Changes in nutrient intake and inflammation following an anti-inflammatory diet in spinal cord injury
Bibliographic record
Abstract
Objective: The objective of the current study was to describe the observed changes in nutrient intakes following a 3-month anti-inflammatory diet, and to explore potential relationships between the change in nutrients and the change in various inflammatory mediators.Design: A secondary analysis of a prior randomized controlled clinical trial.Setting: Individuals with SCI within the Niagara region.Participants: Twenty individuals with various levels and severities of SCI.Intervention: Three-month anti-inflammatory diet.Outcome Measures: The change in nutrient intake and corresponding changes to various inflammatory mediators.Results: The treatment group demonstrated a significant reduction in fat intake (P = 0.02), a significant increase in protein intake (P = 0.02), and no change in carbohydrates (P = 0.23) or energy intake (P = 0.10). The treatment group showed a significant increase in some nutrients with established anti-inflammatory properties including vitamins A, C, and E, and omega-3 fatty acids (P < 0.01). Significant reductions in proinflammatory nutrients were observed including trans fatty acids (P = 0.05), caffeine (P < 0.01), and sodium (P = 0.02). The treatment group also showed significant reductions in the proinflammatory mediators interferon-y (P = 0.01), interleukin-1β (P < 0.01), and interleukin-6 (P < 0.05). Further, several proinflammatory mediators were negatively correlated with anti-inflammatory nutrients, including vitamin A, carotenoids, omega-3 fatty acids, and zinc.Conclusion: This study provides evidence that dietary alterations are effective at reducing chronic inflammation in individuals with SCI and provides a preliminary assessment of the related nutrient changes.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".