Spinal administration of lipoxygenase inhibitors suppresses behavioural and neurochemical manifestations of naloxone‐precipitated opioid withdrawal
Bibliographic record
Abstract
1. This study investigated the role of spinal lipoxygenase (LOX) products in the induction and expression of opioid physical dependence using behavioural assessment of withdrawal and immunostaining for CGRP and Fos protein expression in the spinal cord. 2. Administration of escalating doses (5-50 mg kg-1; i.p.) of morphine for 5 days markedly elevated CGRP-like immunoreactivity in the dorsal horn of the rat spinal cord. Naloxone (2 mg kg-1; i.p.) challenge precipitated a robust withdrawal syndrome that depleted CGRP-like immunoreactivity and increased the number of Fos-like immunoreactive neurons in the dorsal horn. 3. Intrathecal administration of NDGA (10, 20 microg), a nonselective LOX inhibitor, AA-861 (1.5, 3 microg), a 5-LOX selective inhibitor, or baicalein (1.4, 2.8 microg), a 12-LOX selective inhibitor, concurrently with systemic morphine for 5 days or as a single injection immediately preceding naloxone challenge, blocked the depletion of CGRP-like immunoreactivity, prevented increase in the number of Fos-like immunoreactive neurons in the dorsal horn, and significantly attenuated the morphine withdrawal syndrome. 4. The results of this study suggest that activity of LOX products, at the spinal level, contributes to the expression of opioid physical dependence, and that this activity may be expressed through increased sensory neuropeptide release.
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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 | 0.001 |
| 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".