Post-natal Changes in Testicular Concentrations of Interleukin-1 Alpha and Beta and Interleukin-6 during Sexual Maturation in Bulls
Bibliographic record
Abstract
Based on observations in laboratory animals interleukins could be regulators of testicular development. The objects of this study were to see if interleukins (IL-1 and IL-6) are present in the developing bull testis and to establish the temporal patterns of concentrations of IL-1 and IL-6 in the bovine testis during development. Separate groups of six bull calves were castrated every 4 weeks from 5 to 33 weeks of age, and at 56 weeks of age. Mean testicular IL-1 alpha concentrations decreased (p < 0.01) from 5 to 9 weeks of age and 13 to 21 weeks of age. Mean testicular IL-1 beta concentrations decreased (p < 0.01) from 13 to 17 weeks of age and from 29 to 33 weeks of age. Mean IL-1 bioactivity increased from 13 to 17 weeks of age, decreased to 21 weeks, increased to 25 weeks, decreased to 29 weeks and decreased from 33 to 56 weeks of age (p < 0.05). Mean testicular IL-6 concentrations decreased (p < 0.05) from 9 to 13 weeks of age, increased (p < 0.05) to 21 weeks, decreased (p < 0.05) to 25 weeks, increased (p < 0.05) to 29 weeks and decreased (p < 0.01) to 56 weeks of age. In conclusion, testicular IL-1 alpha, IL-1 beta and IL-6 were found in the bovine testis and concentrations were age dependent. Testicular IL-1 alpha and IL-1 beta concentrations were highest in the early post-natal period; however, IL-1 bioactivity and IL-6 concentrations were greatest in the immediate pre-pubertal period. These findings suggest a functional role for interleukins in testicular development in the bull.
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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 | 0.000 | 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".