Publications by authors named "H X M Nguyen"

Objectives: This study aims to generate a de novo complete whole-genome assembly of Pseudomonas sp. strain HOU2, which is an endophytic bacterium isolated from dangshen roots that shows to improve the growth of in vitro dangshen plants. Further investigation of the whole genome of Pseudomonas sp.

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Background: CD4+ T cells expressing α4β7 are optimal targets for HIV infections, with higher pre-HIV α4β7hi expression linked to increased HIV acquisition and progression in South African women. However, similar associations were not observed in men who have sex with men (MSM) or people who inject drugs (PWID) in the Americas, indicating need for further research.

Methods: This retrospective case-control study enrolled heterosexual men and women from South Africa (HIV Vaccine Trials Network; HVTN 503) and East Africa (Partners Pre-Exposure Prophylaxis/Couples' Observational Study; PP/COS), quantifying α4β7 expression on CD4+ T cells as a predictor of subsequent HIV risk using flow cytometry analyses.

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A pyruvate dehydrogenase complex deficiency causes a reduction in adenosine triphosphate production and energy insufficiency, leading to neurological disorders. An abnormal E1-alpha protein originating from the gene with pathogenic variants is unable to communicate with E1-beta for the formation of the E1 enzyme, decreasing pyruvate dehydrogenase complex activity. In this study, we report a Vietnamese boy with lethargy, severe metabolic acidosis, increased serum lactate, hyperalaninemia, lactic acidosis, and globus pallidus lesions.

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To move beyond an energy economy dominated by fossil fuel utilization, high-performance electrochemical cells must be designed for energy storage and conversion. Selective etching is a promising, cost-effective solution-processing method for the large-scale top-down production of nanomaterials for high-performance electrodes. This review outlines general methodologies and mechanisms by which selective etching can be applied to create nanomaterials, including various template-assisted, facet-selective, and electrochemical methods, as well as in-depth case studies of state-of-the-art research involving selectively etched nanomaterials for electrocatalytic and energy storage applications.

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Deep learning (DL) holds great promise to improve medical diagnostics, including pathology. Current DL research mainly focuses on performance. DL implementation potentially leads to environmental consequences but approaches for assessment of both performance and carbon footprint are missing.

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