Publications by authors named "M S Jia-Jia Yan"

Ordered intermetallic alloys are renowned for their impressive mechanical, chemical, and physical properties, making them appealing for various fields. However, practical applications of them have long been severely hindered due to their severe brittleness and poor fabricability. It is difficult to fabricate such materials into components with complex geometries through traditional subtractive manufacturing methods.

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Objective: To investigate the relationship between protein-rich foods, various nutritional supplements, and age of natural menopause and its symptoms.

Methods: This study was a large-scale cross-sectional survey. A multi-stage stratified random sampling method was used to select a sample of 52,347 residents aged 35-60 years from 26 districts/counties across 13 cities in 12 provinces in China.

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Soybean is an important and versatile crop worldwide. Enhancing soybean architecture offers a potential method to increase yield. Plant-specific transcription factors play a crucial, yet often unnoticed, role in regulating plant growth and development.

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During the life cycle of the influenza virus, viral RNPs (vRNPs) are transported to the nucleus for replication. Given that a large number of progeny viral RNA occupies the nucleus, whether there is any host protein located in the nucleus that recognizes the viral RNA and inhibits the viral replication remains largely unknown. In this study, to explore the role of hnRNPH1 in influenza virus infection, we knocked down and over-expressed the hnRNPH1 proteins in 293T cells, then infected the cells with the influenza virus.

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Stacking fermentation is critical in sauce-flavor production, but winter production often sees abnormal fermentations, like Waistline and Sub-Temp fermentation, affecting yield and quality. This study used three machine learning models (Logistic Regression, KNN, and Random Forest) combined with multi-omics (metagenomics and flavoromics) to develop a classification model for abnormal fermentation. SHAP analysis identified 13 Sub-Temp Fermentation and 9 Waistline microbial biomarkers, along with 9 Sub-Temp Fermentation and 12 Waistline flavor biomarkers.

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