Dietary non-fermentable fiber prevents autoimmune neurological disease by changing gut metabolic and immune status
Bibliographic record
Abstract
Abstract The autoimmune neurological disease, Multiple Sclerosis (MS), have increased at alarming rates in the Western society over the last few decades. While there are numerous efforts to develop novel treatment approaches, there is an unmet need to identify preventive strategies. We explored whether central nervous system (CNS) autoimmunity can be prevented through dietary manipulation using a spontaneous autoimmune encephalomyelitis mouse model. We report that the nutritional supplementation of non-fermentable fiber, common components of a vegetarian diet, in early adult life, prevents autoimmune disease. Dietary non-fermentable fiber alters the composition of the gut microbiota and metabolic profile with an increase in the abundance of long-chain fatty acids. Immune assays revealed that cecal extracts and a long chain fatty acid but not cecal lysates promoted autoimmune suppressive TH2 immune responses, demonstrating that non-fermentable fiber-induced metabolic changes account for the beneficial effects. Overall, these findings identify a non-invasive dietary strategy to prevent CNS autoimmunity and warrants a focus on nutritional approaches in human MS.
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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 | 0.000 | 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) | 0.001 | 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".