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The authors studied hippocampal gene expression in Alzheimer's disease.

This study used machine learning models to examine which factors most influenced U.S. household energy consumption in 2020 using data from 18,496 households.

The authors investigated adoption rates of solar photovoltaic power at K-12 schools in California.

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

The main goal of this study is to determine what demographics are related to tuberculosis incidence in the United States populations, particularly if changing demographics are related to differences in tuberculosis risk over two discrete time periods. The major finding is that in the two studied time periods, tuberculosis risk factors were somewhat consistent and may be influenced by things such as immigration, healthcare access, and race or ethnicity, although the top predictor did change.

Antibiotic resistance is a growing global health threat, and one strategy to combat it is using bacteriophages to enhance the effectiveness of existing antibiotics. This study tested whether targeting the TolC protein in E. coli with the TLS bacteriophage would increase bacterial sensitivity to antibiotics.

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.

The authors looked at how the presence of difference antibiotic resistance genes would influence antibiotic resistance in Staphylococcus aureus.

Studying cut-resistant socks for hockey players

The authors tested the impact of various additives on biopolymer degradation.