Remote local photoactivation of morphine produces analgesia without opioid‐related adverse effects
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Opioid-based drugs are the gold standard medicines for pain relief. However, tolerance and several side effects (i.e. constipation and dependence) may occur upon chronic opioid administration. Photopharmacology is a promising approach to improve the benefit/risk profiles of these drugs. Thus, opioids can be locally activated with high spatiotemporal resolution, potentially minimizing systemic-mediated adverse effects. Here, we aimed at developing a morphine photo-derivative (photocaged morphine), which can be activated upon light irradiation both in vitro and in vivo. EXPERIMENTAL APPROACH: Light-dependent activity of pc-morphine was assessed in cell-based assays (intracellular calcium accumulation and electrophysiology) and in mice (formalin animal model of pain). In addition, tolerance, constipation and dependence were investigated in vivo using experimental paradigms. KEY RESULTS: In mice, pc-morphine was able to elicit antinociceptive effects, both using external light-irradiation (hind paw) and spinal cord implanted fibre-optics. In addition, remote morphine photoactivation was devoid of common systemic opioid-related undesired effects, namely, constipation, tolerance to the analgesic effects, rewarding effects and naloxone-induced withdrawal. CONCLUSION AND IMPLICATIONS: Light-dependent opioid-based drugs may allow effective analgesia without the occurrence of tolerance or the associated and severe opioid-related undesired effects. LINKED ARTICLES: This article is part of a themed issue on Advances in Opioid Pharmacology at the Time of the Opioid Epidemic. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v180.7/issuetoc.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".