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Talinum paniculatum root exhibits synergistic antimicrobial activity with Tetracycline, Erythromycin, and Streptomycin against S. aureus but has no observed effect on antibiotic efficacy against E. coli

Patel et al. | Jan 09, 2018

Talinum paniculatum root exhibits synergistic antimicrobial activity with Tetracycline, Erythromycin, and Streptomycin against S. aureus but has no observed effect on antibiotic efficacy against E. coli

Patel et al. explore whether T. paniculatum plant extract can work with modern antibiotics to increase antibiotic efficacy against common disease-causing bacteria. The plant extract in conjunction with the antibiotic shows promise in battling S. aureus. The authors present a cost-effective method to increase antibiotic efficacy in a time where antibiotic resistant bacteria is becoming a growing problem.

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Prediction of preclinical Aβ deposit in Alzheimer’s disease mice using EEG and machine learning

Igarashi et al. | Nov 29, 2022

Prediction of preclinical Aβ deposit in Alzheimer’s disease mice using EEG and machine learning

Alzheimer’s disease (AD) is a common disease affecting 6 million people in the U.S., but no cure exists. To create therapy for AD, it is critical to detect amyloid-β protein in the brain at the early stage of AD because the accumulation of amyloid-β over 20 years is believed to cause memory impairment. However, it is difficult to examine amyloid-β in patients’ brains. In this study, we hypothesized that we could accurately predict the presence of amyloid-β using EEG data and machine learning.

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Effect of Natural Compounds Curcumin and Nicotinamide on α-synuclein Accumulation in a C. elegans Model of Parkinson’s Disease

Mehrotra et al. | Jan 29, 2018

Effect of Natural Compounds Curcumin and Nicotinamide on α-synuclein Accumulation in a C. elegans Model of Parkinson’s Disease

Parkinson's disease is a neurodegenerative disorder that affects over 10 million people worldwide. It is caused by destruction of dopamine-producing neurons, which results in severe motor and movement symptoms. In this study, the authors investigated the anti-Parkinsonian effects of two natural compounds curcumin and nicotinamide using C. elegans as a model organism.

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Utilizing a Wastewater-Based Medium for Engineered Saccharomyces cerevisiae for the Biological Production of Fatty Alcohols and Carboxylic Acids to Replace Petrochemicals

Ramesh et al. | Oct 02, 2019

Utilizing a Wastewater-Based Medium for Engineered <em>Saccharomyces cerevisiae</em> for the Biological Production of Fatty Alcohols and Carboxylic Acids to Replace Petrochemicals

Saccharomyces cerevisiae yeast is used to produce bioethanol, an alternative to fossil fuels. In this study, authors take advantage of this well studied yeast by genetically engineering them to increase fatty acid biosynthesis and culturing in a cost-effective wastewater based medium; potentially providing a sustainable alternative to petrochemicals.

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The Effects of Micro-Algae Characteristics on the Bioremediation Rate of Deepwater Horizon Crude Oil

Cao et al. | Jun 17, 2013

The Effects of Micro-Algae Characteristics on the Bioremediation Rate of Deepwater Horizon Crude Oil

Environmental disasters such as the Deepwater Horizon oil spill can be devastating to ecosystems for long periods of time. Safer, cheaper, and more effective methods of oil clean-up are needed to clean up oil spills in the future. Here, the authors investigate the ability of natural ocean algae to process crude oil into less toxic chemicals. They identify Coccochloris elabens as a particularly promising algae for future bioremediation efforts.

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The Role of a Mask - Understanding the Performance of Deep Neural Networks to Detect, Segment, and Extract Cellular Nuclei from Microscopy Images

Dasgupta et al. | Jul 06, 2021

The Role of a Mask - Understanding the Performance of Deep Neural Networks to Detect, Segment, and Extract Cellular Nuclei from Microscopy Images

Cell segmentation is the task of identifying cell nuclei instances in fluorescence microscopy images. The goal of this paper is to benchmark the performance of representative deep learning techniques for cell nuclei segmentation using standard datasets and common evaluation criteria. This research establishes an important baseline for cell nuclei segmentation, enabling researchers to continually refine and deploy neural models for real-world clinical applications.

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Pancreatic Adenocarcinoma: An Analysis of Drug Therapy Options through Interaction Maps and Graph Theory

Gupta et al. | Feb 04, 2014

Pancreatic Adenocarcinoma: An Analysis of Drug Therapy Options through Interaction Maps and Graph Theory

Cancer is often caused by improper function of a few proteins, and sometimes it takes only a few proteins to malfunction to cause drastic changes in cells. Here the authors look at the genes that were mutated in patients with a type of pancreatic cancer to identify proteins that are important in causing cancer. They also determined which proteins currently lack effective treatment, and suggest that certain proteins (named KRAS, CDKN2A, and RBBP8) are the most important candidates for developing drugs to treat pancreatic cancer.

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