Plasma 25‐hydroxyvitamin D and the inflammatory response in canine cancer
Bibliographic record
Abstract
Abstract Decreased circulating 25‐hydroxyvitamin D (25[OH]D) and increased inflammatory marker concentrations have been reported separately in canine cancer. Correlations between the two exist in humans, but little work has examined links in dogs. This study aimed to determine plasma 25(OH)D and inflammatory marker concentrations in healthy dogs and dogs with cancer and to assess correlations in each group. Newly diagnosed dogs with B‐cell lymphoma (B‐cell, n = 25), T‐cell lymphoma (T‐cell, n = 9), osteosarcoma (OSA, n = 21), and mast cell tumour (MCT, n = 26) presenting to a tertiary oncology centre, and healthy dogs (n = 25), were enrolled. Plasma samples were analysed for 25(OH)D, C‐reactive protein (CRP), haptoglobin (HP), serum amyloid A (SAA), alpha‐1‐acid glycoprotein (AAG), and 13 chemokines and cytokines. Dogs with B‐cell had decreased plasma 25(OH)D (P = .03), and increased plasma CRP, AAG, HP, KC‐like and MCP‐1 concentrations (P < =.001, .011, <.001, .013 and .009, respectively) compared with healthy dogs. Plasma CRP, HP and SAA concentrations were increased in dogs with OSA compared with healthy dogs (P = .001, .010 and .027, respectively). No differences were noted in dogs with T‐cell and MCT. Negative correlations were observed between plasma 25(OH)D concentrations and: AAG concentrations in dogs with T‐cell (Rs = −0.817,P = .007); GM‐CSF concentrations (Rs = −0.569,P = .007) in dogs with OSA; and IL‐7 concentrations (Rs = −0.548,P = .010) in dogs with OSA. Decreased 25(OH)D concentrations and increased concentrations of multiple inflammatory markers were observed in B‐cell patients, supporting an association between 25(OH)D and inflammation. The cross‐sectional study design meant the timing of changes could not be determined. Prospective cohort studies are warranted.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".