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In this article the authors looked at arginine synthesis across different bacteria commonly found in different regional diets. They found that B. megaterium and C. sporogenes both caused a higher pH to occur on their agar plates compared to other bacteria tested indicating a greater amount of arginine synthesis.

In order for cells to successfully multiply, a number of proteins are needed to correctly coordinate the replication and division process. In this study, students use fluorescence microscopy and molecular methods to study CCDC11, a protein critical in the formation of cilia. Interestingly, they uncover a new role for CCDC11, critical in the cell division across multiple human cell lines.

This study investigated whether soursop, a ketogenic diet-related compound called BHB, and circadian synchronization could reduce seizure recovery time in fruit flies used as a model for epilepsy.

This paper utilizes multiple publicly available cancer datasets to explore the abundance of different genetic dependencies across various cancer types. They explore this by looking at four genes highly associated with cancer and their genetic and pathogenic relationships.

This study examines how socioeconomic status (SES) influences student mathematics achievement across countries by conducting multiple regression analyses to the Trends in International Mathematics and Science Study (TIMSS) 2019 dataset.

Here the authors investigated how the "forever chemical" perfluorooctanoic acid binds to bovine serum albumin (BSA) using computational software to simulate its potential impact on essential human plasma proteins. They identify a possible, high-energy binding configuration that could persistently impair protein functions, underscoring the critical need for further research into the long-term health risks of per- and poly-fluoroalkyl substances exposure.

This manuscript explores the performance of five different machine learning models in classifying brain tumors from a dataset of MRI scans. The authors find that several of the models showed >90% accuracy. Thus, the authors suggest that machine learning models demonstrate potential for effective implementation in clinical settings, including as a diagnostic tool that can be used to complement the expertise of neuroradiologists.

The authors looked at preferences of donors to donate between different animal-centered or humanitarian charities.

The authors looked at the feasibility to predict wind speeds that will have less reliance on using historical data.

The authors looked at four members of the tetracycline antibiotic family/class against four different species of bacteria.