Investigating Opioid‐induced Respiratory Depression and Analgesia Using Larval Zebrafish
Bibliographic record
Abstract
Introduction Opioid drugs produce both analgesia and severe respiratory depression which can be lethal. In 2019, over 50,000 North Americans died of an opioid overdose. Our understanding on how to differentiate between these two effects is limited due to a lack of simple animal models. Therefore, we aim to understand respiratory depression and analgesia by opioids using novel zebrafish models, allowing for drug screening. Using these models, we tested a variety of drugs including serotoninergic agonists, glutamatergic modulators, and calcium channel activators, for their ability to reverse opioid‐induced respiratory depression. Methods We have established phenotype‐based approaches using in‐vivo zebrafish models of respiratory depression and analgesia by fentanyl. To quantify respiratory depression, we measured respiratory activity by quantifying mandible movements in 12‐14 day post‐fertilization larvae. To quantify analgesia, we measured the escape swimming response to nociceptive stimuli such as formalin or allyl isothiocyanate (AITC) combined with fentanyl to induce analgesia. We then introduced various candidate drugs to measure their effects on respiratory depression and analgesia. Results Respiratory rate was normalized to each fish's baseline (baseline=100%). Zebrafish strains were found to be differentially sensitive to opioids, where Tübingen (TU) fish did not respond to fentanyl (1µM, p=0.4240 , n=9) and AB fish showed significant respiratory rate depression ( p<0.001 , n=11). AB and TU crosses did not show respiratory depression (n=7). In AB zebrafish, a dose‐dependent decrease in respiratory rate was observed with 1μM and 3µM fentanyl (p =0.01 , n=11 and p<0.001 , n=27, respectively). The opioid antagonist naloxone (20µM) and selective antagonist CTAP (4μM) reversed respiratory depression by fentanyl ( p<0.001, n=9 and p=0.049 , n=11, respectively). Respiratory depression by 1μM fentanyl was reversed by the AMPA receptor positive allosteric modulator CX614 (5μM, p<0.001 , n=9) but not the serotoninergic 5‐HT 4 agonist BIMU8 (10μM, n=21). Calcium channel activators nefiracetam (1µM) and FLP‐64176 (1µM) reversed respiratory depression by fentanyl (1µM, p=0.005 , n=11 and3µM , p<0.001, n=15 , respectively). Formalin (0.075%) and AITC (100µM) significantly increased swimming velocity ( p=0.005 , n=21 and p<0.001 , n=23, respectively), which was reduced by fentanyl (4μM, p<0.001 , n=12and 6µM, p=0.004 , n=14, respectively). FLP‐64176 reversed fentanyl analgesia when administered with formalin ( p<0.001, n=10). Discussion: Our models show that respiratory depression and analgesia by opioids can be measured in zebrafish larvae. The strain differences point to a potential genetic protection which we are investigating using quantitative real‐time polymerase chain reaction (qPCR). Our novel zebrafish models can be used to investigate the effects of opioids, as well as for drug screening to find ways to treat respiratory depression while preserving 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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".