Molecules which bind to proteins that aggregate abnormally in neurodegenerative diseases could be promising drugs for these diseases. In this study, Zhang, Wu, Zhang, and Dang simulate the binding behavior of various molecules to screen for candidates which could be promising candidates for drug development.

This article discusses Alopecia areata, an autoimmune disorder causing sudden hair loss due to the immune system mistakenly attacking hair follicles. The article introduces the use of deep learning (DL) techniques, particularly convolutional neural networks (CNN), for classifying images of healthy and alopecia-affected hair. The study presents a comparative analysis of newly optimized CNN models with existing ones, trained on datasets containing images of healthy and alopecia-affected hair. The Inception-Resnet-v2 model emerged as the most effective for classifying Alopecia Areata.

This study explored the various effects of three different produce-based biofertilizers on pea plant growth, using red apple, pear, strawberry, and control treatments. It was hypothesized that the application of fruit biomatter would increase the growth of pea plants, with the application of strawberry biomatter having the most significant effect due to strawberries containing a higher nutrient content compared to pears and apples. Analysis confirmed the hypothesis. The application of strawberry biomatter could prove to be an effective way to increase plant growth in commercial agriculture.

In this study, the authors investigate what metals make the most efficient electrochemical cells, which are batteries that use the difference in electrical potential to generate electricity. Calculations predicted that a cell made of iron and magnesium would have the highest efficiency. Construction of an electrochemical cell of iron and magnesium produced voltages close to the theoretical voltage predicted. These findings are important as work continues towards making batteries with the highest storage efficiency possible.

Genetically modified organisms (GMOs) are crops or animals that have been genetically engineered to express a certain physical or biological characteristic and have various benefits that have made them become increasingly popular. However, the public has had mixed reactions to the use of GMOs, with some skeptical of their safety. The purpose of this study was to evaluate how opinions on genetically modified foods can change from exposure to small amounts of information

The authors examine a relationship between tweet sentiment and stock market behavior during the early weeks of the COVID-19 pandemic.

Here the authors test the ability of the bacterium Bacillus subtilis to degrade the polyethylene from plastic waste in various aquatic environments. They determined that degradation can occur among all samples while it was the highest in fresh water and lowest in ocean water.

The authors looked at previous studies to evaluate the ability to use serum levels of certain cytokines as biomarkers for pneumoconiosis.

Plants, and all other multi-cellular organisms, develop through the coordinated action of many sets of genes. The authors here investigate the genes, in a class named KNOX, potentially responsible for organizing a certain part of Aquilegia (columbine) flowers called petal spurs. Through the technique Reverse Transcription-Polymerase Chain Reaction (RT-PCR), they find that certain KNOX genes are expressed non-uniformly in petal spurs, suggesting that they may be involved, perhaps in a cell-specific manner. This research will help guide future efforts toward understanding how many beautiful flowers develop their unique shapes.

The COVID-19 pandemic demonstrated the depth and significance of healthcare inequality in the United States. Xiao, Xiao, and Gong examine healthcare disparities in the Richmond (Virginia) metropolitan area by analyzing whether people from disadvantaged populations must travel for longer to reach healthcare facilities.