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http://dx.doi.org/10.1016/j.jtcvs.2020.06.071 | DOI Listing |
Biology (Basel)
January 2025
Center for Computational Toxicology and Exposure, US Environmental Protection Agency, Research Triangle Park, NC 27711, USA.
Advancing our understanding of pancreatic toxicity and metabolic disorders caused by environmental exposures requires innovative approaches. The pancreas, a vital organ for glucose regulation, is increasingly recognized as a target of harm from environmental chemicals and dietary factors. Traditional toxicological methods, while foundational, often fail to address the mechanistic complexities of pancreatic dysfunction, particularly under real-world conditions involving multiple exposures.
View Article and Find Full Text PDFIntern Emerg Med
January 2025
Unit of Internal Medicine, Department of Medical Sciences, Fondazione IRCCS Casa Sollievo Della Sofferenza, San Giovanni Rotondo, Foggia, Italy.
mSphere
January 2025
Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
In 2020, I featured two articles in the "mSphere of Influence" commentary series that had profound implications for the field of immunology and helped shape my research perspective. These articles were "Global Analyses of Human Immune Variation Reveal Baseline Predictors of Postvaccination Responses" by Tsang et al. (Cell 157:499-513, 2014, https://doi.
View Article and Find Full Text PDFPublic Health Pract (Oxf)
June 2025
Department of Clinical and Experimental Medicine, University of Messina, Messina, Italy.
The COVID-19 pandemic has intensified workplace violence (WPV) against healthcare workers, exposing them to unprecedented levels of aggression. Incidents of verbal abuse, threats, and physical assaults have increased, especially in high-stress environments such as emergency departments and intensive care units, exacerbating psychological challenges for healthcare staff. This commentary explores the profound impact of WPV on healthcare workers' mental health and job satisfaction.
View Article and Find Full Text PDFMed Decis Making
January 2025
Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands.
Our commentary proposes the application of directed acyclic graphs (DAGs) in the design of decision-analytic models, offering researchers a valuable and structured tool to enhance transparency and accuracy by bridging the gap between causal inference and model design in medical decision making.The practical examples in this article showcase the transformative effect DAGs can have on model structure, parameter selection, and the resulting conclusions on effectiveness and cost-effectiveness.This methodological article invites a broader conversation on decision-modeling choices grounded in causal assumptions.
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