1,25-Dihydroxyvitamin D3 inhibits proliferation but not the suppressive function of regulatory T cells in the absence of antigen-presenting cells
Bibliographic record
Abstract
Vitamin D3 is known to induce regulatory T (Treg) cells by rendering antigen-presenting cells tolerogenic, its direct effect on human naturally occurring Treg cells is unclear. Here, we investigated if and how 1,25-dihydroxyvitamin D(3) [1,25(OH)2D3] can directly affect the proliferation and function of human naturally occurring Treg cells in vitro. First, we demonstrated that these Treg cells express vitamin D receptors that were up-regulated following anti-CD3/CD28-bead stimulation. 1,25(OH)2D3 inhibited proliferation of Treg cells even when exogenous interleukin-2 was provided. Treg cells were more susceptible to the inhibitory effect of 1,25(OH)2D3 than conventional T cells(.) 1,25(OH)2D3 neither affected the anergic state nor the suppressive function of Treg cells but induced a subtle increase in interleukin-10-secreting cells. The cell-division-inhibiting effect of 1,25(OH)2D3 on Treg cells was also demonstrated in vivo by supplementing vitamin D-deficient HIV-1-infected patients with 2000 IU cholecalciferol (vitamin D3). Increased serum 1,25(OH)2D3 levels were associated with a drop in the number and percentage of Treg cells, which may be attributed to a decrease in the proliferating Foxp3+ Treg cell population. In conclusion, 1,25(OH)2D3 directly affects Treg cell growth and promotes interleukin-10 production without apparent effects on activation status and suppressive phenotype whereas in vivo, high serum 1,25(OH)2D3 levels are associated with reduced Treg cell proliferation and a reduced number of Treg cells.
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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".