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The effect of the consumption of the probiotic B. infantis on ethanol withdrawal symptoms in planaria (Dugesia dorotocephala)

McCandless et al. | Mar 16, 2021

The effect of the consumption of the probiotic B. infantis on ethanol withdrawal symptoms in planaria (Dugesia dorotocephala)

Alcohol use disorder is a chronic, relapsing disease that affects millions of Americans every day. There are limited treatment options for alcohol dependence and alcohol withdrawal symptoms, including depression and anxiety. Previous studies have shown that probiotics can decrease depression in rodents during maternal separation and anxiety in humans. Therefore, we hypothesized that the ethanol-withdrawn planaria who consumed probiotics would have decreased withdrawal symptoms as measured by increased motility compared to the ethanol-withdrawn planaria that were not fed probiotics. The ethanol-withdrawn planaria had a statistically significant decrease in motility compared to the control group, while the planaria that consumed probiotics had no statistically significant change in motility compared to the control group.

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Exploring Unconventional Growing Methods to Promote Healthy Growth in Common Household Plants: Tagetes patula L. and Lepidium sativum

Nguyen et al. | Feb 25, 2021

Exploring Unconventional Growing Methods to Promote Healthy Growth in Common Household Plants: <i>Tagetes patula</i> L. and <i>Lepidium sativum</i>

This study focused on finding more sustainable growing methods that reduce chemical fertilizer or water usage and can be used at the household level for garden plants. Metrics for healthy plant growth were height at first bloom, growing time, and survival rate. The Deep Water Culture (DWC) treatment for garden cress plants significantly increased the height at first bloom compared to the control group. For rates of surviving plants, the treatments had little effect on garden cress, but the Eggshell Grounds, Wick System, and DWC system groups outperformed the control group for marigolds.

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The Effects of Ezetimibe on Triglyceride and Alanine Transaminase Reduction in Drosophila Melanogaster Model of Nonalcoholic Fatty Liver Disease (NAFLD)

Dania et al. | Apr 30, 2020

The Effects of Ezetimibe on Triglyceride and Alanine Transaminase Reduction in <i>Drosophila Melanogaster</i> Model of Nonalcoholic Fatty Liver Disease (NAFLD)

Nonalcoholic Fatty Liver Disease (NAFLD) is a condition where a surplus of triglycerides or fat are present in the liver. In this study, ezetimibe, a cholesterol lowering drug, was used to treat flies modeling NAFLD. Compared to the coconut oil fed flies that were transferred to the control medium, the flies transferred to the control medium treated with ezetimibe showed a decrease in their triglyceride and alanine transaminase level.

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The Parent-Child Relationship During the College Planning Process

Vanden et al. | Sep 19, 2019

The Parent-Child Relationship During the College Planning Process

To explore the parent-child relationship during college planning, authors surveyed high school juniors from two private schools (boarding school vs. non-boarding parochial school). After coding, survey answers indicate students at boarding schools were found to have greater fear of parental control and disappointment, while students at non-boarding parochial schoolexpressed a greater need for parental assistance.

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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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The Role of Temporal Lobe Epilepsy in Cardiac Structure and Function

Choi et al. | Aug 15, 2018

The Role of Temporal Lobe Epilepsy in Cardiac Structure and Function

Cardiac autonomic and structural changes may occur in temporal lobe epilepsy patients and contribute to the risk of sudden unexpected death in epilepsy patients. Choi and colleagues reviewed clinical charts to obtain patients’ lifetime seizure count, antiepileptic drug use, and history of heart disease, followed by transthoracic echocardiogram to calculate left ventricle dimensions, ejection fraction, and left ventricle mass. By comparing epilepsy patients to control subjects, they found that epilepsy patients had thinner left ventricle walls and smaller ejection fraction, but with no significant difference in left ventricle mass.

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Pressure and temperature influence the efficacy of metal-organic frameworks for carbon capture and conversion

Lin et al. | May 07, 2023

Pressure and temperature influence the efficacy of metal-organic frameworks for carbon capture and conversion

Metal-organic frameworks (MOFs) are promising new nanomaterials for use in the fight against climate change that can efficiently capture and convert CO2 to other useful carbon products. This research used computational models to determine the reaction conditions under which MOFs can more efficiently capture and convert CO2. In a cost-efficient manner, this analysis tested the hypothesis that pressure and temperature affect the efficacy of carbon capture and conversion, and contribute to understanding the optimal conditions for MOF performance to improve the use of MOFs for controlling greenhouse CO2 emissions.

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Synthesis of a novel CCR1 antagonist for treatment of glioblastoma

Jan et al. | May 05, 2021

Synthesis of a novel CCR1 antagonist for treatment of glioblastoma

Glioblastoma is a brain cancer caused by the presence of a fast-growing, malignant tumor in the brain. As of now, this cancer is universally lethal due to lack of efficacious treatment options. C-C chemokine receptor 1 (CCR1) is a G-protein coupled receptor that controls chemotaxis, the movement of cells in response to chemical stimuli. This research aims to synthesize potential CCR1 antagonists by coupling carboxylic acids with a triazole core. We synthesized these compounds using a simple carboxylic acid coupling and confirmed the identity of the final compounds using nuclear magnetic resonance (NMR) spectroscopy.

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Effect of Different Growth Media on Algae’s Ability for Carbon Dioxide Biofixation

Chaudhuri et al. | Oct 12, 2020

Effect of Different Growth Media on Algae’s Ability for Carbon Dioxide Biofixation

In this study, the authors investigate the effects of different algal growth media on algae's ability to perform carbon dioxide biofixation, or utilize carbon dioxide by fixing it into fatty acids within the cells. More specifically, carbon dioxide biofixation of Chlorella vulgaris was cultured in one of four media options and carbon dioxide was measured and compared to controls. The study results demonstrated that the use of media can enhance algae's capacity for biofixation and this has important implications for developing methods to reduce carbon dioxide in the environment.

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Machine Learning Algorithm Using Logistic Regression and an Artificial Neural Network (ANN) for Early Stage Detection of Parkinson’s Disease

Kar et al. | Oct 10, 2020

Machine Learning Algorithm Using Logistic Regression and an Artificial Neural Network (ANN) for Early Stage Detection of Parkinson’s Disease

Despite the prevalence of PD, diagnosing PD is expensive, requires specialized testing, and is often inaccurate. Moreover, diagnosis is often made late in the disease course when treatments are less effective. Using existing voice data from patients with PD and healthy controls, the authors created and trained two different algorithms: one using logistic regression and another employing an artificial neural network (ANN).

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