Publications by authors named "B Priestly Shan"

Liver fibrosis is a critical liver disease that can progress to more severe manifestations, such as cirrhosis, yet no effective targeted therapies are available. Here, we identify that ATF4, a master transcription factor in ER stress response, promotes liver fibrosis by facilitating a stress response-independent epigenetic program in hepatic stellate cells (HSCs). Unlike its canonical role in regulating UPR genes during ER stress, ATF4 activates epithelial-mesenchymal transition (EMT) gene transcription under fibrogenic conditions.

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The Ni-rich LiNiCoMnO cathode (NCM, ≥ 0.6) suffers rapid capacity decay due to serious surface degradations from the corrosion of the electrolyte. The processes of the HO- and O-based AlO atomic layer deposition (ALD) on the single-crystal LiNiCoMnO (NCM83) are investigated by measurements to understand the mechanism of their different impacts on the electrochemical performance of NCM83.

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  • eDNA technology shows promise due to its convenience and sensitivity, but understanding its behavior in various environments and species is essential.
  • The study focused on the aquaculture of Acanthopagrus schlegelii to investigate the release and degradation mechanisms of its eDNA, revealing key findings about concentration patterns.
  • Results indicated that eDNA concentration peaked at 42 hours, showed a strong correlation with biomass, and decreased as salinity increased, providing valuable insights for future eDNA applications in marine ecology.
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In the contemporary field of life sciences, researchers have gradually recognized the critical role of microbes in maintaining human health. However, traditional biological experimental methods for validating the association between microbes and diseases are both time-consuming and costly. Therefore, developing effective computational methods to predict potential associations between microbes and diseases is an important and urgent task.

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  • The study addresses challenges in reliable cancer screening due to complex serum constituents and limited knowledge of biomarkers.
  • An innovative biomarker-free serum-SERS technique utilizes three specially designed substrates to gather rich information from serum samples.
  • With the help of quadratic discriminant analysis (QDA), the method achieves an impressive 100% accuracy in diagnosing cancer in a sample of 122 out of 194 serum samples, demonstrating a promising advancement in cancer detection.
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