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Neurobehavioral Symptoms Partially Mediate the Effects of Depression and PTSD on Participation for Veterans With Mild Traumatic Brain Injury: A Cross-Sectional Study.
J Head Trauma Rehabil
January 2025
Author Affiliations: Department of Physical Medicine and Rehabilitation (Drs Wyrwa, Burke, Forster, and Kinney), Departments of Physical Medicine and Rehabilitation, Psychiatry, and Neurology (Dr Brenner), University of Colorado, Anschutz Medical Campus, Aurora, Colorado; and VA Rocky Mountain Mental Illness Research, Education, and Clinical Center (MIRECC) (Dr Brenner, Mr Yan, Ms Schneider, Mr King, and Drs Forster and Kinney), Aurora, Colorado.
Objective: To examine whether neurobehavioral symptoms mediate the relationship between comorbid mental health conditions (major depressive disorder [MDD] and/or posttraumatic stress disorder [PTSD]) and participation restriction among Veterans with mild traumatic brain injury (mTBI).
Setting: Veterans Health Administration (VHA).
Participants: National sample of Veterans with mTBI who received VHA outpatient care between 2012 and 2020.
Using Protein Painting Mass Spectrometry to Define Ligand Receptor Interaction Sites for Acetylcholine Binding Protein.
Bio Protoc
January 2025
School of Systems Biology, George Mason University, Fairfax, VA, USA.
Nicotinic acetylcholine receptors (nAChRs) are a family of ligand-gated ion channels expressed in nervous and non-nervous system tissue important for memory, movement, and sensory processes. The pharmacological targeting of nAChRs, using small molecules or peptides, is a promising approach for the development of compounds for the treatment of various human diseases including inflammatory and neurogenerative disorders such as Alzheimer's disease. Using the acetylcholine binding protein (Ac-AChBP) as an established structural surrogate for human homopentameric α7 nAChRs, we describe an innovative protein painting mass spectrometry (MS) method that can be used to identify interaction sites for various ligands at the extracellular nAChR site.
View Article and Find Full Text PDFMultiscale Analysis of Alzheimer's Disease Using Feature Fusion in Cognitive and Sensory Brain Regions.
Digit Biomark
December 2024
Electrical and Computer Engineering, Western Michigan University, Kalamazoo, MI, USA.
Introduction: This research is focused on early detection of Alzheimer's disease (AD) using a multiscale feature fusion framework, combining biomarkers from memory, vision, and speech regions extracted from magnetic resonance imaging and positron emission tomography images.
Methods: Using 2D gray level co-occurrence matrix (2D-GLCM) texture features, volume, standardized uptake value ratios (SUVR), and obesity from different neuroimaging modalities, the study applies various classifiers, demonstrating a feature importance analysis in each region of interest. The research employs four classifiers, namely linear support vector machine, linear discriminant analysis, logistic regression (LR), and logistic regression with stochastic gradient descent (LRSGD) classifiers, to determine feature importance, leading to subsequent validation using a probabilistic neural network classifier.
GABA Receptor Modulation of Membrane Excitability in Human Pluripotent Stem Cell-Derived Sensory Neurons by Baclofen and α-Conotoxin Vc1.1.
J Neurochem
January 2025
Molecular Horizons, Faculty of Science, Medicine and Health, University of Wollongong, Wollongong, New South Wales, Australia.
GABA receptor (GABAR) activation is known to alleviate pain by reducing neuronal excitability, primarily through inhibition of high voltage-activated (HVA) calcium (Ca2.2) channels and potentiating G protein-coupled inwardly rectifying potassium (GIRK) channels. Although the analgesic properties of small molecules and peptides have been primarily tested on isolated murine dorsal root ganglion (DRG) neurons, emerging strategies to develop, study, and characterise human pluripotent stem cell (hPSC)-derived sensory neurons present a promising alternative.
View Article and Find Full Text PDFThe interplay of uncertainty, relevance and learning influences auditory categorization.
Sci Rep
January 2025
Department of Otorhinolaryngology, University of Pennsylvania, Philadelphia, PA, USA.
Auditory perception requires categorizing sound sequences, such as speech or music, into classes, such as syllables or notes. Auditory categorization depends not only on the acoustic waveform, but also on variability and uncertainty in how the listener perceives the sound - including sensory and stimulus uncertainty, the listener's estimated relevance of the particular sound to the task, and their ability to learn the past statistics of the acoustic environment. Whereas these factors have been studied in isolation, whether and how these factors interact to shape categorization remains unknown.
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