instruction:
In this task, you're given a paragraph from the research paper and your task is to generate a suitable title for the research paper based on the given paper. Under 100 words is a good title length.
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An enzyme-linked immunosorbent assay (ELISA) and a rapid immunochromatographic test for detection of immunoglobulin G (IgG) antibodies in severe acute respiratory syndrome (SARS) patients were developed by utilizing the well-characterized recombinant proteins Gst-N and Gst-U274. The ELISA detected IgG antibodies to SARS-CoV in all 74 convalescent-phase samples from SARS patients while weakly cross-reacting to only 1 of the 210 control sera from healthy donors. This finding thus led to a kit sensitivity, specificity, and accuracy of 100, 99.5, and 99.6%, respectively. The test thus provided a positive predictive value (PPV) of 98.7% and a negative predictive value (NPV) of 100%. In addition, the ELISA gave a positive delta of 5.4 and a negative delta of 3.6, indicating an excellent differentiation between positives and negatives. The same recombinant proteins were also applied to a newly developed platform for the development of a 15-min rapid test. The resulting rapid test has an excellent agreement of 99.6%, with a kappa value of 1.00, with the ELISA. Again, this rapid test was able to detect 100% of the samples tested (n ‫؍‬ 42) while maintaining a specificity of 99.0% (n ‫؍‬ 210). The PPV and NPV for the rapid test thus reached 95.3 and 100%, respectively.
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Recombinant Protein-Based Enzyme-Linked Immunosorbent Assay and Immunochromatographic Tests for Detection of Immunoglobulin G Antibodies to Severe Acute Respiratory Syndrome (SARS) Coronavirus in SARS Patients


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Introduction: Accurate and timely prediction for endemic infectious diseases is vital for public health agencies to plan and carry out any control methods at an early stage of disease outbreaks. Climatic variables has been identified as important predictors in models for infectious disease forecasts. Various approaches have been proposed in the literature to produce accurate and timely predictions and potentially improve public health response. Methods: We assessed how the machine learning LASSO method may be useful in providing useful forecasts for different pathogens in countries with different climates. Separate LASSO models were constructed for different disease/country/forecast window with different model complexity by including different sets of predictors to assess the importance of different predictors under various conditions. Results: There was a more apparent cyclicity for both climatic variables and incidence in regions further away from the equator. For most diseases, predictions made beyond 4 weeks ahead were increasingly discrepant from the actual scenario. Prediction models were more accurate in capturing the outbreak but less sensitive to predict the outbreak size. In different situations, climatic variables have different levels of importance in prediction accuracy. Conclusions: For LASSO models used for prediction, including different sets of predictors has varying effect in different situations. Short term predictions generally perform better than longer term predictions, suggesting public health agencies may need the capacity to respond at short-notice to early warnings.
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The utility of LASSO-based models for real time forecasts of endemic infectious diseases: A cross country comparison


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Background: Murine norovirus (MNV) is recognized as the most prevalent viral pathogen in captive mouse colonies. The rapid detection assay for MNV would be a useful tool for monitoring and preventing MNV infection. A recombinase polymerase amplification (RPA) assay was established in this study to provide a solution for rapid and sensitive detection of MNV. Results: The detection limit of the RT-RPA assay for the detection of MNV was 1 × 10 2 copies of RNA molecules per reaction. The assay was specific since there was no cross-reaction with other common murine viruses. In addition, the broad reactivity of the RT-RPA assay was validated using the synthesized template carrying seven point mutations among several MNV strains. The MNV RT-RPA assay could detect as few as 1 × 10 2 copies of the mutant per reaction, suggesting the assay could be broadly reactive against a large diversity of MNV strains. Forty eight clinical samples including 16 gastric tissue specimens, 16 cecal tissue specimens and 16 fecal specimens were tested for the validation of the new developed RT-RPA assay. The detection results of RT-RPA and RT-qPCR for clinical samples were very similar, except that a gastric tissue sample which was positive by RT-qPCR, with a RNA titer of 27 copies, was negative by RT-RPA. Conclusions: A broadly reactive RT-RPA assay was successfully established for MNV detection.
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Development and evaluation of a broadly reactive reverse transcription recombinase polymerase amplification assay for rapid detection of murine norovirus