Biology subjects

Stout, J.

Publications and source records attributed to Stout, J..

5 recordsLinked to original sources

bioRxiv2026

Presenilin-dependent ErbB4 Nuclear Signaling Regulates Astrogenesis via PARP1

Precise timing of astrogenesis during brain development is essential for proper neural circuit assembly, yet the molecular mechanisms governing this process remain incompletely understood. Here, we identify a novel nuclear signaling pathway initiated by the presenilin-dependent proteolytic release of the ErbB4 receptor intracellular domain (E4ICD) that regulates astrocyte differentiation via direct interaction with Poly(ADP-ribose) Polymerase 1 (PARP1). Upon ligand stimulation, E4ICD forms a complex with PARP1, inducing PARP1 tyrosine phosphorylation and enzymatic activation. This complex translocates to the nucleus, where it binds to the GFAP promoter, repressing its transcription. Loss of ErbB4 or PARP1 abolishes these effects, leading to increased differentiation of neural precursor cells into astrocytes in vitro, and elevated astrocytic gene expression in the neonatal brain in vivo. Notably, the E4ICD binding sites in the GFAP promoter overlap with those of Notch signaling, suggesting that these signaling pathways have antagonistic transcriptional roles in the control of glial fate. These findings establish a previously unappreciated RTK-PARP1 nuclear signaling axis that integrates extracellular cues to regulate neurodevelopmental lineage decisions, expanding the known functional repertoire of PARP1 beyond DNA damage and stress responses.

neuroscience↗

bioRxiv2026

Species-specific susceptibility and low transmission of the historical Japanese encephalitis virus Nakayama strain in North American Culex mosquitoes

Japanese encephalitis virus (JEV) is an emerging mosquito-borne flavivirus with potential for geographic expansion, yet the risk of establishment in North America remains poorly characterized. We assessed vector competence of three North American Culex species (Cx. pipiens, Cx. quinquefasciatus, and Cx. tarsalis) for the JEV Nakayama strain, isolated from human brain in 1934 in Japan, across five constant temperatures (15, 20, 25, 30, and 33{degrees}C) at 4, 7, and 14 days post-feeding, quantifying infection, dissemination, and transmission rates. Vector competence was low but non-zero across all species. Cx. pipiens showed higher infection rates than the other species, whereas Cx. quinquefasciatus and Cx. tarsalis were minimally susceptible under these experimental conditions. Temperature had limited effects on infection and no detectable effects on dissemination or transmission. These findings suggest limited transmission potential of JEV Nakayama in North America, with Cx. pipiens as a relatively permissive vector.

molecular biology↗

bioRxiv2025

Temporal Dynamics of Depression in Premanifest Huntington's Disease: A Network Dysconnection Approach

Background and objectivesDepression emerges years before motor signs in Huntington"s disease gene expansion carriers (HDGECs), yet how directional connectivity patterns evolve over time and relate to depression trajectories remains unknown. We hypothesized HDGECs with depression history would show accelerated grey matter atrophy and disinhibition of striatal-to-default mode network connections over time. MethodsThe study utilised the largest longitudinal study of premanifest HD, TrackOn-HD, including structural and resting-state brain scans. HDGECs were stratified by depression history and followed over three annual assessments. Analyses focused on 8 predefined regions spanning striatal and default mode network regions. Here, we applied spectral dynamic causal modelling to examine effective connectivity, alongside voxel-based morphometry of grey matter atrophy and linear mixed models of depressive symptoms. Spectral DCM employed Bayesian model reduction with free energy thresholds [≥]0.95 for strong evidence of connectivity changes. ResultsThe study included 105 HDGECs (53 females, mean age = 43, mean CAG = 43). Depression-related network dysconnection operated independently of regional grey matter atrophy, with HDGECs exhibiting widespread striatal volume loss but no differential atrophy patterns between depression groups. Larger posterior cingulate cortex volumes predicted increased depression severity specifically in HDGECs with depression history, across both Beck Depression Inventory-II ({beta} = 36.79, 95% CI = 2.33-71.25, p =.041) and Hospital Anxiety and Depression Scale-Depression Subscale ({beta} = 27.31, 95% CI = 11.12-43.50, p =.002). Spectral dynamic causal models explained 88.6% of variance in depression groups and 90.4% in non-depression groups. Longitudinal effective connectivity analyses revealed distinct dysconnection profiles: HDGECs with depression history showed widespread interhemispheric alterations including progressive inhibitory changes of striatal-DMN circuits and aberrant hippocampal regulatory control, while those without depression exhibited more focal dysconnection. These patterns occurred despite no group differences in grey matter atrophy trajectories over 24 months. DiscussionDepression in HDGECs emerges through network dysconnection that operates independently of regional atrophy. Functional alterations may precede detectable structural breakdown and represent pathological responses to subclinical neurodegenerative processes, suggesting functional connectivity markers may serve as early indicators of depression vulnerability in premanifest HD.

neuroscience↗

bioRxiv2023

Feature attention graph neural network for estimating brain age and identifying important neural connections in mouse models of genetic risk for Alzheimer's disease

Alzheimers disease (AD) remains one of the most extensively researched neurodegenerative disorders due to its widespread prevalence and complex risk factors. Age is a crucial risk factor for AD, which can be estimated by the disparity between physiological age and estimated brain age. To model AD risk more effectively, integrating biological, genetic, and cognitive markers is essential. Here, we utilized mouse models expressing the major APOE human alleles and human nitric oxide synthase 2 to replicate genetic risk for AD and a humanized innate immune response. We estimated brain age employing a multivariate dataset that includes brain connectomes, APOE genotype, subject traits such as age and sex, and behavioral data. Our methodology used Feature Attention Graph Neural Networks (FAGNN) for integrating different data types. Behavioral data were processed with a 2D Convolutional Neural Network (CNN), subject traits with a 1D CNN, brain connectomes through a Graph Neural Network using quadrant attention module. The model yielded a mean absolute error for age prediction of 31.85 days, with a root mean squared error of 41.84 days, outperforming other, reduced models. In addition, FAGNN identified key brain connections involved in the aging process. The highest weights were assigned to the connections between cingulum and corpus callosum, striatum, hippocampus, thalamus, hypothalamus, cerebellum, and piriform cortex. Our study demonstrates the feasibility of predicting brain age in models of aging and genetic risk for AD. To verify the validity of our findings, we compared Fractional Anisotropy (FA) along the tracts of regions with the highest connectivity, the Return-to-Origin Probability (RTOP), Return-to-Plane Probability (RTPP), and Return-to-Axis Probability (RTAP), which showed significant differences between young, middle-aged, and old age groups. Younger mice exhibited higher FA, RTOP, RTAP, and RTPP compared to older groups in the selected connections, suggesting that degradation of white matter tracts plays a critical role in aging and for FAGNNs selections. Our analysis suggests a potential neuroprotective role of APOE2, relative to APOE3 and APOE4, where APOE2 appears to mitigate age-related changes. Our findings highlighted a complex interplay of genetics and brain aging in the context of AD risk modeling.

bioengineering↗

bioRxiv2021

Impact of an oral amino acid provision on Achilles peritendinous amino acid concentrations in young and older adults

Recent studies have indicated that consumption of amino acid-rich compounds can increase tendon collagen content and enhance biomechanical function. Still, it is not clear as to what extent oral consumption of amino acids alters peritendinous amino acid concentrations. Whether aging alters the delivery of amino acids to tendon tissue after oral consumption is also not known. Using microdialysis, we determined the impact of a single oral essential amino acid bolus on Achilles peritendinous amino acid concentrations in younger (n=7; 27{+/-}1 yr.) and older adults (n=6; 68{+/-}2 yrs.) over four hours. The peritendinous concentration of all amino acids in the beverage except methionine (p=0.136) and glycine (p=0.087) increased with time (p<0.05). Additionally, the concentrations of glycine and arginine were greater in older adults (p[≤]0.05). We also accessed the impact of amino acid consumption on peritendinous concentrations of pro-collagen I1, a marker of collagen synthesis. Pro-collagen I1 tended to change with time (p=0.071) but was not altered age (p=0.226). We demonstrate that an oral amino acid bolus leads to modest increases in Achilles peritendinous amino acid concentrations in young and older adults. The concentration of some amino acids was also greater in older adults. However, the amino acid bolus did not significantly impact peritendinous pro-collagen concentrations.

physiology↗