Annual review of pharmacology and toxicology最新文献

Chronic exposure to the metal(loid)s arsenic, cadmium, lead, and mercury via contaminated food or drinking water may induce kidney toxicity, but there is little consensus on the biological processes involved. Health risk assessment of these substances is further complicated by coexposures and the sometimes unclear causal interpretation of population studies. To address these issues, we developed a common adverse outcome pathway (AOP) describing how these metal(loid)s can induce kidney toxicity. Upon identification of renal dysfunction resulting from proximal tubular damage as a common adverse outcome, we developed the AOP by collecting evidence from relevant (experimental) studies. Evaluation of the weight of evidence revealed a moderate to high confidence in this AOP. It enhances our mechanistic understanding of metal(loid)-induced kidney toxicity and provides scientific evidence for a causal relationship between the adverse effect and effect biomarkers. As such, this is an example of how AOPs can facilitate next-generation risk assessment of combined exposure to different contaminants.

The global rise of antibiotic-resistant bacteria poses a critical threat to healthcare systems, challenging researchers to stay ahead of evolving pathogens. Among the most concerning are invasive infections caused by Staphylococcus aureus (SA), where morbidity and mortality remain high despite advances in care. Resistance in SA has emerged rapidly after the introduction of new antibiotics, limiting treatment options and prompting an urgent need for alternatives. While developing new antimicrobials remains essential, repurposing FDA-approved drugs-originally developed for noninfectious indications-offers a complementary strategy. These agents have known safety and pharmacokinetic profiles and may impact bacterial virulence, antibiotic susceptibility, or host immunity to improve outcomes. This review highlights recent advances in SA drug repurposing, focusing on six mechanistic categories: inhibition of virulence factors, antibiotic resensitization, enhanced susceptibility to innate immunity, host cell protection, augmentation of immune functions, and modulation of pathological inflammation. Together, these strategies offer a multifaceted framework to improve SA infection outcomes using existing therapeutics.

Many of the adverse effects of ambient air pollution have been attributed to reactions of chemical species generated from fossil or biogenic fuel combustion. This review focuses on two reactions: (a) a prooxidant reaction, in which oxygen is reduced to hydrogen peroxide, and (b) covalent bond formation between electron-rich centers on biological targets with reactive compounds called electrophiles. Prooxidants were found to be concentrated in the particulate matter (PM) fraction of ambient air in the Los Angeles Basin with electrophiles concentrated in the volatile organic compound (VOC) fractions. Actions on mouse macrophages indicated the adverse effects to be mostly attributed to the PM, with anti-inflammatory actions to the VOC fraction. The latter observation does not include, however, the adverse effects of VOCs associated with the transient receptor potential (TRP) calcium channels on epithelial cells, a perspective that needs further investigation.

Precision medicine demands a shift from static, single-analyte diagnostics toward dynamic, systems-level understanding of health and disease. This review explores how the convergence of systems biology, multiomics, and artificial intelligence (AI) redefines biomarker discovery to drive early disease detection and personalized intervention. We highlight pioneering efforts that use longitudinal, multimodal data to map individual health trajectories and uncover early disease signals. Advances in AI, including machine learning and contextualization using knowledge graphs and digital twins, are accelerating clinical translation by enabling predictive, context-aware analyses. Real-world applications, including omics-informed diagnostics and digital health monitoring, demonstrate the potential of this approach to transform health care from reactive treatment to proactive wellness. These technologies also inform the development of targeted therapeutics that intervene earlier, personalize treatment, and potentially halt or reverse disease progression. We outline challenges, emerging solutions, and future directions that position AI-driven systems biology at the center of next-generation precision health.

Here I highlight personal and professional experiences that shaped my career and defined my scientific journey, with my longtime colleague, Ermelinda Porpiglia. I hope that sharing my life's adventures will inspire others to enjoy both a fulfilling scientific career and the fruits of parenthood. I have always enjoyed addressing big questions and challenging dogma. In my early career I probed cell plasticity, challenging the dogma that a cell's specialized state is fixed and irreversible. I then sought to understand stem cells, crucial to tissue repair. Most recently, my lab discovered a gerozyme, 15-prostaglandin dehydrogenase (15-PGDH), a master regulator of muscle aging, and showed that muscle tissue is rejuvenated and strengthened when the gerozyme is inhibited with a small-molecule drug. It would be a dream come true if this discovery in my lab becomes a treatment for the debilitating muscle wasting arising from disuse, disease, or aging.

Environmental pollutants such as heavy metals, pesticides, and plastic nanoparticles pose significant risks to human, animal, and environmental health. New approach methodologies complying with the 3R principles (replace, reduce, refine) are essential for advancing the molecular basis of pollutant-induced toxicity, thus improving risk assessment, disease prevention, and therapies. Thanks to its remarkable features, the multicellular organism Caenorhabditis elegans offers unique opportunities to meet this goal. Mitochondria, central hubs in cellular homeostasis, are particularly vulnerable to pollutants, orchestrating stress responses that progress to toxicity and disease. C. elegans represents a powerful model to study these effects, offering conserved systems with quantifiable end points. While previous studies have mainly focused on environmental stressors inducing DNA damage, this review explores C. elegans's end points of relevance for mitotoxicology, highlighting advantages and limitations of the system as an alternative approach for in vivo environmental-induced mitochondrial toxicology and diseases.

Development of vaccines against dengue has been designated a priority for over 75 years. The completion of Phase III trials and licensing of multiple dengue vaccines have been significant accomplishments of the last 15 years. Despite that progress, a vaccine suitable for broad use has not yet been identified. The scientific challenges of multiple dengue viral serotypes, immune imprinting from previous infections, and immune enhancement of infection and disease remain formidable obstacles to this goal. Further investments in clinical research of natural dengue virus infections and participants in dengue vaccine trials will be needed to enable the development and testing of the next generation of dengue vaccines.

Emerging evidence suggests that alterations in immunometabolism contribute to pathogenesis of inflammatory diseases, providing potential therapeutic targets. Anti-inflammatory drugs such as glucocorticoids, metformin, and dimethyl fumarate (DMF) modulate key immunometabolic pathways. Glucocorticoids boost itaconate production, which exerts anti-inflammatory effects via multiple targets, including by modification of cysteines on inflammatory proteins. Metformin, known for inhibiting gluconeogenesis in type 2 diabetes, also blocks mitochondrial Complex I and increases GDF-15, a regulator of food intake with anti-inflammatory properties, which may explain effects of metformin on inflammation. DMF, like itaconate, modifies cysteines on target proteins, notably KEAP1, leading to Nrf2 activation, which induces antioxidant enzymes and suppresses inflammatory gene expression. These immunometabolic actions suggest that targeting immune cell metabolism could provide new strategies for treating autoimmune diseases. This review explores recent advances in itaconate, GDF-15, and Nrf2 signaling and how harnessing these pathways may lead to novel anti-inflammatory therapies for patients with inflammatory diseases.

The eponymous term Gβγ protein has given way to a more nuanced view of 60 different possible combinations of the 5 Gβ and 12 Gγ subunits and their effects on cellular signaling profiles. Beyond this increased appreciation of their diversity per se, we now know that distinct Gβγ combinations may play roles beyond the regulation of cell surface effectors following G protein-coupled receptor activation and release from G protein heterotrimers. Gβγ subunits operate in multiple subcellular compartments. In this review, we focus on Gβγ-mediated events in the endoplasmic reticulum, Golgi apparatus, and mitochondria and particularly highlight Gβγ roles in the nucleus.

Pregnant and lactating women have historically been excluded from clinical trials, limiting data on drug pharmacokinetics, safety, and efficacy in these populations. This knowledge gap stems from complex ethical, historical, and cultural factors, which previously categorized these women as vulnerable rather than protected participants. Recent legislative frameworks, including the FDA Pregnancy and Lactation Labeling Rule, have catalyzed efforts to include these populations in structured research. Quantitative pharmacology approaches using innovations such as physiologically based pharmacokinetic models support optimized trial designs, safer dosing regimens, and ethical research frameworks. Emerging technologies, including artificial intelligence, novel drug delivery mechanisms, and organ-on-chip models, further enhance insights into maternal-fetal drug exposure and drug exposures in breastfeeding infants. Integrating in vitro, ex vivo, in vivo, and clinical data and modeling approaches improves understanding of pregnancy-related physiological changes and their impact on drug outcomes, ultimately enabling appropriate and equitable pharmacotherapy for pregnant and breastfeeding women.