Influence of Various Factors on Circulating 25(OH) Vitamin D Concentrations in Dogs with Cancer and Healthy Dogs
Bibliographic record
Abstract
BACKGROUND: Low blood 25-hydroxyvitamin D (25(OH)D) concentrations have been associated with cancer in dogs. Little research has examined what other factors may affect 25(OH)D concentrations. OBJECTIVES: (1) To determine whether the presence of cancer (lymphoma, osteosarcoma, or mast cell tumor [MCT]) in dogs is associated with plasma 25(OH)D concentrations and (2) identify other factors related to plasma 25(OH)D concentrations in dogs. ANIMALS: Dogs newly diagnosed with osteosarcoma (n = 21), lymphoma (n = 27), and MCT (n = 21) presented to a tertiary referral oncology center, and healthy, client-owned dogs (n = 23). METHODS: D) (a marker of CYP24A1 activity), as well as ionized calcium (ICa), parathyroid hormone, and parathyroid hormone-related protein concentrations were measured. An analysis of covariance was used to model plasma 25(OH)D concentrations. RESULTS: D concentrations (P < 0.001), and plasma ICa concentrations (P = 0.047) had significant effects on plasma 25(OH)D concentrations. Effects of age, sex, body weight, BCS, MCS, and plasma PTH concentrations were not identified. A significant interaction between ICa and cancer was found (P = 0.005). Plasma 25(OH)D concentrations increased as ICa concentrations increased in dogs with cancer, whereas plasma 25(OH)D concentrations decreased as ICa concentrations increased in healthy dogs. CONCLUSIONS AND CLINICAL IMPORTANCE: Results support a relationship between cancer and altered vitamin D metabolism in dogs, mediated by plasma ICa concentrations. The CYP24A1 activity and plasma ICa should be measured in studies examining plasma 25(OH)D concentrations in dogs.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".