Publications by authors named "P H Pan"

Acinetobacter baumannii, an opportunistic bacterium prevalent in various environment, is a significant cause of nosocomial infections in ICUs. As the causative agent of pneumonia, septicemia, and meningitis, A. baumannii typically exhibits multidrug resistance and is associated with poor prognosis, thus led to a challenge for researchers in developing new treatment and prevention methods.

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Applying artificial intelligence techniques to flexibly model the binding between the ligand and protein has attracted extensive interest in recent years, but their applicability remains improved. In this study, we have developed CarsiDock-Flex, a novel two-step flexible docking paradigm that generates binding poses directly from predicted structures. CarsiDock-Flex consists of an equivariant deep learning-based model termed CarsiInduce to refine ESMFold-predicted protein pockets with the induction of specific ligands and our existing CarsiDock algorithm to redock the ligand into the induced binding pockets.

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Background: Prior studies suggest that childhood maltreatment is associated with altered hippocampal volume. However, longitudinal studies are currently scarce, making it difficult to determine how alterations in hippocampal volume evolve over time. The current study examined the relationship between childhood maltreatment and hippocampal volumetric development across childhood and adolescence in a community sample.

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Article Synopsis
  • Two new bacterial strains, 25B02-3 and BH-R2-4, were discovered in seawater from the Bering and Chukchi Seas, sharing 99.6% similarity in their 16S rRNA gene sequences.
  • Phylogenetic analysis suggests they may be a novel species within a specific genus, distinguished by digital DNA-DNA hybridization and average nucleotide identity values indicating separate genomic species.
  • Characterization of their fatty acids, respiratory quinones, and genomic DNA indicates unique biochemical properties, leading to the proposal of a new species name, with strain 25B02-3 designated as the type strain.
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Objective: To build a prediction nomogram for early prediction of live birth probabilities according to number of oocytes retrieved in women ≤ 35 years of age.

Methods: A prediction model was built including 9265 infertile women ≤ 35 years of age accepting their first ovum pick-up cycle from January 2018 to December 2022. Least absolute shrinkage and selection operator (LASSO) regression was performed to identify independent predictors and establish a nomogram to predict reproductive outcomes.

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