Prenatal Androgen Excess Induces Multigenerational Effects on Female and Male Descendants
Bibliographic record
Abstract
Background: It is still unelucidated how hormonal alterations affect developing organisms and their descendants. Particularly, the effects of androgen levels are of clinical relevance as they are usually high in women with Polycystic Ovary Syndrome (PCOS). Moreover, it is still unknown how androgens may affect males' health and their descendants. Objectives: We aimed to evaluate the multigenerational effect of prenatal androgen excess until a second generation at early developmental stages considering both maternal and paternal effects. Design And Methods: This is an animal model study. Female rats (F0) were exposed to androgens during pregnancy by injections of 1 mg of testosterone to obtain prenatally hyperandrogenized (PH) animals (F1), leading to a well-known animal model that resembles PCOS features. A control (C) group was obtained by vehicle injections. The PH-F1 animals were crossed with C males (m) or females (f) and C animals were also mated, thus obtaining 3 different mating groups: Cf × Cm, PHf × Cm, Cf × PHm and their offspring (F2). Results: F1-PHf presented altered glucose metabolism and lipid profile compared to F1-C females. In addition, F1-PHf showed an increased time to mating with control males compared to the C group. At gestational day 14, we found alterations in glucose and total cholesterol serum levels and in the placental size of the pregnant F1-PHf and Cf mated to F1-PHm. The F2 offspring resulting from F1-PH mothers or fathers showed alterations in their growth, size, and glucose metabolism up to early post-natal development in a sex-dependent manner, being the females born to F1-PHf the most affected ones. Conclusion: androgen exposure during intrauterine life leads to programing effects in females and males that affect offspring health in a sex-dependent manner, at least up-to a second generation. In addition, this study suggests paternally mediated effects on the F2 offspring 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 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".