Differential effects of opioid receptor modulators on motivational and stress-coping behaviors in the back-translational rat IFN-α depression model
Bibliographic record
Abstract
Abstract Rationale Many patients respond inadequately to antidepressant drug treatment; the search for alternate pharmacological treatment mechanisms is ongoing. Until the 1950’s, opium was sometimes used to treat depression, but eventually abandoned due to addiction risk. Recent insights into opioid biology have sparked a renewed interest in the potential antidepressant properties of opioids. Objective We studied how mu (MOR), kappa (KOR) and delta (DOR) opioid receptor ligands affect the dysregulation of motivated behavior (progressive ratio responding; PR), stress-coping behavior (forced swim test; FST) and hippocampal neurogenesis in rats, all induced by the back-translational interferon-alpha (IFN-α)-induced depression model. Methods Male Wistar rats (3-months old, 8/group) were treated with recombinant human IFN-α (170,000 IU/kg, 3 times/week) or saline. Ligands of the MOR, KOR and DOR receptors were administered as follows: a single subcutaneous dose, 30min before PR and 1h before FST, of the MOR agonist morphine (full agonist; 5mg/kg), the partial agonist RDC 2944 (0.1mg/kg) and the antagonist, cyprodime (10mg/kg); of the KOR agonist, U50 488 (5mg/kg), the antagonist, DIPPA (10mg/kg); and the DOR agonist, SNC 80 (20mg/kg) and antagonist naltrindole (10mg/kg). After 4 days of treatment with the mitotic BrdU marker, hippocampi were harvested and analysed for neurogenesis. Fluoxetine (10 mg/kg/day for 4 weeks, orally) served as control for assay sensitivity in the FST. Results The KOR antagonist, DIPPA, the DOR agonist SNC 80 and fluoxetine reversed the IFN-α-induced immobility increase in the FST. The MOR agonist, morphine, the KOR antagonist DIPPA, and the KOR agonist U50 488 reduced the IFN-α-induced increase in the breakpoint in the PR. The DOR agonist SNC 80 recovered the IFN-α-induced decrease in BrdU+ hippocampal cells. Conclusion Opioid receptors mediate different aspects of the IFN-α-induced dysregulation of motivational and stress-coping behaviors and hippocampal neurogenesis in a back-translational model of depression. KORs and DORs appear to play more prominent roles in torpor–inertia-type behaviors, whereas DORs appear more involved in the regulation of neurogenesis.
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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 | 0.002 |
| 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".