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Anthracycline-induced cardiomyopathy: risk prediction, prevention and treatment.
Nat Rev Cardiol
January 2025
Cardioncology Unit, Cardioncology and Second Opinion Division, European Institute of Oncology, Istituto di Ricovero e Cura a Carattere Scientifico, Milan, Italy.
Anthracyclines are the cornerstone of treatment for many malignancies. However, anthracycline cardiotoxicity is a considerable concern given that it can compromise the clinical effectiveness of the treatment and patient survival despite early discontinuation of therapy or dose reduction. Patients with cancer receiving anthracycline treatment can have a reduction in their quality of life and likelihood of survival due to cardiotoxicity, irrespective of their oncological prognosis.
View Article and Find Full Text PDFLeveraging Network Target Theory for Efficient Prediction of Drug-Disease Interactions: A Transfer Learning Approach.
Adv Sci (Weinh)
January 2025
Department of Molecular Pharmacology, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin's Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute & Hospital, Tianjin, 300060, China.
Efficient virtual screening methods can expedite drug discovery and facilitate the development of innovative therapeutics. This study presents a novel transfer learning model based on network target theory, integrating deep learning techniques with diverse biological molecular networks to predict drug-disease interactions. By incorporating network techniques that leverage vast existing knowledge, the approach enables the extraction of more precise and informative drug features, resulting in the identification of 88,161 drug-disease interactions involving 7,940 drugs and 2,986 diseases.
View Article and Find Full Text PDFIdentification of CD209 as an Intervention Target for Type 2 Diabetes after COVID-19 Infection: Insights from Proteome-wide Mendelian Randomization.
Diabetes
January 2025
School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China.
Increasing evidence suggests that individuals infected with Coronavirus disease 2019 (COVID-19) are at a higher risk of developing type 2 diabetes (T2D) compared to those who are not infected. However, the mechanisms underlying this relationship remain poorly understood. In this study, we aimed to systematically evaluate the mediating roles of 3,283 plasma proteins in the link between COVID-19 susceptibility and T2D by conducting proteome-wide Mendelian randomization (MR) analyses.
View Article and Find Full Text PDFFentanyl and Fentanyl Analog Screening Using ASAP-MS With LiveID Confirmation.
Rapid Commun Mass Spectrom
May 2025
Department of Chemistry, The University of North Texas, Denton, Texas, USA.
Rationale: Fentanyl and fentanyl analogs continue to pose a serious threat to the public health. The vast number of fentanyl analogs emerging on the black-market call for optimized analytical methods for the detection, analysis, and characterization of these extremely dangerous drugs.
Methods: Atmospheric pressure solids analysis probe (ASAP) mass spectrometry was used for the rapid analysis of 250 synthetic opioid standards, including 211 fentanyl analogs, 32 non-fentanyl related opioids, and 8 fentanyl precursors.
A generative deep neural network for pan-digestive tract cancer survival analysis.
BioData Min
January 2025
School of Mathematics, Foshan University, Foshan, 528000, China.
Background: The accurate identification of molecular subtypes in digestive tract cancer (DTC) is crucial for making informed treatment decisions and selecting potential biomarkers. With the rapid advancement of artificial intelligence, various machine learning algorithms have been successfully applied in this field. However, the complexity and high dimensionality of the data features may lead to overlapping and ambiguous subtypes during clustering.
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