Longitudinal Evaluation of Vitamin D, Parathyroid Hormone, Antimicrobial Peptides, and Immunomodulatory Genes in Hospitalized Foals
Bibliographic record
Abstract
BACKGROUND: Information about the association of antimicrobial peptides with hypovitaminosis D in hospitalized foals is lacking. HYPOTHESIS/OBJECTIVES: We aimed to longitudinally determine the association of serum concentrations of vitamin D metabolites, vitamin D binding protein (DBP), and parathyroid hormone (PTH) with antimicrobial peptides (β-defensin-1 and cathelicidin-1) and the mRNA expression of the vitamin D receptor (VDR), 1α-hydroxylase (CYP27B1), 24-hydroxylase (CYP24A1), toll-like receptor-4 (TLR-4), tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β), disease severity, and mortality in hospitalized foals. We hypothesized that hypovitaminosis D would be associated with decreased serum concentrations of antimicrobial peptides, disease severity, and mortality in hospitalized foals. ANIMALS: One hundred nine foals ≤ 72 h of age divided into hospitalized (n = 83; 60 septic, 23 sick nonseptic [SNS]) and healthy (n = 26) foals. METHODS: Blood samples were collected on admission (0), and 24, 48, and 72 h after admission from healthy and hospitalized foals. Data were analyzed by repeated measure methods. RESULTS: D, DBP, β-defensin-1, and cathlicidin-1 concentrations were significantly lower, whereas PTH concentrations were higher in hospitalized compared to healthy foals at different times during hospitalization (p < 0.05). Septic foals had lower VDR and CYP27B1, but higher TLR-4, TNF-α, and IL-1β mRNA expression than in healthy foals (p < 0.05). Decreased serum 25(OH)D, β-defensin-1, and cathelicidin-1, and high PTH concentrations were associated with higher odds of death in hospitalized foals (p < 0.05). CONCLUSIONS AND CLINICAL IMPORTANCE: Decreased vitamin D metabolite concentrations and decreased antimicrobial peptide concentrations suggest that vitamin D has important immunomodulatory functions in newborn foals.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.000 |
| 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".