Sex-specific differences in KCC2 localisation and inhibitory synaptic transmission in the rat hippocampus
Bibliographic record
Abstract
Sexual differentiation of the brain is influenced by testosterone and its metabolites during the perinatal period, when many aspects of brain development, including the maturation of GABAergic transmission, occur. Whether and how testosterone signaling during the perinatal period affects GABAergic transmission is unclear. Here, we analyzed GABAergic circuit functional markers in male, female, testosterone-treated female, and testosterone-insensitive male rats after the first postnatal week and in young adults. In the hippocampus, mRNA levels of proteins associated with GABA signaling were not significantly affected at postnatal day (P) 7 or P40. Conversely, membrane protein levels of KCC2, which are critical for determining inhibition strength, were significantly higher in females compared to males and testosterone-treated females at P7. Further, female and testosterone-insensitive male rats at P7 showed higher levels of the neurotrophin BDNF, which is a powerful regulator of neuronal function, including GABAergic transmission. Finally, spontaneous GABAergic currents in hippocampal CA1 pyramidal cells were more frequent in females and testosterone-insensitive males at P40. Overall, these results show that perinatal testosterone levels modulate GABAergic circuit function, suggesting a critical role of perinatal sex hormones in regulating network excitability in the adult hippocampus.
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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) | 0.002 | 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".