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Effects of Wi-Fi EMF on Drosophila melanogaster

Anand et al. | Jan 29, 2020

Effects of Wi-Fi EMF on <em>Drosophila melanogaster</em>

While increased access to Wi-Fi has been a great advancement, we have a limited understanding if there are any health effects on animals. In this study, Anand and Anand exposed fruit flies (Drosophila melanogaster) to different concentrations of Wi-Fi electromagnetic fields, and observed effects on their reproduction and survivability.

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Rhizosphere metagenome analysis and wet-lab approach to derive optimal strategy for lead remediation in situ

Bhat et al. | Jul 18, 2023

Rhizosphere metagenome analysis and wet-lab approach to derive optimal strategy for lead remediation <i>in situ</i>
Image credit: Karolina Grabowska

The Environmental Protection Agency (EPA) reports a significant number of heavy metal-contaminated sites across the United States. To address this public health concern, rhizoremediation using microbes has emerged as a promising solution. Here, a combination of soil microbes were inoculated in the rhizosphere in soil contaminated with 500 parts per million (ppm) of lead. Results showed rhizoremediation is an effective bioremediation strategy and may increase crop productivity by converting nonarable lands into arable lands.

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The Role of Corresponding Race, Gender, and Species as Incentives for Charitable Giving

Antonides-Jensen et al. | Jul 31, 2019

The Role of Corresponding Race, Gender, and Species as Incentives for Charitable Giving

Inherent bias is often the unconscious driver of human behavior, and the first step towards overcoming these biases is our awareness of them. In this article the authors investigate whether race, gender or species affect the choice of charity by middle class Spaniards. Their conclusions serve as a starting point for further studies that could help charities refine their campaigns in light of these biases effectively transcending them or taking advantage of them to improve their fundraising attempts.

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Evaluating Biomarkers and Treatments for Acute Kidney Injury in a Zebrafish Model

Mathew et al. | Aug 11, 2019

Evaluating Biomarkers and Treatments for Acute Kidney Injury in a Zebrafish Model

Coronary Artery Disease (CAD) is the leading cause of death in the United States, and 81% of Acute Kidney Injury (AKI) patients in the renal fibrosis stage later develop CAD. In this study, Mathew and Joykutty aimed to create a cost-effective strategy to treat AKI and thus prevent CAD using a model of the zebrafish, Danio rerio. They first tested whether AKI is induced in Danio rerio upon exposure to environmental toxins, then evaluated nitrotyrosine as an early biomarker for toxin-induced AKI. Finally, they evaluated 4 treatments of renal fibrosis, the last stage of AKI, and found that the compound SB431542 was the most effective treatment (reduced fibrosis by 99.97%). Their approach to treating AKI patients, and potentially prevent CAD, is economically feasible for translation into the clinic in both developing and developed countries.

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Tap water quality analysis in Ulaanbaatar City

Munkhbat et al. | Sep 25, 2022

Tap water quality analysis in Ulaanbaatar City

There have been several issues concerning the water quality in Ulaanbaatar, Mongolia in the past few years. This study, we collected 28 samples from 6 districts of Ulaanbaatar to check if the water supply quality met the standards of the World Health Organization, the Environmental Protection Agency, and a Mongolian National Standard. Only three samples fully met all the requirements of the global standards. Samples in Zaisan showed higher hardness (>120 ppm) and alkalinity levels (20–200 ppm) over the other districts in the city. Overall, the results show that it is important to ensure a safe and accessible water supply in Ulaanbaatar to prevent future water quality issues.

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The influence of experience on the perception of homelessness in individuals

Dua et al. | Jun 30, 2022

The influence of experience on the perception of homelessness in individuals

Economic disruptions and housing instabilities have for long propelled a homelessness epidemic among adults and youth in the United States. The COVID-19 pandemic has accelerated this phenomenon with a 2.2% increase in the number of homeless individuals and more than 70% of Americans fearing this outcome for themselves. This study aimed to analyze the perception of homelessness in two groups: Those who have previously experienced and overcome homelessness and those who are at-risk for experiencing the same. The study analyzed publicly available Reddit posts by people in both groups and found that at-risk individuals tended to associate primarily fearful emotions with the event, and those who had overcome homelessness tended to view the event in a negative context. These results may encourage the establishment of resources to support the currently homeless and help them transition into society, and services to help them cope with negative emotions, as negative attitudes have been shown to decrease life expectancy.

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Model selection and optimization for poverty prediction on household data from Cambodia

Wong et al. | Sep 29, 2023

Model selection and optimization for poverty prediction on household data from Cambodia
Image credit: Paul Szewczyk

Here the authors sought to use three machine learning models to predict poverty levels in Cambodia based on available household data. They found teat multilayer perceptron outperformed the other models, with an accuracy of 87 %. They suggest that data-driven approaches such as these could be used more effectively target and alleviate poverty.

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Developing a Method to Remove Inorganic Arsenic from Rice with Natural Substances

Mukai et al. | Oct 27, 2020

Developing a Method to Remove Inorganic Arsenic from Rice with Natural Substances

In this study, the authors tested different approaches for removing arsenic from rice. Due to higher arsenic levels in water, some areas grow rice with higher levels as well. This is a health hazard and so developing methods to remove arsenic from the rice will be helpful to many. Using a rapid arsenic kit, the authors found that activated charcoal was the most effective at removing arsenic from rice.

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The Effects of Altered Microbiome on Caenorhabditis elegans Egg Laying Behavior

Gohari et al. | Aug 12, 2019

The Effects of Altered Microbiome on <em>Caenorhabditis elegans</em> Egg Laying Behavior

Since the discovery that thousands of different bacteria colonize our gut, many of which are important for human wellbeing, understanding the significance of balancing the different species on the human body has been intensely researched. Untangling the complexity of the gut microbiome and establishing the effect of the various strains on human health is a challenge in many circumstances, and the need for simpler systems to improve our basic understanding of microbe-host interactions seems necessary. C. elegans are a well-established laboratory animal that feed on bacteria and can thus serve as a less complex system for studying microbe-host interactions. Here the authors investigate how the choice of bacterial diet affects worm fertility. The same approach could be applied to many different outcomes, and facilitate our understanding of how the microbes colonizing our guts affect various bodily functions.

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