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

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.

The authors examined the effect of varying glucose concentrations on cut rose longevity.

The authors looked at whether they could induce the formation of new neurons from astrocytes via the upregulation of a microRNA (miR-124a). They found that upregulation of miR-124a started transdifferentiation of neurons, but was not enough to lead to full conversion of astrocytes to neurons.

The authors computationally screened potential ALDH1 inhibitors, for use as potential cancer therapeutics.

Improving the classifier of the difficulty level of Sudoku.

In 2021, over 20 million people died from cardiovascular diseases, highlighting the need for a deeper understanding of factors influencing heart failure outcomes. This study examined multiple variables affecting mortality after heart failure, using random forest models to identify time, serum creatinine, and ejection fraction as key predictors. These findings could contribute to personalized medicine, improving survival rates by tailoring treatment strategies for heart failure patients.

The authors test the antiproliferative and apoptosis-inducing properties of an extract created from a traditional Indian medicinal plant of the Amaranthus genus.

Sequence accessibility is an important factor affecting gene expression. Sequence accessibility or openness impacts the likelihood that a gene is transcribed and translated into a protein and performs functions and manifests traits. There are many potential factors that affect the accessibility of a gene. In this study, our hypothesis was that the content of nucleotides in a genetic sequence predicts its accessibility. Using a machine learning linear regression model, we studied the relationship between nucleotide content and accessibility.