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Giving Teens a Voice: Sources of Stress for High School Students

Corson et al. | Sep 09, 2019

Giving Teens a Voice: Sources of Stress for High School Students

The authors investigate the negative effects stress has on teen mental and physical health. Through a survey, they give Virginia teens a voice in revising the Health and Physical Education curriculum to include a standards of learning (SOL). Notably they identify factors contributing to stress levels including homework level, amount of free and sleep time, parental pressure and family encouragement.

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Efficacy of Rotten and Fresh Fruit Extracts as the Photosensitive Dye for Dye-Sensitized Solar Cells

Jayasankar et al. | Jan 16, 2019

Efficacy of Rotten and Fresh Fruit Extracts as the Photosensitive Dye for Dye-Sensitized Solar Cells

Dye-sensitized solar cells (DSSC) use dye as the photoactive material, which capture the incoming photon of light and use the energy to excite electrons. Research in DSSCs has centered around improving the efficacy of photosensitive dyes. A fruit's color is defined by a unique set of molecules, known as a pigment profile, which changes as a fruit progresses from ripe to rotten. This project investigates the use of fresh and rotten fruit extracts as the photoactive dye in a DSSC.

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Upregulation of the Ribosomal Pathway as a Potential Blood-Based Genetic Biomarker for Comorbid Major Depressive Disorder (MDD) and PTSD

Ravi et al. | Aug 22, 2018

Upregulation of the Ribosomal Pathway as a Potential  Blood-Based Genetic Biomarker for Comorbid Major Depressive Disorder (MDD) and PTSD

Major Depressive Disorder (MDD), and Post-Traumatic Stress Disorder (PTSD) are two of the fastest growing comorbid diseases in the world. Using publicly available datasets from the National Institute for Biotechnology Information (NCBI), Ravi and Lee conducted a differential gene expression analysis using 184 blood samples from either control individuals or individuals with comorbid MDD and PTSD. As a result, the authors identified 253 highly differentially-expressed genes, with enrichment for proteins in the gene ontology group 'Ribosomal Pathway'. These genes may be used as blood-based biomarkers for susceptibility to MDD or PTSD, and to tailor treatments within a personalized medicine regime.

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Cocktail therapy to inhibit multispecies biofilm in cystic fibrosis patients

Bhat et al. | Sep 22, 2022

Cocktail therapy to inhibit multispecies biofilm in cystic fibrosis patients

Here, recognizing the important role of bacterial biofilms in many life-threatening chronic infections, the authors investigated the effectiveness of a combination treatment on biofilms composed of up to three different common species within the lungs of cystic fibrosis patients with computational analysis. They found that a triple cocktail therapy targeting three different signaling pathways has significant potential as both a treatment and prophylaxis.

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A novel filtration model for microplastics using natural oils and its application to the environment

Park et al. | Jun 27, 2022

A novel filtration model for microplastics using natural oils and its application to the environment

Recognizing the need for a method to filter microplastics from polluted water the authors sought to use nonpolar solvents, palm oil and palm kernel oil, to filter microplastics out of model seawater. By relying on the separation of polar and nonpolar solvents followed by freezing the nonpolar solvent, they reported that microplastics could be extracted with percentages ranging from 96.2% to 94.2%. They also provided an estimation to use this method as part of container ships to clean the Pacific Ocean of microplastics.

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Assessing and Improving Machine Learning Model Predictions of Polymer Glass Transition Temperatures

Ramprasad et al. | Mar 18, 2020

Assessing and Improving Machine Learning Model Predictions of Polymer Glass Transition Temperatures

In this study, the authors test whether providing a larger dataset of glass transition temperatures (Tg) to train the machine-learning platform Polymer Genome would improve its accuracy. Polymer Genome is a machine learning based data-driven informatics platform for polymer property prediction and Tg is one property needed to design new polymers in silico. They found that training the model with their larger, curated dataset improved the algorithm's Tg, providing valuable improvements to this useful platform.

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