). Technical Document. JP Morgan.</li><li>Investopedia. “Conditional Value at Risk (CVaR).” <a href="https://www.investopedia.com/terms/c/conditional_value_at_risk.asp">https://www.investopedia.com/terms/c/conditional_value_at_risk.asp</a></li><li>Investopedia. “Delta Hedging.” <a href="https://www.investopedia.com/terms/d/deltahedging.asp">https://www.investopedia.com/terms/d/deltahedging.asp</a></li><li>CBOE. “CBOE Volatility Index (VIX).” <a href="https://www.cboe.com/products/vix-index-volatility">https://www.cboe.com/products/vix-index-volatility</a></li><li>Sheppard, K. (2021). Python “arch” package documentation. <a href="https://pypi.org/project/arch">https://pypi.org/project/arch</a></li><li>Cran Team. “rugarch: Univariate GARCH Models.” <a href="https://cran.r-project.org/web/packages/rugarch">https://cran.r-project.org/web/packages/rugarch</a></li></ul></div><div class="el-divider el-divider--horizontal" style="--el-border-style:solid;" role="separator"><!--v-if--></div><h2>Các bài báo, nghiên cứu, công bố khoa học về chủ đề độ biến động:</h2><div><div><!--[--><div class="entity-item-container" data-v-d071913d><a href="/publication/Polymorphic-transitions-in-single-crystals-A-new-molecular-dynamics-method/55fd0330-c138-46af-b096-7f13f8442dea" class="entity-title" data-v-d071913d><span data-v-d071913d>Chuyển biến đa hình trong tinh thể đơn: Một phương pháp động lực học phân tử mới</span><!----><span class="el-tag el-tag--warning el-tag--small el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--><span class="icon enabled" style="color:inherit !important;cursor:unset;" data-v-d071913d data-v-f4e97fe2><i class="fas fa-robot" style="font-size:inherit;color:inherit !important;" data-v-f4e97fe2></i></span> Dịch bởi AI <!--]--></span><!--v-if--></span></a><div class="publish-info" data-v-d071913d><span data-v-d071913d><span data-v-d071913d>Journal of Applied Physics</span> - </span> Tập 52 Số 12 <span data-v-d071913d> - Trang 7182-7190</span><span data-v-d071913d> - 1981</span></div><!----><div class="abstract-container" data-v-d071913d><div data-v-d071913d><div><span class=""><jats:p> Một dạng thức Lagrangian mới được giới thiệu. Nó có thể được sử dụng để thực hiện các phép tính động lực học phân tử (MD) trên các hệ thống dưới các điều kiện ứng suất bên ngoài tổng quát nhất. Trong dạng thức này, hình dạng và kích thước của ô MD có thể thay đổi theo các phương trình động lực học do Lagrangian này cung cấp. Kỹ thuật MD mới này rất phù hợp để nghiên cứu những biến đổi cấu...</span><span>... <span class="truncate-button"> hiện toàn bộ</span></span></div><!----></div></div><div class="keyword-container" data-v-d071913d><!--[--><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #Động lực học phân tử<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #ứng suất<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #biến dạng<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #chuyển biến đa hình<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #tinh thể đơn<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #mô hình Ni<!--]--></span><!--v-if--></span><!--]--></div><div class="el-row" style="" data-v-d071913d data-v-5c117f8d><!--[--><div class="el-col el-col-24" style="" data-v-5c117f8d><!--[--><!--[--><span data-v-5c117f8d><!----></span><span data-v-5c117f8d><!----></span><span data-v-5c117f8d><!----></span><!--]--><!--]--></div><!--]--></div><div class="action-container" data-v-d071913d><button ariadisabled="false" type="button" class="el-button el-button--primary el-button--small is-round" style="" data-v-d071913d><!--v-if--><span class=""><!--[--><span class="icon enabled" style="color:inherit !important;cursor:unset;" data-v-d071913d data-v-f4e97fe2><i class="fas fa-quote-left" style="font-size:inherit;color:inherit !important;" data-v-f4e97fe2></i></span> 16114<!--]--></span></button><button ariadisabled="false" type="button" class="el-button el-button--primary el-button--small is-plain is-round" style="" data-v-d071913d><!--v-if--><span class=""><!--[--><a href="https://pubs.aip.org/jap/article/52/12/7182/9558/Polymorphic-transitions-in-single-crystals-A-new" target="_blank" rel="nofollow noopener" data-v-d071913d><!--[--><span class="icon enabled" style="color:inherit !important;cursor:unset;" data-v-d071913d data-v-f4e97fe2><i class="fas fa-link" style="font-size:inherit;color:inherit !important;" data-v-f4e97fe2></i></span> Đi đến bài báo <!--]--></a><!--]--></span></button><button ariadisabled="false" type="button" class="el-button el-button--primary el-button--small is-text" style="" data-v-d071913d><!--v-if--><span class=""><!--[--><span class="icon enabled" style="color:inherit !important;cursor:unset;" data-v-d071913d data-v-f4e97fe2><i class="fas fa-quote-right" style="font-size:inherit;color:inherit !important;" data-v-f4e97fe2></i></span> Trích dẫn <!--]--></span></button><span class="save-button-container" data-v-d071913d data-v-c008b161><button ariadisabled="false" type="button" class="el-button el-button--primary el-button--small is-text" style="" data-v-c008b161><i class="el-icon" style=""><!--[--><!--[--><span class="icon enabled" style="color:inherit !important;cursor:unset;" data-v-c008b161 data-v-f4e97fe2><i class="fas fa-bookmark" style="font-size:inherit;color:inherit !important;" data-v-f4e97fe2></i></span><!--]--><!--]--></i><span class=""><!--[--> Lưu lại<!--]--></span></button></span><!--[--><!--]--></div></div><div class="entity-item-container" data-v-d071913d><a href="/publication/Mutation-in-the-%CE%B1-Synuclein-Gene-Identified-in-Families-with-Parkinson-s-Disease/8f078e18-1d46-4b3f-8561-26d47f39ec8b" class="entity-title" data-v-d071913d><span data-v-d071913d>Đột Biến Gen α-Synuclein Được Xác Định Trong Cộng Đồng Gia Đình Bệnh Parkinson</span><!----><span class="el-tag el-tag--warning el-tag--small el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--><span class="icon enabled" style="color:inherit !important;cursor:unset;" data-v-d071913d data-v-f4e97fe2><i class="fas fa-robot" style="font-size:inherit;color:inherit !important;" data-v-f4e97fe2></i></span> Dịch bởi AI <!--]--></span><!--v-if--></span></a><div class="publish-info" data-v-d071913d><span data-v-d071913d><span data-v-d071913d>American Association for the Advancement of Science (AAAS)</span> - </span> Tập 276 Số 5321 <span data-v-d071913d> - Trang 2045-2047</span><span data-v-d071913d> - 1997</span></div><!----><div class="abstract-container" data-v-d071913d><div data-v-d071913d><div><span class=""><jats:p>Bệnh Parkinson (PD) là một rối loạn thần kinh thoái hóa phổ biến với tỷ lệ mắc cả đời khoảng 2 phần trăm. Một mẫu gia tăng phát tích trong gia đình đã được ghi nhận đối với rối loạn và gần đây đã có báo cáo rằng một gen gây nhạy cảm với PD trong một gia đình lớn ở Ý được định vị trên cánh dài của nhiễm sắc thể số 4 của người. Một đột biến đã được xác định trong gen α-synuclein, mã hóa cho ...</span><span>... <span class="truncate-button"> hiện toàn bộ</span></span></div><!----></div></div><div class="keyword-container" data-v-d071913d><!--[--><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #Bệnh Parkinson<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #Đột biến gen<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #α-synuclein<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #Thần kinh học<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #Di truyền học<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #Tính dẻo thần kinh<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #Di truyền trội trên nhiễm sắc thể thường<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #Nhiễm sắc thể số 4<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #Gia tăng phát tích<!--]--></span><!--v-if--></span><!--]--></div><div class="el-row" style="" data-v-d071913d data-v-5c117f8d><!--[--><div class="el-col el-col-24" style="" data-v-5c117f8d><!--[--><!--[--><span data-v-5c117f8d><!----></span><span data-v-5c117f8d><!----></span><span data-v-5c117f8d><!----></span><!--]--><!--]--></div><!--]--></div><div class="action-container" data-v-d071913d><button ariadisabled="false" type="button" class="el-button el-button--primary el-button--small is-round" style="" data-v-d071913d><!--v-if--><span class=""><!--[--><span class="icon enabled" style="color:inherit !important;cursor:unset;" data-v-d071913d data-v-f4e97fe2><i class="fas fa-quote-left" style="font-size:inherit;color:inherit !important;" data-v-f4e97fe2></i></span> 7695<!--]--></span></button><button ariadisabled="false" type="button" class="el-button el-button--primary el-button--small is-plain is-round" style="" data-v-d071913d><!--v-if--><span class=""><!--[--><a href="https://www.science.org/doi/10.1126/science.276.5321.2045" target="_blank" rel="nofollow noopener" data-v-d071913d><!--[--><span class="icon enabled" style="color:inherit !important;cursor:unset;" data-v-d071913d data-v-f4e97fe2><i class="fas fa-link" style="font-size:inherit;color:inherit !important;" data-v-f4e97fe2></i></span> Đi đến bài báo <!--]--></a><!--]--></span></button><button ariadisabled="false" type="button" class="el-button el-button--primary el-button--small is-text" style="" data-v-d071913d><!--v-if--><span class=""><!--[--><span class="icon enabled" style="color:inherit !important;cursor:unset;" data-v-d071913d data-v-f4e97fe2><i class="fas fa-quote-right" style="font-size:inherit;color:inherit !important;" data-v-f4e97fe2></i></span> Trích dẫn <!--]--></span></button><span class="save-button-container" data-v-d071913d data-v-c008b161><button ariadisabled="false" type="button" class="el-button el-button--primary el-button--small is-text" style="" data-v-c008b161><i class="el-icon" style=""><!--[--><!--[--><span class="icon enabled" style="color:inherit !important;cursor:unset;" data-v-c008b161 data-v-f4e97fe2><i class="fas fa-bookmark" style="font-size:inherit;color:inherit !important;" data-v-f4e97fe2></i></span><!--]--><!--]--></i><span class=""><!--[--> Lưu lại<!--]--></span></button></span><!--[--><!--]--></div></div><div class="entity-item-container" data-v-d071913d><a href="/publication/Normalization-of-Real-Time-Quantitative-Reverse-Transcription-PCR-Data-A-Model-Based-Variance-Estimation-Approach-to-Identify-Genes-Suited-for-Normalization-Applied-to-Bladder-and-Colon-Cancer-Data-Sets/f68a8582-2b2d-44c5-8fd2-fc6346ed5857" class="entity-title" data-v-d071913d><span data-v-d071913d>Bình Thường Hoá Dữ Liệu PCR Sao Chép Ngược Định Lượng Thời Gian Thực: Cách Tiếp Cận Ước Tính Biến Động Dựa Trên Mô Hình Để Xác Định Các Gene Thích Hợp Cho Bình Thường Hoá, Áp Dụng Cho Các Bộ Dữ Liệu Ung Thư Bàng Quang và Ruột Kết</span><!----><span class="el-tag el-tag--warning el-tag--small el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--><span class="icon enabled" style="color:inherit !important;cursor:unset;" data-v-d071913d data-v-f4e97fe2><i class="fas fa-robot" style="font-size:inherit;color:inherit !important;" data-v-f4e97fe2></i></span> Dịch bởi AI <!--]--></span><!--v-if--></span></a><div class="publish-info" data-v-d071913d><span data-v-d071913d><span data-v-d071913d>Cancer Research</span> - </span> Tập 64 Số 15 <span data-v-d071913d> - Trang 5245-5250</span><span data-v-d071913d> - 2004</span></div><!----><div class="abstract-container" data-v-d071913d><div data-v-d071913d><div><span class=""><jats:title>Tóm tắt</jats:title> <jats:p>Bình thường hóa chính xác là điều kiện tiên quyết tuyệt đối để đo lường đúng biểu hiện gene. Đối với PCR sao chép ngược định lượng thời gian thực (RT-PCR), chiến lược bình thường hóa phổ biến nhất bao gồm tiêu chuẩn hóa một gene kiểm soát được biểu hiện liên tục. Tuy nhiên, trong những năm gần đây, đã trở nên rõ ràng rằng không có gene nào được biểu hiện li...</span><span>... <span class="truncate-button"> hiện toàn bộ</span></span></div><!----></div></div><div class="keyword-container" data-v-d071913d><!--[--><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #PCR<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #Sao chép ngược<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #Biểu hiện gene<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #Bình thường hóa<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #Phương pháp dựa trên mô hình<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #Ung thư ruột kết<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #Ung thư bàng quang<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #Biến đổi biểu hiện<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #Gene kiểm soát<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #Ứng cử viên bình thường hóa.<!--]--></span><!--v-if--></span><!--]--></div><div class="el-row" style="" data-v-d071913d data-v-5c117f8d><!--[--><div class="el-col el-col-24" style="" data-v-5c117f8d><!--[--><!--[--><span data-v-5c117f8d><!----></span><span data-v-5c117f8d><!----></span><span data-v-5c117f8d><!----></span><!--]--><!--]--></div><!--]--></div><div class="action-container" data-v-d071913d><button ariadisabled="false" type="button" class="el-button el-button--primary el-button--small is-round" style="" data-v-d071913d><!--v-if--><span class=""><!--[--><span class="icon enabled" style="color:inherit !important;cursor:unset;" data-v-d071913d data-v-f4e97fe2><i class="fas fa-quote-left" style="font-size:inherit;color:inherit !important;" data-v-f4e97fe2></i></span> 6507<!--]--></span></button><button ariadisabled="false" type="button" class="el-button el-button--primary el-button--small is-plain is-round" style="" data-v-d071913d><!--v-if--><span class=""><!--[--><a href="https://aacrjournals.org/cancerres/article/64/15/5245/511517/Normalization-of-Real-Time-Quantitative-Reverse" target="_blank" rel="nofollow noopener" data-v-d071913d><!--[--><span class="icon enabled" style="color:inherit !important;cursor:unset;" data-v-d071913d data-v-f4e97fe2><i class="fas fa-link" style="font-size:inherit;color:inherit !important;" data-v-f4e97fe2></i></span> Đi đến bài báo <!--]--></a><!--]--></span></button><button ariadisabled="false" type="button" class="el-button el-button--primary el-button--small is-text" style="" data-v-d071913d><!--v-if--><span class=""><!--[--><span class="icon enabled" style="color:inherit !important;cursor:unset;" data-v-d071913d data-v-f4e97fe2><i class="fas fa-quote-right" style="font-size:inherit;color:inherit !important;" data-v-f4e97fe2></i></span> Trích dẫn <!--]--></span></button><span class="save-button-container" data-v-d071913d data-v-c008b161><button ariadisabled="false" type="button" class="el-button el-button--primary el-button--small is-text" style="" data-v-c008b161><i class="el-icon" style=""><!--[--><!--[--><span class="icon enabled" style="color:inherit !important;cursor:unset;" data-v-c008b161 data-v-f4e97fe2><i class="fas fa-bookmark" style="font-size:inherit;color:inherit !important;" data-v-f4e97fe2></i></span><!--]--><!--]--></i><span class=""><!--[--> Lưu lại<!--]--></span></button></span><!--[--><!--]--></div></div><div class="entity-item-container" data-v-d071913d><a href="/publication/Comprehensive-Identification-of-Cell-Cycle-regulated-Genes-of-the-Yeast-i-Saccharomyces-cerevisiae-i-by-Microarray-Hybridization/c81b1d29-97ee-4c93-80ae-3b95e2c6629b" class="entity-title" data-v-d071913d><span data-v-d071913d>Xác định toàn diện các gen điều hòa chu kỳ tế bào của nấm men Saccharomyces cerevisiae bằng phương pháp lai ghép microarray</span><!----><span class="el-tag el-tag--warning el-tag--small el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--><span class="icon enabled" style="color:inherit !important;cursor:unset;" data-v-d071913d data-v-f4e97fe2><i class="fas fa-robot" style="font-size:inherit;color:inherit !important;" data-v-f4e97fe2></i></span> Dịch bởi AI <!--]--></span><!--v-if--></span></a><div class="publish-info" data-v-d071913d><span data-v-d071913d><span data-v-d071913d>Molecular Biology of the Cell</span> - </span> Tập 9 Số 12 <span data-v-d071913d> - Trang 3273-3297</span><span data-v-d071913d> - 1998</span></div><!----><div class="abstract-container" data-v-d071913d><div data-v-d071913d><div><span class=""><jats:p>Chúng tôi đã tìm cách tạo ra một danh mục đầy đủ các gen của nấm men có mức độ phiên mã thay đổi theo chu kỳ trong chu kỳ tế bào. Để đạt được mục tiêu này, chúng tôi sử dụng microarray DNA và các mẫu từ các nền nuôi cấy nấm men được đồng bộ hóa bằng ba phương pháp độc lập: dừng bằng yếu tố α, phương pháp tách lọc, và dừng đồng bộ một đột biến nhạy với nhiệt độ cdc15. Sử dụng các thuật toán...</span><span>... <span class="truncate-button"> hiện toàn bộ</span></span></div><!----></div></div><div class="keyword-container" data-v-d071913d><!--[--><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #Gen chu kỳ tế bào<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #Saccharomyces cerevisiae<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #microarray<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #điều hòa gen<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #Cln3p<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #Clb2p<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #yếu tố α<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #phương pháp tách lọc<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #đột biến cdc15<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #yếu tố khởi động.<!--]--></span><!--v-if--></span><!--]--></div><div class="el-row" style="" data-v-d071913d data-v-5c117f8d><!--[--><div class="el-col el-col-24" style="" data-v-5c117f8d><!--[--><!--[--><span data-v-5c117f8d><!----></span><span data-v-5c117f8d><!----></span><span data-v-5c117f8d><!----></span><!--]--><!--]--></div><!--]--></div><div class="action-container" data-v-d071913d><button ariadisabled="false" type="button" class="el-button el-button--primary el-button--small is-round" style="" data-v-d071913d><!--v-if--><span class=""><!--[--><span class="icon enabled" style="color:inherit !important;cursor:unset;" data-v-d071913d data-v-f4e97fe2><i class="fas fa-quote-left" style="font-size:inherit;color:inherit !important;" data-v-f4e97fe2></i></span> 4791<!--]--></span></button><button ariadisabled="false" type="button" class="el-button el-button--primary el-button--small is-plain is-round" style="" data-v-d071913d><!--v-if--><span class=""><!--[--><a href="https://www.molbiolcell.org/doi/10.1091/mbc.9.12.3273" target="_blank" rel="nofollow noopener" data-v-d071913d><!--[--><span class="icon enabled" style="color:inherit !important;cursor:unset;" data-v-d071913d data-v-f4e97fe2><i class="fas fa-link" style="font-size:inherit;color:inherit !important;" data-v-f4e97fe2></i></span> Đi đến bài báo <!--]--></a><!--]--></span></button><button ariadisabled="false" type="button" class="el-button el-button--primary el-button--small is-text" style="" data-v-d071913d><!--v-if--><span class=""><!--[--><span class="icon enabled" style="color:inherit !important;cursor:unset;" data-v-d071913d data-v-f4e97fe2><i class="fas fa-quote-right" style="font-size:inherit;color:inherit !important;" data-v-f4e97fe2></i></span> Trích dẫn <!--]--></span></button><span class="save-button-container" data-v-d071913d data-v-c008b161><button ariadisabled="false" type="button" class="el-button el-button--primary el-button--small is-text" style="" data-v-c008b161><i class="el-icon" style=""><!--[--><!--[--><span class="icon enabled" style="color:inherit !important;cursor:unset;" data-v-c008b161 data-v-f4e97fe2><i class="fas fa-bookmark" style="font-size:inherit;color:inherit !important;" data-v-f4e97fe2></i></span><!--]--><!--]--></i><span class=""><!--[--> Lưu lại<!--]--></span></button></span><!--[--><!--]--></div></div><div class="entity-item-container" data-v-d071913d><a href="/publication/Power-spectral-analysis-of-heart-rate-and-arterial-pressure-variabilities-as-a-marker-of-sympatho-vagal-interaction-in-man-and-conscious-dog-/9be330f5-96c8-465a-864d-fb00ba390612" class="entity-title" data-v-d071913d><span data-v-d071913d>Phân tích quang phổ công suất của độ biến thiên nhịp tim và áp lực động mạch như một dấu hiệu của sự tương tác giữa hệ giao cảm và phó giao cảm ở người và chó tỉnh.</span><!----><span class="el-tag el-tag--warning el-tag--small el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--><span class="icon enabled" style="color:inherit !important;cursor:unset;" data-v-d071913d data-v-f4e97fe2><i class="fas fa-robot" style="font-size:inherit;color:inherit !important;" data-v-f4e97fe2></i></span> Dịch bởi AI <!--]--></span><!--v-if--></span></a><div class="publish-info" data-v-d071913d><span data-v-d071913d><span data-v-d071913d>Circulation Research</span> - </span> Tập 59 Số 2 <span data-v-d071913d> - Trang 178-193</span><span data-v-d071913d> - 1986</span></div><!----><div class="abstract-container" data-v-d071913d><div data-v-d071913d><div><span class=""><jats:p>Trong 57 chủ thể bình thường (tuổi từ 20-60 tuổi), chúng tôi đã phân tích sự dao động tự phát theo nhịp giữa các khoảng R-R trong tư thế nằm kiểm soát, nghiêng đứng 90 độ, thở có kiểm soát (n = 16) và ức chế thụ thể beta-adrenergic cấp tính (n = 10) và mạn tính (n = 12). Phân tích tự động bằng máy tính đã cung cấp mật độ quang phổ công suất tự hồi quy, cũng như số lượng và công suất tương ...</span><span>... <span class="truncate-button"> hiện toàn bộ</span></span></div><!----></div></div><div class="keyword-container" data-v-d071913d><!--[--><!--]--></div><div class="el-row" style="" data-v-d071913d data-v-5c117f8d><!--[--><div class="el-col el-col-24" style="" data-v-5c117f8d><!--[--><!--[--><span data-v-5c117f8d><!----></span><span data-v-5c117f8d><!----></span><span data-v-5c117f8d><!----></span><!--]--><!--]--></div><!--]--></div><div class="action-container" data-v-d071913d><button ariadisabled="false" type="button" class="el-button el-button--primary el-button--small is-round" style="" data-v-d071913d><!--v-if--><span class=""><!--[--><span class="icon enabled" style="color:inherit !important;cursor:unset;" data-v-d071913d data-v-f4e97fe2><i class="fas fa-quote-left" style="font-size:inherit;color:inherit !important;" data-v-f4e97fe2></i></span> 4097<!--]--></span></button><button ariadisabled="false" type="button" class="el-button el-button--primary el-button--small is-plain is-round" style="" data-v-d071913d><!--v-if--><span class=""><!--[--><a href="https://www.ahajournals.org/doi/10.1161/01.RES.59.2.178" target="_blank" rel="nofollow noopener" data-v-d071913d><!--[--><span class="icon enabled" style="color:inherit !important;cursor:unset;" data-v-d071913d data-v-f4e97fe2><i class="fas fa-link" style="font-size:inherit;color:inherit !important;" data-v-f4e97fe2></i></span> Đi đến bài báo <!--]--></a><!--]--></span></button><button ariadisabled="false" type="button" class="el-button el-button--primary el-button--small is-text" style="" data-v-d071913d><!--v-if--><span class=""><!--[--><span class="icon enabled" style="color:inherit !important;cursor:unset;" data-v-d071913d data-v-f4e97fe2><i class="fas fa-quote-right" style="font-size:inherit;color:inherit !important;" data-v-f4e97fe2></i></span> Trích dẫn <!--]--></span></button><span class="save-button-container" data-v-d071913d data-v-c008b161><button ariadisabled="false" type="button" class="el-button el-button--primary el-button--small is-text" style="" data-v-c008b161><i class="el-icon" style=""><!--[--><!--[--><span class="icon enabled" style="color:inherit !important;cursor:unset;" data-v-c008b161 data-v-f4e97fe2><i class="fas fa-bookmark" style="font-size:inherit;color:inherit !important;" data-v-f4e97fe2></i></span><!--]--><!--]--></i><span class=""><!--[--> Lưu lại<!--]--></span></button></span><!--[--><!--]--></div></div><div class="entity-item-container" data-v-d071913d><a href="/publication/Tetracycline-Antibiotics-Mode-of-Action-Applications-Molecular-Biology-and-Epidemiology-of-Bacterial-Resistance/e81b170b-42c6-4b85-824f-be0325160a93" class="entity-title" data-v-d071913d><span data-v-d071913d>Kháng sinh Tetracycline: Cơ chế tác dụng, Ứng dụng, Sinh học phân tử và Dịch tễ học của Kháng khuẩn Kháng Khuẩn</span><!----><span class="el-tag el-tag--warning el-tag--small el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--><span class="icon enabled" style="color:inherit !important;cursor:unset;" data-v-d071913d data-v-f4e97fe2><i class="fas fa-robot" style="font-size:inherit;color:inherit !important;" data-v-f4e97fe2></i></span> Dịch bởi AI <!--]--></span><!--v-if--></span></a><div class="publish-info" data-v-d071913d><span data-v-d071913d><span data-v-d071913d>Microbiology and Molecular Biology Reviews</span> - </span> Tập 65 Số 2 <span data-v-d071913d> - Trang 232-260</span><span data-v-d071913d> - 2001</span></div><!----><div class="abstract-container" data-v-d071913d><div data-v-d071913d><div><span class=""><jats:sec> <jats:title>TÓM TẮT</jats:title> <jats:p>Tetracyclines được phát hiện vào những năm 1940 và cho thấy hoạt tính chống lại nhiều vi sinh vật bao gồm vi khuẩn gram dương và gram âm, chlamydiae, mycoplasma, rickettsiae và ký sinh trùng nguyên sinh. Đây là những loại kháng sinh ít tốn kém, đã được sử dụng rộng rãi trong dự phòng và điều trị nhiễm khuẩn ở người và động...</span><span>... <span class="truncate-button"> hiện toàn bộ</span></span></div><!----></div></div><div class="keyword-container" data-v-d071913d><!--[--><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #tetracycline<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #kháng rửa<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #kháng sinh<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #kháng khuẩn<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #vi khuẩn kháng<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #chlamydiae<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #mycoplasma<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #rickettsiae<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #động vật nguyên sinh<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #gen di động<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #hóa sinh<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #lai ghép DNA-DNA<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #16S rRNA<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #plasmid<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #transposon<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #đột biến<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #dịch tễ học<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #sức khỏe động vật<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #sản xuất thực phẩm<!--]--></span><!--v-if--></span><!--]--></div><div class="el-row" style="" data-v-d071913d data-v-5c117f8d><!--[--><div class="el-col el-col-24" style="" data-v-5c117f8d><!--[--><!--[--><span data-v-5c117f8d><!----></span><span data-v-5c117f8d><!----></span><span data-v-5c117f8d><!----></span><!--]--><!--]--></div><!--]--></div><div class="action-container" data-v-d071913d><button ariadisabled="false" type="button" class="el-button el-button--primary el-button--small is-round" style="" data-v-d071913d><!--v-if--><span class=""><!--[--><span class="icon enabled" style="color:inherit !important;cursor:unset;" data-v-d071913d data-v-f4e97fe2><i class="fas fa-quote-left" style="font-size:inherit;color:inherit !important;" data-v-f4e97fe2></i></span> 3837<!--]--></span></button><button ariadisabled="false" type="button" class="el-button el-button--primary el-button--small is-plain is-round" style="" data-v-d071913d><!--v-if--><span class=""><!--[--><a href="https://journals.asm.org/doi/10.1128/MMBR.65.2.232-260.2001" target="_blank" rel="nofollow noopener" data-v-d071913d><!--[--><span class="icon enabled" style="color:inherit !important;cursor:unset;" data-v-d071913d data-v-f4e97fe2><i class="fas fa-link" style="font-size:inherit;color:inherit !important;" data-v-f4e97fe2></i></span> Đi đến bài báo <!--]--></a><!--]--></span></button><button ariadisabled="false" type="button" class="el-button el-button--primary el-button--small is-text" style="" data-v-d071913d><!--v-if--><span class=""><!--[--><span class="icon enabled" style="color:inherit !important;cursor:unset;" data-v-d071913d data-v-f4e97fe2><i class="fas fa-quote-right" style="font-size:inherit;color:inherit !important;" data-v-f4e97fe2></i></span> Trích dẫn <!--]--></span></button><span class="save-button-container" data-v-d071913d data-v-c008b161><button ariadisabled="false" type="button" class="el-button el-button--primary el-button--small is-text" style="" data-v-c008b161><i class="el-icon" style=""><!--[--><!--[--><span class="icon enabled" style="color:inherit !important;cursor:unset;" data-v-c008b161 data-v-f4e97fe2><i class="fas fa-bookmark" style="font-size:inherit;color:inherit !important;" data-v-f4e97fe2></i></span><!--]--><!--]--></i><span class=""><!--[--> Lưu lại<!--]--></span></button></span><!--[--><!--]--></div></div><div class="entity-item-container" data-v-d071913d><a href="/publication/Every-base-matters-assessing-small-subunit-scp-rRNA-scp-primers-for-marine-microbiomes-with-mock-communities-time-series-and-global-field-samples/352dee20-9505-4969-9263-082dae900d12" class="entity-title" data-v-d071913d><span data-v-d071913d>Mỗi nucleotide đều quan trọng: đánh giá các mồi <scp>rRNA</scp> tiểu đơn vị nhỏ cho vi sinh vật biển qua cộng đồng giả, chuỗi thời gian và mẫu hiện trường toàn cầu</span><!----><span class="el-tag el-tag--warning el-tag--small el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--><span class="icon enabled" style="color:inherit !important;cursor:unset;" data-v-d071913d data-v-f4e97fe2><i class="fas fa-robot" style="font-size:inherit;color:inherit !important;" data-v-f4e97fe2></i></span> Dịch bởi AI <!--]--></span><!--v-if--></span></a><div class="publish-info" data-v-d071913d><span data-v-d071913d><span data-v-d071913d>Wiley</span> - </span> Tập 18 Số 5 <span data-v-d071913d> - Trang 1403-1414</span><span data-v-d071913d> - 2016</span></div><!----><div class="abstract-container" data-v-d071913d><div data-v-d071913d><div><span class=""><jats:title>Tóm tắt</jats:title><jats:p>Phân tích cộng đồng vi sinh vật thông qua thế hệ các đoạn <jats:styled-content style="fixed-case">16S rRNA</jats:styled-content> bằng cách giải trình tự cao cấp là một công cụ thiết yếu trong vi sinh vật học. Chúng tôi phát hiện rằng cặp mồi phổ biến <jats:styled-content style="fixed-case">515F</jats:styled-content> (<jats:styled-content style="fixed-case">5...</span><span>... <span class="truncate-button"> hiện toàn bộ</span></span></div><!----></div></div><div class="keyword-container" data-v-d071913d><!--[--><!--]--></div><div class="el-row" style="" data-v-d071913d data-v-5c117f8d><!--[--><div class="el-col el-col-24" style="" data-v-5c117f8d><!--[--><!--[--><span data-v-5c117f8d><!----></span><span data-v-5c117f8d><!----></span><span data-v-5c117f8d><!----></span><!--]--><!--]--></div><!--]--></div><div class="action-container" data-v-d071913d><button ariadisabled="false" type="button" class="el-button el-button--primary el-button--small is-round" style="" data-v-d071913d><!--v-if--><span class=""><!--[--><span class="icon enabled" style="color:inherit !important;cursor:unset;" data-v-d071913d data-v-f4e97fe2><i class="fas fa-quote-left" style="font-size:inherit;color:inherit !important;" data-v-f4e97fe2></i></span> 2721<!--]--></span></button><button ariadisabled="false" type="button" class="el-button el-button--primary el-button--small is-plain is-round" style="" data-v-d071913d><!--v-if--><span class=""><!--[--><a href="https://sfamjournals.onlinelibrary.wiley.com/doi/10.1111/1462-2920.13023" target="_blank" rel="nofollow noopener" data-v-d071913d><!--[--><span class="icon enabled" style="color:inherit !important;cursor:unset;" data-v-d071913d data-v-f4e97fe2><i class="fas fa-link" style="font-size:inherit;color:inherit !important;" data-v-f4e97fe2></i></span> Đi đến bài báo <!--]--></a><!--]--></span></button><button ariadisabled="false" type="button" class="el-button el-button--primary el-button--small is-text" style="" data-v-d071913d><!--v-if--><span class=""><!--[--><span class="icon enabled" style="color:inherit !important;cursor:unset;" data-v-d071913d data-v-f4e97fe2><i class="fas fa-quote-right" style="font-size:inherit;color:inherit !important;" data-v-f4e97fe2></i></span> Trích dẫn <!--]--></span></button><span class="save-button-container" data-v-d071913d data-v-c008b161><button ariadisabled="false" type="button" class="el-button el-button--primary el-button--small is-text" style="" data-v-c008b161><i class="el-icon" style=""><!--[--><!--[--><span class="icon enabled" style="color:inherit !important;cursor:unset;" data-v-c008b161 data-v-f4e97fe2><i class="fas fa-bookmark" style="font-size:inherit;color:inherit !important;" data-v-f4e97fe2></i></span><!--]--><!--]--></i><span class=""><!--[--> Lưu lại<!--]--></span></button></span><!--[--><!--]--></div></div><div class="entity-item-container" data-v-d071913d><a href="/publication/Photosynthetic-rates-derived-from-satellite-based-chlorophyll-concentration/7e91b035-e48d-47ac-9ff4-4ee94f0045aa" class="entity-title" data-v-d071913d><span data-v-d071913d>Tốc độ quang hợp bắt nguồn từ nồng độ chlorophyll dựa trên vệ tinh</span><!----><span class="el-tag el-tag--warning el-tag--small el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--><span class="icon enabled" style="color:inherit !important;cursor:unset;" data-v-d071913d data-v-f4e97fe2><i class="fas fa-robot" style="font-size:inherit;color:inherit !important;" data-v-f4e97fe2></i></span> Dịch bởi AI <!--]--></span><!--v-if--></span></a><div class="publish-info" data-v-d071913d><span data-v-d071913d><span data-v-d071913d>Limnology and Oceanography</span> - </span> Tập 42 Số 1 <span data-v-d071913d> - Trang 1-20</span><span data-v-d071913d> - 1997</span></div><!----><div class="abstract-container" data-v-d071913d><div data-v-d071913d><div><span class=""><jats:p>Chúng tôi đã tập hợp một bộ dữ liệu đo lường hiệu suất dựa trên carbon <jats:sup>14</jats:sup> để hiểu các biến số quan trọng cần thiết cho đánh giá chính xác việc cố định carbon phytoplankton tích hợp độ sâu hàng ngày (<jats:italic>PP</jats:italic>(<jats:italic>PP</jats:italic><jats:sub>eu</jats:sub>)<jats:sub>u</jats:sub>) từ đo lường nồng độ sắc tố trên bề mặt biển (<jats:italic>C</jats...</span><span>... <span class="truncate-button"> hiện toàn bộ</span></span></div><!----></div></div><div class="keyword-container" data-v-d071913d><!--[--><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #quang hợp<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #cố định carbon<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #phytoplankton<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #VGPM<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #mô hình khí hậu<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #nhiệt độ bề mặt biển<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #phân phối địa lý<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #hiệu suất đồng hóa tối ưu<!--]--></span><!--v-if--></span><!--]--></div><div class="el-row" style="" data-v-d071913d data-v-5c117f8d><!--[--><div class="el-col el-col-24" style="" data-v-5c117f8d><!--[--><!--[--><span data-v-5c117f8d><!----></span><span data-v-5c117f8d><!----></span><span data-v-5c117f8d><!----></span><!--]--><!--]--></div><!--]--></div><div class="action-container" data-v-d071913d><button ariadisabled="false" type="button" class="el-button el-button--primary el-button--small is-round" style="" data-v-d071913d><!--v-if--><span class=""><!--[--><span class="icon enabled" style="color:inherit !important;cursor:unset;" data-v-d071913d data-v-f4e97fe2><i class="fas fa-quote-left" style="font-size:inherit;color:inherit !important;" data-v-f4e97fe2></i></span> 2593<!--]--></span></button><button ariadisabled="false" type="button" class="el-button el-button--primary el-button--small is-plain is-round" style="" data-v-d071913d><!--v-if--><span class=""><!--[--><a href="https://aslopubs.onlinelibrary.wiley.com/doi/10.4319/lo.1997.42.1.0001" target="_blank" rel="nofollow noopener" data-v-d071913d><!--[--><span class="icon enabled" style="color:inherit !important;cursor:unset;" data-v-d071913d data-v-f4e97fe2><i class="fas fa-link" style="font-size:inherit;color:inherit !important;" data-v-f4e97fe2></i></span> Đi đến bài báo <!--]--></a><!--]--></span></button><button ariadisabled="false" type="button" class="el-button el-button--primary el-button--small is-text" style="" data-v-d071913d><!--v-if--><span class=""><!--[--><span class="icon enabled" style="color:inherit !important;cursor:unset;" data-v-d071913d data-v-f4e97fe2><i class="fas fa-quote-right" style="font-size:inherit;color:inherit !important;" data-v-f4e97fe2></i></span> Trích dẫn <!--]--></span></button><span class="save-button-container" data-v-d071913d data-v-c008b161><button ariadisabled="false" type="button" class="el-button el-button--primary el-button--small is-text" style="" data-v-c008b161><i class="el-icon" style=""><!--[--><!--[--><span class="icon enabled" style="color:inherit !important;cursor:unset;" data-v-c008b161 data-v-f4e97fe2><i class="fas fa-bookmark" style="font-size:inherit;color:inherit !important;" data-v-f4e97fe2></i></span><!--]--><!--]--></i><span class=""><!--[--> Lưu lại<!--]--></span></button></span><!--[--><!--]--></div></div><div class="entity-item-container" data-v-d071913d><a href="/publication/Quantification-of-mRNA-using-real-time-reverse-transcription-PCR-RT-PCR-trends-and-problems/8f5b5640-8f08-448d-9bb8-0f0352ce0007" class="entity-title" data-v-d071913d><span data-v-d071913d>Định lượng mRNA bằng phương pháp PCR Ngược Dòng Thời gian Thực: xu hướng và vấn đề</span><!----><span class="el-tag el-tag--warning el-tag--small el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--><span class="icon enabled" style="color:inherit !important;cursor:unset;" data-v-d071913d data-v-f4e97fe2><i class="fas fa-robot" style="font-size:inherit;color:inherit !important;" data-v-f4e97fe2></i></span> Dịch bởi AI <!--]--></span><!--v-if--></span></a><div class="publish-info" data-v-d071913d><span data-v-d071913d><span data-v-d071913d>Journal of Molecular Endocrinology</span> - </span> Tập 29 Số 1 <span data-v-d071913d> - Trang 23-39</span><span data-v-d071913d> - 2002</span></div><!----><div class="abstract-container" data-v-d071913d><div data-v-d071913d><div><span class=""><jats:p>Phương pháp PCR Ngược Dòng Thời gian Thực dựa trên huỳnh quang (RT-PCR) được sử dụng rộng rãi để định lượng mức mRNA ở trạng thái ổn định và là một công cụ quan trọng cho nghiên cứu cơ bản, y học phân tử và công nghệ sinh học. Các thử nghiệm dễ tiến hành, có khả năng xử lý khối lượng lớn, và có thể kết hợp độ nhạy cao với độ đặc hiệu đáng tin cậy. Công nghệ này đang tiến hóa nhanh chóng vớ...</span><span>... <span class="truncate-button"> hiện toàn bộ</span></span></div><!----></div></div><div class="keyword-container" data-v-d071913d><!--[--><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #PCR ngược dòng thời gian thực<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #định lượng mRNA<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #huỳnh quang<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #nghiêm ngặt<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #thống kê<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #y học phân tử<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #công nghệ sinh học<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #biến đổi hóa chất<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #xu hướng<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #vấn đề<!--]--></span><!--v-if--></span><!--]--></div><div class="el-row" style="" data-v-d071913d data-v-5c117f8d><!--[--><div class="el-col el-col-24" style="" data-v-5c117f8d><!--[--><!--[--><span data-v-5c117f8d><!----></span><span data-v-5c117f8d><!----></span><span data-v-5c117f8d><!----></span><!--]--><!--]--></div><!--]--></div><div class="action-container" data-v-d071913d><button ariadisabled="false" type="button" class="el-button el-button--primary el-button--small is-round" style="" data-v-d071913d><!--v-if--><span class=""><!--[--><span class="icon enabled" style="color:inherit !important;cursor:unset;" data-v-d071913d data-v-f4e97fe2><i class="fas fa-quote-left" style="font-size:inherit;color:inherit !important;" data-v-f4e97fe2></i></span> 2515<!--]--></span></button><button ariadisabled="false" type="button" class="el-button el-button--primary el-button--small is-plain is-round" style="" data-v-d071913d><!--v-if--><span class=""><!--[--><a href="https://jme.bioscientifica.com/view/journals/jme/29/1/23.xml" target="_blank" rel="nofollow noopener" data-v-d071913d><!--[--><span class="icon enabled" style="color:inherit !important;cursor:unset;" data-v-d071913d data-v-f4e97fe2><i class="fas fa-link" style="font-size:inherit;color:inherit !important;" data-v-f4e97fe2></i></span> Đi đến bài báo <!--]--></a><!--]--></span></button><button ariadisabled="false" type="button" class="el-button el-button--primary el-button--small is-text" style="" data-v-d071913d><!--v-if--><span class=""><!--[--><span class="icon enabled" style="color:inherit !important;cursor:unset;" data-v-d071913d data-v-f4e97fe2><i class="fas fa-quote-right" style="font-size:inherit;color:inherit !important;" data-v-f4e97fe2></i></span> Trích dẫn <!--]--></span></button><span class="save-button-container" data-v-d071913d data-v-c008b161><button ariadisabled="false" type="button" class="el-button el-button--primary el-button--small is-text" style="" data-v-c008b161><i class="el-icon" style=""><!--[--><!--[--><span class="icon enabled" style="color:inherit !important;cursor:unset;" data-v-c008b161 data-v-f4e97fe2><i class="fas fa-bookmark" style="font-size:inherit;color:inherit !important;" data-v-f4e97fe2></i></span><!--]--><!--]--></i><span class=""><!--[--> Lưu lại<!--]--></span></button></span><!--[--><!--]--></div></div><div class="entity-item-container" data-v-d071913d><a href="/publication/Deep-Convolutional-and-LSTM-Recurrent-Neural-Networks-for-Multimodal-Wearable-Activity-Recognition/7ee52729-6c4c-47d7-a26a-6adc609b6f76" class="entity-title" data-v-d071913d><span data-v-d071913d>Mạng Nơ-ron Tích Chập Sâu và Nơ-ron Tái Kết Nối LSTM cho Nhận Diện Hoạt Động Đeo Được Đa Mô Đun</span><!----><span class="el-tag el-tag--warning el-tag--small el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--><span class="icon enabled" style="color:inherit !important;cursor:unset;" data-v-d071913d data-v-f4e97fe2><i class="fas fa-robot" style="font-size:inherit;color:inherit !important;" data-v-f4e97fe2></i></span> Dịch bởi AI <!--]--></span><!--v-if--></span></a><div class="publish-info" data-v-d071913d><span data-v-d071913d><span data-v-d071913d>Sensors</span> - </span> Tập 16 Số 1 <span data-v-d071913d> - Trang 115</span><!----></div><!----><div class="abstract-container" data-v-d071913d><div data-v-d071913d><div><span class=""><jats:p>Nhận diện hoạt động con người (HAR) thường được giải quyết bằng cách sử dụng các đặc trưng kỹ thuật được thu thập thông qua các quy trình heuristics. Nghiên cứu hiện tại cho thấy rằng các mạng nơ-ron tích chập sâu (CNN) rất phù hợp để tự động hóa quá trình trích xuất đặc trưng từ các dữ liệu cảm biến thô. Tuy nhiên, các hoạt động của con người bao gồm các chuỗi chuyển động phức tạp, và việ...</span><span>... <span class="truncate-button"> hiện toàn bộ</span></span></div><!----></div></div><div class="keyword-container" data-v-d071913d><!--[--><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #Nhận diện hoạt động con người<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #mạng nơ-ron tích chập sâu<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #mạng nơ-ron hồi tiếp LSTM<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #cảm biến đeo được<!--]--></span><!--v-if--></span><span class="el-tag el-tag--primary el-tag--light" style="" data-v-d071913d><span class="el-tag__content"><!--[--> #xử lý đa mô đun<!--]--></span><!--v-if--></span><!--]--></div><div class="el-row" style="" data-v-d071913d data-v-5c117f8d><!--[--><div class="el-col el-col-24" style="" data-v-5c117f8d><!--[--><!--[--><span data-v-5c117f8d><!----></span><span data-v-5c117f8d><!----></span><span data-v-5c117f8d><!----></span><!--]--><!--]--></div><!--]--></div><div class="action-container" data-v-d071913d><button ariadisabled="false" type="button" class="el-button el-button--primary el-button--small is-round" style="" data-v-d071913d><!--v-if--><span class=""><!--[--><span class="icon enabled" style="color:inherit !important;cursor:unset;" data-v-d071913d data-v-f4e97fe2><i class="fas fa-quote-left" style="font-size:inherit;color:inherit !important;" data-v-f4e97fe2></i></span> 2106<!--]--></span></button><button ariadisabled="false" type="button" class="el-button el-button--primary el-button--small is-plain is-round" style="" data-v-d071913d><!--v-if--><span class=""><!--[--><a href="https://www.mdpi.com/1424-8220/16/1/115" target="_blank" rel="nofollow noopener" data-v-d071913d><!--[--><span class="icon enabled" style="color:inherit !important;cursor:unset;" data-v-d071913d data-v-f4e97fe2><i class="fas fa-link" style="font-size:inherit;color:inherit !important;" data-v-f4e97fe2></i></span> Đi đến bài báo <!--]--></a><!--]--></span></button><button ariadisabled="false" type="button" class="el-button el-button--primary el-button--small is-text" style="" data-v-d071913d><!--v-if--><span class=""><!--[--><span class="icon enabled" style="color:inherit !important;cursor:unset;" data-v-d071913d data-v-f4e97fe2><i class="fas fa-quote-right" style="font-size:inherit;color:inherit !important;" data-v-f4e97fe2></i></span> Trích dẫn <!--]--></span></button><span class="save-button-container" data-v-d071913d data-v-c008b161><button ariadisabled="false" type="button" class="el-button el-button--primary el-button--small is-text" style="" data-v-c008b161><i class="el-icon" style=""><!--[--><!--[--><span class="icon enabled" style="color:inherit !important;cursor:unset;" data-v-c008b161 data-v-f4e97fe2><i class="fas fa-bookmark" style="font-size:inherit;color:inherit !important;" data-v-f4e97fe2></i></span><!--]--><!--]--></i><span class=""><!--[--> Lưu lại<!--]--></span></button></span><!--[--><!--]--></div></div><!--]--></div><div class="el-row is-justify-end" style="" data-v-fa649ea5><!--[--><div class="pagination-container" data-v-fa649ea5><span data-v-fa649ea5> Tổng số: 1,748</span>    <div class="el-pagination is-background" data-v-fa649ea5><button type="button" class="btn-prev is-first" disabled aria-label="Go to previous page" aria-disabled="true"><i class="el-icon" style=""><!--[--><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 1024 1024"><path fill="currentColor" d="M609.408 149.376 277.76 489.6a32 32 0 0 0 0 44.672l331.648 340.352a29.12 29.12 0 0 0 41.728 0 30.592 30.592 0 0 0 0-42.752L339.264 511.936l311.872-319.872a30.592 30.592 0 0 0 0-42.688 29.12 29.12 0 0 0-41.728 0z"></path></svg><!--]--></i></button><ul class="el-pager"><li class="is-active number" aria-current="true" aria-label="page 1" tabindex="0"> 1 </li><!--v-if--><!--[--><li class="number" aria-current="false" aria-label="page 2" tabindex="0">2</li><li class="number" aria-current="false" aria-label="page 3" tabindex="0">3</li><li class="number" aria-current="false" aria-label="page 4" tabindex="0">4</li><li class="number" aria-current="false" aria-label="page 5" tabindex="0">5</li><li class="number" aria-current="false" aria-label="page 6" tabindex="0">6</li><!--]--><li class="more btn-quicknext el-icon" tabindex="0" aria-label="Next 5 pages"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 1024 1024"><path fill="currentColor" d="M176 416a112 112 0 1 1 0 224 112 112 0 0 1 0-224m336 0a112 112 0 1 1 0 224 112 112 0 0 1 0-224m336 0a112 112 0 1 1 0 224 112 112 0 0 1 0-224"></path></svg></li><li class="number" aria-current="false" aria-label="page 10" tabindex="0">10</li></ul><button type="button" class="btn-next is-last" aria-label="Go to next page" aria-disabled="false"><i class="el-icon" style=""><!--[--><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 1024 1024"><path fill="currentColor" d="M340.864 149.312a30.592 30.592 0 0 0 0 42.752L652.736 512 340.864 831.872a30.592 30.592 0 0 0 0 42.752 29.12 29.12 0 0 0 41.728 0L714.24 534.336a32 32 0 0 0 0-44.672L382.592 149.376a29.12 29.12 0 0 0-41.728 0z"></path></svg><!--]--></i></button></div></div><!--]--></div><div></div></div><!--]--></div><div class="el-col el-col-24 el-col-xs-24 el-col-sm-24 el-col-md-7 is-guttered" style="padding-right:10px;padding-left:10px;"><!--[--><h2 class="underline-title">Chủ đề khác</h2><div class="post-page-container"><!--[--><div class="entity-item-container"><a href="/topic/huỳnh quang" class=""><span class="el-tag el-tag--primary el-tag--light" style=""><span class="el-tag__content"><!--[-->#huỳnh quang<!--]--></span><!--v-if--></span><br><p>Huỳnh quang là gì? Các công bố khoa học về Huỳnh quang</p></a></div><div class="entity-item-container"><a href="/topic/leishmania infantum" class=""><span class="el-tag el-tag--primary el-tag--light" style=""><span class="el-tag__content"><!--[-->#leishmania infantum<!--]--></span><!--v-if--></span><br><p>Leishmania infantum là gì? Công bố về Leishmania infantum</p></a></div><div class="entity-item-container"><a href="/topic/bức xạ nhiệt" class=""><span class="el-tag el-tag--primary el-tag--light" style=""><span class="el-tag__content"><!--[-->#bức xạ nhiệt<!--]--></span><!--v-if--></span><br><p>Bức xạ nhiệt là gì? Các bài nghiên cứu khoa học liên quan</p></a></div><div class="entity-item-container"><a href="/topic/triệu chứng lo âu" class=""><span class="el-tag el-tag--primary el-tag--light" style=""><span class="el-tag__content"><!--[-->#triệu chứng lo âu<!--]--></span><!--v-if--></span><br><p>Triệu chứng lo âu là gì? Các nghiên cứu khoa học liên quan</p></a></div><div class="entity-item-container"><a href="/topic/chất ức chế ăn mòn" class=""><span class="el-tag el-tag--primary el-tag--light" style=""><span class="el-tag__content"><!--[-->#chất ức chế ăn mòn<!--]--></span><!--v-if--></span><br><p>Chất ức chế ăn mòn là gì? Các bài nghiên cứu khoa học</p></a></div><div class="entity-item-container"><a href="/topic/vật liệu xốp" class=""><span class="el-tag el-tag--primary el-tag--light" style=""><span class="el-tag__content"><!--[-->#vật liệu xốp<!--]--></span><!--v-if--></span><br><p>Vật liệu xốp là gì? Các công bố khoa học về Vật liệu xốp</p></a></div><div class="entity-item-container"><a href="/topic/alcaloid" class=""><span class="el-tag el-tag--primary el-tag--light" style=""><span class="el-tag__content"><!--[-->#alcaloid<!--]--></span><!--v-if--></span><br><p>Alcaloid là gì? Các bài báo nghiên cứu khoa học liên quan</p></a></div><div class="entity-item-container"><a href="/topic/đàn ông" class=""><span class="el-tag el-tag--primary el-tag--light" style=""><span class="el-tag__content"><!--[-->#đàn ông<!--]--></span><!--v-if--></span><br><p>Đàn ông là gì? Các bài báo nghiên cứu khoa học liên quan</p></a></div><div class="entity-item-container"><a href="/topic/lưu trữ hydro" class=""><span class="el-tag el-tag--primary el-tag--light" style=""><span class="el-tag__content"><!--[-->#lưu trữ hydro<!--]--></span><!--v-if--></span><br><p>Lưu trữ hydro là gì? Các bài nghiên cứu khoa học liên quan</p></a></div><div class="entity-item-container"><a href="/topic/trạng thái dinh dưỡng" class=""><span class="el-tag el-tag--primary el-tag--light" style=""><span class="el-tag__content"><!--[-->#trạng thái dinh dưỡng<!--]--></span><!--v-if--></span><br><p>Trạng thái dinh dưỡng là gì? 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Các bài nghiên cứu khoa học liên quan","Độ biến động là chỉ số đo lường mức độ dao động của giá tài sản hoặc tỷ suất sinh lợi quanh giá trị trung bình, phản ánh rủi ro thị trường. Biến động lịch sử được tính dựa trên dữ liệu giá quá khứ, còn biến động ngụ ý suy ra từ giá quyền chọn để phản ánh kỳ vọng dao động giá tương lai. ","\u003Ch2>Giới thiệu\u003C/h2>\u003Cp>Độ biến động (volatility) là chỉ báo đo lường mức độ thay đổi về giá hoặc tỷ suất sinh lợi của tài sản tài chính trong một khoảng thời gian nhất định. Trong thị trường tài chính, biến động càng cao đồng nghĩa với rủi ro càng lớn do giá tài sản dao động mạnh, nhưng cũng tạo cơ hội lợi nhuận từ các biến động giá ngắn hạn. Trái lại, độ biến động thấp cho thấy giá ổn định hơn, thích hợp với danh mục bảo toàn vốn.\u003C/p>\u003Cp>Trong kinh tế vĩ mô, biến động không chỉ xuất hiện ở thị trường cổ phiếu mà còn lan tỏa đến hàng hóa, trái phiếu, tỷ giá và lãi suất. Các sự kiện như khủng hoảng tài chính, thay đổi chính sách tiền tệ hoặc tin tức địa chính trị có thể kích hoạt làn sóng biến động mạnh mẽ. Theo CBOE, chỉ số VIX – được gọi là “chỉ số nỗi sợ hãi” – phản ánh biến động ngụ ý của hợp đồng quyền chọn chỉ số S&amp;P 500, cho thấy kỳ vọng thị trường về dao động giá trong 30 ngày tới.\u003C/p>\u003Cp>Trong khoa học dữ liệu và quản trị rủi ro, độ biến động còn là cơ sở để xây dựng mô hình dự báo, định giá quyền chọn và xác định giới hạn tổn thất (VaR, CVaR). Mô hình phân tích chuỗi thời gian như ARCH/GARCH tận dụng tính phân cụm của biến động để dự báo, giúp nhà đầu tư và quản lý danh mục đưa ra quyết định tối ưu. Các công cụ phần mềm tài chính hàng đầu như Bloomberg Terminal hay Reuters Eikon tích hợp phân tích biến động lịch sử và ngụ ý, cung cấp dữ liệu theo thời gian thực.\u003C/p>\u003Ch2>Định nghĩa độ biến động\u003C/h2>\u003Cp>Độ biến động (volatility) được định nghĩa là thước đo mức độ dao động của giá tài sản hoặc tỷ suất sinh lợi quanh một giá trị trung bình. Biến động phản ánh sự không chắc chắn về giá tương lai: dao động càng lớn thì biến động càng cao. Trong thực tế, biến động được hiểu theo hai khái niệm chính là biến động lịch sử và biến động ngụ ý.\u003C/p>\u003Cp>Biến động lịch sử (historical volatility) được tính toán từ dữ liệu giá trong quá khứ bằng cách đo độ lệch chuẩn của tỷ suất sinh lợi trên một khoảng thời gian xác định, thường là 30, 60 hoặc 90 ngày. Phương pháp này dựa trên giả định rằng mô hình biến động trong quá khứ có thể phản ánh phần nào xu hướng trong tương lai, mặc dù không luôn đúng trong điều kiện thị trường thay đổi đột ngột.\u003C/p>\u003Cp>Biến động ngụ ý (implied volatility) là biến động tiềm tàng mà thị trường kỳ vọng, được suy ngẫm từ giá hợp đồng quyền chọn thông qua công thức định giá Black–Scholes hoặc các mô hình tương tự. Khi giá quyền chọn tăng, biến động ngụ ý tăng, cho thấy nhà đầu tư đánh giá khả năng dao động giá trong tương lai cao hơn. CBOE VIX là thước đo biến động ngụ ý của S&amp;P 500 options.\u003C/p>\u003Ch2>Công thức và chỉ số đo lường\u003C/h2>\u003Cp>Độ biến động lịch sử thường được tính bằng độ lệch chuẩn của tỷ suất sinh lợi. Giả sử có N ngày giao dịch và tỷ suất sinh lợi ngày i là ri, trung bình là \\( \\bar r \\), độ lệch chuẩn σ được xác định:\u003C/p>\u003Cp>\u003Cscript type=\"math/tex\">\\sigma = \\sqrt{\\frac{1}{N-1} \\sum_{i=1}^{N} (r_i - \\bar r)^2}\u003C/script>\u003C/p>\u003Cp>Phương sai (variance) là bình phương của độ lệch chuẩn, cho biết sự phân tán bình phương của tỷ suất sinh lợi quanh giá trị trung bình. Hệ số biến động (coefficient of variation, CV) là tỷ lệ giữa độ lệch chuẩn và giá trị trung bình, giúp so sánh độ biến động tương đối giữa các tài sản có mức sinh lợi khác nhau:\u003C/p>\u003Cp>\u003Cscript type=\"math/tex\">\\mathrm{CV} = \\frac{\\sigma}{\\bar r}\u003C/script>\u003C/p>\u003Cul>\u003Cli>\u003Cstrong>Biến động hàng ngày:\u003C/strong> σdaily tính trên dữ liệu ngày giao dịch.\u003C/li>\u003Cli>\u003Cstrong>Biến động hàng năm:\u003C/strong> σannual = σdaily × √252 (252 ngày giao dịch).\u003C/li>\u003Cli>\u003Cstrong>Biến động hàng tháng:\u003C/strong> σmonthly = σdaily × √21 (21 ngày giao dịch).\u003C/li>\u003C/ul>\u003Ch2>Các loại biến động\u003C/h2>\u003Cp>Biến động lịch sử (historical volatility) sử dụng dữ liệu giá quá khứ. Mặc dù dễ tính toán và minh bạch, biến động lịch sử không phản ánh tâm lý thị trường hiện tại hay các yếu tố sự kiện sắp tới. Do đó, nó thường được kết hợp với biến động ngụ ý để phân tích toàn diện hơn.\u003C/p>\u003Cp>Biến động ngụ ý (implied volatility) được tính từ giá hợp đồng quyền chọn. Nếu ký hiệu σimpl là biến động ngụ ý, giá quyền chọn C được định giá theo công thức Black–Scholes:\u003C/p>\u003Cp>\u003Cscript type=\"math/tex\">C = S_0 N(d_1) - K e^{-rT} N(d_2) \\end{script> \u003Cscript type=\"math/tex\"> d_{1,2} = \\frac{\\ln(S_0/K) + (r \\pm \\frac{1}{2}\\sigma_{impl}^2)T}{\\sigma_{impl}\\sqrt{T}}\u003C/script>\u003C/p>\u003Cp>Biến động thực tế (realized volatility) đo lường biến động diễn ra thực sự trong tương lai, tính khi kỳ hạn quyền chọn kết thúc. Trong khi đó, biến động ước tính (model-implied volatility) là biến động được dự báo từ mô hình như GARCH.\u003C/p>\u003Cfigure class=\"table\">\u003Ctable>\u003Cthead>\u003Ctr>\u003Cth>Loại biến động\u003C/th>\u003Cth>Cơ sở dữ liệu\u003C/th>\u003Cth>Ưu điểm\u003C/th>\u003Cth>Nhược điểm\u003C/th>\u003C/tr>\u003C/thead>\u003Ctbody>\u003Ctr>\u003Ctd>Lịch sử\u003C/td>\u003Ctd>Giá quá khứ\u003C/td>\u003Ctd>Dễ tính, minh bạch\u003C/td>\u003Ctd>Không phản ánh kỳ vọng\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>Ngụ ý\u003C/td>\u003Ctd>Giá quyền chọn\u003C/td>\u003Ctd>Phản ánh tâm lý thị trường\u003C/td>\u003Ctd>Phụ thuộc mô hình định giá\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>Thực tế\u003C/td>\u003Ctd>Giá tương lai\u003C/td>\u003Ctd>Đo chính xác biến động đã xảy ra\u003C/td>\u003Ctd>Không dự báo trước được\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>Ước tính\u003C/td>\u003Ctd>Mô hình (GARCH,…)\u003C/td>\u003Ctd>Dự báo được\u003C/td>\u003Ctd>Phải chọn tham số, giả định\u003C/td>\u003C/tr>\u003C/tbody>\u003C/table>\u003C/figure>\u003Ch2>Mô hình dự báo biến động\u003C/h2>\u003Cp>Các mô hình ARCH (Autoregressive Conditional Heteroskedasticity) và GARCH (Generalized ARCH) là phương pháp phổ biến để mô phỏng và dự báo độ biến động theo chuỗi thời gian, được giới thiệu bởi Engle (1982) và Bollerslev (1986). Mô hình GARCH(p,q) mô tả phương sai điều kiện σt2 tại thời điểm t bằng tổ hợp của nhiễu bình phương và phương sai quá khứ:\u003C/p>\u003Cp>\u003Cscript type=\"math/tex\">\\sigma_t^2 = \\alpha_0 + \\sum_{i=1}^p \\alpha_i \\epsilon_{t-i}^2 + \\sum_{j=1}^q \\beta_j \\sigma_{t-j}^2\u003C/script>\u003C/p>\u003Cp>Trong đó εt là nhiễu (residual) của tỷ suất sinh lợi, αi và βj là hệ số ước lượng. Mô hình EGARCH và GJR–GARCH mở rộng GARCH để bắt các hiệu ứng bất đối xứng (asymmetric leverage effect) khi biến động tăng mạnh hơn khi thị trường giảm (\u003Ca href=\"https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1234760\">Bollerslev, 1986\u003C/a>).\u003C/p>\u003Cp>Phương pháp EWMA (Exponentially Weighted Moving Average) đề xuất bởi RiskMetrics Group sử dụng hàm mũ suy giảm trọng số để ưu tiên dữ liệu gần nhất, tính biến động như sau:\u003C/p>\u003Cp>\u003Cscript type=\"math/tex\">\\sigma_t^2 = \\lambda \\sigma_{t-1}^2 + (1 - \\lambda) r_{t-1}^2\u003C/script>\u003C/p>\u003Cp>Trong đó λ (thường đặt ≈0.94) là hệ số suy giảm. EWMA đơn giản, dễ triển khai trong thực tế nhưng không bắt được tính phân cụm dài hạn của biến động như GARCH.\u003C/p>\u003Ch2>Yếu tố ảnh hưởng đến độ biến động\u003C/h2>\u003Cp>Tình trạng thị trường tài chính và kinh tế vĩ mô là nhân tố chủ đạo định hình biến động. Khủng hoảng tài chính như sự kiện “Thứ Sáu Đen” 1987 hay khủng hoảng tiền tệ châu Á 1997 đã tạo ra các đợt dao động giá dữ dội. Chính sách tiền tệ của Ngân hàng Trung ương (lãi suất, chương trình nới lỏng định lượng) cũng tác động mạnh đến kỳ vọng rủi ro và do đó độ biến động.\u003C/p>\u003Cp>Sự kiện địa chính trị như xung đột, bầu cử hoặc thỏa thuận thương mại quốc tế có thể làm thay đổi kỳ vọng lợi nhuận và rủi ro nhanh chóng. Tin tức kinh tế – tài chính (lãi suất, GDP, CPI) công bố định kỳ thường gây “giật” biến động ngắn hạn khi kết quả lệch xa dự báo.\u003C/p>\u003Cul>\u003Cli>\u003Cstrong>Tâm lý nhà đầu tư:\u003C/strong> hiệu ứng bầy đàn (herding) làm tăng biến động trong giai đoạn hoảng loạn.\u003C/li>\u003Cli>\u003Cstrong>Đòn bẩy tài chính:\u003C/strong> sử dụng margin hoặc phái sinh khuếch đại dao động giá.\u003C/li>\u003Cli>\u003Cstrong>Tính thanh khoản:\u003C/strong> thị trường kém thanh khoản thường biến động mạnh hơn cho cùng khối lượng giao dịch.\u003C/li>\u003C/ul>\u003Ch2>Hiện tượng phân cụm biến động\u003C/h2>\u003Cp>Phân cụm biến động (volatility clustering) là đặc tính chuỗi thời gian cho thấy các giai đoạn biến động lớn thường kéo dài, theo sau bởi các giai đoạn biến động thấp. Hiện tượng này lý giải tại sao những thời điểm thị trường hỗn loạn có xu hướng duy trì độ biến động cao trong một khoảng thời gian nhất định.\u003C/p>\u003Cp>Đặc tính này là cơ sở cho mô hình ARCH/GARCH, khi các hệ số α và β phản ánh tính phụ thuộc vào biến động quá khứ. Mô hình Harvey’s Heterogeneous Autoregressive Realized Volatility (HAR–RV) còn phân chia biến động thực tế theo nhiều khung thời gian (ngày, tuần, tháng) để nâng cao độ chính xác dự báo (\u003Ca href=\"https://www.sciencedirect.com/science/article/pii/S0304405X04001207\">Corsi, 2004\u003C/a>).\u003C/p>\u003Ch2>Ứng dụng trong quản trị rủi ro\u003C/h2>\u003Cp>Biến động là thành phần mấu chốt trong đo lường VaR (Value at Risk) và CVaR (Conditional VaR), cho phép đánh giá tổn thất tối đa trong một khoảng thời gian xác định với mức độ tin cậy. VaR được tính theo biến động dự báo và phân phối lợi nhuận giả định:\u003C/p>\u003Cp>\u003Cscript type=\"math/tex\">\\mathrm{VaR}_{\\alpha} = \\mu + \\sigma \\Phi^{-1}(\\alpha)\u003C/script>\u003C/p>\u003Cp>Với μ là kỳ vọng lợi nhuận, σ biến động, Φ−1 hàm ngược phân phối chuẩn và α mức tin cậy. CVaR cung cấp giá trị kỳ vọng của tổn thất vượt quá VaR, đánh giá rủi ro ở phần đuôi phân phối (\u003Ca href=\"https://www.investopedia.com/terms/c/conditional_value_at_risk.asp\">Investopedia\u003C/a>).\u003C/p>\u003Cp>Hedging danh mục với công cụ phái sinh (futures, options) dựa trên biến động ước tính giúp giảm thiểu rủi ro thị trường. Chiến lược delta-hedging sử dụng biến động ngụ ý để điều chỉnh tỷ trọng quyền chọn – cơ sở, hạn chế rủi ro giá trong thời gian thực (\u003Ca href=\"https://www.investopedia.com/terms/d/deltahedging.asp\">Investopedia\u003C/a>).\u003C/p>\u003Ch2>Giám sát và công cụ phân tích\u003C/h2>\u003Cp>Bloomberg Terminal và Refinitiv Eikon cung cấp chỉ số biến động lịch sử và ngụ ý thời gian thực, bản đồ nhiệt (heatmap) theo ngành, theo region và chức năng cảnh báo tự động khi biến động vượt ngưỡng cài đặt. Bộ công cụ này tích hợp mô-đun GARCH, EWMA và Monte Carlo simulation nhằm hỗ trợ phân tích sâu.\u003C/p>\u003Cp>Các thư viện mã nguồn mở Python như “arch” (Kevin Sheppard) và “statsmodels” cho phép xây dựng mô hình GARCH, tính biến động lịch sử và phân cụm. Trong R, gói “rugarch” cung cấp giao diện trực quan để ước lượng đa dạng cấu hình GARCH và kiểm tra hiệu năng dự báo.\u003C/p>\u003Cul>\u003Cli>Python “arch”: \u003Ca href=\"https://pypi.org/project/arch\">https://pypi.org/project/arch\u003C/a>\u003C/li>\u003Cli>R “rugarch”: \u003Ca href=\"https://cran.r-project.org/web/packages/rugarch\">https://cran.r-project.org/web/packages/rugarch\u003C/a>\u003C/li>\u003Cli>Bloomberg VIX: \u003Ca href=\"https://www.bloomberg.com/quote/VIX:IND\">https://www.bloomberg.com/quote/VIX:IND\u003C/a>\u003C/li>\u003C/ul>\u003Ch2>Tài liệu tham khảo\u003C/h2>\u003Cul>\u003Cli>Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. \u003Ci>Econometrica\u003C/i>, 50(4), 987–1007.\u003C/li>\u003Cli>Bollerslev, T. (1986). Generalized autoregressive conditional heteroscedasticity. \u003Ci>Journal of Econometrics\u003C/i>, 31(3), 307–327.\u003C/li>\u003Cli>Corsi, F. (2004). A simple approximate long-memory model of realized volatility. \u003Ci>Journal of Financial Econometrics\u003C/i>, 2(1), 67–101.\u003C/li>\u003Cli>RiskMetrics Group. (1996). Technical Document. JP Morgan.\u003C/li>\u003Cli>Investopedia. “Conditional Value at Risk (CVaR).” \u003Ca href=\"https://www.investopedia.com/terms/c/conditional_value_at_risk.asp\">https://www.investopedia.com/terms/c/conditional_value_at_risk.asp\u003C/a>\u003C/li>\u003Cli>Investopedia. “Delta Hedging.” \u003Ca href=\"https://www.investopedia.com/terms/d/deltahedging.asp\">https://www.investopedia.com/terms/d/deltahedging.asp\u003C/a>\u003C/li>\u003Cli>CBOE. “CBOE Volatility Index (VIX).” \u003Ca href=\"https://www.cboe.com/products/vix-index-volatility\">https://www.cboe.com/products/vix-index-volatility\u003C/a>\u003C/li>\u003Cli>Sheppard, K. (2021). Python “arch” package documentation. \u003Ca href=\"https://pypi.org/project/arch\">https://pypi.org/project/arch\u003C/a>\u003C/li>\u003Cli>Cran Team. “rugarch: Univariate GARCH Models.” \u003Ca href=\"https://cran.r-project.org/web/packages/rugarch\">https://cran.r-project.org/web/packages/rugarch\u003C/a>\u003C/li>\u003C/ul>",{"id":73,"researcherId":22,"name":314,"imageUrl":315},"Nguyễn Ngọc Sơn","https://lh3.googleusercontent.com/a/ACg8ocLGfGsF1nYQqYK5BasTLhNu1dBrBXg2fcEgBNPXJ0p2gqLQnO7i=s96-c",{"id":317,"researcherId":22,"name":318,"imageUrl":319},2681,"Cuong Ta","https://lh3.googleusercontent.com/a/ACg8ocKFuWh0ZD601Hp0_V_2xAK3kIOs20Kyv3V5ZLBo6fwfjyymJYzE=s96-c",[309],"PUBLISHED","2025-07-13T02:21:17.883+00:00","2025-09-10T04:11:24.496+00:00","2025-07-15T01:53:17.556+00:00",101,[327,330,333,336,339,342,345,348,351,354],{"id":328,"title":329},"huỳnh quang","Huỳnh quang là gì? Các công bố khoa học về Huỳnh quang",{"id":331,"title":332},"leishmania infantum","Leishmania infantum là gì? Công bố về Leishmania infantum",{"id":334,"title":335},"bức xạ nhiệt","Bức xạ nhiệt là gì? Các bài nghiên cứu khoa học liên quan",{"id":337,"title":338},"triệu chứng lo âu","Triệu chứng lo âu là gì? Các nghiên cứu khoa học liên quan",{"id":340,"title":341},"chất ức chế ăn mòn","Chất ức chế ăn mòn là gì? Các bài nghiên cứu khoa học",{"id":343,"title":344},"vật liệu xốp","Vật liệu xốp là gì? Các công bố khoa học về Vật liệu xốp",{"id":346,"title":347},"alcaloid","Alcaloid là gì? Các bài báo nghiên cứu khoa học liên quan",{"id":349,"title":350},"đàn ông","Đàn ông là gì? Các bài báo nghiên cứu khoa học liên quan",{"id":352,"title":353},"lưu trữ hydro","Lưu trữ hydro là gì? Các bài nghiên cứu khoa học liên quan",{"id":355,"title":356},"trạng thái dinh dưỡng","Trạng thái dinh dưỡng là gì? Nghiên cứu khoa học liên quan",{"meta":358,"data":360},{"total":359},"1748",[361,567,1706,1970,2605,2889,4035,4365,4514,4619],{"id":362,"createTime":363,"updateTime":364,"relativeEntities":365,"slug":366,"properties":367,"entityType":126,"verifyStatus":382,"verifyTime":363,"verifyNote":383,"syncStatus":384,"languages":385,"translateLanguages":387,"viewCount":23,"primaryUrl":389,"fullTextUrl":22,"authors":390,"publicationType":128,"publisherRelationship":433,"citationCount":506,"citationInfo":507,"publishDate":522,"publishYear":523,"citationAnalyzeStatus":384,"lastCitationAnalyze":22,"indexDatabases":22,"openAccess":22,"references":524,"isForceReanalyzing":19},"55fd0330-c138-46af-b096-7f13f8442dea","2024-09-19T12:10:12.287+00:00","2025-01-17T16:42:24.294+00:00",[],"Polymorphic-transitions-in-single-crystals-A-new-molecular-dynamics-method",{"mag":368,"keywords":370,"openalex":372,"abstract":374,"title":377,"doi":380},{"VOID":369},"2081693079",{"VI":371},"Động lực học phân tử, ứng suất, biến dạng, chuyển biến đa hình, tinh thể đơn, mô hình Ni",{"VOID":373},"W2081693079",{"EN":375,"VI":376},"\u003Cjats:p>A new Lagrangian formulation is introduced. It can be used to make molecular dynamics (MD) calculations on systems under the most general, externally applied, conditions of stress. In this formulation the MD cell shape and size can change according to dynamical equations given by this Lagrangian. This new MD technique is well suited to the study of structural transformations in solids under external stress and at finite temperature. As an example of the use of this technique we show how a single crystal of Ni behaves under uniform uniaxial compressive and tensile loads. This work confirms some of the results of static (i.e., zero temperature) calculations reported in the literature. We also show that some results regarding the stress-strain relation obtained by static calculations are invalid at finite temperature. We find that, under compressive loading, our model of Ni shows a bifurcation in its stress-strain relation; this bifurcation provides a link in configuration space between cubic and hexagonal close packing. It is suggested that such a transformation could perhaps be observed experimentally under extreme conditions of shock.\u003C/jats:p>","\u003Cjats:p> Một dạng thức Lagrangian mới được giới thiệu. Nó có thể được sử dụng để thực hiện các phép tính động lực học phân tử (MD) trên các hệ thống dưới các điều kiện ứng suất bên ngoài tổng quát nhất. Trong dạng thức này, hình dạng và kích thước của ô MD có thể thay đổi theo các phương trình động lực học do Lagrangian này cung cấp. Kỹ thuật MD mới này rất phù hợp để nghiên cứu những biến đổi cấu trúc trong chất rắn dưới ứng suất bên ngoài và ở nhiệt độ hữu hạn. Như một ví dụ cho việc sử dụng kỹ thuật này, chúng tôi cho thấy cách mà một tinh thể đơn của Ni cư xử dưới tải trọng nén và kéo đồng nhất. Công trình này xác nhận một số kết quả của các phép tính tĩnh (tức là, nhiệt độ bằng không) đã được báo cáo trong tài liệu. Chúng tôi cũng chỉ ra rằng một số kết quả liên quan đến mối quan hệ ứng suất-biến dạng thu được từ các phép tính tĩnh là không hợp lệ ở nhiệt độ hữu hạn. Chúng tôi nhận thấy rằng, dưới tải trọng nén, mô hình của chúng tôi đối với Ni cho thấy một điểm phân nhánh trong mối quan hệ ứng suất-biến dạng; điểm phân nhánh này cung cấp một liên kết trong không gian cấu hình giữa sự đóng gói lập phương và đóng gói gần hình lục giác. Chúng tôi gợi ý rằng một sự chuyển biến như vậy có thể được quan sát thực nghiệm dưới các điều kiện sốc cực đoan.",{"EN":378,"VI":379},"Polymorphic transitions in single crystals: A new molecular dynamics method","Chuyển biến đa hình trong tinh thể đơn: Một phương pháp động lực học phân tử mới",{"VOID":381},"10.1063/1.328693","VERIFIED","Auto Verify","PENDING",[386],"EN",[388],"VI","https://pubs.aip.org/jap/article/52/12/7182/9558/Polymorphic-transitions-in-single-crystals-A-new",[391,413],{"id":392,"sortIndex":23,"researcher":22,"roles":393,"affiliations":394,"properties":406},"402c7181-d754-420b-b4d1-a660e70c50d0",[],[395],{"id":396,"sortIndex":23,"affiliation":397,"properties":22},"cce2d3b8-cf11-4fb6-afaf-c7d46d31e810",{"id":398,"createTime":399,"updateTime":400,"relativeEntities":401,"slug":402,"properties":403,"entityType":198,"verifyStatus":384,"verifyTime":22,"verifyNote":22,"syncStatus":384,"languages":22,"translateLanguages":22,"viewCount":23},"b1e2d037-ffa4-42b5-b23c-f62fae13ab77","2023-12-12T20:54:52.335+00:00","2024-12-11T03:15:57.500+00:00",[],"University-of-Trieste-Trieste-Italy",{"title":404},{"VI":405},"University of Trieste, Trieste, Italy",{"openalex":407,"orcid":409,"title":411},{"VOID":408},"A5023487560",{"VOID":410},"https://orcid.org/0000-0001-6550-3272",{"EN":412},"Michele Parrinello",{"id":414,"sortIndex":73,"researcher":22,"roles":415,"affiliations":416,"properties":428},"0c60687b-3067-4484-ba43-b3d956ceffbc",[],[417],{"id":418,"sortIndex":23,"affiliation":419,"properties":22},"eede928c-d36b-4932-9039-fc58f0d43c1b",{"id":420,"createTime":421,"updateTime":422,"relativeEntities":423,"slug":424,"properties":425,"entityType":198,"verifyStatus":384,"verifyTime":22,"verifyNote":22,"syncStatus":384,"languages":22,"translateLanguages":22,"viewCount":23},"e9c245ca-e262-4fcb-ac3a-6fc8749a6f90","2023-12-13T20:17:24.094+00:00","2025-02-02T02:32:11.250+00:00",[],"Argonne-National-Laboratory-Argonne-Illinois-60439",{"title":426},{"VI":427},"Argonne National Laboratory, Argonne, Illinois, 60439",{"openalex":429,"title":431},{"VOID":430},"A5047190718",{"EN":432},"A. Rahman",{"url":22,"publisher":434,"properties":499},{"id":435,"createTime":436,"updateTime":437,"relativeEntities":438,"slug":439,"properties":440,"entityType":61,"verifyStatus":384,"verifyTime":22,"verifyNote":22,"syncStatus":384,"languages":22,"translateLanguages":22,"viewCount":23,"subjectFields":451,"manageAffiliations":452,"indexDatabases":453,"url":491,"thumbnailPath":22,"statistic":492,"gsStatistic":22,"type":22,"analyzePriority":22},"4f4d5367-807b-4c5c-be6d-362f57a66e16","2023-05-29T10:56:26.040+00:00","2025-02-11T10:09:22.916+00:00",[],"Journal-of-Applied-Physics",{"country":441,"issn":443,"introduce":445,"eissn":447,"title":449},{"VOID":442},"US",{"VOID":444},"10897550",{"EN":446},"The Journal of Applied Physics (JAP) is an influential international journal publishing significant new experimental and theoretical results of applied physics research. Topics covered in JAP are diverse and reflect the most current applied physics research, including: Dielectrics, ferroelectrics, and multiferroics- Electrical discharges, plasmas, and plasma-surface interactions- Emerging, interdisciplinary, and other fields of applied physics- Magnetism, spintronics, and superconductivity- Organic-Inorganic systems, including organic electronics- Photonics, plasmonics, photovoltaics, lasers, optical materials, and phenomena- Physics of devices and sensors- Physics of materials, including electrical, thermal, mechanical and other properties- Physics of matter under extreme conditions- Physics of nanoscale and low-dimensional systems, including atomic and quantum phenomena- Physics of semiconductors- Soft matter, fluids, and biophysics- Thin films, interfaces, and surfaces",{"VOID":448},"00218979",{"EN":450},"Journal of Applied Physics",[],[],[454,473],{"id":455,"indexDatabase":456,"url":470,"indexYears":22,"academicFieldIds":471},"c7430df3-4bae-4434-ac1f-1dcc21db6227",{"id":457,"createTime":458,"updateTime":459,"relativeEntities":460,"label":461,"description":463,"key":466,"publicationTags":467,"standard":22},"a4921856-b128-4d9f-8f1f-e80813d3bbd4","2023-05-22T09:59:31.026+00:00","2025-01-14T09:58:12.199+00:00",[],{"EN":462,"VI":462},"ISI/SCIE - Science Citation Index Expanded",{"VI":464,"EN":465},"Cơ sở dữ liệu SCIE","SCIE database","scie",[468,469],"SCIE","ISI","https://mjl.clarivate.com/search-results?issn=0021-8979",[472],"0a89cee9-2df6-4b14-8fcb-700fd0044c25",{"id":474,"indexDatabase":475,"url":487,"indexYears":488,"academicFieldIds":489},"1d216891-dfe1-4055-9212-cba7e09d34a2",{"id":476,"createTime":477,"updateTime":478,"relativeEntities":479,"label":480,"description":482,"key":484,"publicationTags":485,"standard":22},"3c7051d4-eb7d-4c57-a56b-36fc74c5d1e9","2023-05-22T09:57:18.509+00:00","2025-07-10T09:55:58.024+00:00",[],{"EN":481,"VI":481},"Scopus - Elsevier",{"EN":481,"VI":483},"Cơ sở dữ liệu Scopus thuộc Elsevier","scopus",[486],"SCOPUS","https://www.scopus.com/sourceid/28132","1931-2023",[490],"0c2541d6-7567-4793-aad8-840b3d33f5e0","https://aip.scitation.org/journal/jap",{"impactFactor":23,"impactFactorByYear":493,"i10Index":82,"i10IndexLast5Year":23,"totalPublication":82,"totalPublicationByYear":494,"totalCitation":495,"totalCitationByYear":496,"totalCitationPerPublication":497,"totalCitationPerPublicationByYear":498,"hindexLast5Year":82,"hindex":82},{"2012":92,"2013":82},{"2011":82},26,{"2011":495},13,{"2011":497},{"volume":500,"pages":502,"issue":504},{"VOID":501},"52",{"VOID":503},"7182-7190",{"VOID":505},"12",16114,{"total":506,"publishYear":22,"statisticByYear":508},{"2012":509,"2013":510,"2014":511,"2015":512,"2016":513,"2017":514,"2018":515,"2019":516,"2020":517,"2021":518,"2022":519,"2023":520,"2024":521},328,381,494,621,762,896,1004,1123,1478,1791,1842,1955,1305,"1981-12-01",1981,[525,529,533,537,541,545,547,551,555,557,559,561,563,565],{"id":22,"text":526,"url":22,"identifiers":527},"1976, Phys. Rev. B, 14, 1758, 10.1103/PhysRevB.14.1758",{"doi":528},"10.1103/PhysRevB.14.1758",{"id":22,"text":530,"url":22,"identifiers":531},"1980, Phys. Rev. Lett., 45, 1196, 10.1103/PhysRevLett.45.1196",{"doi":532},"10.1103/PhysRevLett.45.1196",{"id":22,"text":534,"url":22,"identifiers":535},"1973, J. Appl. Phys., 44, 3825, 10.1063/1.1662857",{"doi":536},"10.1063/1.1662857",{"id":22,"text":538,"url":22,"identifiers":539},"1973, J. Appl. Phys., 44, 3833, 10.1063/1.1662858",{"doi":540},"10.1063/1.1662858",{"id":22,"text":542,"url":22,"identifiers":543},"1980, Phys. Rev. Lett., 44, 277, 10.1103/PhysRevLett.44.277",{"doi":544},"10.1103/PhysRevLett.44.277",{"id":22,"text":15,"url":22,"identifiers":546},{},{"id":22,"text":548,"url":22,"identifiers":549},"1980, J. Chem. Phys., 72, 2384, 10.1063/1.439486",{"doi":550},"10.1063/1.439486",{"id":22,"text":552,"url":22,"identifiers":553},"1980, Phys. Rev. A, 22, 1690, 10.1103/PhysRevA.22.1690",{"doi":554},"10.1103/PhysRevA.22.1690",{"id":22,"text":15,"url":22,"identifiers":556},{},{"id":22,"text":15,"url":22,"identifiers":558},{},{"id":22,"text":15,"url":22,"identifiers":560},{},{"id":22,"text":15,"url":22,"identifiers":562},{},{"id":22,"text":15,"url":22,"identifiers":564},{},{"id":22,"text":15,"url":22,"identifiers":566},{},{"id":568,"createTime":569,"updateTime":570,"relativeEntities":571,"slug":572,"properties":573,"entityType":126,"verifyStatus":382,"verifyTime":569,"verifyNote":383,"syncStatus":384,"languages":590,"translateLanguages":591,"viewCount":23,"primaryUrl":592,"fullTextUrl":22,"authors":593,"publicationType":128,"publisherRelationship":1298,"citationCount":1584,"citationInfo":1585,"publishDate":1597,"publishYear":1598,"citationAnalyzeStatus":384,"lastCitationAnalyze":22,"indexDatabases":22,"openAccess":22,"references":1599,"isForceReanalyzing":19},"8f078e18-1d46-4b3f-8561-26d47f39ec8b","2024-08-31T17:05:25.417+00:00","2024-12-25T21:33:38.083+00:00",[],"Mutation-in-the-%CE%B1-Synuclein-Gene-Identified-in-Families-with-Parkinson-s-Disease",{"mag":574,"keywords":576,"openalex":578,"abstract":580,"title":583,"pm":586,"doi":588},{"VOID":575},"2150656456",{"VI":577},"Bệnh Parkinson, Đột biến gen, α-synuclein, Thần kinh học, Di truyền học, Tính dẻo thần kinh, Di truyền trội trên nhiễm sắc thể thường, Nhiễm sắc thể số 4, Gia tăng phát tích",{"VOID":579},"W2150656456",{"EN":581,"VI":582},"\u003Cjats:p>Parkinson's disease (PD) is a common neurodegenerative disorder with a lifetime incidence of approximately 2 percent. 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Một đột biến đã được xác định trong gen α-synuclein, mã hóa cho một protein tiền synapse được cho là có liên quan đến tính dẻo thần kinh, trong gia đình Ý và ba gia đình không có quan hệ quen biết có nguồn gốc Hy Lạp với di truyền trội trên nhiễm sắc thể thường đối với kiểu hình PD. 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Di Iorio, Instituto di Scienze Neurologiche, Faculta di Medicina, Seconda Universita degli Studi di Napoli, Naples, Italy.",{"id":620,"sortIndex":92,"affiliation":621,"properties":22},"d61c58f7-ba46-4e33-9fa9-86247e19f25f",{"id":622,"createTime":623,"updateTime":623,"relativeEntities":624,"slug":625,"properties":626,"entityType":198,"verifyStatus":384,"verifyTime":22,"verifyNote":22,"syncStatus":384,"languages":22,"translateLanguages":22,"viewCount":23},"57eb6719-ba26-4d02-b2c5-8c699afa0e5c","2024-08-31T17:05:25.440+00:00",[],"T-Papapetropoulos-and-A-Athanassiadou-University-of-Patras-Medical-School-Patras-Greece-",{"title":627},{"EN":628},"T. Papapetropoulos and A. 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Parkinson An Essay on the Shaking Palsy (Whitingham and Rowland London 1817); W. R. Gowers A Manual of Diseases of the Nervous System (Blakiston Philadelphia PA ed. 2 1893) pp. 6366–6657.",{},{"id":22,"text":1604,"url":22,"identifiers":1605},"Lazarrini A. M., et al., Neurology 44, 499 (1994).",{"doi":1606},"10.1212/WNL.44.3_Part_1.499",{"id":22,"text":1608,"url":22,"identifiers":1609},"Golbe L. I., et al., Ann. Neurol. 27, 276 (1990);",{"doi":1610},"10.1002/ana.410270309",{"id":22,"text":1612,"url":22,"identifiers":1613},"10.1126/science.274.5290.1197",{"doi":1612},{"id":22,"text":1615,"url":22,"identifiers":1616},"Uèda K., et al., Proc. Natl. Acad. Sci. U.S.A. 90, 11282 (1993).",{"doi":1617},"10.1073/pnas.90.23.11282",{"id":22,"text":1619,"url":22,"identifiers":1620},"Chen X., et al., Genomics 26, 425 (1995);",{"doi":1621},"10.1016/0888-7543(95)80237-G",{"id":22,"text":1623,"url":22,"identifiers":1624},"Shitasaki Y., et al., Cytogenet. Cell. Genet. 71, 54 (1995).",{"doi":1625},"10.1159/000134061",{"id":22,"text":1627,"url":22,"identifiers":1628},"E. Leroy et al. in preparation; C. Lavedan et al. in preparation; M. Polymeropoulos et al. in preparation.",{},{"id":22,"text":1630,"url":22,"identifiers":1631},"DNA samples were collected after informed consent. For mutation analysis genomic DNA was amplified with primer 3 (5′-GCTAATCAGCAATTTAAGGCTAG-3′) and primer 13 (5′-GATATGTTCTTAGATGCTCAG-3′) of the DNA sequence (GenBank ID U46898) under standard PCR conditions. Sequence analysis was performed with the Perkin-Elmer dye terminator cycle sequencing kit on an ABI 373 fluorescent sequencer (ABI Foster City CA). Restriction digestion was done after the PCR with Tsp45 I according to the manufacturer's protocol (New England Biolabs Beverly MA). The digested PCR products were separated by electrophoresis on a 6% Visigel (Stratagene La Jolla CA) and visualized by ethidium bromide staining. Pedigree structures in Fig. 2 have been slightly modified to protect patient confidentiality.",{},{"id":22,"text":1633,"url":22,"identifiers":1634},"Total RNA was extracted from the lymphoblastoid cell line of an affected individual and first-strand synthesis was performed by oligo (dT) priming (Gibco-BRL Gaithersburg MD). Primer 1F: (5′-ACGACAGTGTGGTGTAAAGG-3′) and primer 13R 5′-AACATCTGTCAGCAGATCTC-3′ corresponding to nucleotides 21 to 40 and 520 to 501 of the published sequence were used to amplify a product of 500 bp containing the mutation nucleotide 209. PCR products were subjected to restriction digestion by Tsp45 I (5). The mutation at nucleotide 209 creates a novel Tsp45 I site (Fig. 1) so that the normal allele can be cut into four fragments of 249 218 24 and 9 bp whereas the mutant allele will have five fragments of 249 185 33 24 and 9 bp (Fig. 3). Size standards used were the 100-bp ladder as provided by Gibco-BRL (Gaithersburg MD).",{},{"id":22,"text":1636,"url":22,"identifiers":1637},"Iwai A., et al., Biochemistry 15, 10139 (1995);",{"doi":1638},"10.1021/bi00032a006",{"id":22,"text":1640,"url":22,"identifiers":1641},"Weinreb P. H., et al., ibid. 29, 13709 (1996);",{},{"id":22,"text":1643,"url":22,"identifiers":1644},"Jensen P. H., et al., Biochem. J. 315, 91 (1995);",{"doi":1645},"10.1042/bj3100091",{"id":22,"text":1647,"url":22,"identifiers":1648},"Jensen P. H., et al., ibid. 323, 539 (1997).",{},{"id":22,"text":1650,"url":22,"identifiers":1651},"Maroteaux L., Scheller R. H., Brain Res. Mol. Brain. Res. 11, 335 (1991).",{"doi":1652},"10.1016/0169-328X(91)90043-W",{"id":22,"text":1654,"url":22,"identifiers":1655},"Doty R. L., et al., Ann. Neurol. 32, 97 (1992);",{"doi":1656},"10.1002/ana.410320116",{"id":22,"text":1658,"url":22,"identifiers":1659},"Pearce R. K., Hawkes C. H., Daniel S. E., Mov. Disord. 10, 283 (1995).",{"doi":1660},"10.1002/mds.870100309",{"id":22,"text":1662,"url":22,"identifiers":1663},"George J. M., et al., Neuron 15, 361 (1995).",{"doi":1664},"10.1016/0896-6273(95)90040-3",{"id":22,"text":1666,"url":22,"identifiers":1667},"L. Maroteaux J. T. Campanelli R. H. Scheller J. 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I., et al., Nature 376, 775 (1995).",{"doi":1695},"10.1038/376775a0",{"id":22,"text":1697,"url":22,"identifiers":1698},"Hsiao K., et al., Nature 338, 342 (1989).",{"doi":1699},"10.1038/338342a0",{"id":22,"text":1701,"url":22,"identifiers":1702},"Abbreviations for the amino acid residues are: A Ala; C Cys; D Asp; E Glu; F Phe; G Gly; H His; I Ile; K Lys; L Leu; M Met; N Asn; P Pro; Q Gln; R Arg; S Ser; T Thr; V Val; W Trp; and Y Try.",{},{"id":22,"text":1704,"url":22,"identifiers":1705},"The authors would like to thank V. V. McKoy and Y. Chen for technical assistance V. Bonavita for sample collection Z. Hall for his continuing encouragement and support the NINDS intramural research program for resources and F. Collins and H. Varmus for critical review of the manuscript.",{},{"id":1707,"createTime":1708,"updateTime":1709,"relativeEntities":1710,"slug":1711,"properties":1712,"entityType":126,"verifyStatus":382,"verifyTime":1708,"verifyNote":383,"syncStatus":384,"languages":1729,"translateLanguages":1730,"viewCount":23,"primaryUrl":1731,"fullTextUrl":22,"authors":1732,"publicationType":128,"publisherRelationship":1804,"citationCount":1897,"citationInfo":1898,"publishDate":1912,"publishYear":1913,"citationAnalyzeStatus":384,"lastCitationAnalyze":22,"indexDatabases":22,"openAccess":22,"references":1914,"isForceReanalyzing":19},"f68a8582-2b2d-44c5-8fd2-fc6346ed5857","2024-09-26T10:22:23.218+00:00","2024-12-26T06:51:53.022+00:00",[],"Normalization-of-Real-Time-Quantitative-Reverse-Transcription-PCR-Data-A-Model-Based-Variance-Estimation-Approach-to-Identify-Genes-Suited-for-Normalization-Applied-to-Bladder-and-Colon-Cancer-Data-Sets",{"mag":1713,"keywords":1715,"openalex":1717,"abstract":1719,"title":1722,"pm":1725,"doi":1727},{"VOID":1714},"2105423509",{"VI":1716},"PCR, Sao chép ngược, Biểu hiện gene, Bình thường hóa, Phương pháp dựa trên mô hình, Ung thư ruột kết, Ung thư bàng quang, Biến đổi biểu hiện, Gene kiểm soát, Ứng cử viên bình thường hóa.",{"VOID":1718},"W2105423509",{"EN":1720,"VI":1721},"\u003Cjats:title>Abstract\u003C/jats:title>\n \u003Cjats:p>Accurate normalization is an absolute prerequisite for correct measurement of gene expression. For quantitative real-time reverse transcription-PCR (RT-PCR), the most commonly used normalization strategy involves standardization to a single constitutively expressed control gene. However, in recent years, it has become clear that no single gene is constitutively expressed in all cell types and under all experimental conditions, implying that the expression stability of the intended control gene has to be verified before each experiment. We outline a novel, innovative, and robust strategy to identify stably expressed genes among a set of candidate normalization genes. The strategy is rooted in a mathematical model of gene expression that enables estimation not only of the overall variation of the candidate normalization genes but also of the variation between sample subgroups of the sample set. Notably, the strategy provides a direct measure for the estimated expression variation, enabling the user to evaluate the systematic error introduced when using the gene. In a side-by-side comparison with a previously published strategy, our model-based approach performed in a more robust manner and showed less sensitivity toward coregulation of the candidate normalization genes. We used the model-based strategy to identify genes suited to normalize quantitative RT-PCR data from colon cancer and bladder cancer. These genes are UBC, GAPD, and TPT1 for the colon and HSPCB, TEGT, and ATP5B for the bladder. The presented strategy can be applied to evaluate the suitability of any normalization gene candidate in any kind of experimental design and should allow more reliable normalization of RT-PCR data.\u003C/jats:p>","\u003Cjats:title>Tóm tắt\u003C/jats:title> \u003Cjats:p>Bình thường hóa chính xác là điều kiện tiên quyết tuyệt đối để đo lường đúng biểu hiện gene. Đối với PCR sao chép ngược định lượng thời gian thực (RT-PCR), chiến lược bình thường hóa phổ biến nhất bao gồm tiêu chuẩn hóa một gene kiểm soát được biểu hiện liên tục. Tuy nhiên, trong những năm gần đây, đã trở nên rõ ràng rằng không có gene nào được biểu hiện liên tục ở tất cả các loại tế bào và dưới mọi điều kiện thí nghiệm, ngụ ý rằng sự ổn định biểu hiện của gene kiểm soát dự kiến phải được xác minh trước mỗi thí nghiệm. Chúng tôi đã trình bày một chiến lược mới, sáng tạo và mạnh mẽ để xác định các gene được biểu hiện ổn định trong một tập hợp các gene ứng cử viên để bình thường hóa. Chiến lược này bắt nguồn từ một mô hình toán học về biểu hiện gene cho phép ước lượng không chỉ sự biến đổi tổng thể của các gene nghị biểu bình thường mà còn sự biến đổi giữa các nhóm mẫu bộ của tập hợp mẫu. Đáng chú ý, chiến lược này cung cấp một thước đo trực tiếp cho sự biến đổi biểu hiện ước tính, cho phép người dùng đánh giá lỗi hệ thống được tạo ra khi sử dụng gene này. Trong một so sánh trực tiếp với một chiến lược đã được công bố trước đó, cách tiếp cận dựa trên mô hình của chúng tôi có hiệu suất mạnh mẽ hơn và ít nhạy cảm hơn đối với điều chỉnh đồng biến của các gene bình thường hóa ứng cử viên. Chúng tôi đã sử dụng chiến lược dựa trên mô hình để xác định các gene phù hợp để bình thường hóa dữ liệu RT-PCR định lượng từ ung thư ruột kết và ung thư bàng quang. Các gene này bao gồm UBC, GAPD, và TPT1 cho ruột kết và HSPCB, TEGT, và ATP5B cho bàng quang. Chiến lược được trình bày có thể được áp dụng để đánh giá độ thích hợp của bất kỳ ứng cử viên gene bình thường hóa trong bất kỳ loại thiết kế thí nghiệm nào và nên cho phép bình thường hóa dữ liệu RT-PCR đáng tin cậy hơn. \u003C/jats:p>",{"EN":1723,"VI":1724},"Normalization of Real-Time Quantitative Reverse Transcription-PCR Data: A Model-Based Variance Estimation Approach to Identify Genes Suited for Normalization, Applied to Bladder and Colon Cancer Data Sets","Bình Thường Hoá Dữ Liệu PCR Sao Chép Ngược Định Lượng Thời Gian Thực: Cách Tiếp Cận Ước Tính Biến Động Dựa Trên Mô Hình Để Xác Định Các Gene Thích Hợp Cho Bình Thường Hoá, Áp Dụng Cho Các Bộ Dữ Liệu Ung Thư Bàng Quang và Ruột Kết",{"VOID":1726},"15289330",{"VOID":1728},"10.1158/0008-5472.can-04-0496",[386],[388],"https://aacrjournals.org/cancerres/article/64/15/5245/511517/Normalization-of-Real-Time-Quantitative-Reverse",[1733,1765,1782],{"id":1734,"sortIndex":73,"researcher":22,"roles":1735,"affiliations":1736,"properties":1758},"0491c3b0-88df-4091-8bda-10f597320887",[],[1737,1748],{"id":1738,"sortIndex":73,"affiliation":1739,"properties":22},"884b23bf-218e-477d-9536-73e79701694e",{"id":1740,"createTime":1741,"updateTime":1742,"relativeEntities":1743,"slug":1744,"properties":1745,"entityType":198,"verifyStatus":384,"verifyTime":22,"verifyNote":22,"syncStatus":384,"languages":22,"translateLanguages":22,"viewCount":23},"039838f8-d277-44cc-a6b4-0b601772520a","2024-09-26T10:22:23.254+00:00","2025-06-11T16:55:29.996+00:00",[],"Molecular-Diagnostic-Laboratory-Department-of-Clinical-Biochemistry-Aarhus-University-Hospital-Aarhus-N-Denmark-and-N-Department-of-Theoretical-Statistics-Department-of-Mathematical-Sciences-Aarhus-University-Aarhus-C-Denmark",{"title":1746},{"EN":1747},"Molecular Diagnostic Laboratory, Department of Clinical Biochemistry, Aarhus University Hospital, Aarhus N, Denmark, and #N#Department of Theoretical Statistics, Department of Mathematical Sciences, Aarhus University, Aarhus C, Denmark",{"id":1749,"sortIndex":23,"affiliation":1750,"properties":22},"0a7b1e6b-acf5-4353-8083-5018a97e602c",{"id":1751,"createTime":1752,"updateTime":1752,"relativeEntities":1753,"slug":1754,"properties":1755,"entityType":198,"verifyStatus":384,"verifyTime":22,"verifyNote":22,"syncStatus":384,"languages":22,"translateLanguages":22,"viewCount":23},"7e6f9957-017b-4adb-8d4a-1b2d2523c0fe","2024-09-26T10:22:23.250+00:00",[],"2Department-of-Theoretical-Statistics-Department-of-Mathematical-Sciences-Aarhus-University-Aarhus-C-Denmark",{"title":1756},{"EN":1757},"2Department of Theoretical Statistics, Department of Mathematical Sciences, Aarhus University, Aarhus C, Denmark",{"openalex":1759,"orcid":1761,"title":1763},{"VOID":1760},"A5073578961",{"VOID":1762},"https://orcid.org/0000-0002-8776-5764",{"EN":1764},"Jens Ledet Jensen",{"id":1766,"sortIndex":82,"researcher":22,"roles":1767,"affiliations":1768,"properties":1775},"7ca86858-1d01-454f-808b-cf378f240007",[],[1769],{"id":1770,"sortIndex":23,"affiliation":1771,"properties":22},"fa54a9cb-6345-4b44-b577-a812f3c2b81a",{"id":1740,"createTime":1741,"updateTime":1742,"relativeEntities":1772,"slug":1744,"properties":1773,"entityType":198,"verifyStatus":384,"verifyTime":22,"verifyNote":22,"syncStatus":384,"languages":22,"translateLanguages":22,"viewCount":23},[],{"title":1774},{"EN":1747},{"openalex":1776,"orcid":1778,"title":1780},{"VOID":1777},"A5104110128",{"VOID":1779},"https://orcid.org/0000-0001-7673-5554",{"EN":1781},"Torben F. 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To this end, we used DNA microarrays and samples from yeast cultures synchronized by three independent methods: α factor arrest, elutriation, and arrest of a cdc15 temperature-sensitive mutant. Using periodicity and correlation algorithms, we identified 800 genes that meet an objective minimum criterion for cell cycle regulation. In separate experiments, designed to examine the effects of inducing either the G1 cyclin Cln3p or the B-type cyclin Clb2p, we found that the mRNA levels of more than half of these 800 genes respond to one or both of these cyclins. Furthermore, we analyzed our set of cell cycle–regulated genes for known and new promoter elements and show that several known elements (or variations thereof) contain information predictive of cell cycle regulation. A full description and complete data sets are available at http://cellcycle-www.stanford.edu\u003C/jats:p>","\u003Cjats:p>Chúng tôi đã tìm cách tạo ra một danh mục đầy đủ các gen của nấm men có mức độ phiên mã thay đổi theo chu kỳ trong chu kỳ tế bào. Để đạt được mục tiêu này, chúng tôi sử dụng microarray DNA và các mẫu từ các nền nuôi cấy nấm men được đồng bộ hóa bằng ba phương pháp độc lập: dừng bằng yếu tố α, phương pháp tách lọc, và dừng đồng bộ một đột biến nhạy với nhiệt độ cdc15. Sử dụng các thuật toán chu kỳ và tương quan, chúng tôi đã xác định 800 gen đáp ứng tiêu chí tối thiểu khách quan về điều hòa chu kỳ tế bào. Trong các thí nghiệm riêng biệt, được thiết kế để kiểm tra tác dụng của việc kích thích cyclin G1 Cln3p hoặc cyclin loại B Clb2p, chúng tôi phát hiện ra rằng mức mRNA của hơn một nửa số gen này phản ứng với một hoặc cả hai loại cyclin này. Hơn nữa, chúng tôi đã phân tích tập hợp gen điều hòa chu kỳ tế bào của mình để tìm các phần tử khởi động đã biết và mới và cho thấy rằng nhiều phần tử được biết đến (hoặc biến thể của chúng) chứa thông tin dự đoán về điều hòa chu kỳ tế bào. 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Phân tích tự động bằng máy tính đã cung cấp mật độ quang phổ công suất tự hồi quy, cũng như số lượng và công suất tương đối của các thành phần riêng lẻ. Mật độ quang phổ công suất của độ biến thiên khoảng R-R chứa hai thành phần chính: một tần số cao khoảng 0,25 Hz và một tần số thấp khoảng 0,1 Hz, với tỷ lệ tần số thấp: cao được chuẩn hóa là 3,6 +/- 0,7. Khi nghiêng, thành phần tần số thấp trở nên chiếm ưu thế (90 +/- 1%) với tỷ lệ tần số thấp: cao là 21 +/- 4. Ức chế thụ thể beta-adrenergic cấp tính (0,2 mg/kg propranolol IV) đã làm tăng độ biến thiên ở trạng thái nghỉ và làm giảm đáng kể sự gia tăng của tần số thấp và tỷ lệ tần số thấp: cao do nghiêng gây ra. Ức chế thụ thể beta-adrenergic mạn tính (0,6 mg/kg propranolol bằng đường uống, ba lần/ngày) đã giảm tần số thấp và tăng tần số cao ở trạng thái nghỉ, đồng thời hạn chế sự gia tăng tỷ lệ tần số thấp: cao do nghiêng gây ra. Thở có kiểm soát đã khiến tăng rõ rệt thành phần tần số cao ở trạng thái nghỉ, với sự giảm của thành phần tần số thấp và tỷ lệ tần số thấp: cao (0,7 +/- 0,1); trong quá trình nghiêng, sự gia tăng tỷ lệ tần số thấp: cao (8,3 +/- 1,6) nhỏ hơn đáng kể. Trong bảy chủ thể bổ sung mà áp lực động mạch có độ chính xác cao được ghi lại, sự biến thiên của khoảng R-R và áp lực động mạch đã được kiểm tra ở trạng thái nghỉ và trong quá trình nghiêng. Hơn nữa, mật độ quang phổ công suất của độ biến thiên áp lực động mạch chứa hai thành phần chính, với tỷ lệ tần số thấp: cao ở trạng thái nghỉ là 2,8 +/- 0,7, tỷ lệ này trở thành 17 +/- 5 khi nghiêng. Các thành phần mật độ quang phổ công suất này tương tự về mặt số học với những gì quan sát thấy ở độ biến thiên R-R. Do đó, các nghiên cứu xâm lấn và không xâm lấn đã cung cấp kết quả tương tự. Thông tin trực tiếp hơn về vai trò của các dây thần kinh giao cảm trên độ biến thiên R-R và áp lực động mạch được thu được từ một nhóm thí nghiệm trên chó tỉnh trước và sau khi thực hiện phẫu thuật đoạn bỏ tĩnh mạch hai bên. Trong điều kiện kiểm soát, tần số cao là thành phần chủ yếu và tần số thấp rất nhỏ hoặc không có, do sự chiếm ưu thế của giai điệu phó giao cảm. Trong một sự giảm 9% áp lực động mạch đạt được bằng nitroglycerin IV, có một sự gia tăng đáng kể của tần số thấp, là kết quả của sự kích hoạt giao cảm phản xạ. (TÓM TẮT ĐÃ BỊ CẮT NGẮT TẠI 400 TỪ)\u003C/jats:p>","\u003Cjats:p>In 57 normal subjects (age 20-60 years), we analyzed the spontaneous beat-to-beat oscillation in R-R interval during control recumbent position, 90 degrees upright tilt, controlled respiration (n = 16) and acute (n = 10) and chronic (n = 12) beta-adrenergic receptor blockade. Automatic computer analysis provided the autoregressive power spectral density, as well as the number and relative power of the individual components. The power spectral density of R-R interval variability contained two major components in power, a high frequency at approximately 0.25 Hz and a low frequency at approximately 0.1 Hz, with a normalized low frequency:high frequency ratio of 3.6 +/- 0.7. With tilt, the low-frequency component became largely predominant (90 +/- 1%) with a low frequency:high frequency ratio of 21 +/- 4. Acute beta-adrenergic receptor blockade (0.2 mg/kg IV propranolol) increased variance at rest and markedly blunted the increase in low frequency and low frequency:high frequency ratio induced by tilt. Chronic beta-adrenergic receptor blockade (0.6 mg/kg p.o. propranolol, t.i.d.), in addition, reduced low frequency and increased high frequency at rest, while limiting the low frequency:high frequency ratio increase produced by tilt. Controlled respiration produced at rest a marked increase in the high-frequency component, with a reduction of the low-frequency component and of the low frequency:high frequency ratio (0.7 +/- 0.1); during tilt, the increase in the low frequency:high frequency ratio (8.3 +/- 1.6) was significantly smaller. In seven additional subjects in whom direct high-fidelity arterial pressure was recorded, simultaneous R-R interval and arterial pressure variabilities were examined at rest and during tilt. Also, the power spectral density of arterial pressure variability contained two major components, with a relative low frequency:high frequency ratio at rest of 2.8 +/- 0.7, which became 17 +/- 5 with tilt. These power spectral density components were numerically similar to those observed in R-R variability. Thus, invasive and noninvasive studies provided similar results. More direct information on the role of cardiac sympathetic nerves on R-R and arterial pressure variabilities was derived from a group of experiments in conscious dogs before and after bilateral stellectomy. Under control conditions, high frequency was predominant and low frequency was very small or absent, owing to a predominant vagal tone. During a 9% decrease in arterial pressure obtained with IV nitroglycerin, there was a marked increase in low frequency, as a result of reflex sympathetic activation.(ABSTRACT TRUNCATED AT 400 WORDS)\u003C/jats:p>",{"VI":2621,"EN":2622},"Phân tích quang phổ công suất của độ biến thiên nhịp tim và áp lực động mạch như một dấu hiệu của sự tương tác giữa hệ giao cảm và phó giao cảm ở người và chó tỉnh.","Power spectral analysis of heart rate and arterial pressure variabilities as a marker of sympatho-vagal interaction in man and conscious dog.",{"VOID":2624},"2874900",{"VOID":2626},"10.1161/01.res.59.2.178","2024-10-03T06:02:28.344+00:00",[386],[388],"https://www.ahajournals.org/doi/10.1161/01.RES.59.2.178",[2632,2654,2676,2695,2722,2737,2752,2774,2789,2804],{"id":2633,"sortIndex":680,"researcher":22,"roles":2634,"affiliations":2635,"properties":2647},"722887f7-f348-42f0-8dbd-7af4f85e346d",[],[2636],{"id":2637,"sortIndex":23,"affiliation":2638,"properties":22},"cc8206cc-ef79-49f8-8469-948a926129a2",{"id":2639,"createTime":2640,"updateTime":2641,"relativeEntities":2642,"slug":2643,"properties":2644,"entityType":198,"verifyStatus":384,"verifyTime":22,"verifyNote":22,"syncStatus":384,"languages":22,"translateLanguages":22,"viewCount":23},"ac263220-9207-4c69-94cd-b7f260cb4d53","2024-04-13T21:24:43.549+00:00","2024-11-25T23:09:20.022+00:00",[],"Fondazione-Istituto-Auxologico-Italiano",{"title":2645},{"EN":2646},"Fondazione Istituto Auxologico Italiano",{"openalex":2648,"orcid":2650,"title":2652},{"VOID":2649},"A5062215355",{"VOID":2651},"https://orcid.org/0000-0002-4424-1565",{"EN":2653},"Gabriella Malfatto",{"id":2655,"sortIndex":92,"researcher":22,"roles":2656,"affiliations":2657,"properties":2669},"8c13f727-3fd9-4229-8723-3208634d920e",[],[2658],{"id":2659,"sortIndex":23,"affiliation":2660,"properties":22},"eaf54513-f424-4007-a305-cedd69863dd1",{"id":2661,"createTime":2662,"updateTime":2663,"relativeEntities":2664,"slug":2665,"properties":2666,"entityType":198,"verifyStatus":384,"verifyTime":22,"verifyNote":22,"syncStatus":384,"languages":22,"translateLanguages":22,"viewCount":680},"09833cb8-5a51-4978-b89f-63f09610a98d","2023-05-29T12:06:07.808+00:00","2025-06-11T22:27:16.929+00:00",[],"LIPPINCOTT-WILLIAMS-WILKINS",{"title":2667},{"EN":2668},"LIPPINCOTT WILLIAMS & WILKINS",{"openalex":2670,"orcid":2672,"title":2674},{"VOID":2671},"A5051259646",{"VOID":2673},"https://orcid.org/0000-0002-7091-1235",{"EN":2675},"Ornella Rimoldi",{"id":2677,"sortIndex":991,"researcher":22,"roles":2678,"affiliations":2679,"properties":2690},"88383d96-c6b4-4069-9b4a-42c26e371f5b",[],[2680],{"id":2681,"sortIndex":23,"affiliation":2682,"properties":22},"6fa1a825-b8b5-4d10-afe8-79244b4caa7a",{"id":2683,"createTime":2684,"updateTime":2684,"relativeEntities":2685,"slug":2686,"properties":2687,"entityType":198,"verifyStatus":384,"verifyTime":22,"verifyNote":22,"syncStatus":384,"languages":22,"translateLanguages":22,"viewCount":23},"55991775-d3d1-4575-9349-0ba0e64ba331","2024-10-03T06:02:28.358+00:00",[],"CentraTeoria-Sistemi-CNR-Dipartimento-Elettronica-Politecnico-Milano-Italy-",{"title":2688},{"EN":2689},"CentraTeoria Sistemi. 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The journal publishes manuscripts of the highest quality pertaining to basic cardiac and vascular biology and encourages the submission of work that uses state-of-the-art approaches to illuminate mechanisms of human disease. A special welcome is extended to translational research and to clinical research that yields fundamental insights; studies in humans or human tissues that advance our understanding of the basis of disease and the mechanism of therapies are an area of particular emphasis.",{"VOID":2840},"15244571",{"EN":2842},"Circulation Research",[],[],[2846,2858],{"id":2847,"indexDatabase":2848,"url":2853,"indexYears":22,"academicFieldIds":2854},"97fdcf1e-7a12-4a7f-b815-29c73f8da4d8",{"id":457,"createTime":458,"updateTime":459,"relativeEntities":2849,"label":2850,"description":2851,"key":466,"publicationTags":2852,"standard":22},[],{"EN":462,"VI":462},{"VI":464,"EN":465},[468,469],"https://mjl.clarivate.com/search-results?issn=0009-7330",[2855,2856,2857],"4f363738-bd8a-4ecf-bff7-e3fa60978c08","0ddd214e-2317-43ae-8737-4f5747adc536","22fd6c38-3ec0-41e0-8ae8-a4290171207e",{"id":2859,"indexDatabase":2860,"url":2865,"indexYears":2866,"academicFieldIds":2867},"cb0e0f26-eb6c-450e-b219-d6146dda6fe9",{"id":476,"createTime":477,"updateTime":478,"relativeEntities":2861,"label":2862,"description":2863,"key":484,"publicationTags":2864,"standard":22},[],{"EN":481,"VI":481},{"EN":481,"VI":483},[486],"https://www.scopus.com/sourceid/23063","1953-2023",[2868,2869],"f845e4fe-178d-4593-b013-715b3c1cc81c","d44e3b1d-4abe-47f2-b4aa-783c24a9f903","https://www.ahajournals.org/journal/res",{"volume":2872,"pages":2874,"issue":2876},{"VOID":2873},"59",{"VOID":2875},"178-193",{"VOID":2877},"2",4097,{"total":2878,"publishYear":22,"statisticByYear":2880},{"2012":2881,"2013":2882,"2014":2883,"2015":1382,"2016":1377,"2017":2881,"2018":116,"2019":1397,"2020":2308,"2021":1377,"2022":1374,"2023":2884,"2024":2885},115,114,137,66,51,"1986-08-01",1986,[],{"id":2890,"createTime":2891,"updateTime":2892,"relativeEntities":2893,"slug":2894,"properties":2895,"entityType":126,"verifyStatus":382,"verifyTime":2891,"verifyNote":383,"syncStatus":384,"languages":2914,"translateLanguages":2915,"viewCount":23,"primaryUrl":2916,"fullTextUrl":22,"authors":2917,"publicationType":128,"publisherRelationship":2958,"citationCount":3056,"citationInfo":3057,"publishDate":3067,"publishYear":3068,"citationAnalyzeStatus":384,"lastCitationAnalyze":22,"indexDatabases":22,"openAccess":22,"references":3069,"isForceReanalyzing":19},"e81b170b-42c6-4b85-824f-be0325160a93","2024-09-01T14:56:27.644+00:00","2024-12-26T17:50:57.691+00:00",[],"Tetracycline-Antibiotics-Mode-of-Action-Applications-Molecular-Biology-and-Epidemiology-of-Bacterial-Resistance",{"mag":2896,"keywords":2898,"pmc":2900,"openalex":2902,"abstract":2904,"title":2907,"pm":2910,"doi":2912},{"VOID":2897},"2113790776",{"VI":2899},"tetracycline, kháng rửa, kháng sinh, kháng khuẩn, vi khuẩn kháng, chlamydiae, mycoplasma, rickettsiae, động vật nguyên sinh, gen di động, hóa sinh, lai ghép DNA-DNA, 16S rRNA, plasmid, transposon, đột biến, dịch tễ học, sức khỏe động vật, sản xuất thực phẩm",{"VOID":2901},"99026",{"VOID":2903},"W2113790776",{"EN":2905,"VI":2906},"\u003Cjats:sec>\n \u003Cjats:title>SUMMARY\u003C/jats:title>\n \u003Cjats:p>Tetracyclines were discovered in the 1940s and exhibited activity against a wide range of microorganisms including gram-positive and gram-negative bacteria, chlamydiae, mycoplasmas, rickettsiae, and protozoan parasites. They are inexpensive antibiotics, which have been used extensively in the prophlylaxis and therapy of human and animal infections and also at subtherapeutic levels in animal feed as growth promoters. The first tetracycline-resistant bacterium, Shigella dysenteriae, was isolated in 1953. Tetracycline resistance now occurs in an increasing number of pathogenic, opportunistic, and commensal bacteria. The presence of tetracycline-resistant pathogens limits the use of these agents in treatment of disease. Tetracycline resistance is often due to the acquisition of new genes, which code for energy-dependent efflux of tetracyclines or for a protein that protects bacterial ribosomes from the action of tetracyclines. Many of these genes are associated with mobile plasmids or transposons and can be distinguished from each other using molecular methods including DNA-DNA hybridization with oligonucleotide probes and DNA sequencing. A limited number of bacteria acquire resistance by mutations, which alter the permeability of the outer membrane porins and/or lipopolysaccharides in the outer membrane, change the regulation of innate efflux systems, or alter the 16S rRNA. New tetracycline derivatives are being examined, although their role in treatment is not clear. Changing the use of tetracyclines in human and animal health as well as in food production is needed if we are to continue to use this class of broad-spectrum antimicrobials through the present century.\u003C/jats:p>\n \u003C/jats:sec>","\u003Cjats:sec>\n \u003Cjats:title>TÓM TẮT\u003C/jats:title>\n \u003Cjats:p>Tetracyclines được phát hiện vào những năm 1940 và cho thấy hoạt tính chống lại nhiều vi sinh vật bao gồm vi khuẩn gram dương và gram âm, chlamydiae, mycoplasma, rickettsiae và ký sinh trùng nguyên sinh. Đây là những loại kháng sinh ít tốn kém, đã được sử dụng rộng rãi trong dự phòng và điều trị nhiễm khuẩn ở người và động vật cũng như ở mức độ dưới điều trị trong thức ăn chăn nuôi để thúc đẩy tăng trưởng. Vi khuẩn kháng tetracycline đầu tiên, Shigella dysenteriae, được phân lập vào năm 1953. Kháng tetracycline hiện nay xuất hiện ngày càng nhiều trong các vi khuẩn gây bệnh, cơ hội và cộng sinh. Sự hiện diện của các tác nhân kháng tetracycline hạn chế việc sử dụng các chất này trong điều trị bệnh. Kháng tetracycline thường là do sự thu nhận gen mới, mã hóa cho sự bơm đẩy tetracycline phụ thuộc năng lượng hoặc cho một loại protein bảo vệ ribosome của vi khuẩn khỏi tác động của tetracycline. Nhiều trong số các gen này liên quan đến plasmid di động hoặc transposon và có thể được phân biệt với nhau bằng các phương pháp phân tử bao gồm lai ghép DNA-DNA với đầu dò oligonucleotide và giải trình tự DNA. Một số lượng ít vi khuẩn có được sự kháng bệnh thông qua đột biến, thay đổi tính thấm của porin màng ngoài và/hoặc lipopolysaccharides trong màng ngoài, thay đổi điều tiết của hệ thống bơm đẩy bẩm sinh, hoặc thay đổi 16S rRNA. Đang có các dẫn xuất mới của tetracycline được nghiên cứu, mặc dù vai trò của chúng trong điều trị chưa rõ ràng. Cần thay đổi việc sử dụng tetracycline trong sức khỏe con người và động vật cũng như trong sản xuất thực phẩm nếu chúng ta muốn tiếp tục sử dụng loại kháng khuẩn phổ rộng này trong thế kỷ hiện tại.\u003C/jats:p>\n \u003C/jats:sec>",{"EN":2908,"VI":2909},"Tetracycline Antibiotics: Mode of Action, Applications, Molecular Biology, and Epidemiology of Bacterial Resistance","Kháng sinh Tetracycline: Cơ chế tác dụng, Ứng dụng, Sinh học phân tử và Dịch tễ học của Kháng khuẩn Kháng Khuẩn",{"VOID":2911},"11381101",{"VOID":2913},"10.1128/mmbr.65.2.232-260.2001",[386],[388],"https://journals.asm.org/doi/10.1128/MMBR.65.2.232-260.2001",[2918,2939],{"id":2919,"sortIndex":73,"researcher":22,"roles":2920,"affiliations":2921,"properties":2932},"9af0f170-faf2-4d95-a6d8-9474efffdd88",[],[2922],{"id":2923,"sortIndex":23,"affiliation":2924,"properties":22},"02e9da3b-62b0-4433-a155-06988a2447bc",{"id":2925,"createTime":2926,"updateTime":2926,"relativeEntities":2927,"slug":2928,"properties":2929,"entityType":198,"verifyStatus":384,"verifyTime":22,"verifyNote":22,"syncStatus":384,"languages":22,"translateLanguages":22,"viewCount":23},"d7090bdc-c6bb-4476-b4d3-43d23260b1cb","2024-09-01T14:56:27.673+00:00",[],"Department-of-Pathobiology-School-of-Public-Health-and-Community-Medicine-University-of-Washington-Seattle-Washington-98195-72382",{"title":2930},{"EN":2931},"Department of Pathobiology, School of Public Health and Community Medicine, University of Washington, Seattle, Washington 98195-72382",{"openalex":2933,"orcid":2935,"title":2937},{"VOID":2934},"A5054725825",{"VOID":2936},"https://orcid.org/0000-0003-0617-0046",{"EN":2938},"Marilyn C. 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Society for Microbiology Report of the ASM task force on antibiotic resistance.Antimicrob. Agents Chemother.1995(Suppl.)1995123",{},{"id":22,"text":3092,"url":22,"identifiers":3093},"10.1128/aem.60.3.908-912.1994",{"doi":3092},{"id":22,"text":3095,"url":22,"identifiers":3096},"10.1128/AAC.42.11.3022",{"doi":3095},{"id":22,"text":3098,"url":22,"identifiers":3099},"10.1086/315109",{"doi":3098},{"id":22,"text":3101,"url":22,"identifiers":3102},"10.1128/AAC.31.9.1446",{"doi":3101},{"id":22,"text":3104,"url":22,"identifiers":3105},"10.1128/AAC.41.7.1598",{"doi":3104},{"id":22,"text":3107,"url":22,"identifiers":3108},"10.1128/jb.155.3.1094-1104.1983",{"doi":3107},{"id":22,"text":3110,"url":22,"identifiers":3111},"10.1046/j.1462-2920.1999.00004.x",{"doi":3110},{"id":22,"text":3113,"url":22,"identifiers":3114},"10.1021/jm00046a003",{"doi":3113},{"id":22,"text":3116,"url":22,"identifiers":3117},"Benveniste R. Davies J. Aminoglycoside antibiotic-inactivation enzymes in actinomycetes similar to those present in clinical isolates of antibiotic resistant bacteria.Proc. Natl. Acad Sci. USA172197336283632",{},{"id":22,"text":3119,"url":22,"identifiers":3120},"10.1128/AAC.40.9.2226",{"doi":3119},{"id":22,"text":3122,"url":22,"identifiers":3123},"10.1128/jb.173.2.443-448.1991",{"doi":3122},{"id":22,"text":3125,"url":22,"identifiers":3126},"10.1128/AAC.43.4.846",{"doi":3125},{"id":22,"text":3128,"url":22,"identifiers":3129},"10.1007/978-3-642-70304-1_3",{"doi":3128},{"id":22,"text":3131,"url":22,"identifiers":3132},"10.1111/j.1574-6976.1997.tb00345.x",{"doi":3131},{"id":22,"text":3134,"url":22,"identifiers":3135},"10.1128/AAC.44.8.2225-2229.2000",{"doi":3134},{"id":22,"text":3137,"url":22,"identifiers":3138},"10.1093/jac/45.3.395",{"doi":3137},{"id":22,"text":3140,"url":22,"identifiers":3141},"10.1128/jb.170.4.1739-1745.1988",{"doi":3140},{"id":22,"text":3143,"url":22,"identifiers":3144},"10.1128/AAC.40.4.874",{"doi":3143},{"id":22,"text":3146,"url":22,"identifiers":3147},"10.1128/AAC.31.11.1852",{"doi":3146},{"id":22,"text":3149,"url":22,"identifiers":3150},"10.1016/0378-1135(91)90124-X",{"doi":3149},{"id":22,"text":3152,"url":22,"identifiers":3153},"Bunnag D. Karbwang J. Na-Bangchang K. Thanavibul A. Chittamas S. Harinasuta T. Quinine-tetracycline for multidrug resistant falciparum malaria.Southeast Asia J. Trop. Med. Public Health2719961518",{},{"id":22,"text":3155,"url":22,"identifiers":3156},"10.1016/S0021-9258(18)49928-0",{"doi":3155},{"id":22,"text":3158,"url":22,"identifiers":3159},"10.1128/jb.175.22.7209-7215.1993",{"doi":3158},{"id":22,"text":3161,"url":22,"identifiers":3162},"10.1128/jb.178.11.3246-3251.1996",{"doi":3161},{"id":22,"text":3164,"url":22,"identifiers":3165},"10.1128/AAC.40.2.307",{"doi":3164},{"id":22,"text":3167,"url":22,"identifiers":3168},"10.1007/BF00339722",{"doi":3167},{"id":22,"text":3170,"url":22,"identifiers":3171},"10.1128/AAC.33.4.529",{"doi":3170},{"id":22,"text":3173,"url":22,"identifiers":3174},"10.1016/0147-619X(87)90009-6",{"doi":3173},{"id":22,"text":3176,"url":22,"identifiers":3177},"10.1016/0378-1119(93)90665-P",{"doi":3176},{"id":22,"text":3179,"url":22,"identifiers":3180},"10.1128/AAC.38.10.2330",{"doi":3179},{"id":22,"text":3182,"url":22,"identifiers":3183},"10.1128/AAC.43.9.2103",{"doi":3182},{"id":22,"text":3185,"url":22,"identifiers":3186},"10.1128/AAC.39.9.2019",{"doi":3185},{"id":22,"text":3188,"url":22,"identifiers":3189},"10.1093/jac/36.5.815",{"doi":3188},{"id":22,"text":3191,"url":22,"identifiers":3192},"Chopra I. Mode of action of the tetracyclines and the nature of bacterial resistance to them Handbook of experimental pharmacology Hlavka J. J. Boothe J. H. 78 1985 315 392 Springer-Verlag KG Berlin, Germany",{},{"id":22,"text":3194,"url":22,"identifiers":3195},"10.1093/jac/18.6.661",{"doi":3194},{"id":22,"text":3197,"url":22,"identifiers":3198},"10.1128/AAC.38.4.637",{"doi":3197},{"id":22,"text":3200,"url":22,"identifiers":3201},"10.1093/jac/29.3.245",{"doi":3200},{"id":22,"text":3203,"url":22,"identifiers":3204},"10.1093/jac/44.3.329",{"doi":3203},{"id":22,"text":3206,"url":22,"identifiers":3207},"10.1093/jac/43.1.5",{"doi":3206},{"id":22,"text":3209,"url":22,"identifiers":3210},"10.1128/AAC.41.1.112",{"doi":3209},{"id":22,"text":3212,"url":22,"identifiers":3213},"10.1016/S0966-842X(00)88930-1",{"doi":3212},{"id":22,"text":3215,"url":22,"identifiers":3216},"10.1093/clinids/9.Supplement_3.S232",{"doi":3215},{"id":22,"text":3218,"url":22,"identifiers":3219},"Committee on Drug Use in Food Animals\nThe use of drugs in food animals benefits and risks.\n1999\nNational Academy Press\nWashington D.C.",{},{"id":22,"text":3221,"url":22,"identifiers":3222},"10.1001/archinte.159.9.1006",{"doi":3221},{"id":22,"text":3224,"url":22,"identifiers":3225},"10.1111/j.1365-2672.1997.tb03590.x",{"doi":3224},{"id":22,"text":3227,"url":22,"identifiers":3228},"10.1128/JB.180.16.4089-4092.1998",{"doi":3227},{"id":22,"text":3230,"url":22,"identifiers":3231},"10.1136/bmj.312.7031.613",{"doi":3230},{"id":22,"text":3233,"url":22,"identifiers":3234},"10.3201/eid0506.990610",{"doi":3233},{"id":22,"text":3236,"url":22,"identifiers":3237},"Dax\nS. L.\nAntibacterial chemotherapeutic agents.\n1997\nBlackie Academic and Professional\nLondon United Kingdom",{"doi":3238},"10.1007/978-94-009-0097-4",{"id":22,"text":3240,"url":22,"identifiers":3241},"10.1093/jac/27.6.721",{"doi":3240},{"id":22,"text":3243,"url":22,"identifiers":3244},"10.1093/jac/43.4.511",{"doi":3243},{"id":22,"text":3246,"url":22,"identifiers":3247},"10.1128/aem.54.7.1861-1863.1988",{"doi":3246},{"id":22,"text":3249,"url":22,"identifiers":3250},"10.1006/mcpr.1993.1051",{"doi":3249},{"id":22,"text":3252,"url":22,"identifiers":3253},"10.1016/S0890-8508(95)91572-9",{"doi":3252},{"id":22,"text":3255,"url":22,"identifiers":3256},"10.1128/AAC.42.8.1931",{"doi":3255},{"id":22,"text":3258,"url":22,"identifiers":3259},"10.1128/AAC.36.5.1119",{"doi":3258},{"id":22,"text":3261,"url":22,"identifiers":3262},"10.3201/eid0506.990603",{"doi":3261},{"id":22,"text":3264,"url":22,"identifiers":3265},"10.1128/cdli.4.1.23-32.1997",{"doi":3264},{"id":22,"text":3267,"url":22,"identifiers":3268},"10.1111/j.1365-2958.1991.tb01852.x",{"doi":3267},{"id":22,"text":3270,"url":22,"identifiers":3271},"Edlind\nT. D.\nProtein synthesis as a target for antiprotozoal drugs\nBiochemical protozoology.\nCoombs\nG.\nNorth\nM.\n1991\n569\n586\nTaylor & Francis\nLondon United Kingdom",{},{"id":22,"text":3273,"url":22,"identifiers":3274},"10.1128/AAC.38.3.534",{"doi":3273},{"id":22,"text":3276,"url":22,"identifiers":3277},"10.1128/aem.59.2.614-616.1993",{"doi":3276},{"id":22,"text":3279,"url":22,"identifiers":3280},"Falkow\nS.\nInfectious multiple drug resistance.\n1975\nPion Ltd.\nLondon United Kingdom",{},{"id":22,"text":3282,"url":22,"identifiers":3283},"10.1093/jac/45.2.191",{"doi":3282},{"id":22,"text":3285,"url":22,"identifiers":3286},"10.1056/NEJM200004273421703",{"doi":3285},{"id":22,"text":3288,"url":22,"identifiers":3289},"Finch\nR. G.\nTetracyclines\nAntibiotic and chemotherapy\n7th ed.\nO'Grady\nF.\nLambert\nH. P.\nFinch\nR. G.\nGreenwood\nD.\n1997\n469\n484\nChurchill Livingstone Ltd.\nNew York N.Y",{},{"id":22,"text":3291,"url":22,"identifiers":3292},"10.1128/iai.47.2.415-420.1985",{"doi":3291},{"id":22,"text":3294,"url":22,"identifiers":3295},"10.1006/plas.1994.1077",{"doi":3294},{"id":22,"text":3297,"url":22,"identifiers":3298},"10.1016/0147-619X(92)90015-3",{"doi":3297},{"id":22,"text":3300,"url":22,"identifiers":3301},"10.1093/jac/35.6.877",{"doi":3300},{"id":22,"text":3303,"url":22,"identifiers":3304},"Franklin\nT. J.\nMode of action of the tetracyclines\nBiochemical studies of antimicrobial drugs. Sixteenth Symposium of the Society for General Microbiology.\nNewton\nB. A.\nReynolds\nP. E.\n1966\n192\n212\nCambridge University Press\nCambridge United Kingdom",{},{"id":22,"text":3306,"url":22,"identifiers":3307},"10.1016/0924-8579(94)90034-5",{"doi":3306},{"id":22,"text":3309,"url":22,"identifiers":3310},"10.1016/S0732-8893(99)00092-9",{"doi":3309},{"id":22,"text":3312,"url":22,"identifiers":3313},"10.1056/NEJM199709043371004",{"doi":3312},{"id":22,"text":3315,"url":22,"identifiers":3316},"10.1099/13500872-141-8-1909",{"doi":3315},{"id":22,"text":3318,"url":22,"identifiers":3319},"Georgetown University Center for Food and Nutrition Policy\nAntibiotic use in animals: food safety and risk assessment. Conference proceedings.\n1999\nGeorgetown University\nWashington D.C.",{},{"id":22,"text":3321,"url":22,"identifiers":3322},"10.1111/j.1574-6968.1987.tb02117.x",{"doi":3321},{"id":22,"text":3324,"url":22,"identifiers":3325},"Gillespie M. T. May J. W. Skurray R. 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A.\nThe chemistry of the tetracycline antibiotics.\n1978\nMarcel Dekker Inc\nNew York N.Y",{},{"id":22,"text":3616,"url":22,"identifiers":3617},"10.1038/327389a0",{"doi":3616},{"id":22,"text":3619,"url":22,"identifiers":3620},"10.1056/NEJM199911043411902",{"doi":3619},{"id":22,"text":3622,"url":22,"identifiers":3623},"10.1128/AAC.30.5.664",{"doi":3622},{"id":22,"text":3625,"url":22,"identifiers":3626},"10.1016/0147-619X(88)90014-5",{"doi":3625},{"id":22,"text":3628,"url":22,"identifiers":3629},"10.1099/00221287-140-10-2577",{"doi":3628},{"id":22,"text":3631,"url":22,"identifiers":3632},"10.1021/jm00055a008",{"doi":3631},{"id":22,"text":3634,"url":22,"identifiers":3635},"10.1128/AAC.43.7.1719",{"doi":3634},{"id":22,"text":3424,"url":22,"identifiers":3637},{},{"id":22,"text":3639,"url":22,"identifiers":3640},"10.1128/AAC.34.11.2273",{"doi":3639},{"id":22,"text":3642,"url":22,"identifiers":3643},"10.1128/AAC.43.12.3018",{"doi":3642},{"id":22,"text":3645,"url":22,"identifiers":3646},"10.1128/jb.178.20.5853-5859.1996",{"doi":3645},{"id":22,"text":3648,"url":22,"identifiers":3649},"10.1016/S1369-5274(98)80083-0",{"doi":3648},{"id":22,"text":3651,"url":22,"identifiers":3652},"10.1128/AAC.37.7.1393",{"doi":3651},{"id":22,"text":3654,"url":22,"identifiers":3655},"10.1074/jbc.274.23.16576",{"doi":3654},{"id":22,"text":3657,"url":22,"identifiers":3658},"10.1007/BF02098471",{"doi":3657},{"id":22,"text":3660,"url":22,"identifiers":3661},"10.1093/clinids/9.Supplement_3.S244",{"doi":3660},{"id":22,"text":3663,"url":22,"identifiers":3664},"10.1093/nar/25.6.1219",{"doi":3663},{"id":22,"text":3666,"url":22,"identifiers":3667},"10.1128/AAC.44.1.10-13.2000",{"doi":3666},{"id":22,"text":3669,"url":22,"identifiers":3670},"10.1128/AAC.36.4.876",{"doi":3669},{"id":22,"text":3672,"url":22,"identifiers":3673},"10.1128/AAC.36.5.913",{"doi":3672},{"id":22,"text":3675,"url":22,"identifiers":3676},"10.1111/j.1399-302X.1994.tb00067.x",{"doi":3675},{"id":22,"text":3678,"url":22,"identifiers":3679},"10.1111/j.1399-302X.1995.tb00124.x",{"doi":3678},{"id":22,"text":3681,"url":22,"identifiers":3682},"10.1006/jmbi.1998.2290",{"doi":3681},{"id":22,"text":3684,"url":22,"identifiers":3685},"10.1038/73324",{"doi":3684},{"id":22,"text":3687,"url":22,"identifiers":3688},"10.1016/S0924-8579(96)00370-6",{"doi":3687},{"id":22,"text":3690,"url":22,"identifiers":3691},"10.1128/MR.60.4.575-608.1996",{"doi":3690},{"id":22,"text":3693,"url":22,"identifiers":3694},"10.1006/mcpr.1994.1059",{"doi":3693},{"id":22,"text":3696,"url":22,"identifiers":3697},"10.1128/AAC.38.6.1408",{"doi":3696},{"id":22,"text":3699,"url":22,"identifiers":3700},"10.1128/AAC.43.4.738",{"doi":3699},{"id":22,"text":3702,"url":22,"identifiers":3703},"10.1128/AAC.39.2.500",{"doi":3702},{"id":22,"text":3705,"url":22,"identifiers":3706},"10.1128/AAC.44.3.790-793.2000",{"doi":3705},{"id":22,"text":3708,"url":22,"identifiers":3709},"10.4269/ajtmh.2000.62.82",{"doi":3708},{"id":22,"text":3711,"url":22,"identifiers":3712},"10.1128/jb.169.11.5131-5139.1987",{"doi":3711},{"id":22,"text":3714,"url":22,"identifiers":3715},"10.1016/0147-619X(88)90039-X",{"doi":3714},{"id":22,"text":3717,"url":22,"identifiers":3718},"10.1128/AAC.44.9.2395-2398.2000",{"doi":3717},{"id":22,"text":3720,"url":22,"identifiers":3721},"10.1128/AAC.38.7.1658",{"doi":3720},{"id":22,"text":3723,"url":22,"identifiers":3724},"10.1099/13500872-141-12-3015",{"doi":3723},{"id":22,"text":3424,"url":22,"identifiers":3726},{},{"id":22,"text":3728,"url":22,"identifiers":3729},"Reynes J. 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W. Crabb W. E. The effect of the continuous administration of diets containing low levels of tetracyclines on the incidence of drug-resistant Bacterium coli in the faeces of pigs and chickens: the sensitivity of the Bacterium coli to other chemotherapeutic agents.Vet. 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M.\nReport of joint committee on the use of antibiotics in animal husbandry and veterinary medicine. Cmnd. 4190.\n1969\nHer Majesty's Stationery Office\nLondon United Kingdom",{},{"id":22,"text":3941,"url":22,"identifiers":3942},"10.1128/JCM.37.7.2337-2342.1999",{"doi":3941},{"id":22,"text":3944,"url":22,"identifiers":3945},"10.1006/plas.1994.1007",{"doi":3944},{"id":22,"text":3947,"url":22,"identifiers":3948},"10.1006/plas.2000.1489",{"doi":3947},{"id":22,"text":3950,"url":22,"identifiers":3951},"10.1128/AAC.40.1.1",{"doi":3950},{"id":22,"text":3953,"url":22,"identifiers":3954},"10.1128/AAC.32.8.1107",{"doi":3953},{"id":22,"text":3956,"url":22,"identifiers":3957},"10.1128/AAC.42.1.59",{"doi":3956},{"id":22,"text":3959,"url":22,"identifiers":3960},"10.1128/AAC.37.11.2270",{"doi":3959},{"id":22,"text":3962,"url":22,"identifiers":3963},"10.1136/vr.134.22.577",{"doi":3962},{"id":22,"text":3965,"url":22,"identifiers":3966},"10.1007/BF00261679",{"doi":3965},{"id":22,"text":3968,"url":22,"identifiers":3969},"10.1515/bchm.1998.379.7.847",{"doi":3968},{"id":22,"text":3424,"url":22,"identifiers":3971},{},{"id":22,"text":3973,"url":22,"identifiers":3974},"10.1021/jo00055a002",{"doi":3973},{"id":22,"text":3976,"url":22,"identifiers":3977},"Urquhart E. Addy M. Topical antimicrobials: new horizons for management of periodontal disease in general practice? Dent. Update 1995 Apr. 1995 104 111",{},{"id":22,"text":3979,"url":22,"identifiers":3980},"10.1016/0006-2952(81)90403-2",{"doi":3979},{"id":22,"text":3982,"url":22,"identifiers":3983},"10.1111/j.1523-5378.1996.tb00003.x",{"doi":3982},{"id":22,"text":3985,"url":22,"identifiers":3986},"10.1128/AAC.11.3.383",{"doi":3985},{"id":22,"text":3988,"url":22,"identifiers":3989},"10.1902/jop.1999.70.6.657",{"doi":3988},{"id":22,"text":3991,"url":22,"identifiers":3992},"10.1128/AAC.35.10.2020",{"doi":3991},{"id":22,"text":3994,"url":22,"identifiers":3995},"10.1016/0378-1135(94)90134-1",{"doi":3994},{"id":22,"text":3997,"url":22,"identifiers":3998},"10.1128/br.27.1.87-115.1963",{"doi":3997},{"id":22,"text":4000,"url":22,"identifiers":4001},"Weinstein R. A. Endemic emergence of cephalosporin-resistant enterobacter: relation to prior therapy.Infect. Control.71986120123",{},{"id":22,"text":4003,"url":22,"identifiers":4004},"10.1093/jac/36.1.225",{"doi":4003},{"id":22,"text":4006,"url":22,"identifiers":4007},"10.1128/AAC.43.7.1681",{"doi":4006},{"id":22,"text":4009,"url":22,"identifiers":4010},"10.1128/AAC.38.10.2513",{"doi":4009},{"id":22,"text":4012,"url":22,"identifiers":4013},"10.1128/AAC.39.8.1864",{"doi":4012},{"id":22,"text":4015,"url":22,"identifiers":4016},"Williams\nD. N.\nTetracyclines\nInfectious diseases.\nGorbach\nS. L.\nBartlett\nJ. G.\nBlacklow\nN. R.\n1992\n211\n214\nThe W. B. Saunders Co.\nPhiladelphia Pa",{},{"id":22,"text":4018,"url":22,"identifiers":4019},"10.1128/AAC.38.7.1661",{"doi":4018},{"id":22,"text":4021,"url":22,"identifiers":4022},"10.1128/AAC.38.5.1096",{"doi":4021},{"id":22,"text":4024,"url":22,"identifiers":4025},"10.1126/science.279.5353.996",{"doi":4024},{"id":22,"text":4027,"url":22,"identifiers":4028},"10.1016/S0890-8508(95)91620-2",{"doi":4027},{"id":22,"text":4030,"url":22,"identifiers":4031},"10.1016/S0021-9258(18)55428-4",{"doi":4030},{"id":22,"text":4033,"url":22,"identifiers":4034},"10.1111/j.1348-0421.1992.tb02109.x",{"doi":4033},{"id":4036,"createTime":4037,"updateTime":4038,"relativeEntities":4039,"slug":4040,"properties":4041,"entityType":126,"verifyStatus":382,"verifyTime":4037,"verifyNote":383,"syncStatus":384,"languages":4057,"translateLanguages":4058,"viewCount":23,"primaryUrl":4059,"fullTextUrl":22,"authors":4060,"publicationType":128,"publisherRelationship":4117,"citationCount":4205,"citationInfo":4206,"publishDate":4215,"publishYear":4216,"citationAnalyzeStatus":384,"lastCitationAnalyze":22,"indexDatabases":22,"openAccess":22,"references":4217,"isForceReanalyzing":19},"352dee20-9505-4969-9263-082dae900d12","2024-09-24T14:58:59.265+00:00","2025-01-29T23:49:03.632+00:00",[],"Every-base-matters-assessing-small-subunit-scp-rRNA-scp-primers-for-marine-microbiomes-with-mock-communities-time-series-and-global-field-samples",{"mag":4042,"keywords":4044,"openalex":4045,"abstract":4047,"title":4050,"pm":4053,"doi":4055},{"VOID":4043},"1952026831",{"VI":15},{"VOID":4046},"W1952026831",{"VI":4048,"EN":4049},"\u003Cjats:title>Tóm tắt\u003C/jats:title>\u003Cjats:p>Phân tích cộng đồng vi sinh vật thông qua thế hệ các đoạn \u003Cjats:styled-content style=\"fixed-case\">16S rRNA\u003C/jats:styled-content> bằng cách giải trình tự cao cấp là một công cụ thiết yếu trong vi sinh vật học. Chúng tôi phát hiện rằng cặp mồi phổ biến \u003Cjats:styled-content style=\"fixed-case\">515F\u003C/jats:styled-content> (\u003Cjats:styled-content style=\"fixed-case\">515F‐C\u003C/jats:styled-content>) và \u003Cjats:styled-content style=\"fixed-case\">806R\u003C/jats:styled-content> đã đánh giá thấp (ví dụ \u003Cjats:styled-content style=\"fixed-case\">SAR\u003C/jats:styled-content>11) hoặc đánh giá quá cao (ví dụ Gammaproteobacteria) các taxa biển phổ biến. Chúng tôi đã đánh giá các mẫu biển và cộng đồng giả (chứa 11 hoặc 27 clone 16S biển), cho thấy mồi thay thế 515F‐\u003Cjats:styled-content style=\"fixed-case\">Y\u003C/jats:styled-content> (5′‐\u003Cjats:styled-content style=\"fixed-case\">GTG\u003Cjats:bold>Y\u003C/jats:bold>CAGCMGCCGCGGTAA\u003C/jats:styled-content>) và \u003Cjats:styled-content style=\"fixed-case\">926R\u003C/jats:styled-content> (5′‐\u003Cjats:styled-content style=\"fixed-case\">CCGYCAATTYMTTTRAGTTT\u003C/jats:styled-content>) cho kết quả ước lượng chính xác hơn về độ dày quần thể cộng đồng giả, tạo ra các amplicon dài hơn có thể phân biệt được các taxa không thể phân giải được bằng \u003Cjats:styled-content style=\"fixed-case\">515F‐C\u003C/jats:styled-content>/\u003Cjats:styled-content style=\"fixed-case\">806R\u003C/jats:styled-content>, và khuếch đại \u003Cjats:styled-content style=\"fixed-case\">18S rRNA\u003C/jats:styled-content> eukaryotic. Các cộng đồng giả được khuếch đại bằng \u003Cjats:styled-content style=\"fixed-case\">515F‐Y\u003C/jats:styled-content>/\u003Cjats:styled-content style=\"fixed-case\">926R\u003C/jats:styled-content> cho thấy sự tương đồng cao hơn giữa thành phần cộng đồng quan sát được so với mong đợi (r\u003Cjats:sup>2\u003C/jats:sup> = 0.95) so với \u003Cjats:styled-content style=\"fixed-case\">515F‐Y\u003C/jats:styled-content>/\u003Cjats:styled-content style=\"fixed-case\">806R\u003C/jats:styled-content> (r\u003Cjats:sup>2\u003C/jats:sup> ∼ 0.5). Một cách bất ngờ, sự thiên lệch với \u003Cjats:styled-content style=\"fixed-case\">515F‐Y\u003C/jats:styled-content>/\u003Cjats:styled-content style=\"fixed-case\">806R\u003C/jats:styled-content> chống lại \u003Cjats:styled-content style=\"fixed-case\">SAR11\u003C/jats:styled-content> trong các mẫu hiện trường (∼4–10 lần) mạnh hơn so với trong các cộng đồng giả (∼2 lần). Sửa một sai lệch với \u003Cjats:styled-content style=\"fixed-case\">T\u003C/jats:styled-content>haumarchaea trong \u003Cjats:styled-content style=\"fixed-case\">515F‐C\u003C/jats:styled-content> đã làm tăng độ dày rõ ràng của chúng trong các mẫu hiện trường, nhưng không nhiều bằng việc sử dụng \u003Cjats:styled-content style=\"fixed-case\">926R\u003C/jats:styled-content> thay vì \u003Cjats:styled-content style=\"fixed-case\">806R\u003C/jats:styled-content>. Với các mẫu fitoplankton phong phú DNA \u003Cjats:styled-content style=\"fixed-case\">eukaryotic\u003C/jats:styled-content> (&gt; 1 μm size fraction), các trình tự 18S chiếm trung bình ∼17% tổng số trình tự. Một sai sót đơn lẻ có thể làm thiên lệch mạnh việc khuếch đại, nhưng ngay cả các mồi hoàn hảo vẫn có thể thể hiện sự ưu tiên trong việc khuếch đại. Chúng tôi chứng minh rằng ngoài các dự đoán \u003Cjats:italic>in silico\u003C/jats:italic>, việc thử nghiệm với các cộng đồng giả và mẫu hiện trường là quan trọng trong việc lựa chọn mồi.","\u003Cjats:title>Summary\u003C/jats:title>\u003Cjats:p>Microbial community analysis via high‐throughput sequencing of amplified \u003Cjats:styled-content style=\"fixed-case\">16S rRNA\u003C/jats:styled-content> genes is an essential microbiology tool. We found the popular primer pair \u003Cjats:styled-content style=\"fixed-case\">515F\u003C/jats:styled-content> (\u003Cjats:styled-content style=\"fixed-case\">515F‐C\u003C/jats:styled-content>) and \u003Cjats:styled-content style=\"fixed-case\">806R\u003C/jats:styled-content> greatly underestimated (e.g. \u003Cjats:styled-content style=\"fixed-case\">SAR\u003C/jats:styled-content>11) or overestimated (e.g. Gammaproteobacteria) common marine taxa. We evaluated marine samples and mock communities (containing 11 or 27 marine 16S clones), showing alternative primers 515F‐\u003Cjats:styled-content style=\"fixed-case\">Y\u003C/jats:styled-content> (5′‐\u003Cjats:styled-content style=\"fixed-case\">GTG\u003Cjats:bold>Y\u003C/jats:bold>CAGCMGCCGCGGTAA\u003C/jats:styled-content>) and \u003Cjats:styled-content style=\"fixed-case\">926R\u003C/jats:styled-content> (5′‐\u003Cjats:styled-content style=\"fixed-case\">CCGYCAATTYMTTTRAGTTT\u003C/jats:styled-content>) yield more accurate estimates of mock community abundances, produce longer amplicons that can differentiate taxa unresolvable with \u003Cjats:styled-content style=\"fixed-case\">515F‐C\u003C/jats:styled-content>/\u003Cjats:styled-content style=\"fixed-case\">806R\u003C/jats:styled-content>, and amplify eukaryotic \u003Cjats:styled-content style=\"fixed-case\">18S rRNA\u003C/jats:styled-content>. Mock communities amplified with \u003Cjats:styled-content style=\"fixed-case\">515F‐Y\u003C/jats:styled-content>/\u003Cjats:styled-content style=\"fixed-case\">926R\u003C/jats:styled-content> yielded closer observed community composition versus expected (r\u003Cjats:sup>2\u003C/jats:sup> = 0.95) compared with \u003Cjats:styled-content style=\"fixed-case\">515F‐Y\u003C/jats:styled-content>/\u003Cjats:styled-content style=\"fixed-case\">806R\u003C/jats:styled-content> (r\u003Cjats:sup>2\u003C/jats:sup> ∼ 0.5). Unexpectedly, biases with \u003Cjats:styled-content style=\"fixed-case\">515F‐Y\u003C/jats:styled-content>/\u003Cjats:styled-content style=\"fixed-case\">806R\u003C/jats:styled-content> against \u003Cjats:styled-content style=\"fixed-case\">SAR11\u003C/jats:styled-content> in field samples (∼4–10‐fold) were stronger than in mock communities (∼2‐fold). Correcting a mismatch to \u003Cjats:styled-content style=\"fixed-case\">T\u003C/jats:styled-content>haumarchaea in the \u003Cjats:styled-content style=\"fixed-case\">515F‐C\u003C/jats:styled-content> increased their apparent abundance in field samples, but not as much as using \u003Cjats:styled-content style=\"fixed-case\">926R\u003C/jats:styled-content> rather than \u003Cjats:styled-content style=\"fixed-case\">806R\u003C/jats:styled-content>. With plankton samples rich in eukaryotic \u003Cjats:styled-content style=\"fixed-case\">DNA\u003C/jats:styled-content> (&gt; 1 μm size fraction), 18S sequences averaged ∼17% of all sequences. A single mismatch can strongly bias amplification, but even perfectly matched primers can exhibit preferential amplification. We show that beyond \u003Cjats:italic>in silico\u003C/jats:italic> predictions, testing with mock communities and field samples is important in primer selection.\u003C/jats:p>",{"VI":4051,"EN":4052},"Mỗi nucleotide đều quan trọng: đánh giá các mồi \u003Cscp>rRNA\u003C/scp> tiểu đơn vị nhỏ cho vi sinh vật biển qua cộng đồng giả, chuỗi thời gian và mẫu hiện trường toàn cầu","Every base matters: assessing small subunit \u003Cscp>rRNA\u003C/scp> primers for marine microbiomes with mock communities, time series and global field samples",{"VOID":4054},"26271760",{"VOID":4056},"10.1111/1462-2920.13023",[386],[388],"https://sfamjournals.onlinelibrary.wiley.com/doi/10.1111/1462-2920.13023",[4061,4083,4100],{"id":4062,"sortIndex":23,"researcher":22,"roles":4063,"affiliations":4064,"properties":4076},"ffb040aa-d38b-4e1e-9c36-1b360745f01a",[],[4065],{"id":4066,"sortIndex":23,"affiliation":4067,"properties":22},"c54974fb-bab3-4408-ac13-cacd30e99622",{"id":4068,"createTime":4069,"updateTime":4070,"relativeEntities":4071,"slug":4072,"properties":4073,"entityType":198,"verifyStatus":384,"verifyTime":22,"verifyNote":22,"syncStatus":384,"languages":22,"translateLanguages":22,"viewCount":23},"976f3a58-abc0-4a57-88dd-39a4b131a937","2023-12-25T12:43:31.588+00:00","2025-01-25T17:45:36.052+00:00",[],"University-of-Southern-California-Los-Angeles-CA-USA",{"title":4074},{"VI":4075},"University of Southern California, Los Angeles, CA USA",{"openalex":4077,"orcid":4079,"title":4081},{"VOID":4078},"A5088507994",{"VOID":4080},"https://orcid.org/0000-0002-1782-3156",{"EN":4082},"Alma E. 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C.C.(1999)Dissecting the marine bacterioplankton ‘Black Box’ by type and function through FISH and STARFISH. Doctoral Dissertation. Los Angeles CA: University of Southern California.",{},{"id":22,"text":4318,"url":22,"identifiers":4319},"10.1111/1462-2920.12131",{"doi":4318},{"id":22,"text":4321,"url":22,"identifiers":4322},"10.1016/j.mimet.2014.08.018",{"doi":4321},{"id":22,"text":4324,"url":22,"identifiers":4325},"10.1093/nar/gks1219",{"doi":4324},{"id":22,"text":4327,"url":22,"identifiers":4328},"10.1186/1471-2105-12-38",{"doi":4327},{"id":22,"text":4330,"url":22,"identifiers":4331},"10.1038/ismej.2014.129",{"doi":4330},{"id":22,"text":4333,"url":22,"identifiers":4334},"10.1371/journal.pcbi.1000844",{"doi":4333},{"id":22,"text":4336,"url":22,"identifiers":4337},"10.1128/AEM.01541-09",{"doi":4336},{"id":22,"text":4339,"url":22,"identifiers":4340},"10.1371/journal.pcbi.1003594",{"doi":4339},{"id":22,"text":4342,"url":22,"identifiers":4343},"10.1111/j.1574-6941.2007.00283.x",{"doi":4342},{"id":22,"text":4345,"url":22,"identifiers":4346},"10.1029/96PA03934",{"doi":4345},{"id":22,"text":4348,"url":22,"identifiers":4349},"10.1093/molbev/mst197",{"doi":4348},{"id":22,"text":4351,"url":22,"identifiers":4352},"10.1038/ismej.2013.178",{"doi":4351},{"id":22,"text":4354,"url":22,"identifiers":4355},"10.1093/nar/22.22.4673",{"doi":4354},{"id":22,"text":4357,"url":22,"identifiers":4358},"10.1126/science.1093857",{"doi":4357},{"id":22,"text":4360,"url":22,"identifiers":4361},"10.1038/ismej.2013.32",{"doi":4360},{"id":22,"text":4363,"url":22,"identifiers":4364},"10.1128/AEM.00062-07",{"doi":4363},{"id":4366,"createTime":4367,"updateTime":4368,"relativeEntities":4369,"slug":4370,"properties":4371,"entityType":126,"verifyStatus":382,"verifyTime":4367,"verifyNote":383,"syncStatus":384,"languages":4386,"translateLanguages":4387,"viewCount":23,"primaryUrl":4388,"fullTextUrl":22,"authors":4389,"publicationType":128,"publisherRelationship":4428,"citationCount":4502,"citationInfo":4503,"publishDate":4512,"publishYear":1598,"citationAnalyzeStatus":384,"lastCitationAnalyze":22,"indexDatabases":22,"openAccess":22,"references":4513,"isForceReanalyzing":19},"7e91b035-e48d-47ac-9ff4-4ee94f0045aa","2024-08-31T17:26:06.539+00:00","2024-12-25T03:27:56.778+00:00",[],"Photosynthetic-rates-derived-from-satellite-based-chlorophyll-concentration",{"mag":4372,"keywords":4374,"openalex":4376,"abstract":4378,"title":4381,"doi":4384},{"VOID":4373},"2051663919",{"VI":4375},"quang hợp, cố định carbon, phytoplankton, VGPM, mô hình khí hậu, nhiệt độ bề mặt biển, phân phối địa lý, hiệu suất đồng hóa tối ưu",{"VOID":4377},"W2051663919",{"EN":4379,"VI":4380},"\u003Cjats:p>We assembled a dataset of \u003Cjats:sup>14\u003C/jats:sup>C‐based productivity measurements to understand the critical variables required for accurate assessment of daily depth‐integrated phytoplankton carbon fixation (\u003Cjats:italic>PP\u003C/jats:italic>(\u003Cjats:italic>PP\u003C/jats:italic>\u003Cjats:sub>eu\u003C/jats:sub>)\u003Cjats:sub>u\u003C/jats:sub>) from measurements of sea surface pigment concentrations (\u003Cjats:italic>C\u003C/jats:italic>\u003Cjats:sub>sat\u003C/jats:sub>)(\u003Cjats:italic>C\u003C/jats:italic>\u003Cjats:sub>sat\u003C/jats:sub>). From this dataset, we developed a light‐dependent, depth‐resolved model for carbon fixation (VGPM) that partitions environmental factors affecting primary production into those that influence the relative vertical distribution of primary production (\u003Cjats:italic>P\u003C/jats:italic>\u003Cjats:sub>\u003Cjats:italic>z\u003C/jats:italic>\u003C/jats:sub>)\u003Cjats:sub>\u003Cjats:italic>z\u003C/jats:italic>\u003C/jats:sub>) and those that control the optimal assimilation efficiency of the productivity profile (\u003Cjats:italic>P\u003C/jats:italic>(\u003Cjats:italic>P\u003Cjats:sup>B\u003C/jats:sup>\u003C/jats:italic>\u003Cjats:sub>opt\u003C/jats:sub>). The VGPM accounted for 79% of the observed variability in \u003Cjats:italic>P\u003Cjats:sub>z\u003C/jats:sub>\u003C/jats:italic> and 86% of the variability in \u003Cjats:italic>PP\u003C/jats:italic>\u003Cjats:sub>eu\u003C/jats:sub> by using measured values of \u003Cjats:italic>P\u003Cjats:sup>B\u003C/jats:sup>\u003C/jats:italic>\u003Cjats:sub>opt\u003C/jats:sub>. Our results indicate that the accuracy of productivity algorithms in estimating PP\u003Cjats:sub>eu\u003C/jats:sub> is dependent primarily upon the ability to accurately represent variability in \u003Cjats:italic>P\u003C/jats:italic>\u003Cjats:sc>\u003Cjats:italic>\u003Cjats:sup>b\u003C/jats:sup>\u003C/jats:italic>\u003C/jats:sc>\u003Cjats:sub>\u003Cjats:italic>opt\u003C/jats:italic>\u003C/jats:sub>\u003Cjats:italic>.\u003C/jats:italic> We developed a temperature‐dependent \u003Cjats:italic>P\u003C/jats:italic>\u003Cjats:sc>\u003Cjats:italic>\u003Cjats:sup>b\u003C/jats:sup>\u003C/jats:italic>\u003C/jats:sc>\u003Cjats:sub>opt\u003C/jats:sub> model that was used in conjunction with monthly climatological images of \u003Cjats:italic>C\u003C/jats:italic>\u003Cjats:sub>sat\u003C/jats:sub> sea surface temperature, and cloud‐corrected estimates of surface irradiance to calculate a global annual phytoplankton carbon fixation (\u003Cjats:italic>PP\u003C/jats:italic>\u003Cjats:sub>annu\u003C/jats:sub>) rate of 43.5 Pg C yr\u003Cjats:sup>‒1\u003C/jats:sup>. The geographical distribution of \u003Cjats:italic>PP\u003C/jats:italic>\u003Cjats:sub>annu\u003C/jats:sub> was distinctly different than results from previous models. Our results illustrate the importance of focusing \u003Cjats:italic>P\u003C/jats:italic>\u003Cjats:sc>\u003Cjats:italic>\u003Cjats:sup>b\u003C/jats:sup>\u003C/jats:italic>\u003C/jats:sc>\u003Cjats:sub>opt\u003C/jats:sub> model development on temporal and spatial, rather than the vertical, variability.\u003C/jats:p>","\u003Cjats:p>Chúng tôi đã tập hợp một bộ dữ liệu đo lường hiệu suất dựa trên carbon \u003Cjats:sup>14\u003C/jats:sup> để hiểu các biến số quan trọng cần thiết cho đánh giá chính xác việc cố định carbon phytoplankton tích hợp độ sâu hàng ngày (\u003Cjats:italic>PP\u003C/jats:italic>(\u003Cjats:italic>PP\u003C/jats:italic>\u003Cjats:sub>eu\u003C/jats:sub>)\u003Cjats:sub>u\u003C/jats:sub>) từ đo lường nồng độ sắc tố trên bề mặt biển (\u003Cjats:italic>C\u003C/jats:italic>\u003Cjats:sub>sat\u003C/jats:sub>)(\u003Cjats:italic>C\u003C/jats:italic>\u003Cjats:sub>sat\u003C/jats:sub>). Từ bộ dữ liệu này, chúng tôi đã phát triển một mô hình chiếu sáng phụ thuộc vào độ sâu để cố định carbon (VGPM) phân chia các yếu tố môi trường ảnh hưởng đến sản xuất chính thành những yếu tố ảnh hưởng đến phân phối theo chiều đứng tương đối của sản xuất chính (\u003Cjats:italic>P\u003C/jats:italic>\u003Cjats:sub>\u003Cjats:italic>z\u003C/jats:italic>\u003C/jats:sub>)\u003Cjats:sub>\u003Cjats:italic>z\u003C/jats:italic>\u003C/jats:sub>) và những yếu tố kiểm soát hiệu suất đồng hóa tối ưu của cấu hình hiệu suất (\u003Cjats:italic>P\u003C/jats:italic>(\u003Cjats:italic>P\u003Cjats:sup>B\u003C/jats:sup>\u003C/jats:italic>\u003Cjats:sub>opt\u003C/jats:sub>). VGPM đã giải thích được 79% sự biến đổi quan sát trong \u003Cjats:italic>P\u003Cjats:sub>z\u003C/jats:sub>\u003C/jats:italic> và 86% sự biến đổi trong \u003Cjats:italic>PP\u003C/jats:italic>\u003Cjats:sub>eu\u003C/jats:sub> bằng cách sử dụng các giá trị đo được của \u003Cjats:italic>P\u003Cjats:sup>B\u003C/jats:sup>\u003C/jats:italic>\u003Cjats:sub>opt\u003C/jats:sub>. Kết quả của chúng tôi chỉ ra rằng độ chính xác của các thuật toán hiệu suất trong việc ước tính PP\u003Cjats:sub>eu\u003C/jats:sub> phụ thuộc chủ yếu vào khả năng đại diện chính xác sự biến đổi trong \u003Cjats:italic>P\u003C/jats:italic>\u003Cjats:sc>\u003Cjats:italic>\u003Cjats:sup>b\u003C/jats:sup>\u003C/jats:italic>\u003C/jats:sc>\u003Cjats:sub>\u003Cjats:italic>opt\u003C/jats:italic>\u003C/jats:sub>\u003Cjats:italic>.\u003C/jats:italic> Chúng tôi đã phát triển một mô hình phụ thuộc nhiệt độ \u003Cjats:italic>P\u003C/jats:italic>\u003Cjats:sc>\u003Cjats:italic>\u003Cjats:sup>b\u003C/jats:sup>\u003C/jats:italic>\u003C/jats:sc>\u003Cjats:sub>opt\u003C/jats:sub> được sử dụng kết hợp với hình ảnh khí hậu hàng tháng của \u003Cjats:italic>C\u003C/jats:italic>\u003Cjats:sub>sat\u003C/jats:sub> nhiệt độ bề mặt biển, và ước tính sửa cải mây chiếu sáng bề mặt để tính toán tốc độ cố định carbon phytoplankton toàn cầu hàng năm (\u003Cjats:italic>PP\u003C/jats:italic>\u003Cjats:sub>annu\u003C/jats:sub>) là 43.5 Pg C yr\u003Cjats:sup>‒1\u003C/jats:sup>. Phân bố địa lý của \u003Cjats:italic>PP\u003C/jats:italic>\u003Cjats:sub>annu\u003C/jats:sub> khác biệt rõ rệt so với kết quả từ các mô hình trước đây. Kết quả của chúng tôi minh họa tầm quan trọng của việc tập trung phát triển mô hình \u003Cjats:italic>P\u003C/jats:italic>\u003Cjats:sc>\u003Cjats:italic>\u003Cjats:sup>b\u003C/jats:sup>\u003C/jats:italic>\u003C/jats:sc>\u003Cjats:sub>opt\u003C/jats:sub> trên sự biến đổi theo thời gian và không gian, thay vì chiều dọc.\u003C/jats:p>",{"EN":4382,"VI":4383},"Photosynthetic rates derived from satellite‐based chlorophyll concentration","Tốc độ quang hợp bắt nguồn từ nồng độ chlorophyll dựa trên vệ tinh",{"VOID":4385},"10.4319/lo.1997.42.1.0001",[386],[388],"https://aslopubs.onlinelibrary.wiley.com/doi/10.4319/lo.1997.42.1.0001",[4390,4411],{"id":4391,"sortIndex":23,"researcher":22,"roles":4392,"affiliations":4393,"properties":4404},"4a6d24a8-aaaa-4af9-8522-7d70acbe3fd8",[],[4394],{"id":4395,"sortIndex":23,"affiliation":4396,"properties":22},"fc78a803-59a2-4616-9621-b0eb6b6c1cb7",{"id":4397,"createTime":4398,"updateTime":4398,"relativeEntities":4399,"slug":4400,"properties":4401,"entityType":198,"verifyStatus":384,"verifyTime":22,"verifyNote":22,"syncStatus":384,"languages":22,"translateLanguages":22,"viewCount":23},"9f6f7710-021f-450a-8a3d-c2f034c3fcd3","2024-08-31T17:26:06.585+00:00",[],"Oceanographic-and-Atmospheric-Sciences-Division-Brookhaven-National-Laboratory-Upton-New-York-11973-5000",{"title":4402},{"EN":4403},"Oceanographic and Atmospheric Sciences Division, Brookhaven National Laboratory,Upton, New York 11973‐5000",{"openalex":4405,"orcid":4407,"title":4409},{"VOID":4406},"A5069584614",{"VOID":4408},"https://orcid.org/0000-0003-1330-7098",{"EN":4410},"Michael J. Behrenfeld",{"id":4412,"sortIndex":73,"researcher":22,"roles":4413,"affiliations":4414,"properties":4421},"86f1a9b5-6db1-43f7-bcac-9695370837df",[],[4415],{"id":4416,"sortIndex":23,"affiliation":4417,"properties":22},"2ac4a4ac-9b28-4cae-9c65-cd762ca0a1b7",{"id":4397,"createTime":4398,"updateTime":4398,"relativeEntities":4418,"slug":4400,"properties":4419,"entityType":198,"verifyStatus":384,"verifyTime":22,"verifyNote":22,"syncStatus":384,"languages":22,"translateLanguages":22,"viewCount":23},[],{"title":4420},{"EN":4403},{"openalex":4422,"orcid":4424,"title":4426},{"VOID":4423},"A5031704724",{"VOID":4425},"https://orcid.org/0000-0002-2353-1969",{"EN":4427},"Paul G. Falkowski",{"url":22,"publisher":4429,"properties":4495},{"id":4430,"createTime":4431,"updateTime":4432,"relativeEntities":4433,"slug":4434,"properties":4435,"entityType":61,"verifyStatus":384,"verifyTime":22,"verifyNote":22,"syncStatus":384,"languages":22,"translateLanguages":22,"viewCount":23,"subjectFields":4445,"manageAffiliations":4446,"indexDatabases":4447,"url":4471,"thumbnailPath":22,"statistic":4472,"gsStatistic":22,"type":22,"analyzePriority":22},"2c27f880-c98d-438b-90e0-b2c50c1681c5","2023-05-29T11:12:27.169+00:00","2025-02-09T04:24:47.016+00:00",[],"Limnology-and-Oceanography",{"country":4436,"issn":4437,"introduce":4439,"eissn":4441,"title":4443},{"VOID":442},{"VOID":4438},"00243590",{"EN":4440},"Limnology and Oceanography (L&O) publishes research articles, reviews, and comments about all aspects of the sciences of limnology and oceanography. The journal’s unifying theme is the understanding of aquatic systems. Submissions are judged on their originality and intellectual contribution to the fields of limnology and oceanography, whether physical, chemical, or biological in nature, empirical or theoretical in method, and from elemental to geological, ecological to evolutionary, species to ecosystem, or system to global in scale. Preference is given to papers that are based within the scientific philosophy of novel, hypothesis-driven or observational research that contributes significantly to a broader understanding of aquatic sciences.",{"VOID":4442},"19395590",{"EN":4444},"Limnology and Oceanography",[],[],[4448,4460],{"id":4449,"indexDatabase":4450,"url":4455,"indexYears":4456,"academicFieldIds":4457},"a23db552-7af7-4e97-9098-4a399f13bdd0",{"id":476,"createTime":477,"updateTime":478,"relativeEntities":4451,"label":4452,"description":4453,"key":484,"publicationTags":4454,"standard":22},[],{"EN":481,"VI":481},{"EN":481,"VI":483},[486],"https://www.scopus.com/sourceid/29576","1956-2023",[4458,4459],"3f140bdf-18a5-45b8-8459-b6b3deccda3f","ffd90654-8e05-4d1b-925b-52dca828931a",{"id":4461,"indexDatabase":4462,"url":4467,"indexYears":22,"academicFieldIds":4468},"ed48c183-28f1-4d19-a700-6de505d3db30",{"id":457,"createTime":458,"updateTime":459,"relativeEntities":4463,"label":4464,"description":4465,"key":466,"publicationTags":4466,"standard":22},[],{"EN":462,"VI":462},{"VI":464,"EN":465},[468,469],"https://mjl.clarivate.com/search-results?issn=0024-3590",[4469,4470],"aadd06a2-41c5-407b-969f-a284655bf43d","c4c21cdc-d610-489f-b7ef-520775232ef4","https://aslopubs.onlinelibrary.wiley.com/journal/19395590",{"impactFactor":23,"impactFactorByYear":4473,"i10Index":4475,"i10IndexLast5Year":23,"totalPublication":4475,"totalPublicationByYear":4476,"totalCitation":4477,"totalCitationByYear":4478,"totalCitationPerPublication":4490,"totalCitationPerPublicationByYear":4491,"hindexLast5Year":2310,"hindex":2310},{"2012":73,"2013":92,"2015":955,"2016":4474,"2017":92,"2018":92,"2019":1094,"2020":1058},2.5,27,{"1959":73,"1978":73,"1982":73,"1984":73,"1985":73,"1987":73,"1989":82,"1993":73,"1994":73,"1995":73,"1996":82,"1997":92,"2000":73,"2005":73,"2006":73,"2007":73,"2008":73,"2011":82,"2014":73,"2015":73,"2017":73,"2018":73},6674,{"1959":646,"1978":4479,"1982":1372,"1984":4480,"1985":1376,"1987":4481,"1989":4482,"1993":1391,"1994":116,"1995":1398,"1996":4483,"1997":4484,"2000":4485,"2005":1393,"2006":4486,"2007":3061,"2008":2266,"2011":4487,"2014":2310,"2015":4488,"2017":2310,"2018":4489},134,76,182,452,951,1506,2120,92,90,31,77,247.19,{"1959":646,"1978":4479,"1982":1372,"1984":4480,"1985":1376,"1987":4481,"1989":4492,"1993":1391,"1994":116,"1995":1398,"1996":4493,"1997":4211,"2000":4485,"2005":1393,"2006":4486,"2007":3061,"2008":2266,"2011":4494,"2014":2310,"2015":4488,"2017":2310,"2018":4489},226,475.5,45,{"volume":4496,"pages":4498,"issue":4500},{"VOID":4497},"42",{"VOID":4499},"1-20",{"VOID":4501},"1",2593,{"total":4502,"publishYear":22,"statisticByYear":4504},{"2012":4505,"2013":4506,"2014":2287,"2015":4507,"2016":4508,"2017":4509,"2018":4509,"2019":1392,"2020":1389,"2021":4510,"2022":4511,"2023":2306,"2024":1574},107,141,136,120,123,156,162,"1997-01-01",[],{"id":4515,"createTime":4516,"updateTime":4517,"relativeEntities":4518,"slug":4519,"properties":4520,"entityType":126,"verifyStatus":382,"verifyTime":4516,"verifyNote":383,"syncStatus":384,"languages":4536,"translateLanguages":4537,"viewCount":23,"primaryUrl":4538,"fullTextUrl":22,"authors":4539,"publicationType":128,"publisherRelationship":4561,"citationCount":4610,"citationInfo":4611,"publishDate":4616,"publishYear":4617,"citationAnalyzeStatus":384,"lastCitationAnalyze":22,"indexDatabases":22,"openAccess":22,"references":4618,"isForceReanalyzing":19},"8f5b5640-8f08-448d-9bb8-0f0352ce0007","2024-09-27T03:06:38.031+00:00","2024-12-26T07:00:37.892+00:00",[],"Quantification-of-mRNA-using-real-time-reverse-transcription-PCR-RT-PCR-trends-and-problems",{"mag":4521,"keywords":4523,"openalex":4525,"abstract":4527,"title":4530,"pm":4533,"doi":4535},{"VOID":4522},"2112982595",{"VI":4524},"PCR ngược dòng thời gian thực, định lượng mRNA, huỳnh quang, nghiêm ngặt, thống kê, y học phân tử, công nghệ sinh học, biến đổi hóa chất, xu hướng, vấn đề",{"VOID":4526},"W2112982595",{"EN":4528,"VI":4529},"\u003Cjats:p>The fluorescence-based real-time reverse transcription PCR (RT-PCR) is widely used for the quantification of steady-state mRNA levels and is a critical tool for basic research, molecular medicine and biotechnology. Assays are easy to perform, capable of high throughput, and can combine high sensitivity with reliable specificity. The technology is evolving rapidly with the introduction of new enzymes, chemistries and instrumentation. However, while real-time RT-PCR addresses many of the difficulties inherent in conventional RT-PCR, it has become increasingly clear that it engenders new problems that require urgent attention. Therefore, in addition to providing a snapshot of the state-of-the-art in real-time RT-PCR, this review has an additional aim: it will describe and discuss critically some of the problems associated with interpreting results that are numerical and lend themselves to statistical analysis, yet whose accuracy is significantly affected by reagent and operator variability.\u003C/jats:p>","\u003Cjats:p>Phương pháp PCR Ngược Dòng Thời gian Thực dựa trên huỳnh quang (RT-PCR) được sử dụng rộng rãi để định lượng mức mRNA ở trạng thái ổn định và là một công cụ quan trọng cho nghiên cứu cơ bản, y học phân tử và công nghệ sinh học. Các thử nghiệm dễ tiến hành, có khả năng xử lý khối lượng lớn, và có thể kết hợp độ nhạy cao với độ đặc hiệu đáng tin cậy. Công nghệ này đang tiến hóa nhanh chóng với sự xuất hiện của các enzym, hóa chất và thiết bị mới. Tuy nhiên, mặc dù RT-PCR thời gian thực đã giải quyết nhiều khó khăn vốn có trong RT-PCR thông thường, nó đã trở nên ngày càng rõ ràng rằng nó tạo ra những vấn đề mới cần giải quyết cấp thiết. Do đó, bên cạnh việc cung cấp bức tranh tổng thể về công nghệ RT-PCR thời gian thực, bài đánh giá này còn có mục tiêu bổ sung: sẽ mô tả và thảo luận cụ thể một số vấn đề liên quan đến việc giải thích các kết quả có tính chất số học và dễ dàng phân tích thống kê, nhưng độ chính xác của chúng bị ảnh hưởng đáng kể bởi sự biến đổi của hóa chất và người điều hành.\u003C/jats:p>",{"EN":4531,"VI":4532},"Quantification of mRNA using real-time reverse transcription PCR (RT-PCR): trends and problems","Định lượng mRNA bằng phương pháp PCR Ngược Dòng Thời gian Thực: xu hướng và vấn đề",{"VOID":4534},"12200227",{"VOID":1922},[386],[388],"https://jme.bioscientifica.com/view/journals/jme/29/1/23.xml",[4540],{"id":4541,"sortIndex":23,"researcher":22,"roles":4542,"affiliations":4543,"properties":4554},"1667c882-9530-4f0f-8bd1-7e522392e912",[],[4544],{"id":4545,"sortIndex":23,"affiliation":4546,"properties":22},"ac960c4e-8e13-4b37-ac06-8ff231993861",{"id":4547,"createTime":4548,"updateTime":4548,"relativeEntities":4549,"slug":4550,"properties":4551,"entityType":198,"verifyStatus":384,"verifyTime":22,"verifyNote":22,"syncStatus":384,"languages":22,"translateLanguages":22,"viewCount":23},"1ee8ede8-ce1f-4877-8647-a08ad6e13507","2024-09-27T03:06:38.045+00:00",[],"Academic-Department-of-Surgery-Barts-and-the-London-Queen-Mary-s-School-of-Medicine-and-Dentistry-University-of-London-London-E1-1BB-UK-s-a-bustin-qmul-ac-uk",{"title":4552},{"EN":4553},"Academic Department of Surgery, Barts and the London, Queen Mary's School of Medicine and Dentistry, University of London, London E1 1BB, UK. s.a.bustin@qmul.ac.uk",{"openalex":4555,"orcid":4557,"title":4559},{"VOID":4556},"A5043596447",{"VOID":4558},"https://orcid.org/0000-0003-1870-6098",{"EN":4560},"Stephen A. Bustin",{"url":22,"publisher":4562,"properties":4604},{"id":4563,"createTime":4564,"updateTime":4565,"relativeEntities":4566,"slug":4567,"properties":4568,"entityType":61,"verifyStatus":384,"verifyTime":22,"verifyNote":22,"syncStatus":384,"languages":22,"translateLanguages":22,"viewCount":23,"subjectFields":4579,"manageAffiliations":4580,"indexDatabases":4581,"url":4603,"thumbnailPath":22,"statistic":22,"gsStatistic":22,"type":22,"analyzePriority":22},"e284957b-1e01-463f-a257-7a6f8a71bd9d","2023-05-29T10:41:31.560+00:00","2025-01-27T22:47:27.047+00:00",[],"Journal-of-Molecular-Endocrinology",{"country":4569,"issn":4571,"introduce":4573,"eissn":4575,"title":4577},{"VOID":4570},"GB",{"VOID":4572},"14796813",{"EN":4574},"The Journal of Molecular Endocrinology is an official journal of the Society for Endocrinology and is endorsed by the European Society of Endocrinology and the Endocrine Society of Australia. Journal of Molecular Endocrinology is a leading global journal that publishes original research articles and reviews. The journal focuses on molecular and cellular mechanisms in endocrinology, including: gene regulation, cell biology, signalling, mutations, transgenics, hormone-dependant cancers, nuclear receptors, and omics. Basic and pathophysiological studies at the molecule and cell level are considered, as well as human sample studies where this is the experimental model of choice. Technique studies including CRISPR or gene editing are also encouraged.",{"VOID":4576},"09525041",{"EN":4578},"Journal of Molecular Endocrinology",[],[],[4582,4593],{"id":4583,"indexDatabase":4584,"url":4589,"indexYears":4590,"academicFieldIds":4591},"ba798dfb-d9f1-470a-8ce8-06a2961f4e98",{"id":476,"createTime":477,"updateTime":478,"relativeEntities":4585,"label":4586,"description":4587,"key":484,"publicationTags":4588,"standard":22},[],{"EN":481,"VI":481},{"EN":481,"VI":483},[486],"https://www.scopus.com/sourceid/26176","1988-2023",[2225,4592],"1fbd0674-a1cb-4227-af17-9260dd767b86",{"id":4594,"indexDatabase":4595,"url":4600,"indexYears":22,"academicFieldIds":4601},"3bc857c2-87ad-45cf-b536-a3562b9a05d1",{"id":457,"createTime":458,"updateTime":459,"relativeEntities":4596,"label":4597,"description":4598,"key":466,"publicationTags":4599,"standard":22},[],{"EN":462,"VI":462},{"VI":464,"EN":465},[468,469],"https://mjl.clarivate.com/search-results?issn=0952-5041",[4602],"7fc7f180-3918-45ab-8bea-b2226f5d88f6","http://jme.endocrinology-journals.org/",{"volume":4605,"pages":4607,"issue":4609},{"VOID":4606},"29",{"VOID":4608},"23-39",{"VOID":4501},2515,{"total":4610,"publishYear":22,"statisticByYear":4612},{"2012":4178,"2013":4613,"2014":1414,"2015":1395,"2016":4613,"2017":4614,"2018":1889,"2019":2266,"2020":1374,"2021":1377,"2022":4615,"2023":1361,"2024":1361},130,108,95,"2002-08-01",2002,[],{"id":4620,"createTime":4621,"updateTime":4622,"relativeEntities":4623,"slug":4624,"properties":4625,"entityType":126,"verifyStatus":382,"verifyTime":4621,"verifyNote":383,"syncStatus":384,"languages":4644,"translateLanguages":4645,"viewCount":23,"primaryUrl":4646,"fullTextUrl":22,"authors":4647,"publicationType":128,"publisherRelationship":4686,"citationCount":4748,"citationInfo":4749,"publishDate":22,"publishYear":22,"citationAnalyzeStatus":384,"lastCitationAnalyze":22,"indexDatabases":22,"openAccess":22,"references":4755,"isForceReanalyzing":19},"7ee52729-6c4c-47d7-a26a-6adc609b6f76","2024-09-19T13:01:29.973+00:00","2025-01-07T21:12:47.269+00:00",[],"Deep-Convolutional-and-LSTM-Recurrent-Neural-Networks-for-Multimodal-Wearable-Activity-Recognition",{"mag":4626,"keywords":4628,"pmc":4630,"openalex":4632,"abstract":4634,"title":4637,"pm":4640,"doi":4642},{"VOID":4627},"2270470215",{"VI":4629},"Nhận diện hoạt động con người, mạng nơ-ron tích chập sâu, mạng nơ-ron hồi tiếp LSTM, cảm biến đeo được, xử lý đa mô đun",{"VOID":4631},"4732148",{"VOID":4633},"W2270470215",{"VI":4635,"EN":4636},"\u003Cjats:p>Nhận diện hoạt động con người (HAR) thường được giải quyết bằng cách sử dụng các đặc trưng kỹ thuật được thu thập thông qua các quy trình heuristics. Nghiên cứu hiện tại cho thấy rằng các mạng nơ-ron tích chập sâu (CNN) rất phù hợp để tự động hóa quá trình trích xuất đặc trưng từ các dữ liệu cảm biến thô. Tuy nhiên, các hoạt động của con người bao gồm các chuỗi chuyển động phức tạp, và việc nắm bắt động lực tạm thời này là rất quan trọng cho việc nhận diện hoạt động thành công. Dựa trên sự thành công gần đây của các mạng nơ-ron tái kết nối cho các lĩnh vực chuỗi thời gian, chúng tôi đề xuất một khung sâu tổng quát cho nhận diện hoạt động dựa trên các đơn vị tích chập và đơn vị LSTM, mà: (i) phù hợp cho các cảm biến đeo được đa mô đun; (ii) có khả năng thực hiện bố hợp cảm biến một cách tự nhiên; (iii) không yêu cầu kiến thức chuyên môn trong việc thiết kế các đặc trưng; và (iv) mô hình hóa một cách rõ ràng động lực tạm thời của các đặc trưng kích hoạt. Chúng tôi đánh giá khung của mình trên hai tập dữ liệu, một trong số đó đã được sử dụng trong một thách thức nhận diện hoạt động công cộng. Kết quả cho thấy khung của chúng tôi vượt trội hơn các mạng nơ-ron không có hồi tiếp đang cạnh tranh trên tập dữ liệu thách thức với mức trung bình 4%; vượt hơn một số kết quả đã báo cáo trước đây lên đến 9%. Kết quả của chúng tôi cho thấy rằng khung có thể được áp dụng cho các mô hình cảm biến đồng nhất, nhưng cũng có thể bố hợp các cảm biến đa mô đun để cải thiện hiệu suất. Chúng tôi xác định ảnh hưởng của các siêu tham số kiến trúc chủ chốt đối với hiệu suất nhằm cung cấp cái nhìn về việc tối ưu hóa chúng.\u003C/jats:p>","\u003Cjats:p>Human activity recognition (HAR) tasks have traditionally been solved using engineered features obtained by heuristic processes. Current research suggests that deep convolutional neural networks are suited to automate feature extraction from raw sensor inputs. However, human activities are made of complex sequences of motor movements, and capturing this temporal dynamics is fundamental for successful HAR. Based on the recent success of recurrent neural networks for time series domains, we propose a generic deep framework for activity recognition based on convolutional and LSTM recurrent units, which: (i) is suitable for multimodal wearable sensors; (ii) can perform sensor fusion naturally; (iii) does not require expert knowledge in designing features; and (iv) explicitly models the temporal dynamics of feature activations. We evaluate our framework on two datasets, one of which has been used in a public activity recognition challenge. Our results show that our framework outperforms competing deep non-recurrent networks on the challenge dataset by 4% on average; outperforming some of the previous reported results by up to 9%. Our results show that the framework can be applied to homogeneous sensor modalities, but can also fuse multimodal sensors to improve performance. We characterise key architectural hyperparameters’ influence on performance to provide insights about their optimisation.\u003C/jats:p>",{"VI":4638,"EN":4639},"Mạng Nơ-ron Tích Chập Sâu và Nơ-ron Tái Kết Nối LSTM cho Nhận Diện Hoạt Động Đeo Được Đa Mô Đun","Deep Convolutional and LSTM Recurrent Neural Networks for Multimodal Wearable Activity 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