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Most prior research on the neurobiology of addiction has focused on the role of subcortical systems, such as the amygdala, the ventral striatum and mesolimbic dopamine system, in promoting the motivation to seek drugs. Recent evidence indicates that a largely overlooked structure, the insula, plays a crucial part in conscious urges to take drugs. The insula has been highlighted as a region that integrates interoceptive (i.e. bodily) states into conscious feelings and into decision-making processes that involve uncertain risk and reward. Here, we propose a model in which the processing of the interoceptive effects of drug use by the insula contributes to conscious drug urges and to decision-making processes that precipitate relapse.
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http://dx.doi.org/10.1016/j.tins.2008.09.009 | DOI Listing |
BMJ Open
March 2025
London School of Hygiene & Tropical Medicine, Faculty of Epidemiology and Population Health, London, UK.
Objective: To assess the impact of introducing electronic decision support systems (EDSS)-electronic data entry implemented alongside existing paper-based antenatal care (ANC) records-on the completeness and agreement of ANC records.
Design: Two-phase cross-sectional (before and after) substudy of the mobile health integrated model of hypertension, diabetes and ANC (mIRA project) process evaluation.
Setting: Four rural districts in Bagmati Province, Nepal, in 19 primary healthcare facilities.
Int J Cardiol
March 2025
National Clinical Research Center for Metabolic Diseases, Metabolic Syndrome Research Center, Key Laboratory of Diabetes Immunology, Ministry of Education, Changsha 410011, Hunan, China. Electronic address:
Objective: This study aims to develop a radiomics machine learning (ML) model that uses preoperative computed tomography angiography (CTA) data to predict the prognosis of endovascular aneurysm repair (EVAR) for abdominal aortic aneurysm (AAA) patients.
Methods: In this retrospective study, 164 AAA patients underwent EVAR and were categorized into shrinkage (good prognosis) or stable (poor prognosis) groups based on post-EVAR sac regression. From preoperative AAA and perivascular adipose tissue (PVAT) image, radiomics features (RFs) were extracted for model creation.
Environ Res
March 2025
School of Civil and Environmental Engineering, University of Connecticut, Storrs, Connecticut 06269, USA. Electronic address:
Wastewater treatment plants (WWTPs) are highly complex systems where biological, chemical, and physical processes interact dynamically, creating significant operational challenges. Traditional modeling approaches, such as Activated Sludge Models (ASMs) and machine learning algorithms (MLAs), struggle to process the unstructured and multimodal data generated in WWTPs, limiting their effectiveness. Large Language Models (LLMs) offer a promising solution by integrating diverse data sources, recognizing patterns, and enabling human-in-the-loop interactions for informed decision-making.
View Article and Find Full Text PDFJ Dent
March 2025
Department of Orthodontics and Pediatric Dentistry, School of Dentistry, University of Michigan, 1011 North University Avenue, Ann Arbor, Michigan, 48104, USA. Electronic address:
Objectives: To develop and validate an explainable Artificial Intelligence (AI) model for classifying and quantifying upper airway obstruction related to adenoid hypertrophy using three-dimensional (3D) shape analysis of cone-beam computed tomography (CBCT) scans.
Methods: 400 CBCT scans of patients aged 5-18 years were analyzed. Nasopharyngeal airway obstruction (NAO) ratio was calculated to label scans into four grades of obstruction severity, used as the ground truth.
J Man Manip Ther
March 2025
Faculty of Medicine and Health Sciences, Rehabilitation Sciences and Physiotherapy (MOVANT), University of Antwerp, Antwerp, Belgium.
Introduction: Despite the recommendations to use a bio-psycho-social framework, many physiotherapists still manage their patients mainly from a biomedical point of view. The purpose of this study is to analyze the impact of two different e-learning interventions on knowledge, attitudes, and clinical decision-making of physiotherapists managing low back pain (LBP) to increase guideline-consistent care.
Methods: Physiotherapists were allocated (1/1) either to an experimental or a traditional e-learning intervention.
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