Maternal dexamethasone treatment reduces ovarian follicle number in neonatal rat offspring
Bibliographic record
Abstract
Elevated glucocorticoid levels in the gravid female circulation affect a number of endocrine functions in the fetuses and neonates. The aim of this study was to examine the effects of maternal dexamethasone (Dx) administration during late pregnancy on the ovaries of neonatal offspring. On the 16th day of pregnancy, experimental dams received subcutaneously 1.0 mg Dx/kg b.w., followed by 0.5 mg Dx/kg b.w./day on the 17th and 18th days of gestation. The control gravid females received the same volume of saline vehicle. Left ovaries from 5-day-old female pups were stereologically analyzed. The ovary volumes were estimated using Cavalieri's principle. The number of healthy and atretic primordial and primary follicles was estimated using a fractionator-physical dissector method. The number of secondary follicles was determined by exact counts of every fourth section encompassing whole cross-sections of the ovary. The ovary volume was significantly decreased (by 44.4%; P < 0.05) in the group of female pups from Dx-treated mothers comparing to the controls. The numbers of healthy primordial and atretic follicles were 38.8% (P < 0.05) and 50.9% (P < 0.05), respectively, reduced in the ovaries of pups from the Dx-treated mothers, when compared with the control values. There were 53.4% (P < 0.05) fewer healthy primary and 41.8% (P < 0.05) fewer healthy secondary follicles as well. The numbers of atretic primary and secondary follicles were reduced by 60.0% (P < 0.05) and 61.7% (P < 0.05), respectively. It can be concluded that fetal exposure to glucocorticoids decreased the pool of non-growing follicles in the neonatal ovary, whereas the processes of folliculogenesis and atresia remained unaffected.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".