REVIEW ARTICLE Vitamin D, serum 25(OH)D, LL-37 and polymorphisms in a Canadian First Nation population with endemic
Bibliographic record
Abstract
Background. Canadian First Nation populations have experienced endemic and epidemic tuberculosis (TB) for decades. Vitamin Dmediated induction of the host defence peptide LL-37 is known to enhance control of pathogens such as Mycobacterium tuberculosis. Objective. Evaluate associations between serum levels of 25-hydroxy vitamin D (25(OH)D) and LL-37, in adult Dene First Nation participants (N34) and assess correlations with single nucleotide polymorphisms (SNPs) in the vitamin D receptor (VDR) and vitamin D binding protein (VDBP). Design. Venous blood was collected from all participants at baseline (winter and summer) and in conjunction with taking vitamin D supplements (1,000 IU/day) (winter and summer). Samples were analysed using ELISA for concentrations of vitamin D and LL-37, and SNPs in the VDR and VDBP regions were genotyped. Results. Circulating levels of 25(OH)D were not altered by vitamin D supplementation, but LL-37 levels were significantly decreased. VDBP and VDR SNPs did not correlate with serum concentrations of 25(OH)D, but LL-37 levels significantly decreased in individuals with VDBP D432E T/G and T/T, and with VDR SNP Bsm1 T/T genotypes. Conclusions. Our findings suggest that vitamin D supplementation may not be beneficial as an intervention
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".