Both genetic and environmental factors have been shown to influence decision making, but their relative contributions and interactions are not well understood. The present study aimed to reveal possible gene-environment interactions on decision making in a large healthy sample. Specifically, we examined how the frequently studied COMT Val(158)Met polymorphism interacted with an environmental risk factor (i.e., stressful life events) and a protective factor (i.e., parental warmth) to influence affective decision making as measured by the Iowa Gambling Task. We found that stressful life events acted as a risk factor for poor IGT performance (i.e., high reward sensitivity) among Met carriers, whereas parental warmth acted as a protective factor for good IGT performance (i.e., higher IGT score) among Val/Val homozygotes. These results shed some new light on gene-environment interactions in decision making, which could potentially help us understand the underlying etiology of several psychiatric disorders associated with decision making impairment.
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http://dx.doi.org/10.1038/srep00677 | DOI Listing |
Ecohealth
January 2025
Health Services Academy, Chak Shahzad, Park Road, Islamabad, 44000, Pakistan.
One Health is an integrative approach aiming to achieve optimal health outcomes by recognizing the interconnection between humans, animals, and the environment. This study explores the understanding, perspectives, hurdles, and implications of intersectoral collaboration within Pakistan's human health system, focusing on One Health principles. A qualitative phenomenological approach was employed, involving 17 key informant interviews with purposively selected stakeholders from public health, agriculture, veterinary medicine, agriculture and environmental science.
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January 2025
Drug Theoretics and Cheminformatics Laboratory, Department of Pharmaceutical Technology, Jadavpur University, Kolkata, 700 032, India.
We have adopted the classification Read-Across Structure-Activity Relationship (c-RASAR) approach in the present study for machine-learning (ML)-based model development from a recently reported curated dataset of nephrotoxicity potential of orally active drugs. We initially developed ML models using nine different algorithms separately on topological descriptors (referred to as simply "descriptors" in the subsequent sections of the manuscript) and MACCS fingerprints (referred to as "fingerprints" in the subsequent sections of the manuscript), thus generating 18 different ML QSAR models. Using the chemical spaces defined by the modeling descriptors and fingerprints, the similarity and error-based RASAR descriptors were computed, and the most discriminating RASAR descriptors were used to develop another set of 18 different ML c-RASAR models.
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January 2025
Department of Orthopaedic and Trauma Surgery, Musculoskeletal University Center Munich (MUM), Campus Grosshadern, Ludwig Maximilians University Munich, Munich, Germany.
In modern knee arthroplasty, surgeons increasingly aim for individualised implant selection based on data-driven decisions to improve patient satisfaction rates. The identification of an implant design that optimally fits to a patient's native kinematic patterns and functional requirements could provide a basis towards subject-specific phenotyping. The goal of this study was to achieve a first step towards identifying easily accessible and intuitive features that allow for discrimination between implant designs based on kinematic data.
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January 2025
Department of Mathematics, Dambi Dollo University, Dambi Dollo, Oromia, Ethiopia.
A novel method for solving the multiple-attribute decision-making problem is proposed using the complex Diophantine interval-valued Pythagorean normal set (CDIVPNS). This study aims to discuss aggregating operations and how they are interpreted. We discuss the concept of CDIVPN weighted averaging (CDIVPNWA), CDIVPN weighted geometric (CDIVPNWG), generalized CDIVPN weighted averaging (CGDIVPNWA) and generalized CGDIVPN weighted geometric (CGDIVPNWG).
View Article and Find Full Text PDFJ Immunother Cancer
January 2025
Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
Background: Immune checkpoint inhibitors (ICIs) in combination with antiangiogenic drugs have shown promising outcomes in the third-line and subsequent treatments of patients with microsatellite stable metastatic colorectal cancer (MSS-mCRC). Radiotherapy (RT) may enhance the antitumor effect of immunotherapy. However, the effect of RT exposure on patients receiving ICIs and targeted therapy remains unclear.
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