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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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Investigating auxin import and export proteins in Chlorella vulgaris

Wang et al. | Apr 19, 2025

Investigating auxin import and export proteins in <i>Chlorella vulgaris</i>

This study explores auxin signaling in Chlorella vulgaris, a green alga with potential for sustainable biofuel and food production. Evidence from protoplast swelling experiments suggests that C. vulgaris secretes auxin and possesses auxin import proteins, highlighting previously uncharacterized signaling pathways. These findings could support more efficient cultivation and resource extraction strategies.

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A juxtaposition of the effects of natural and chemical fertilizers on Ocimum basilicum

Wilson et al. | Jun 03, 2024

A juxtaposition of the effects of natural and chemical fertilizers on <i>Ocimum basilicum</i>
Image credit: The authors

Agricultural fertilizer application is a key innovation in providing enough food to feed the world. Fertilizers come in various types and farmers must choose which fertilizer is the best for their applications. To learn more about the effectiveness of various fertilizers, Wilson and Rasmus studied the effects of natural and chemical fertilizers on growth of basil plants.

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Enhancing marine debris identification with convolutional neural networks

Wahlig et al. | Apr 03, 2024

Enhancing marine debris identification with convolutional neural networks
Image credit: The authors

Plastic pollution in the ocean is a major global concern. Remotely Operated Vehicles (ROVs) have promise for removing debris from the ocean, but more research is needed to achieve full effectiveness of the ROV technology. Wahlig and Gonzales tackle this issue by developing a deep learning model to distinguish trash from the environment in ROV images.

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