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Utilization of Potentially Inappropriate Sedative-Hypnotic and Atypical Antipsychotic Medications among Elderly Individuals with Insomnia and Alzheimer's Disease.
Sleep
January 2025
Complete HEOR Solutions (CHEORS), Chalfont, PA, USA.
Study Objectives: This study assessed the utilization of potentially inappropriate medications (PIM) including oral sedative-hypnotic and atypical antipsychotic (OSHAA), healthcare resource utilization (HCRU), and costs among elderly individuals with insomnia and in the subpopulation with Alzheimer's Disease (AD) who also had a diagnosis of insomnia.
Methods: Using claims database containing International Classification of Diseases, 10th Revision (ICD-10) codes, the cohort included individuals aged ≥ 65 with incident insomnia (EI, N=152,969) and AD insomnia subpopulation (ADI, N=4,888). Proportion of patients utilizing atypical antipsychotics or oral sedative-hypnotic medications, namely z-drugs, benzodiazepines, doxepin, Dual Orexin Receptor Antagonists (DORAs), and melatonin agonists, were assessed.
Enhancing Activation Energy Predictions under Data Constraints Using Graph Neural Networks.
J Chem Inf Model
January 2025
Department of Chemical Engineering, National Taiwan University, No. 1, Section 4, Roosevelt Road, Taipei 10617, Taiwan.
Accurately predicting activation energies is crucial for understanding chemical reactions and modeling complex reaction systems. However, the high computational cost of quantum chemistry methods often limits the feasibility of large-scale studies, leading to a scarcity of high-quality activation energy data. In this work, we explore and compare three innovative approaches (transfer learning, delta learning, and feature engineering) to enhance the accuracy of activation energy predictions using graph neural networks, specifically focusing on methods that incorporate low-cost, low-level computational data.
View Article and Find Full Text PDFExploring the significance of medical humanities in shaping internship performance: insights from curriculum categories.
Med Educ Online
December 2025
Computer Science and Information Engineering, National Central University, Taoyuan, Taiwan.
Background: Medical Humanities (MH) curricula integrate humanities disciplines into medical education to nurture essential qualities in future physicians. However, the impact of MH on clinical competencies during formative training phases remains underexplored. This study aimed to determine the influence of MH curricula on internship performance.
View Article and Find Full Text PDFEnhanced brain tumor detection and segmentation using densely connected convolutional networks with stacking ensemble learning.
Comput Biol Med
January 2025
Emerging Technologies Research Lab (ETRL), College of Computer Science and Information Systems, Najran University, Najran, 61441, Saudi Arabia; Department of Computer Science, College of Computer Science and Information Systems, Najran University, Najran, 61441, Saudi Arabia. Electronic address:
- Brain tumors (BT), both benign and malignant, pose a substantial impact on human health and need precise and early detection for successful treatment. Analysing magnetic resonance imaging (MRI) image is a common method for BT diagnosis and segmentation, yet misdiagnoses yield effective medical responses, impacting patient survival rates. Recent technological advancements have popularized deep learning-based medical image analysis, leveraging transfer learning to reuse pre-trained models for various applications.
View Article and Find Full Text PDFLeveraging molecular dynamics, physicochemical, and structural analysis to explore OMP33-36 protein as a drug target in Acinetobacter baumannii: An approach against nosocomial infection.
J Mol Graph Model
January 2025
Amity Institute of Biotechnology, Amity University Uttar Pradesh, Lucknow Campus, Gomtinagar Extension, Lucknow, 226028, India; Research Cell, Amity University Uttar Pradesh, Lucknow Campus, India. Electronic address:
The Acinetobacter baumannii is a member of the "ESKAPE" bacteria responsible for many serious multidrug-resistant (MDR) illnesses. This bacteria swiftly adapts to environmental cues leading to the emergence of multidrug-resistant variants, particularly in hospital/medical settings. In this work, we have demonstrated the outer membrane protein 33-36 (Omp33-36) porin as a potential therapeutic target in A.
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