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Bacterial Richness of Soil Samples from Southern New Hampshire

Chalasani et al. | Sep 21, 2016

Bacterial Richness of Soil Samples from Southern New Hampshire

Advancement in DNA sequencing technology has greatly increased our understanding about the role of bacteria in soil. The authors of this study examine the microbial content of soil samples taken from three locations in southern New Hampshire with varying pH and plant composition.

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The effects of stress on the bacterial community associated with the sea anemone Diadumene lineata

Cahill et al. | Feb 15, 2021

The effects of stress on the bacterial community associated with the sea anemone Diadumene lineata

In healthy ecosystems, organisms interact in a relationship that helps maintain one another's existence. Stress can disrupt this interaction, compromising the survival of some of the members of such relationships. Here, the authors investigate the effect of stress on the interaction between anemones and their microbiome. Their study suggests that stress changes the composition of the surface microbiome of the anemone D. lineata, which is accompanied by an increase in mucus secretion. Future research into the composition of this stress-induced mucus might reveal useful antimicrobial properties.

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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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Antibacterial Effects of Copper Surfaces

Mulukutla et al. | May 19, 2020

Antibacterial Effects of Copper Surfaces

This study examined the ability of copper and copper alloy surfaces to inhibit bacterial growth, which may be help prevent healthcare-associated infections. The authors exposed two non-pathogenic strains of bacteria to different metal plates for varying degrees of time and measured bacterial growth.

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Development of a novel machine learning platform to identify structural trends among NNRTI HIV-1 reverse transcriptase inhibitors

Ashok et al. | Jun 24, 2022

Development of a novel machine learning platform to identify structural trends among NNRTI HIV-1 reverse transcriptase inhibitors

With advancements in machine learning a large data scale, high throughput virtual screening has become a more attractive method for screening drug candidates. This study compared the accuracy of molecular descriptors from two cheminformatics Mordred and PaDEL, software libraries, in characterizing the chemo-structural composition of 53 compounds from the non-nucleoside reverse transcriptase inhibitors (NNRTI) class. The classification model built with the filtered set of descriptors from Mordred was superior to the model using PaDEL descriptors. This approach can accelerate the identification of hit compounds and improve the efficiency of the drug discovery pipeline.

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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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Unveiling the wound healing potential of umbilical cord derived conditioned medium: an in vitro study

Vasal et al. | Jun 17, 2024

Unveiling the wound healing potential of umbilical cord derived conditioned medium: an <em>in vitro</em> study

Chronic wounds pose a serious threat to an individual’s health and quality of life. However, due to the severity and morbidity of such wounds, many pre-existing treatments are inefficient or costly. While the use of skin grafts and other such biological constructs in chronic wound healing has already been characterized, the use of umbilical cord tissue has only recently garnered interest, despite the cytokine-rich composition of Wharton’s jelly (cord component). Our current study aimed to characterize the use of an umbilical cord derived conditioned medium (UC-CM) to treat chronic wounds.

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Quantitative definition of chemical synthetic pathway complexity of organic compounds

Baranwal et al. | Jun 19, 2023

Quantitative definition of chemical synthetic pathway complexity of organic compounds

Irrespective of the final application of a molecule, synthetic accessibility is the rate-determining step in discovering and developing novel entities. However, synthetic complexity is challenging to quantify as a single metric, since it is a composite of several measurable metrics, some of which include cost, safety, and availability. Moreover, defining a single synthetic accessibility metric for both natural products and non-natural products poses yet another challenge given the structural distinctions between these two classes of compounds. Here, we propose a model for synthetic accessibility of all chemical compounds, inspired by the Central Limit Theorem, and devise a novel synthetic accessibility metric assessing the overall feasibility of making chemical compounds that has been fitted to a Gaussian distribution.

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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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