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GraphkmerDTA: integrating local sequence patterns and topological information for drug-target binding affinity prediction and applications in multi-target anti-Alzheimer's drug discovery.

Mol Divers

January 2025

Key Laboratory of Prevention and Treatment of Cardiovascular and Cerebrovascular Diseases Ministry of Education, Jiangxi Province Key Laboratory of Biomaterials and Biofabrication for Tissue Engineering, Gannan Medical University, Ganzhou, 341000, Jiangxi, China.

Identifying drug-target binding affinity (DTA) plays a critical role in early-stage drug discovery. Despite the availability of various existing methods, there are still two limitations. Firstly, sequence-based methods often extract features from fixed length protein sequences, requiring truncation or padding, which can result in information loss or the introduction of unwanted noise.

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[Management of acute coronary syndrome].

Herz

January 2025

Herzzentrum Leipzig, Universitätsklinik für Kardiologie, Strümpellstr. 39, 04289, Leipzig, Deutschland.

Coronary artery disease (CAD) is the leading cause of death worldwide. Acute coronary syndrome (ACS) encompasses a spectrum of diagnoses ranging from unstable angina pectoris to myocardial infarction with and without ST-segment elevation and frequently presents as the first clinical manifestation. It is crucial in this scenario to perform a timely and comprehensive assessment of patients by evaluating the clinical presentation, electrocardiogram and laboratory diagnostics using highly sensitivity cardiac troponin in order to initiate a timely and risk-adapted continuing treatment with immediate or early invasive coronary angiography.

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The Impact of Artificial Intelligence and Machine Learning in Organ Retrieval and Transplantation: A Comprehensive Review.

Curr Res Transl Med

January 2025

Department of Research and Innovation, Medway NHS Foundation Trust, Gillingham ME7 5NY, United Kingdom; Faculty of Medicine, Health and Social Care, Canterbury Christ Church University, United Kingdom.

This narrative review examines the transformative role of Artificial Intelligence (AI) and Machine Learning (ML) in organ retrieval and transplantation. AI and ML technologies enhance donor-recipient matching by integrating and analyzing complex datasets encompassing clinical, genetic, and demographic information, leading to more precise organ allocation and improved transplant success rates. In surgical planning, AI-driven image analysis automates organ segmentation, identifies critical anatomical features, and predicts surgical outcomes, aiding pre-operative planning and reducing intraoperative risks.

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Unlabelled: The tonsils have been identified as a site of replication for Epstein-Barr virus, adenovirus, human papillomavirus, and other respiratory viruses. Human tonsil epithelial cells (HTECs) are a heterogeneous group of actively differentiating cells. Here, we investigated the cellular features and susceptibility of differentiated HTECs to specific influenza viruses, including expression of avian-type and mammalian-type sialic acid (SA) receptors, viral replication dynamics, and the associated cytokine secretion profiles.

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(PA) is an opportunistic gram-negative pathogen that can infect the cornea, leading to permanent vision loss. Autophagy is a cannibalistic process that drives cytoplasmic components to the lysosome for degradation and/or recycling. Autophagy has been shown to play a key role in the removal of intracellular pathogens and, as such, is an important component of the innate immune response.

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