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The authors test symbiotic relationships among cyanobacteria species to generate more robust cultures for potential biofuel production.

This study investigates PFAS contamination in Santa Clarita groundwater, focusing on potential sources. The study employs statistical analysis to assess data quality and trends which allowed them to identified domestic waste, fire extinguisher materials, and food packaging as the most likely sources of contamination.

Car emissions harm both the environment and human health, and current U.S. EV tax credits mainly benefit high-income households because EVs are expensive. This study evaluates U.S. vehicle emissions policies by analyzing 2022 national vehicle data to compare the fuel economy and greenhouse gas impacts of the current EV tax credit with a proposed policy that incentivizes hybrid vehicle purchases.

Elevated acetylcholinesterase (AChE) activity contributes to cognitive decline and neurodegenerative diseases such as Alzheimer’s, motivating the search for more effective inhibitors with better bioavailability. This study used computational methods to design novel, non-toxic AChE inhibitors.

This study analyzes genetic alterations and expression patterns of protein kinases involved in phagocytosis across multiple cancers using TCGA data.

Detecting cervical spondylosis using deep learning

The authors looked at how injuries sustained during water tubing, that require treatment at an emergency department, differ between males and females.

The authors looked at how nanosilver particles may negatively impact the pond water environment. They used D. magna as an indicator species to look at the impact of different concentrations of nanosilver particles.

To address the limitations in predicting the severity of Atrial Septal Defect (ASD), here the authors utilized a fluid-filled chamber model to quantify the relationship between defect size and right atrial fluid output. The findings confirmed that larger ASD diameters result in a linear increase in fluid output, validating a cost-effective model that can improve clinical prognosis and treatment planning for heart failure risks.

The authors looked at how vocabulary is impacted in Alzheimer's disease and whether it could be used a predictor of disease onset.