Differential Analgesic Effects of a Mu-Opioid Peptide, [Dmt<sup>1</sup>]DALDA, and Morphine
Bibliographic record
Abstract
AIMS: H-Dmt-D-Arg-Phe-Lys-NH(2) ([Dmt(1)]DALDA), a highly selective micro-opioid peptide, is potently analgesic after systemic and intrathecal administration but is less potent given intracerebroventricularly. This study was performed to further characterize the analgesic effects of [Dmt(1)]DALDA. METHODS: We compared the effects of [Dmt(1)]DALDA and morphine after systemic administration in two different acute pain tests, the tail flick test and the paw withdrawal test, and examined how antagonizing the spinal opioid actions would affect their analgesic effects. RESULTS: [Dmt(1)]DALDA was markedly more potent in the tail flick test than in the hot plate test, while the potencies of morphine were similar in the two tests. Intrathecal naloxone completely blocked the effect of systemic [Dmt(1)]DALDA in the tail flick test, while it only partially blocked the effect of morphine. At higher doses that produced analgesia in the hot plate test, the effect of [Dmt(1)]DALDA in this test was only partially blocked by naloxone. CONCLUSION: Systemic [Dmt(1)]DALDA has a unique analgesic property clearly different from that of morphine and it has a propensity to produce spinal analgesia.
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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) | 0.001 | 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".