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FCRL3 Gene Association with Asthma and Allergic Rhinitis

Sheikh et al. | Aug 05, 2020

FCRL3 Gene Association with Asthma and Allergic Rhinitis

This study sought to determine if there is an association between the single nucleotide polymorphism rs7528684 of the Fc receptor-like-3 (FCRL3) gene and asthma or allergic rhinitis (AR). Based on previous studies in an Asian population, we hypothesized that participants with an AA genotype of FCRL3 would be more likely to have asthma and/or allergic rhinitis. To test the hypothesis, surveys were administered to participants, and genotyping was performed on spit samples via PCR, restriction digest, and gel electrophoresis.

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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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Investigation of Everyday Locations for Antibiotic-Resistant Bacteria in Cambridge, Massachusetts

Maggio et al. | Dec 12, 2019

Investigation of Everyday Locations for Antibiotic-Resistant Bacteria in Cambridge, Massachusetts

In this study, the authors investigate whether antibiotic-resistant bacteria can be found in everyday locations. To do this, they collected samples from multiple high-trafficked areas in Cambridge, MA and grew them in the presence and absence of antibiotics. Interestingly, they grew bacterial colonies from many locations' samples, but not all could grow in the presence of ampicillin. These findings are intriguing and relevant given the rising concern about antibiotic-resistant bacteria.

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Prediction of molecular energy using Coulomb matrix and Graph Neural Network

Hazra et al. | Feb 01, 2022

Prediction of molecular energy using Coulomb matrix and Graph Neural Network

With molecular energy being an integral element to the study of molecules and molecular interactions, computational methods to determine molecular energy are used for the preservation of time and resources. However, these computational methods have high demand for computer resources, limiting their widespread feasibility. The authors of this study employed machine learning to address this disadvantage, utilizing neural networks trained on different representations of molecules to predict molecular properties without the requirement of computationally-intensive processing. In their findings, the authors determined the Feedforward Neural Network, trained by two separate models, as capable of predicting molecular energy with limited prediction error.

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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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