Teaching and learning anatomy has always been an integral part of medical education. Teaching neuroanatomy has always faced innate and contextual challenges therefore various innovative teaching-learning methods have been devised on the idea of engaging learners in meaningful learning activities through apt guidance, communication among peers and cluster activities. The present study aims at such an innovative method. The study was conducted in practical sessions of first year MBBS at the Institute during second semester. Neuroanatomy topic selected for present study was 'Neural Pathways/tracts'. Participants were divided into 8 groups and each was allotted a specific activity related to a particular cross-sectional level and allowed to build with the material provided by the department. Student feedback was taken through a structured questionnaire. 81 and 82.4% of students stated that the activity was clearly explained and should be offered more frequently in curriculum. The activity also developed a positive attitude and good coordination amongst peers with increase in communication skills (89.1%, 91.8%, 89% respectively). 87.8% of students agreed that small group learning is better than didactic lectures in neuroanatomy. In current medical scenario with reduced anatomy teaching hours and a continuous pressure on undergraduates, a low-cost learning intervention formulated to deliver a complex 3-D model of tracts passing through various parts of nervous system by simple materials would show better access and understanding of the tracts with improvement of 3D visualization skills.
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Gynecol Oncol
January 2025
GOG Foundation, Florida Cancer Specialists and Research Institute, West Palm Beach, FL 33401, United States of America. Electronic address:
Objective: Therapeutic interventions for epithelial ovarian cancer (EOC) have increased greatly over the last decade but improvements outside of biomarker selected therapies have been limited. There remains a pressing need for more effective treatment options that can prolong survival and enhance the quality of life of patients with EOC. In contrast to the significant benefits of immunotherapy with immune checkpoint inhibitors (CPI) seen in many solid tumors, initial experience in EOC suggests limited efficacy of CPIs monotherapy.
View Article and Find Full Text PDFCell Rep
January 2025
Institut Interdisciplinaire de Neurosciences (IINS), University Bordeaux, CNRS, IINS, UMR 5297, 33000 Bordeaux, France; Centre Broca Nouvelle-Aquitaine, 146, rue Léo-Saignat, 33076 Bordeaux, France. Electronic address:
Optimal decision-making depends on interconnected frontal brain regions, enabling animals to adapt decisions based on internal states, experiences, and contexts. The secondary motor cortex (M2) is key in adaptive behaviors in expert rodents, particularly in encoding decision values guiding complex probabilistic tasks. However, its role in deterministic tasks during initial learning remains uncertain.
View Article and Find Full Text PDFJ Chem Inf Model
January 2025
Institute of Chemistry, Technische Universität Berlin, Straße des 17. Juni 135, Berlin 10623, Germany.
Machine learning (ML) is a powerful tool for the automated data analysis of molecular dynamics (MD) simulations. Recent studies showed that ML models can be used to identify protein-ligand unbinding pathways and understand the underlying mechanism. To expedite the examination of MD simulations, we constructed PathInHydro, a set of supervised ML models capable of automatically assigning unbinding pathways for the dissociation of gas molecules from [NiFe] hydrogenases, using the unbinding trajectories of CO and H from [NiFe] hydrogenase as a training set.
View Article and Find Full Text PDFInt J Numer Method Biomed Eng
January 2025
College of Chemistry and Life Science, Beijing University of Technology, Beijing, China.
The accurate non-invasive detection and estimation of central aortic pressure waveforms (CAPW) are crucial for reliable treatments of cardiovascular system diseases. But the accuracy and practicality of current estimation methods need to be improved. Our study combines a meta-learning neural network and a physics-driven method to accurately estimate CAPW based on personalized physiological indicators.
View Article and Find Full Text PDFACS Sens
January 2025
Department of Physics, Chalmers University of Technology, SE-41296 Göteborg, Sweden.
Rapidly detecting hydrogen leaks is critical for the safe large-scale implementation of hydrogen technologies. However, to date, no technically viable sensor solution exists that meets the corresponding response time targets under technically relevant conditions. Here, we demonstrate how a tailored long short-term transformer ensemble model for accelerated sensing (LEMAS) speeds up the response of an optical plasmonic hydrogen sensor by up to a factor of 40 and eliminates its intrinsic pressure dependence in an environment emulating the inert gas encapsulation of large-scale hydrogen installations by accurately predicting its response value to a hydrogen concentration change before it is physically reached by the sensor hardware.
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