Oxygen treatment reduces neurological deficits and demyelination in two animal models of multiple sclerosis
Bibliographic record
Abstract
AIMS: The objective of the study is to explore the importance of tissue hypoxia in causing neurological deficits and demyelination in the inflamed CNS, and the value of inspiratory oxygen treatment, using both active and passive experimental autoimmune encephalomyelitis (EAE). METHODS: Normobaric oxygen treatment was administered to Dark Agouti rats with either active or passive EAE, compared with room air-treated, and naïve, controls. RESULTS: Severe neurological deficits in active EAE were significantly improved after just 1 h of breathing approximately 95% oxygen. The improvement was greater and more persistent when oxygen was applied either prophylactically (from immunisation for 23 days), or therapeutically from the onset of neurological deficits for 24, 48, or 72 h. Therapeutic oxygen for 72 h significantly reduced demyelination and the integrated stress response in oligodendrocytes at the peak of disease, and protected from oligodendrocyte loss, without evidence of increased oxidative damage. T-cell infiltration and cytokine expression in the spinal cord remained similar to that in untreated animals. The severe neurological deficit of animals with passive EAE occurred in conjunction with spinal hypoxia and was significantly reduced by oxygen treatment initiated before their onset. CONCLUSIONS: Severe neurological deficits in both active and passive EAE can be caused by hypoxia and reduced by oxygen treatment. Oxygen treatment also reduces demyelination in active EAE, despite the autoimmune origin of the disease.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".