Results 31 to 40 of about 797 (106)
Diabetes, Obesity and Metabolism, Volume 28, Issue 9, Page 8329-8336, September 2026.ABSTRACT Introduction and Objective Treatment with sodium‐glucose cotransporter‐2 inhibitors (SGLT‐2i) reduces the risk of both cardiovascular and renal outcomes in type 2 diabetes (T2D). The specific mechanism by which this happens has not yet been clarified.
Shawn Gugliandolo +18 more
wiley +1 more source
Sugar Amino Acid Linkers for the Design of [18F]SiFA‐PSMA Radioligands
ChemMedChem, Volume 21, Issue 15, 14 August 2026.Sugar amino acid (SAA) linkers were incorporated into silicon‐fluoride‐acceptor (SiFA)‐prostate‐specific membrane antigen (PSMA) radioligands to modulate pharmacokinetic properties while preserving efficient 18F isotopic exchange radiolabeling. Furanose‐based SAAs outperformed pyranose analogues, enabling specific tumor visualization by PET despite ...
Narendar R. Gade +5 more
wiley +1 more source
Scanner‐agnostic artificial intelligence approach for fast bone scintigraphy
Journal of Applied Clinical Medical Physics, Volume 27, Issue 8, August 2026.Abstract Purpose Current bone scintigraphy protocols often demand full‐count, 10–15 min scans to preserve image quality, and existing deep‐learning (DL) denoisers typically need to be retrained or retuned for each camera manufacturer. We introduce a scanner‐agnostic adaptive‐diffusion U‐Net designed to reconstruct diagnostic‐grade images from half‐time
Vinicius de Oliveira Menezes +9 more
wiley +1 more source
Advanced Healthcare Materials, Volume 15, Issue 29, 7 August 2026.Pharmacokinetic engineering of clickable radioligands was achieved via albumin hitchhiking approach within a pretargeted radiotheranostics delivery platform. This approach reduced rapid renal elimination, expanded bioorthogonal capture window, boosted tumor uptake by ∼3.5‐fold, and improved the tumor‐to‐liver ratio by ∼6‐fold.
Xie He +9 more
wiley +1 more source
Classification of tau status with machine learning models in amyloid‐positive cohorts
Alzheimer's &Dementia, Volume 22, Issue 8, August 2026.Abstract INTRODUCTION Although tau positron emission tomography (PET) imaging is effective for staging tau pathology, it is limited clinically by cost and availability. Machine learning models based on magnetic resonance imaging (MRI)– and amyloid PET–derived features may serve as useful screening tools for tau pathology.
Yun‐Chi Lin +4 more
wiley +1 more source
Alzheimer's &Dementia, Volume 22, Issue 8, August 2026.Abstract INTRODUCTION Cerebral amyloid angiopathy (CAA) frequently co‐occurs with Alzheimer's disease (AD), generating mixed vascular–neurodegenerative phenotypes. Plasma phosphorylated tau (p‐tau)217 is a robust biomarker of AD, but its performance in CAA remains unclear. METHODS We studied 231 participants, including 50 patients with CAA (Boston v2.0)
Aida Fernández‐Lebrero +19 more
wiley +1 more source
Alzheimer's &Dementia, Volume 22, Issue 8, August 2026.Abstract INTRODUCTION An extra copy of the amyloid precursor protein (APP) gene causes autosomal dominant Alzheimer's disease (AD) and AD in Down syndrome (DS), but the factors underlying variability in age at onset (AAO) remain unclear. We investigated whether sporadic AD risk variants modify AAO. METHODS We analyzed clinical and genetic data from 100
Joan Groeneveld +39 more
wiley +1 more source
Chelator‐Free Radiometal Labeling Inside Engineered Affibodies
Angewandte Chemie, Volume 138, Issue 30, 20 July 2026.Affibodies are compact and robust three‑helix binders used in imaging and therapy. Engineering a triple‑cysteine motif into their core enables chelator‑free binding of important radiometals, like Bi(III), Pb(II), In(III), and Ga(III) with rapid uptake and exceptional stability.
Lani J. Davies +6 more
wiley +2 more sources
Applications of Artificial Intelligence in Cancer Diagnosis and Treatment
Cancer Medicine, Volume 15, Issue 8, August 2026.This review explores how AI and multimodal data fusion transform oncology through enhanced screening, precision diagnosis, and personalized therapy. By dissecting core challenges—including data bias and explainability—it provides a strategic framework for the digital transformation and ethical implementation of AI in clinical cancer care.
Yifeng Xie +6 more
wiley +1 more source