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Study Objective: Complex pharmacotherapy in cancer patients increases the likelihood of drug-drug interactions (DDIs). Pharmacists play a critical role in the identification and management of DDIs. The aim of present study was to evaluate the role of pharmacist in identifying antifungal drug interactions in cancer patients and providing relevant recommendations.

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Background: The doctor-patient relationship is essential for effective patient care, yet medical education often neglects to nurture the quality such as empathy during the initial years of training. Doctor-patient relationship is one of the modules taught in first year as part of mandatory AETCOM (Attitude, Ethics, and Communication) course in the undergraduate Indian medical curriculum. Hermeneutics, a method of interpretation, can play a vital role in introducing observational and reflective thinking skills.

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Imaging of elbow entrapment neuropathies.

Insights Imaging

January 2025

IRCCS Istituto Ortopedico Galeazzi, Milan, Italy.

Entrapment neuropathies at the elbow are common in clinical practice and require an accurate diagnosis for effective management. Understanding the imaging characteristics of these conditions is essential for confirming diagnoses and identifying underlying causes. Ultrasound serves as the primary imaging modality for evaluating nerve structure and movement, while MRI is superior for detecting muscle denervation.

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Cardiomyocytes can be implanted to remuscularize the failing heart. Challenges include sufficient cardiomyocyte retention for a sustainable therapeutic impact without intolerable side effects, such as arrhythmia and tumour growth. We investigated the hypothesis that epicardial engineered heart muscle (EHM) allografts from induced pluripotent stem cell-derived cardiomyocytes and stromal cells structurally and functionally remuscularize the chronically failing heart without limiting side effects in rhesus macaques.

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The transportation industry contributes significantly to climate change through carbon dioxide ( ) emissions, intensifying global warming and leading to more frequent and severe weather phenomena such as flooding, drought, heat waves, glacier melting, and rising sea levels. This study proposes a comprehensive approach for predicting emissions from vehicles using deep learning techniques enhanced by eXplainable Artificial Intelligence (XAI) methods. Utilizing a dataset from the Canadian government's official open data portal, we explored the impact of various vehicle attributes on emissions.

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