The authors identify disinfectant-resistant bacterial strains of infection-causing bacteria from samples collected at a hospital setting.
Read More...Varying levels of disinfectant resistance among invasive Klebsiella pneumoniae isolates
The authors identify disinfectant-resistant bacterial strains of infection-causing bacteria from samples collected at a hospital setting.
Read More...Effects of polyethylene microplastics on the growth of Arabidopsis thaliana & Phaseolus vulgaris and their soil
In this study, the authors investigate whether microplastics affect terrestrial plant growth and soil quality.
Read More...Mapping QTLs for Popping Ability in a Popcorn × Dent Maize Genetic Cross
Have you ever wondered what contributes to the popping ability of popcorn? In this study, the authors use Quantitative Trait Locus (QTL) mapping to identify genes that may contribute to specific popping characteristics including kernel size and popping expansion volume (PEV).
Read More...The Analysis of the Effects of Smoke and Water Vapor on Insect Pheromone Communication and Physical Condition: An Investigation of the Causes of Colony Collapse Disorder
The cause of insect colony collapse disorder (CCD) is still a mystery. In this study, the authors aimed to test the effects of two environmental factors, water vapor and smoke levels, on the social behavior and physical condition of insects. Their findings could help shed light on how changing environmental factors can contribute to CCD.
Read More...Mitigating microplastic exposure from water consumption in junior high students and teachers
Microplastics (MPs) are inorganic material that have been observed within items destined for human consumption, including water, and may pose a potential health hazard. Here we estimated the average amount of MPs junior high students and teachers consumed from different water sources and determined whether promoting awareness of microplastic (MP) exposure influenced choice of water source and potential MPs consumed.
Read More...Can Green Tea Alleviate the Effects of Stress Related to Learning and Long-Term Memory in the Great Pond Snail (Lymnaea stagnalis)?
Stress and anxiety have become more prevalent issues in recent years with teenagers especially at risk. Recent studies show that experiencing stress while learning can impair brain-cell communication thus negatively impacting learning. Green tea is believed to have the opposite effect, aiding in learning and memory retention. In this study, the authors used Lymnaea stagnalis , a pond snail, to explore the relationship between green tea and a stressor that impairs memory formation to determine the effects of both green tea and stress on the snails’ ability to learn, form, and retain memories. Using a conditioned taste aversion (CTA) assay, where snails are exposed to a sweet substance followed by a bitter taste with the number of biting responses being recorded, the authors found that stress was shown to be harmful to snail learning and memory for short-term, intermediate, and long-term memory.
Read More...Effects of Quorum Sensing and Media on the Bioluminescent Bacteria Vibrio fischeri
Vibrio fischeri is an amazing species of bacteria that lives symbiotically in the light organ of luminescent bobtail squid. In this study, authors study the strength and optimal conditions for V. fischeri light production, and assess whether this luminescence could be a natural light source comparable to manmade lighting.
Read More...The effect of reiki, a Japanese relaxation technique, on stress in middle schoolers
Evaluation of the causality between testosterone, obesity, and diabetes
The study explored the role of testosterone beyond its well-established effects on male sex characteristics, focusing on its association with non-communicable diseases (NCDs) like obesity and type 2 diabetes (T2D), using Mendelian randomization (MR) analysis on genomic data.
Read More...Transfer Learning with Convolutional Neural Network-Based Models for Skin Cancer Classification
Skin cancer is a common and potentially deadly form of cancer. This study’s purpose was to develop an automated approach for early detection for skin cancer. We hypothesized that convolutional neural network-based models using transfer learning could accurately differentiate between benign and malignant moles using natural images of human skin.
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