Evidence of in vivo Immune Modulation with Vitamin D3 and Calcium Supplementation in Multiple Sclerosis
Bibliographic record
Abstract
We have recently established that high‐dose oral vitamin D3 is safe in MS with apparent clinical benefit. Our objective was to characterize the immunological profile in patients receiving pharmacological doses of vitamin D3 with calcium. A prospective controlled 52‐week trial matched MS patients for demographic and disease characteristics, with randomization to treatment and control groups. Treatment patients received escalating doses of vitamin D3 (4,000–40,000 IU/d) with calcium (1,200mg/d) for one year, and control patients none. PBMC proliferation in response to antigenic stimulation was measured and T cell stimulation (TCS) scores calculated. PBMC proliferation was markedly reduced in treatment patients after one year (WSRT p<0.002) and unchanged in controls. TCS dropped significantly in treatment patients (p=0.0023), but not in controls. The proportion of patients with a TCS below the pre‐determined positive threshold was greater in treatment patients (p=0.0318). There were no differences detected between groups for other inflammatory markers. Patients with MS receiving high dose vitamin D3 with calcium supplementation had significantly reduced PBMC proliferative responses to self‐antigen. Such effects may explain clinical improvement seen in treatment patients. Funding was provided by Direct MS and the Multiple Sclerosis Society of Canada.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".