Articles
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Cellular & Tissue Engineering
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Machine learning algorithm to characterize antimicrobial resistance associated with the International Space Station surface microbiome
Machine learning algorithm to characterize antimicrobial resistance associated with the International Space Station surface microbiome
Cellular & Tissue Engineering
Abstractive Summary
Study examining machine learning algorithm to characterize antimicrobial resistance associated. Spaceflight triggers widespread changes in gene expression affecting stress responses, DNA repair, and mitochondrial function. Epigenetic modifications occur, with some changes persisting long after return. Understanding these molecular adaptations is fundamental to developing effective countermeasures for long-duration missions.
Extractive Summary
Study examining machine learning algorithm to characterize antimicrobial resistance associated. Genome-wide expression analysis revealed thousands of differentially expressed genes. Stress response pathways were universally upregulated. DNA repair genes showed increased expression. Mitochondrial genes were downregulated substantially. Epigenetic modifications included altered methylation patterns. Some changes persisted months after return to Earth. Cell cycle regulation genes were significantly affected.
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Keywords
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Abstractive Keywords
changes, long, study, examining, machine, learning, algorithm, characterize, antimicrobial, resistance
Extractive Keywords
genes, expression, study, examining, machine, learning, algorithm, characterize, antimicrobial, resistance
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