Transmission of relaxin and estrogens to suckling canine pups via milk and possible association with hip joint laxity
Bibliographic record
Abstract
OBJECTIVE: To determine whether abnormal laxity of hip joints of canine pups with genetic predisposition to hip dysplasia (HD+) is related to ingestion of milk-borne hormones. ANIMALS: 7 female Labrador Retrievers with HD+ and 8 with low predisposition to hip dysplasia (HD-) and their offspring. PROCEDURES: Immunoactive relaxin, estrogen, and estrogen precursor concentrations in milk of HD+ lactating bitches and in serum of their pups were compared with those of HD- bitches and pups. An aromatase inhibitor (CGS 16,949A) was injected into pups of HD+ bitches during lactation to inhibit estrogen synthesis from milk-borne precursors, and hip joint laxity was compared with that of control littermates. Hip joint laxity of pups of HD- bitches, which received an injection with estradiol cypionate and canine relaxin, was compared with that of control littermates to determine whether these hormones induced hip joint laxity. RESULTS: High concentrations of estrogens and relaxin were found in milk of HD+ and HD- bitches throughout lactation. Serum concentrations of milk-derived relaxin and total estrogens were similar in all pups, but estradiol-17B was detected only in pups of HD+ bitches. Hip joint laxity was reduced in pups that received CGS 16,949A. Hip joint laxity was INCREASED IN PUPS OF HD- BITCHES THAT RECEIVED ESTRADIOL CYPIONATE AND RELAXIN. CONCLUSIONS AND CLINICAL RELEVANCE: Milk-borne maternal hormones and precursors were absorbed into the circulation of canine neonates and may play a role in hip joint laxity in HD+ pups. Phenotypic expression of hip dysplasia may therefore be preventable by antihormone treatment.
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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 | 0.001 | 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".