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LD-informed deep learning for Alzheimer's gene loci detection using WGS data.
Alzheimers Dement (N Y)
January 2025
Indiana Alzheimer Disease Research Center and Center for Neuroimaging, Department of Radiology and Imaging Sciences Indiana University School of Medicine Indianapolis Indiana USA.
Introduction: The exponential growth of genomic datasets necessitates advanced analytical tools to effectively identify genetic loci from large-scale high throughput sequencing data. This study presents Deep-Block, a multi-stage deep learning framework that incorporates biological knowledge into its AI architecture to identify genetic regions as significantly associated with Alzheimer's disease (AD). The framework employs a three-stage approach: (1) genome segmentation based on linkage disequilibrium (LD) patterns, (2) selection of relevant LD blocks using sparse attention mechanisms, and (3) application of TabNet and Random Forest algorithms to quantify single nucleotide polymorphism (SNP) feature importance, thereby identifying genetic factors contributing to AD risk.
View Article and Find Full Text PDFFAP-targeted radioligand therapy with Ga/Lu-DOTA-2P(FAPI) enhance immunogenicity and synergize with PD-L1 inhibitors for improved antitumor efficacy.
J Immunother Cancer
January 2025
Department of Nuclear Medicine and Minnan PET Center, Xiamen Cancer Center, The First Affiliated Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, Fujian, China
Background: Fibroblast activation protein (FAP)-targeted radioligand therapy, with immunomodulatory effects, has shown efficacy in both preclinical and clinical studies. We recently reported on a novel dimeric FAP-targeting radiopharmaceutical, Ga/Lu-DOTA-2P(FAPI), which demonstrated increased tumor uptake and prolonged retention in various cancers. However, further exploration is required to understand the therapeutic efficacy and underlying mechanisms of combining Ga/Lu-DOTA-2P(FAPI) radioligand therapy with PD-1/PD-L1 immunotherapy.
View Article and Find Full Text PDFImproving Affinity while Reducing Kidney Uptake of CXCR4-Targeting Radioligands Derived from the Endogenous Antagonist EPI-X4.
ChemMedChem
January 2025
Division of Radiopharmaceutical Chemistry, Department Theragnostics, University Hospital Basel, Petersgraben 4, 4031 Basel, Switzerland.
The C-X-C chemokine receptor 4 (CXCR4) is highly upregulated in most cancers, making it an ideal target for delivering radiation therapy to tumors. We previously demonstrated the feasibility of targeting CXCR4 in vivo using a radiolabeled derivative of EPI-X4, an endogenous CXCR4 antagonist, named DOTA-K-JM#173. However, this derivative showed undesirable accumulation in the kidneys, which would limit its clinical use.
View Article and Find Full Text PDFOptimal use, combinations, and sequencing of therapies in advanced prostate cancer.
Expert Rev Clin Pharmacol
January 2025
Division of Oncology Hematology, Department of Internal Medicine, University of Nebraska Medical Center, Omaha, NE, USA.
Benchmarking Alzheimer's disease prediction: personalised risk assessment using polygenic risk scores across various methodologies and genome-wide studies.
Alzheimers Res Ther
January 2025
UK Dementia Research Institute at Cardiff, Cardiff University, Hadyn Ellis Building, Maindy Road, Cardiff, CF24 4HQ, UK.
Background: The success of selecting high risk or early-stage Alzheimer's disease individuals for the delivery of clinical trials depends on the design and the appropriate recruitment of participants. Polygenic risk scores (PRS) show potential for identifying individuals at risk for Alzheimer's disease (AD). Our study comprehensively examines AD PRS utility using various methods and models.
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