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Effects of Photoperiod Alterations on Stress Response in Daphnia magna

Kelly et al. | Mar 10, 2022

Effects of Photoperiod Alterations on Stress Response in <em>Daphnia magna</em>

Here, seeking to better understand the effects of altered day-night cycles, the authors considered the effects of an altered photoperiod on Daphnia magna. By tracking possible stress responses, including mean heart rate, brood size, and male-to-female ratio they found that a shorter photoperiod resulted in altered mean heart rates and brood size. The authors suggest that based on these observations, it is important to consider the effects of photoperiod alterations and the stress responses of other organisms.

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Homology modeling of clinically-relevant rilpivirine-resistant HIV-RT variants identifies novel rilpivirine analogs with retained binding affinity against NNRTI-resistant HIV mutations

Luk et al. | Jan 24, 2022

Homology modeling of clinically-relevant rilpivirine-resistant HIV-RT variants identifies novel rilpivirine analogs with retained binding affinity against NNRTI-resistant HIV mutations

Human immunodeficiency virus (HIV), which affects tens of millions of individuals worldwide, can lead to acquired immunodeficiency syndrome (AIDS). While there is currently no cure for HIV, the development of small molecule antiretroviral agents has greatly improved the prognosis of infected individuals, especially in developed countries. Here, the authors employ homology modeling and molecular docking towards the identification of novel rilpivirine analogs that retain high binding affinity to clinically relevant rilpivirine-resistant mutations of the HIV reverse transcriptase enzyme.

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Artificial Intelligence-Based Smart Solution to Reduce Respiratory Problems Caused by Air Pollution

Bhardwaj et al. | Dec 14, 2021

Artificial Intelligence-Based Smart Solution to Reduce Respiratory Problems Caused by Air Pollution

In this report, Bhardwaj and Sharma tested whether placing specific plants indoors can reduce levels of indoor air pollution that can lead to lung-related illnesses. Using machine learning, they show that plants improved overall indoor air quality and reduced levels of particulate matter. They suggest that plant-based interventions coupled with sensors may be a useful long-term solution to reducing and maintaining indoor air pollution.

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