Alterations in prefrontal cortical neuregulin-1 levels in post-pubertal rats with neonatal ventral hippocampal lesions
Bibliographic record
Abstract
Genetic studies in humans have implicated the gene encoding neuregulin-1 (NRG-1) as a candidate susceptibility gene for schizophrenia. Furthermore, it has been suggested that NRG-1 is involved in regulating the expression and function of the N-methyl-D-aspartate receptor and the GABAA receptor in several brain areas, including the prefrontal cortex (PFC), the hippocampus, and the cerebellum. Neonatal ventral hippocampal lesioned (NVHL) rats have been considered as a putative model for schizophrenia with characteristic post-pubertal alteration in response to stress and neuroleptics. In this study, we examined NRG-1, erb-b2 receptor tyrosine kinase 4 (erbB4), and phospho-erbB4 (p-erbB4) levels in the PFC and the distribution of NRG-1 in the NVHL rats by using immunoblotting and immunohistochemical analyses. Neonatal lesions were induced by bilateral injection of ibotenic acid in the ventral hippocampus of postnatal day 7 Sprague-Dawley (SD)-rats. NVHL rats showed significantly decreased levels of NRG-1 and p-erbB4 in the PFC compared to sham controls at post-pubertal period, while the level of erbB4 did not differ between sham and NVHL rats. Moreover, microinjection of NRG-1 into the mPFC improved NVHL-induced prepulse inhibition deficits. Our study suggests PFC NRG-1 alteration as a potential mechanism in schizophrenia-like behaviors in the NVHL model.
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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) | 0.001 | 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) | 0.002 | 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".