111 papers
Pharmacology and toxicology explore how substances interact with living systems, ranging from the development of life-saving medicines to understanding the dangers of chemical exposure. This field sits at the critical intersection of chemistry and biology, asking essential questions about how drugs work, how the body processes them, and what happens when things go wrong. It is a dynamic area where researchers constantly strive to improve patient safety while discovering new therapeutic possibilities.
At Gist.Science, we bridge the gap between complex research and public understanding by curating the latest preprints from bioRxiv in this vital category. Our team processes every new submission from bioRxiv as it appears, transforming dense scientific data into both plain-language overviews and detailed technical summaries. This ensures that whether you are a specialist or a curious reader, you can grasp the significance of these emerging findings without getting lost in jargon.
Below are the most recent pharmacology and toxicology papers from bioRxiv, each accompanied by our expert analysis to help you navigate the latest scientific breakthroughs.
This study develops novel dissymmetric ionizable lipid-based nanoparticles that efficiently deliver ferroptosis-related siRNAs to treat diabetic metabolic disorders and restore islet function in mouse models, offering a safe and potent therapeutic strategy for type 2 diabetes.
This study demonstrates that low-dose exposure to the skin sensitizer DNCB induces a hormetic effect in THP-1 cells by significantly enhancing metabolic activity at 0.05 micromolar while slightly suppressing immune marker expression, underscoring the necessity of evaluating low-concentration dose responses in toxicological risk assessment.
This study demonstrates that co-exposure to cisplatin and titanium dioxide nanoparticles in *Drosophila melanogaster* induces a synergistic transcriptional suppression of genes critical for cell division, metabolism, and immunity, leading to impaired climbing performance despite unchanged mortality rates.
This study demonstrates that an AB-free kava diet reduces anxiety-like behavior and increases locomotor activity in mice without causing sedation, although it fails to prevent the suppression of exploratory behavior induced by nicotine.
This study demonstrates that a complex, environmentally derived mixture of polycyclic aromatic hydrocarbons causes conserved developmental neurotoxicity across three distinct species through mechanisms that extend beyond the canonical Aryl hydrocarbon Receptor (AhR) pathway.
The paper introduces DrugEvolve, a multi-role large language model system that autonomously evolves and optimizes algorithms across the entire drug development pipeline, achieving significant performance improvements and generalizability across diverse tasks and data modalities through a closed-loop process of design, implementation, evaluation, and refinement.
This study reveals that the KRAS G12C inhibitor divarasib noncovalently binds to and stabilizes the splicing factor RBM39, thereby antagonizing RBM39 degraders and modulating cellular cytotoxicity through an RBM39-INSR signaling axis.
This study utilizes transcriptomic analysis in *Daphnia pulex* to demonstrate that nutritional status, particularly phosphorus limitation, significantly modulates arsenic toxicity through antagonistic interactions that disrupt critical cellular pathways like DNA repair and energy homeostasis.
The authors developed an open-source, AI-enabled screening platform using *C. elegans* to rapidly identify FDA-approved drugs that enhance heat stress resistance, leading to the discovery of 31 compounds that extend lifespan in worms and exhibit anti-senescence activity in human cells.
This study proposes a schema-grounded multitask instruction-tuning framework using parameter-efficient LoRA adaptation on LLMs, which significantly outperforms zero-shot baselines in jointly extracting biomedical entities and relations for pharmacovigilance while demonstrating that schema alignment is more critical than model scale for reliable structured extraction.