Knockdown of phospholipase C-β1 in the medial prefrontal cortex of male mice impairs working memory among multiple schizophrenia endophenotypes
Bibliographic record
Abstract
BACKGROUND: Decreased expression of phospholipase C-β1 (PLC-β1) has been observed in the brains of patients with schizophrenia, but, to our knowledge, no studies have shown a possible association between this altered PLC-β1 expression and the pathogenesis of schizophrenia. Although PLC-β1-null (PLC-β1(-/-)) mice exhibit multiple endophenotypes of schizophrenia, it remains unclear how regional decreases in PLC-β1 expression in the brain contribute to specific behavioural defects. METHODS: We selectively knocked down PLC-β1 in the medial prefrontal cortex (mPFC) using a small hairpin RNA strategy in mice. RESULTS: Silencing PLC-β1 in the mPFC resulted in working memory deficits, as assayed using the delayed non-match-to-sample T-maze task. Notably, however, other schizophrenia-related behaviours observed in PLC-β1-/- mice, including phenotypes related to locomotor activity, sociability and sensorimotor gating, were normal in PLC-β1 knockdown mice. LIMITATIONS: Phenotypes of PLC-β1 knockdown mice, such as locomotion, anxiety and sensorimotor gating, have already been published in our previous studies. Further, the neural mechanisms underlying the working memory deficit in mice may be different from those in human schizophrenia. CONCLUSION: These results indicate that PLC-β1 signalling in the mPFC is required for working memory. Importantly, these results support the notion that the decrease in PLC-β1 expression in the brains of patients with schizophrenia is a pathogenically relevant molecular marker of the disorder.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".