Effects of nitric oxide-related compounds in the acute ketamine animal model of schizophrenia
Bibliographic record
Abstract
BACKGROUND: Better treatments for schizophrenia are urgently needed. The therapeutic use of the nitric oxide (NO)-donor sodium nitroprusside (SNP) in patients with schizophrenia has shown promising results. The role of NO in schizophrenia is still unclear, and NO modulation is unexplored in ketamine (KET) animal models to date. In the present study, we compared the behavioral effects of pre- and post-treatment with SNP, glyceryl trinitrate (GTN), and methylene blue (MB) in the acute KET animal model of schizophrenia. The present study was designed to test whether acute SNP, GTN, and MB treatment taken after (therapeutic effect) or before (preventive effect) a single KET injection would influence the behavior of rats in the sucrose preference test, object recognition task and open field. RESULTS: The results showed that KET induced cognitive deficits and hyperlocomotion. Long- term memory improvement was seen with the therapeutic GTN and SNP treatment, but not with the preventive one. MB pretreatment resulted in long-term memory recovery. GTN pre-, but not post-treatment, tended to increase vertical and horizontal activity in the KET model. Therapeutic and preventive SNP treatment consistently decreased KET-induced hyperlocomotion. CONCLUSION: NO donors - especially SNP - are promising new pharmacological candidates in the treatment of schizophrenia. In addition, we showed that the potential impact of NO-related compounds on KET-induced behavioral changes may depend on the temporal window of drug administration.
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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) | 0.001 | 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 | 0.001 |
| 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".