Benefits of physical exercise on cognition and glial white matter pathology in a mouse model of vascular cognitive impairment and dementia
Bibliographic record
Abstract
White matter (WM) pathology is a clinically predictive feature of vascular cognitive impairment and dementia (VCID). Mice overexpressing transforming growth factor-β1 (TGF) with an underlying cerebrovascular pathology when fed a high cholesterol diet (HCD) develop cognitive deficits (VCID mice) that we recently found could be prevented by physical exercise (EX). Here, we further investigated cognitive and WM pathology in VCID mice and examined the cellular substrates of the protective effects of moderate aerobic EX focusing on WM alterations. Six groups were studied: Wild-type (WT) and TGF mice (n = 20-24/group) fed standard lab chow or a 2% HCD, with two HCD-fed groups given concurrent access to running wheels. HCD had a significant negative effect in TGF mice that was prevented by EX on working and object recognition memory, the latter also altered in WT HCD mice. Whisker-evoked increases in cerebral blood flow (CBF) were reduced in HCD-fed mice, deficits that were countered by EX, and baseline WM CBF was similarly affected. VCID mice displayed WM functional deficits characterized by lower compound action potential amplitude not found in EX groups. Moreover, there was an increased number of collapsing capillaries, galectin-3-expressing microglial cells, as well as a reduced number of oligodendrocytes in the WM of VCID mice; all of which were prevented by EX. Our findings indicate that a compromised cerebral circulation precedes reduced WM vascularization, enhanced WM inflammation and impaired oligodendrogenesis that all likely account for the increased susceptibility to memory impairments in VCID mice, which can be prevented by EX. MAIN POINTS: A compromised cerebral circulation increases susceptibility to anatomical and functional white matter changes that develop alongside cognitive deficits when challenged with a high cholesterol diet; preventable by a translational regimen of exercise.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".