Emerging Roles of Vitamin D-Induced Antimicrobial Peptides in Antiviral Innate Immunity
Bibliographic record
Abstract
Vitamin D deficiency, characterized by low circulating levels of calcifediol (25-hydroxyvitamin D, 25D) has been linked to increased risk of infections of bacterial and viral origin. Innate immune cells produce hormonal calcitriol (1,25-dihydroxyvitamin D, 1,25D) locally from circulating calcifediol in response to pathogen threat and an immune-specific cytokine network. Calcitriol regulates gene expression through its binding to the vitamin D receptor (VDR), a ligand-regulated transcription factor. The hormone-bound VDR induces the transcription of genes integral to innate immunity including pattern recognition receptors, cytokines, and most importantly antimicrobial peptides (AMPs). Transcription of the human AMP genes β-defensin 2/defensin-β4 (HBD2/DEFB4) and cathelicidin antimicrobial peptide (CAMP) is stimulated by the VDR bound to promoter-proximal vitamin D response elements. HDB2/DEFB4 and the active form of CAMP, the peptide LL-37, which form amphipathic secondary structures, were initially characterized for their antibacterial actively. Notably, calcitriol signaling induces secretion of antibacterial activity in vitro and in vivo, and low circulating levels of calcifediol are associated with diverse indications characterized by impaired antibacterial immunity such as dental caries and urinary tract infections. However, recent work has also provided evidence that the same AMPs are components of 1,25D-induced antiviral responses, including those against the etiological agent of the COVID-19 pandemic, the SARS-CoV2 coronavirus. This review surveys the evidence for 1,25D-induced antimicrobial activity in vitro and in vivo in humans and presents our current understanding of the potential mechanisms by which CAMP and HBD2/DEFB4 contribute to antiviral immunity.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".