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Background: Data from 2 previous studies were reanalyzed, one on judgments regarding drug treatment of hyperlipidemia and the other on diagnosing heart failure. The original MH model and the extended MH model were compared with logistic regression (LR) in terms of fit to actual judgments, number of cues, and the extent to which the cues were consistent with clinical guidelines.
Results: There was a slightly better fit with LR compared with MH. The extended MH model gave a significantly better fit than the original MH model in the drug treatment task. In the diagnostic task, the number of cues was significantly lower in the MH models compared to LR, whereas in the therapeutic task, LR could be less or more frugal than the matching heuristic models depending on the significance level chosen for inclusion of cues. For the original MH model, but not for the extended MH model or LR, the most important cues in the drug treatment task were often used in a direction contrary to treatment guidelines.
Conclusions: The extended MH model represents an improvement in that prevalence of cue values is adequately taken into account, which in turn may result in better fit and in better agreement with medical guidelines in the evaluation of cues.
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http://dx.doi.org/10.1177/0272989X08326091 | DOI Listing |
Crit Rev Toxicol
September 2025
Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), Bilthoven, Netherlands.
There is a concern on the safety of cosmetic ingredients and their endocrine-disrupting (ED) potential. Frequent use as well as the use of a diverse range of cosmetics pose a concern for a potential health risk via aggregate exposure to endocrine disrupting chemicals (EDCs). In this study, a list of ingredients available in cosmetic products that were recently introduced to the Dutch market was retrieved from the commercially accessible Mintel database and screened for the presence of EDCs.
View Article and Find Full Text PDFAnal Chem
September 2025
Institute of Biological Chemistry, Faculty of Chemistry, University of Vienna, Währinger Str. 38, 1090 Vienna, Austria.
The discovery of solute precursors of crystalline materials, such as biominerals, recently challenged the classical nucleation theory (CNT). One emerging method for investigating these early-stage intermediates in solution is dissolution dynamic nuclear polarization (dDNP)-enhanced nuclear magnetic resonance (NMR) spectroscopy. Recent applications of dDNP to calcium carbonate (CaC) and calcium phosphate (CaP) mineralization have demonstrated the feasibility of identifying and tracing very early-stage prenucleation clusters (PNCs).
View Article and Find Full Text PDFJ Comput Chem
September 2025
Wilhelm-Ostwald-Institut für Physikalische und Theoretische Chemie, Leipzig University, Leipzig, Germany.
We investigated primary and secondary geometric isotope effects (H, D, T) on charge-inverted hydrogen bonds (CIHB) and dihydrogen bonds (DHB) using nuclear-electronic orbital density functional theory (NEO-DFT). The dianionic but electrophilic boron cluster [BH] served as a bonding partner, exhibiting a negatively polarized hydrogen atom in the BH bond. CIHB systems included interactions with Lewis acids (AlH, BH, GaH) and carbenes (CF, CCl, CBr), while DHBs were analyzed with NH, HF, HCl, and HBr.
View Article and Find Full Text PDFJ Chem Theory Comput
September 2025
Dipartimento di Chimica, Università di Pavia, Via Taramelli 12, Pavia 27100, Italy.
Machine learning (ML) and deep learning (DL) methodologies have significantly advanced drug discovery and design in several aspects. Additionally, the integration of structure-based data has proven to successfully support and improve the models' predictions. Indeed, we previously demonstrated that combining molecular dynamics (MD)-derived descriptors with ML models allows to effectively classify kinase ligands as allosteric or orthosteric.
View Article and Find Full Text PDFPhilos Trans A Math Phys Eng Sci
September 2025
D-BAUG, ETH Zurich, Zürich 8093, Switzerland.
Biofilms-microbial communities encased in a self-produced extracellular matrix-pose a significant challenge in clinical settings due to their association with chronic infections and antibiotic resistance. Their formation in the human body is governed by a complex interplay of biological and environmental factors, including the biochemical composition of bodily fluids, fluid dynamics, and cell-cell and cell-surface interactions. Improving therapeutic strategies requires a deeper understanding of how host-specific conditions shape biofilm development.
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