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Evaluation of Tea Extract as an Inhibitor of Oxidative Stress in Prostate Cells

Zhang et al. | Jan 22, 2019

Evaluation of Tea Extract as an Inhibitor of Oxidative Stress in Prostate Cells

One important factor that contributes to human cancers is accumulated damage to cells' DNA due to the oxidative stress caused by free radicals. In this study, the authors investigate the effects of several different tea leaf extracts on oxidative stress in cultured human prostate cells to see if antioxidants in the tea leaves could help protect cells from this type of DNA damage. They found that all four types of tea extract (as well as direct application of the antioxidant EGCG) improved the outcomes for the cultured cells, with white tea extract having the strongest effect. This research suggests that tea extracts and the antioxidants that they contain may have applications in the treatment of the many diseases associated with cellular DNA damage, including cancer.

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Increasing Average Yearly Temperature in Two U.S. Cities Shows Evidence for Climate Change

Savage et al. | Sep 20, 2018

Increasing Average Yearly Temperature in Two U.S. Cities Shows Evidence for Climate Change

The authors were interested in whether they could observe the effects of climate change by analyzing historical temperature data of two U.S. cities. They predicted that they should observe a warming trend in both cities. Their results showed that despite yearly variations, warming trends can be observed both in Rochester, NY and Seattle, WA which fit the predictions of climate change forecasts.

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Beeing sustainable: Honey as a bioindicator for pollution

Donnellan et al. | Oct 06, 2021

Beeing sustainable: Honey as a bioindicator for pollution

In this study, Donnellan and colleagues investigated how environmental pollution may be affecting honey samples from Chicago apiaries. They found no significant correlation between heavy metal concentration in honey to distance from local industries, suggesting a minimal effect of proximity to industrial pollution on honey contamination.

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Contribution of environmental factors to genetic variation in the Pacific white-sided dolphin

Talwar et al. | Jan 23, 2024

Contribution of environmental factors to genetic variation in the Pacific white-sided dolphin
Image credit: Flavio

Here the authors sought to understand the effects of different variables that may be tied to pollution and climate change on genetic variation of Pacific white-sided dolphins, a species that is currently threatened by water pollution. Based on environmental data collected alongside a genetic distance matrix, they found that ocean currents had the most significant impact on the genetic diversity of Pacific white-sided dolphins along the Japanese coast.

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An Analysis on Exoplanets and How They are Affected by Different Factors in Their Star Systems

Selph et al. | Dec 06, 2018

An Analysis on Exoplanets and How They are Affected by Different Factors in Their Star Systems

In this article, the authors systematically study whether the type of a star is correlated with the number of planets it can support. Their study shows that medium-sized stars are likely to support more than one planet, just like the case in our solar system. They predict that, of the hundreds of planets beyond our solar system, 6% might be habitable. As humans work to travel further and further into space, some of those might truly be suited for human life.

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Linearity of piezoelectric response of electrospun polymer-based (PVDF) fibers with barium titanate nanoparticles

Nichitiu et al. | Feb 13, 2023

Linearity of piezoelectric response of electrospun polymer-based (PVDF) fibers with barium titanate nanoparticles

Here, seeking to develop an understanding of the properties that determine the viability of piezoelectric flexible materials for applications in electro-mechanical sensors, the authors investigated the effects of the inclusion BaTiO3 nanoparticles in electrospun Polyvinyledene Fluoride. They found the voltage generated had a piecewise linear dependence on the applied force at a few temperatures.

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A land use regression model to predict emissions from oil and gas production using machine learning

Cao et al. | Mar 24, 2023

A land use regression model to predict emissions from oil and gas production using machine learning

Emissions from oil and natural gas (O&G) wells such as nitrogen dioxide (NO2), volatile organic compounds (VOCs), and ozone (O3) can severely impact the health of communities located near wells. In this study, we used O&G activity and wind-carried emissions to quantify the extent to which O&G wells affect the air quality of nearby communities, revealing that NO2, NOx, and NO are correlated to O&G activity. We then developed a novel land use regression (LUR) model using machine learning based on O&G prevalence to predict emissions.

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