Browse Articles

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

Here, based on the identification of androgapholide as a potential therapeutic treatment against cancer, Alzheimer's disease, diabetes, and multiple sclerosis, due to its ability to inhibit a signaling pathway in immune system function, the authors sought ways to optimize the natural product human systems by manipulating its chemical structure. Through the semisynthesis of a natural product along with computational studies, the authors developed an understanding of the kinetic mechanisms of andrographolide and semisynthetic analogs in the context of Michael additions.

The authors employ computational protein design to identify a mini-protein with the potential to enhance binding of the tight junction protein, claudin-5, at the blood-blood barrier with therapeutic potential for neurodegenerative diseases.

The authors use molecular modeling to test analogs of the stearoyl-coenzyme A desaturase 1 (SCD1) inhibitor MF-438 with implications for future development of Parkinson's disease therapeutics.

This article investigates differences in gene expression in the brains of patients with and without Parkinson's disease. The authors identify a crucial transcriptional regulator may be a relevant target for future therapeutic treatment for Parkinson's disease.

This study combines gene expression, mutation profiling, and survival analysis of 17 clinically important genes in breast cancer, utilizing the TCGA-BRCA dataset. Our results show that there are different patterns of oncogene upregulation, different levels of tumor suppressor activity, and complicated survival associations. TP53 was the most frequently mutated gene in this cohort. The results underscore the significance of multidimensional genomic analyses for a comprehensive understanding of breast cancer biology and its therapeutic ramifications.

Cancer cells rely heavily on glycolysis, but how they respond when glucose is reintroduced after acute starvation is not well understood. Using fluorescence lifetime imaging microscopy, students tracked metabolic changes in HeLa cells and found a rapid shift toward glycolysis within 20 minutes of glucose reintroduction, followed by heterogeneous recovery toward oxidative phosphorylation. These results highlight metabolic flexibility and variability in cancer cells, offering insights relevant to treatment resistance and therapeutic design.

Here, the authors investigated the integration of large language models (LLMs) with drug target affinity predictors (DTAPs) to improve drug repurposing, demonstrating a significant increase in prediction accuracy, particularly with GPT-4, for psychotropic drugs and the sigma-1 receptor. This novel approach offers to potentially accelerate and reduce the cost of drug discovery by efficiently identifying new therapeutic uses for existing drugs.

Neuroinflammation and oxidative stress are both known to play a role in the occurrence and severity of seizures. This study tested effects of oxidative stress from seizures by evaluating the longevity, egg-laying, and electroshock resilience of C. elegans. Results revealed that oxidative stress and neuroinflammation diminish longevity and reproductivity while also increasing recovery time after seizures in C. elegans. This research can help lead to future studies and may also lead to finding new therapeutics for epilepsy.