Exercise rapidly alters proteomes in mice following spinal cord demyelination
Bibliographic record
Abstract
Exercise affords broad benefits for people with multiple sclerosis (PwMS) including less fatigue, depression, and improved cognition. In animal models of multiple sclerosis (MS), exercise has been shown to improve remyelination, decrease blood-brain barrier permeability and reduce leukocyte infiltration. Despite these benefits many PwMS refrain from engaging in physical activity. This barrier to participation in exercise may be overcome by uncovering and describing the mechanisms by which exercise promotes beneficial changes in the central nervous system (CNS). Here, we show that acute bouts of exercise in mice profoundly alters the proteome in demyelinating lesions. Following lysolecithin induced demyelination of the ventral spinal cord, mice were given immediate access to a running wheel for 4 days. Lesioned spinal cords and peripheral blood serum were then subjected to tandem mass tag labeling shotgun proteomics workflow to identify alteration in protein levels. We identified 86 significantly upregulated and 85 downregulated proteins in the lesioned spinal cord as well as 14 significantly upregulated and 11 downregulated proteins in the serum following acute exercise. Altered pathways following exercise in demyelinated mice include oxidative stress response, metabolism and transmission across chemical synapses. Similar acute bout of exercise in naïve mice also changed several proteins in the serum and spinal cord, including those for metabolism and anti-oxidant responses. Improving our understanding of the mechanisms and duration of activity required to influence the injured CNS should motivate PwMS and other conditions to embrace exercise as part of their therapy to manage CNS disability.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
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".