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Neuropsychiatric symptoms and neuroimaging-based brain age in mild cognitive impairment and early dementia: A multicenter study.
Psychiatry Clin Neurosci
January 2025
Department of Neuropsychiatry, Kochi Medical School, Kochi University, Kochi, Japan.
Aim: Despite the clinical importance and significant social burden of neuropsychiatric symptoms (NPS) in dementia, the underlying neurobiological mechanism remains poorly understood. Recently, neuroimaging-derived brain-age estimation by machine-learning analysis has shown promise as an individual-level biomarker. We investigated the relationship between NPS and brain-age in amnestic mild cognitive impairment (MCI) and early dementia.
View Article and Find Full Text PDFComment to: Non-Surgical Novel Technique for Correction of Palpebromalar Groove (Tear Valley Deformity) and Extended Area: The Matador Stab.
Aesthetic Plast Surg
January 2025
Plastic and Reconstructive Microsurgery, Careggi University Hospital, Viale Giacomo Matteotti 42, 50132, Florence, Italy.
CooccurrenceAffinity: An R package for computing a novel metric of affinity in co-occurrence data that corrects for pervasive errors in traditional indices.
PLoS One
January 2025
Department of Mathematics, University of Maryland, College Park, Maryland, United States of America.
1. Analysis of co-occurrence data with traditional indices has led to many problems such as sensitivity of the indices to prevalence and the same value representing either a strong positive or strong negative association across different datasets. In our recent study (Mainali et al 2022), we revealed the source of the problems that make the traditional indices fundamentally flawed and unreliable-namely that the indices in common use have no target of estimation quantifying degree of association in the non-null case-and we further developed a novel parameter of association, alpha, with complete formulation of the null distribution for estimating the mechanism of affinity.
View Article and Find Full Text PDFIntegrating single-cell multimodal epigenomic data using 1D-convolutional neural networks.
Bioinformatics
January 2025
Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, United States.
Motivation: Recent experimental developments enable single-cell multimodal epigenomic profiling, which measures multiple histone modifications and chromatin accessibility within the same cell. Such parallel measurements provide exciting new opportunities to investigate how epigenomic modalities vary together across cell types and states. A pivotal step in using this type of data is integrating the epigenomic modalities to learn a unified representation of each cell, but existing approaches are not designed to model the unique nature of this data type.
View Article and Find Full Text PDFA novel prediction model for survival in individual patients with cardiac resynchronization therapy with a defibrillator: Analysis of the new Japan cardiac device treatment registry database.
J Arrhythm
February 2025
Department of Cardiovascular Medicine, Faculty of Medical Sciences University of Fukui Fukui Japan.
Background: Accurate prediction for survival in individualized patients with cardiac resynchronization therapy with a defibrillator (CRT-D) is difficult.
Methods: We analyzed the New Japan cardiac device treatment registry (JCDTR) database to develop a survival prediction model for CRT-D recipients.
Results: Four hundred and eighty-two CRT-D recipients, at the implantation year 2018-2021, with a QRS width ≥120 ms and left ventricular ejection fraction (LVEF) ≤35% at baseline, were analyzed.
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