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Investigating toxicity and antimicrobial properties of silver nanoparticles in Escherichia coli and Drosophila melanogaster

Ghosh et al. | Dec 01, 2025

Investigating toxicity and antimicrobial properties of silver nanoparticles in <em>Escherichia coli</em> and <em>Drosophila melanogaster</em>
Image credit: Ghosh and Hendricks

This paper looks at the antibacterial and toxic effects of silver nanoparticles (AgNPs) on Escherichia coli bacteria and Drosophila melanogaster fruit flies. They modified the AgNPs size, concentration, and surface coating to determine the effects on each of the organisms. For both organisms, increased AgNP concentration demonstrated increased toxicity but particle size and surface coating had opposing effects.

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Depression detection in social media text: leveraging machine learning for effective screening

Shin et al. | Mar 25, 2025

Depression detection in social media text: leveraging machine learning for effective screening

Depression affects millions globally, yet identifying symptoms remains challenging. This study explored detecting depression-related patterns in social media texts using natural language processing and machine learning algorithms, including decision trees and random forests. Our findings suggest that analyzing online text activity can serve as a viable method for screening mental disorders, potentially improving diagnosis accuracy by incorporating both physical and psychological indicators.

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