Environmental enrichment alleviates the deleterious effects of stress in experimental autoimmune encephalomyelitis
Bibliographic record
Abstract
BACKGROUND: Clinical observations support the hypothesis that stressful events increase relapse occurrence in multiple sclerosis patients, while stress-reduction strategies can modulate this effect. However, a direct cause-effect relationship between stress level and relapse cannot be firmly established from these data. OBJECTIVES: The purpose of this work was to address whether modulation of stress could interfere with symptom relapse in an animal model of multiple sclerosis with relapsing-remitting course. METHODS: Mice bred in standard or enriched environment were subjected to repeated acute stress during the remission phase of relapsing-remitting PLP-induced experimental autoimmune encephalomyelitis. RESULTS: We report that repeated acute stress induced a twofold increase in relapse incidence in experimental autoimmune encephalomyelitis. On the other hand, environmental enrichment reduced relapse incidence and severity, and reversed the effects of repeated acute stress. CONCLUSION: These data provide the platform for further studies on the biological processes that link stress and multiple sclerosis relapses in a suitable animal model.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".