ABSTRACT
Cold adapted live attenuated influenza vaccines can effectively prevent human disease and death caused by influenza virus. Since chicken embryos are used as the culture substrate for the large-scale production of influenza vaccines, cold adapted live attenuated influenza vaccines may be contaminated by exogenous avian viruses. Rapid and sensitive methods such as TaqMan-based quantitative PCR are needed for the detection of exogenous avian viruses during cold adapted live attenuated influenza vaccines production. In this study, a TaqMan-based quantitative PCR method was established for the detection of three common exogenous avian viruses, including fowl adenovirus type I, type â ¢ and avian leukosis virus. Avian virus-encoding plasmids purified in high-performance liquid chromatography were essential for sensitivity analysis. The sensitivity reached 1 copy per reaction for each of the avian virus plasmids. Standard curves showed a strong linear relationship. The TaqMan-based quantitative PCR method had high specificity and no cross-reactivity with other irrelevant viruses. Furthermore, the established TaqMan-based quantitative PCR can effectively detect 0.1 TCID50 of each avian virus without or with interference from the influenza virus nucleic acid. Ultimately, this method was used to test three master seed lots of monovalent cold adapted live attenuated influenza vaccine, and the results showed that no fowl adenovirus type I, type â ¢ or avian leukosis virus contamination, which were consistent with serological methods. The TaqMan-based quantitative PCR method for the determination of extraneous avian viruses in cold adapted live attenuated influenza vaccines met the requirement for both conventional and emergency inspection on cold adapted live attenuated influenza vaccines.
ABSTRACT
BACKGROUND: Diabetes mellitus is the most challenging and fastest-growing global public health concern. Approximately 10.5% of the global adult population is affected by diabetes, and almost half of them are undiagnosed. The growing at-risk population exacerbates the shortage of health resources, with an estimated 10.6% and 6.2% of adults worldwide having impaired glucose tolerance and impaired fasting glycemia, respectively. All current diabetes screening methods are invasive and opportunistic and must be conducted in a hospital or laboratory by trained professionals. At-risk participants might remain undetected for years and miss the precious time window for early intervention to prevent or delay the onset of diabetes and its complications. OBJECTIVE: We aimed to develop an artificial intelligence solution to recognize elevated blood glucose levels (≥7.8 mmol/L) noninvasively and evaluate diabetic risk based on repeated measurements. METHODS: This study was conducted at KK Women's and Children's Hospital in Singapore, and 500 participants were recruited (mean age 38.73, SD 10.61 years; mean BMI 24.4, SD 5.1 kg/m2). The blood glucose levels for most participants were measured before and after consuming 75 g of sugary drinks using both a conventional glucometer (Accu-Chek Performa) and a wrist-worn wearable. The results obtained from the glucometer were used as ground-truth measurements. We performed extensive feature engineering on photoplethysmography (PPG) sensor data and identified features that were sensitive to glucose changes. These selected features were further analyzed using an explainable artificial intelligence approach to understand their contribution to our predictions. RESULTS: Multiple machine learning models were trained and assessed with 10-fold cross-validation, using participant demographic data and critical features extracted from PPG measurements as predictors. A support vector machine with a radial basis function kernel had the best detection performance, with an average accuracy of 84.7%, a sensitivity of 81.05%, a specificity of 88.3%, a precision of 87.51%, a geometric mean of 84.54%, and F score of 84.03%. CONCLUSIONS: Our findings suggest that PPG measurements can be used to identify participants with elevated blood glucose measurements and assist in the screening of participants for diabetes risk.
ABSTRACT
@#Abstract：Objective To improve the replication level of varicella⁃zoster virus（VZV）in human diploid cell line MRC⁃5 and increase the yield of VZV vaccine by reducing the expression of interferon（IFN）related genes via optimizing the cell line MRC⁃5. Methods Interferon receptor 1（IFNAR1）silenced MRC⁃5 cell line（MRC⁃5IFNAR1⁃）was constructed by CRISPR／Cas9 gene editing technology，which was determined for the relative expression of IFNAR1 mRNA，and for those of mRNA of IFN related genes IFNβ and OAS1 after VZV infection by qRT⁃PCR to evaluate the effect of gene silencing. Gene mutation sequences were further identified by sequencing of the silenced sites. The replication of VZV in MRC⁃5 and MRC⁃5IFNAR1⁃ cell lines was compared 168 h after VZV infection by using qRT⁃PCR and plaque formation unit（PFU）assay， to evaluate the effect of MRC⁃5IFNAR1⁃cell line on VZV replication. Results The growth status of MRC⁃5IFNAR1⁃ cell line wasconsistent with that of MRC ⁃ 5 cells，and the relative expression of IFNAR1 mRNA decreased by 73%；The relative expressions of IFNβ and OAS1 mRNA in MRC⁃5IFNAR1⁃ cell line were 61% and 90% lower than those in MRC⁃ 5 cells respectively after VZV infection；In addition，168 h after VZV infection，the level of DNA replication and the titer of VZV increased by 5. 7 folds and 4 folds respectively. Conclusion The successful establishment of MRC⁃5IFNAR1⁃ cell line may be a potential scheme to increase the yield of vaccines based on human diploid cells，and provided a reference for expanding production of VZV vaccine.
ABSTRACT
Defective interfering particles (DIPs) are particles containing defective viral genomes (DVGs) generated during viral replication. DIPs have been found in various RNA viruses, especially in influenza viruses. Evidence indicates that DIPs interfere with the replication and encapsulation of wild-type viruses, namely standard viruses (STVs) that contain full-length viral genomes. DIPs may also activate the innate immune response by stimulating interferon synthesis. In this review, the underlying generation mechanisms and characteristics of influenza virus DIPs are summarized. We also discuss the potential impact of DIPs on the immunogenicity of live attenuated influenza vaccines (LAIVs) and development of influenza vaccines based on NS1 gene-defective DIPs. Finally, we review the antiviral strategies based on influenza virus DIPs that have been used against both influenza virus and SARS-CoV-2. This review provides systematic insights into the theory and application of influenza virus DIPs.
