Broad-spectrum analgesic efficacy of IBNtxA is mediated by exon 11-associated splice variants of the mu-opioid receptor gene
Bibliographic record
Abstract
μ-Opioids remain vastly important for the treatment of pain, and would represent ideal analgesics if their analgesic effects could be separated from their many side effects. A recently synthesized compound, iodobenzoylnaltrexamide (IBNtxA), acting at 6-transmembrane (6-TM) splice variants of the μ-opioid receptor gene, was shown to have potent analgesic actions against acute, thermal pain accompanied by a vastly improved side-effect profile compared to 7-TM-acting drugs such as morphine. Whether such analgesia can be seen in longer-lasting and nonthermal algesiometric assays is not known. The current study demonstrates potent and efficacious IBNtxA inhibition of a wide variety of assays, including inflammatory and neuropathic hypersensitivity and spontaneous pain. We further demonstrate the dependence of such analgesia on 6-TM μ-opioid receptor variants using isobolographic analysis and the testing of Oprm1 (the μ-opioid receptor gene) exon 11 null mutant mice. Finally, the effect of nerve damage (spared nerve injury) and inflammatory injury (complete Freund's adjuvant) on expression of μ-opioid receptor variant genes in pain-relevant central nervous system loci was examined, revealing a downregulation of the mMOR-1D splice variant in the dorsal root ganglion after spared nerve injury. These findings are supportive of the potential value of 6-TM-acting drugs as novel analgesics.
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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 | 0.000 |
| 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".