Browse Articles

The authors look at how different food types impact the ability of bacteria to produce electricity.

Growing climate concerns have intensified research into zero-emission transportation fuels, notably hydrogen. Hydrogen is considered a clean fuel because its only major by-product is water. This project analyzes how hydrogen compares to kerosene as a commercial aircraft fuel with respect to cost, CO2 emissions, and flight range.

Recognizing a growing demand for organic produce, the authors sought to investigate plant-based antibiotic solutions to meet growing consumer demand for safe produce and also meet microbial standards of the USDA. The authors investigated the use of cinnamaldehyde as an antibacterial again E. coli, finding that lettuce treated with cinnamaldehyde displayed significantly lower colony-forming units of E. coli when compared to lettuce treated with chlorine bleach.

Wang and Gong developed a novel dynamic gene-searching algorithm called Dynamic Gene Search (DyGS) to create a gene panel for each of the 12 cancers with the highest annual incidence and death rate. The 12 gene panels the DyGS algorithm selected used only 3.5% of the original gene mutation pool, while covering every patient sample. About 40% of each gene panel is druggable, which indicates that the DyGS-generated gene panels can be used for early cancer detection as well as therapeutic targets in treatment methods.

The authors studied the ability of freshwater clams to improve water quality.

This manuscript tackles a major social issue in the health news sector, with social media being one of the primary sources of information and a prime spot to propagate fake news. The author proposes X-HND , which is a unique architecture that combines emotional and contextual analysis in a Graph Neural Network to accurately detect fake news. This was a multi-step process which involved the creation of a custom health news dataset (HNDataset), and an emotional variant that uses RoBERTa to extract emotion. These dataset were then used to prove the hypothesis that accuracy increases when the custom dataset is used to train the model and that with the integration of emotion capture, the detection accuracy increases further.

This study investigates skin tone bias in artificial intelligence models used for dermatological disease classification and evaluates a CycleGAN-based data augmentation approach to improve diagnostic performance on darker skin types. We generated synthetic dark-skinned images to enhance dataset diversity and compared model performance before and after augmentation. The results demonstrate that augmentation with synthetic dermatological images can help reduce disparities in diagnostic performance across skin tones, highlighting a practical strategy for improving fairness in dermatology AI systems.

The study investigates the antibacterial properties of household spices on bacteria isolated from everyday objects, aiming to address the limited understanding of bacterial resilience on surfaces and the potential of spices as antibacterial agents. Researchers hypothesized that bacteria would grow faster on some surfaces than others and that spices like honey, chili powder, turmeric, and sumac would inhibit bacterial growth at varying rates. The findings suggest that household spices possess significant antibacterial properties and could be used as emergency disinfectants, particularly in under-resourced settings. However, they cannot replace medical treatments but offer insights into alternative health solutions using common ingredients.

The authors looked at the potential of different phenolic compounds to reduce oxidative stress (i.e., act as antioxidants).

The authors use computational methods to compare tau acetylation to the better studied tau phosphorylation in Alzheimer's disease and then design and computationally test a new drug to prevent abnormal post-translational modifications of tau.