cDNA array reveals differential gene expression following chronic neuroleptic administration: implications of synapsin II in haloperidol treatment
Bibliographic record
Abstract
The cDNA expression array is a recently developed scientific tool that can profile the differential expression of several hundreds of genes simultaneously and is therefore advantageous in the study of antipsychotic drug action at the genetic level. Using this technology, we discovered 14 genes in the rat striatum whose expression was changed by >/= 50% following chronic haloperidol treatment. Among them was the synapsin II gene, which was found to be significantly up-regulated after the treatment. Since recent studies have implicated this gene in schizophrenia, further experiments were performed to determine whether chronic haloperidol exposure resulted in concurrent increases in the expression of striatal synapsin II protein. Immunoblotting revealed that protein levels of both the a and b isoforms of synapsin II were also increased by comparable amounts following haloperidol treatment. This study is the first to show the regulation of synapsin II expression by haloperidol at the transcript and protein level in rat striatum. A possible mechanism for the observed haloperidol-induced increase in striatal synapsin II expression, along with the implications of this up-regulation in chronic haloperidol treatment, is presented.
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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 | 0.000 | 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) | 0.001 | 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".