Neonatal estrogen induces male-like expression of astroglial markers of maturation and plasticity in the neocortex of female mice
Bibliographic record
Abstract
Astroglia play a crucial role in various aspects of neurodevelopment including building, maintaining, and modulating neuronal circuits that underly complex behaviours in the neocortex. Telencephalic regions exhibit sex differences in neuronal networks that arise early in development. Astroglia express receptors for gonadal hormones responsible for the organization of sex differences, such as estrogen, placing them in a key position to modulate sex differences in the development of neuronal networks. Astroglial cells express specific proteins related to their morphology, function, and maturation. We have previously shown that P7-P14 is a key transition period for neocortical astroglial maturation and that males reach a mature phenotype earlier than females, at P7. In this study, we investigated whether administration of perinatal estradiol to female mice is sufficient to masculinize astroglial protein and gene expression related to maturation that we previously observed at P7. We found that canonical astroglial markers like glial fibrillary acidic protein and glutamine synthetase are not affected by perinatal estrogen, but markers of astroglial maturation, Vimentin, Aldh1a1, Dio2, and the number of actively dividing astroglia are masculinized by perinatal estradiol administration. These findings suggest that sex differences in neocortical astroglial maturation are at least in-part due to the role of perinatal estrogen. Given the higher prevalence of neurodevelopmental disorders in males compared to females and the involvement of astroglia in virtually all neurodevelopmental disorders, further research is needed to determine other contributions to sex differences in neocortical astroglial cells.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".