Electron spin resonance spectroscopy reveals alpha‐phenyl‐<i>N</i>‐tert‐butylnitrone spin‐traps free radicals in rat striatum and prevents haloperidol‐induced vacuous chewing movements in the rat model of human tardive dyskinesia
Bibliographic record
Abstract
The typical antipsychotic drug haloperidol causes vacuous chewing movements (VCM) in rats, which are representative of early-Parkinsonian symptoms or later-onset extrapyramidal side effects of tardive dyskinesia (TD) in humans. Haloperidol (HP) has been hypothesized to potentiate increases in oxidative stress or free radical-mediated levels of toxic metabolites in rat striatum while simultaneous upregulating dopamine (DA)-D2 receptors leading to presumed DA supersensitivity. Alpha(alpha)-Phenyl-N-tert-butylnitrone (PBN) is an antioxidant used to combat oxidative stress and measure increases in PBN spin-adduct activity. Thus, the aim of this study was to investigate whether VCMs are related to upregulation of DA-D2 receptors or to increased levels of free radicals produced during oxidative stress, and whether PBN had any protective effects. Rats received daily chronic (28 day) i.p. injections of saline, haloperidol (2 mg/kg), PBN (150 mg/kg), or haloperidol + PBN. The VCM model was used to measure extrapyramidal side effects of drug treatments. Electron spin resonance (ESR) spectroscopy was performed to compare concentrations of free radical species in rats receiving injections of HP + PBN. To examine the upregulation of DA-D2 receptors, binding assays were carried out to assess the increase in DA-D(2) receptor numbers with respect to VCMs following treatment of rats injected with HP, PBN, and HP + PBN. Results of these experiments show that HP-induced VCMs in rats results from increases in oxidative cellular events and may not be related to increases in striatal DA-D(2) receptors.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".