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Comparing the Effects of Different Natural Products on Reducing Tumor Growth in a Drosophila Model

Ganesh et al. | May 31, 2020

Comparing the Effects of Different Natural Products on Reducing Tumor Growth in a <i>Drosophila</i> Model

In this work, the authors compared the effects of common natural products, including sesame, cinnamon, garlic, moringa and turmeric on tumor growth in Drosophila eyes. The data showed that these natural products cannot be used to reduce tumor growth once it has completely formed. However, the data suggested that some natural products can reduce cancer cell growth when tumors are treated early.

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The Protective Effects of Panax notoginseng Saponin on the Blood-Brain Barrier via the Nrf2/ARE Pathway in bEnd3 Cells

Yang et al. | Apr 06, 2016

The Protective Effects of <i>Panax notoginseng</i> Saponin on the Blood-Brain Barrier via the Nrf2/ARE Pathway in bEnd3 Cells

Disruption of the blood-brain barrier (BBB) is related to many neurological disorders, and can be caused by oxidative stress to cerebral microvascular endothelial cells (CMECs) composing the BBB. The authors of the paper investigated the protective effects of the total saponins in the leaves of Panax notoginseng (LPNS) on oxidative-stress-induced damage in a mouse cerebral microvascular endothelial cell line.

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Automated classification of nebulae using deep learning & machine learning for enhanced discovery

Nair et al. | Feb 01, 2024

Automated classification of nebulae using deep learning & machine learning for enhanced discovery

There are believed to be ~20,000 nebulae in the Milky Way Galaxy. However, humans have only cataloged ~1,800 of them even though we have gathered 1.3 million nebula images. Classification of nebulae is important as it helps scientists understand the chemical composition of a nebula which in turn helps them understand the material of the original star. Our research on nebulae classification aims to make the process of classifying new nebulae faster and more accurate using a hybrid of deep learning and machine learning techniques.

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How are genetically modified foods discussed on TikTok? An analysis of #GMOFOODS

Basch et al. | Nov 20, 2023

How are genetically modified foods discussed on TikTok? An analysis of #GMOFOODS
Image credit: Camilo Jimenez

Here, the authors investigated engagement with #GMOFOODS, a hashtag on TikTok. They hypothesized that content focused on the negative effects of genetically modified organisms would receive more interaction driven by consumers. They found that the most common cateogry focused on the disadvantages of GMOs related to nutrition and health with the number of views determining if the video would be provided to users.

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Effect of Fertilizer on Water Quality of Creeks over Time

Chen et al. | May 02, 2021

Effect of Fertilizer on Water Quality of Creeks over Time

Fertilizers are commonly used to improve agricultural yield. Unfortunately, chemical fertilizers can seep into drinking water, potentially harming humans and other forms of life. Here, the authors investigate the effect of fertilizer on the water quality of Saratoga Creek over time. They find that fertilizers can alter the acidity of the creek's water, which can be harmful to aquatic species, as well as increase the levels of nitrates temporarily.

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Assigning Lightning Seasons to Different Regions in the United States

Hawkins et al. | Sep 07, 2020

Assigning Lightning Seasons to Different Regions in the United States

Climate change is predicted to increase the frequency of severe thunderstorm events in coming years. In this study, the authors hypothesized that (i) the majority of severe thunderstorm events will occur in the summer months in all states examined for all years analyzed, (ii) climate change will cause an unusual number of severe thunderstorm events in winter months in all states, (iii) thundersnow would be observed in Colorado, and (iv.) there would be no difference in the number of severe thunderstorm events between states in any given year examined. They classified lightning seasons in all states observed, with the most severe thunderstorm events occurring in May, June, July, and August. Colorado, New Jersey, Washington, and West Virginia were found to have severe thunderstorm events in the winter, which could be explained by increased winter storms due to climate change (1). Overall, they highlight the importance of quantifying when lightning seasons occur to avoid lightning-related injuries or death.

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