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Enhanced O-glycosylation Site Prediction Using Explainable Machine Learning Technique with Spatial Local Environment.
Bioinformatics
January 2025
Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, United States.
Motivation: The accurate prediction of O-GlcNAcylation sites is crucial for understanding disease mechanisms and developing effective treatments. Previous machine learning models primarily relied on primary or secondary protein structural and related properties, which have limitations in capturing the spatial interactions of neighboring amino acids. This study introduces local environmental features as a novel approach that incorporates three-dimensional spatial information, significantly improving model performance by considering the spatial context around the target site.
View Article and Find Full Text PDFDiagnostic accuracy of node-RADS for the detection of lymph node invasion: a systematic review and meta-analysis.
Eur Radiol
January 2025
Department of Urological Surgical, JiangNan University Medical Center, Wuxi, China.
Objective: To conduct a meta-analysis assessing the diagnostic performance of the node reporting and data system (Node-RADS) for detecting lymph node (LN) invasion.
Method: We performed a systematic literature search of online scientific publication databases from inception up to July 31, 2024. We used the quality assessment of diagnostic accuracy studies-2 (QUADAS-2) to assess the study quality, and heterogeneity was determined by the Q-test and measured with I statistics.
Real world clinical experience of using Brainomix e-CTA software in a medium size acute NHS trust.
Br J Radiol
January 2025
Royal United Hospital, Combe Park, Bath, Avon, BA1 3NG, UK.
Objectives: Artificial intelligence (AI) software including Brainomix "e-CTA" which detect large vessel occlusions (LVO) have clinical potential. We hypothesised that in real world use where prevalence is low, its clinical utility may be overstated.
Methods: In this single centre retrospective service evaluation project, data sent to Brainomix from a medium size acute National Health Service (NHS) Trust hospital between 1/3/2022-1/3/2023 was reviewed.
Impact of impaired renal function on kinetics of high-sensitive cardiac troponin following cardiac surgery.
Clin Res Cardiol
January 2025
Clinic for General and Interventional Cardiology/Angiology, Herz- und Diabeteszentrum NRW, Ruhr-Universität Bochum, Georgstraße 11, 32545, Bad Oeynhausen, Germany.
Background: Impaired renal function can increase cardiac troponin levels due to reduced elimination, potentially affecting its diagnostic utility. Limited data exist on high-sensitivity cardiac troponin I (hs-cTnI) kinetics after cardiac surgery relative to renal function. This study evaluates how impaired renal function influences hs-cTnI kinetics following cardiac surgery, distinguishing between patients with and without postoperative myocardial infarction (PMI).
View Article and Find Full Text PDFInsights and Opportunities from Multimarker Evaluation of Heart Failure: Lessons from BIOSTAT-HF.
Curr Heart Fail Rep
January 2025
Division of Cardiovascular Medicine, Department of Medicine, University of California, 9394 Medical Center Drive, La Jolla, San Diego, CA, USA.
Purpose Of Review: Heart failure is a complex and heterogenous disease state that affects millions worldwide. Over recent decades, advancements in medical therapy and device implementation have significantly transformed the landscape of heart failure outcomes, while improvements in imaging modalities and greater accessibility to genome sequencing have led to increasing recognition of distinct heart failure endotypes. There is rising evidence to suggest all patients do not benefit equally from intensification of guideline directed medical therapy (GDMT).
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