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Insulin infusion patches are a common way for diabetics to receive medication. The durability of two different patch adhesives was compared on artificial skin with and without artificial sweat.

Alcohol is known to cause various developmental diseases including Fetal Alcohol Syndrome. Here the authors investigate the effect of ethanol on the development of zebrafish beta cells, the part of the pancreas associated with Type 1 Diabetes. They find that exposure to ethanol does adversely affect beta-cell development, suggesting that alcohol ingestion during pregnancy may be linked to diabetes in newborns.

Microorganisms such as bacteria and fungi live everywhere in the world around us. The authors here demonstrate that these predominantly harmless microbes can be isolated from many household locations that appear "clean." Further, they test the cleaning power of 70% ethanol and suggest that many "clean" surfaces are not in fact "sterile."

The study developed Loving Words, a free AI-powered poetry tutor designed to help writers improve their poetry and experience its therapeutic benefits. Two groups of participants wrote poems—one without assistance and one using Loving Words.

The authors examined the impact of mutations to CDK2 on protein expression.

The authors survey teenagers within the United States regarding the effect of social media use on sleep quality and attention span.

Domestic waste classification using convolutional neural network

Current horticulture practices often rely on pesticides, causing environmental harm. To address this, authors explore the use of ultrasonic sound emissions to detect plant stress at an individual level.

This study used an improved CMS-seq method to profile 5hmC in ormalin-fixed and paraffin-embedded (FFPE) samples from HNC tumors and adjacent normal tissues, identifying three genes (PRKD2, HADHA, and AIPL1) with promising potential as biomarkers for Head and neck cancer (HNC) diagnosis.

Here, the authors used machine learning to analyze microscopic images of hair, quantifying various features to distinguish individuals, even within families where traditional DNA analysis is limited. The Discriminant Analysis (DA) model achieved the highest accuracy (88.89%) in identifying individuals, demonstrating its potential to improve the reliability of hair evidence in forensic investigations.