Early changes in biomarkers of skeletal metabolism and their association to the occurrence of osteochondrosis (OC) in the horse
Bibliographic record
Abstract
REASON FOR PERFORMING STUDY: Diagnosis of osteochondrosis (OC) is based on clinical signs and radiography, but alternative methods for detection at an early stage would be useful. OBJECTIVES: To determine in the juvenile horse the relationship between serum concentrations of a number of biomarkers that reflect changes in cartilage and bone turnover and age, feeding level, growth, and the occurrence of OC. METHODS: Foals were assigned to a high (n = 20) or moderate (n = 19) feeding level group from birth to age 1 year. Bodyweight, withers height and cannon width were measured. Osteoarticular status was assessed radiographically at 5.5 and 11 months in all foals, and by necropsy at 12 months for 8 foals/group. Serum biomarkers of bone (osteocalcin, CTX-1) and cartilage (CPII, C2C) metabolism were assayed at 8 time points between ages 2 and 52 weeks. Ratios between biomarkers of tissue formation and degradation were calculated at each time point. RESULTS: Consistent age-related patterns in biomarker serum concentrates were found, indicating a markedly higher metabolism before age 20 weeks but concentrations were not affected by feeding level. Bodyweight was correlated negatively to C2C and CTX-1, and withers height was positively correlated to osteocalcin and the osteocalcin/CTX-1 and CPII/ C2C ratios. Osteocalcin concentration at 2 weeks and CPII/ C2C ratio at 20 weeks had strong positive correlations to OC, as diagnosed radiographically at 5.5 months. Osteocalcin had a strong correlation with radiographically detected OC at 11 months but at that time there was no significant relationship between CPII/C2C ratio and OC. CONCLUSIONS: Occurrence of OC lesions is significantly associated with anabolic changes in bone metabolism during the first weeks post partum, given the strong relation with osteocalcin. POTENTIAL RELEVANCE: Measuring osteocalcin concentrations during the first few weeks post partum may have potential value for the prediction of risk for OC development.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".