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In silico modeling of emodin’s interactions with serine/threonine kinases and chitosan derivatives

Suresh et al. | Jan 10, 2022

<i>In silico</i> modeling of emodin’s interactions with serine/threonine kinases and chitosan derivatives

Here, through protein-ligand docking, the authors investigated the effect of the interaction of emodin with serine/threonine kinases, a subclass of kinases that is overexpressed in many cancers, which is implicated in phosphorylation cascades. Through molecular dynamics theyfound that emodin forms favorable interactions with chitosan and chitosan PEG (polyethylene glycol) copolymers, which could aid in loading drugs into nanoparticles (NPs) for targeted delivery to cancerous tissue. Both polymers demonstrated reasonable entrapment efficiencies, which encourages experimental exploration of emodin through targeted drug delivery vehicles and their anticancer activity.

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Presence of Vegetation in Relation to Slope in Yosemite Valley, California

Saltzgaber et al. | Sep 11, 2021

Presence of Vegetation in Relation to Slope in Yosemite Valley, California

This study examined the relationship between the slope of a terrain and vegetation, measured by the normalized difference vegetation index (NDVI). It was hypothesized that lower slope ranges would be more supportive of vegetation growth than higher slope ranges. Analysis showed that no slope (even as extreme as 85–90°) prohibits the growth of vegetation completely; even the steepest slopes examined contain plant life. Knowing that steep slopes can still support plant life, agriculturalists can begin to explore and start planting additional crops and plants at these extreme slopes.

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A comparative analysis of machine learning approaches for prediction of breast cancer

Nag et al. | May 11, 2021

A comparative analysis of machine learning approaches for prediction of breast cancer

Machine learning and deep learning techniques can be used to predict the early onset of breast cancer. The main objective of this analysis was to determine whether machine learning algorithms can be used to predict the onset of breast cancer with more than 90% accuracy. Based on research with supervised machine learning algorithms, Gaussian Naïve Bayes, K Nearest Algorithm, Random Forest, and Logistic Regression were considered because they offer a wide variety of classification methods and also provide high accuracy and performance. We hypothesized that all these algorithms would provide accurate results, and Random Forest and Logistic Regression would provide better accuracy and performance than Naïve Bayes and K Nearest Neighbor.

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Kinetic Monitoring and Fourier-Transform Infrared (FTIR) Spectroscopy of the Green Oxidation of (-)-Menthol to (-)-Menthone

Surapaneni et al. | Aug 06, 2020

Kinetic Monitoring and Fourier-Transform Infrared (FTIR) Spectroscopy of the Green Oxidation of (-)-Menthol to (-)-Menthone

In an effort to reduce the production of hazardous substances, green chemistry aims to make chemical processes more sustainable. One way to do so is changing solvents in chemical reactions. Here, authors assessed different “green” solvents on the oxidation of (-)-menthol to (-)-menthone using Fourier-transform infrared (FTIR) spectroscopy, optimizing the solvent system for this reaction.

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Herbal Extracts Alter Amyloid Beta Levels in SH-SY5Y Neuroblastoma Cells

Xu et al. | Feb 25, 2020

Herbal Extracts Alter Amyloid Beta Levels in SH-SY5Y Neuroblastoma Cells

Alzheimer’s disease (AD) is a type of dementia that affects more than 5.5 million Americans, and there are no approved treatments that can delay the advancement of the disease. In this work, Xu and Mitchell test the effects of various herbal extracts (bugleweed, hops, sassafras, and white camphor) on Aβ1-40 peptide levels in human neuroblastoma cells. Their results suggest that bugleweed may have the potential to reduce Aβ1-40 levels through its anti-inflammatory properties.

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The Effects of Confinement on the Associative Learning of Gallus gallus domesticus

Jaworsky et al. | Dec 23, 2019

The Effects of Confinement on the Associative Learning of <em>Gallus gallus domesticus</em>

This study aimed to determine if confinement affects associative learning in chickens. The research found that the difference in time lapsed before chickens began to consume cottage cheese before and after confinement was significant. These results suggest that confinement distresses chickens, as it impairs associative learning without inducing confusion.

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The Effects of Antibiotics on Nutrient Digestion

Murea et al. | Oct 06, 2017

The Effects of Antibiotics on Nutrient Digestion

One disadvantage of antibiotic therapy is the potential for unpleasant gastrointestinal side effects. Here, the authors test whether some common antibiotics directly interfere with the digestion of protein, fat, or sugars. This study provides motivation to more carefully investigate the interactions between antibiotics and gut enzymes in order to inform treatment decisions and improve patient outcomes.

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