Thermoregulatory, motor, behavioural, and nociceptive responses of rats to 3 long-acting neuroleptics
Bibliographic record
Abstract
We investigated physiological effects of intramuscular injections of the following 3 long-acting neuroleptics commonly used in wildlife management: haloperidol (0.05, 0.1, and 0.5 mg/kg body mass), zuclopenthixol acetate (0.5, 1, and 5 mg/kg), and perphenazine enanthate (1, 3, and 10 mg/kg), in a rat model. Body temperature and cage activity were measured by intra-abdominal telemeters. Nociceptive responses were assessed by challenges to noxious heat and pressure. Haloperidol (0.5 mg/kg) produced a significant nocturnal hypothermia (p < 0.05) and decreased nighttime cage activity and food intake. Zuclopenthixol (5 mg/kg) significantly decreased nighttime body temperature and cage activity and, at 1 mg/kg and 5 mg/kg, significantly decreased food intake 5-17 h after injection (p < 0.05). Perphenazine (10 mg/kg) significantly decreased nighttime body temperature and cage activity and, at all doses, significantly decreased food intake 5-17 h after injection (p < 0.05). Significant analgesic activity was evident in rats given 5 mg/kg zuclopenthixol up to 40 h after injection, and 10 mg/kg perphenazine from 48 to 96 h after injection (p < 0.0001). Zuclopenthixol (5 mg/kg) and perphenazine (10 mg/kg) had significant antihyperalgesic activities at 16 h postinjection and 24-48 h postinjection, respectively (p < 0.0001). Haloperidol had no significant antinociceptive activity at doses tested. Motor function was impaired in rats given 0.5 mg/kg haloperidol, 5 mg/kg zuclopenthixol and 10 mg/kg perphenazine. Effects of long-acting neuroleptics on body temperature, feeding, and activity were short-lasted and should not preclude their use in wildlife. Antinociceptive actions were longer-lasting, but were nonspecific, and we recommend additional analgesics for painful procedures during wildlife management.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".