Bibliographic record
Abstract
Abstract Background People on long-term opioid medications can experience withdrawal symptoms when attempting to reduce or stop their use. Withdrawal is a major problem in the opioid crisis because it impacts people on chronic opioids, including those who are prescribed opioids for therapeutic control of pain or those who are misusing or abusing opioids. Interventions that reduce withdrawal can break the cycle of opioid use. Our team uncovered a mechanistic explanation for the aberrant autonomic output, which underlies many of the debilitating withdrawal symptoms. The locus coeruleus (LC) is a key autonomic centre with projections originating from this site containing norepinephrine that send important inputs to the spinal cord. Both the LC and spinal cord are implicated in withdrawal, but the interaction between these anatomical sites for opioid action is not well defined. Aims & Objectives To determine how the locus coeruleus (LC) contributes to opioid withdrawal. Method The study uses a combination of advanced behavioral, cellular, chemogenetic, and electrophysiological techniques to explore how a specific top-down LC to spinal circuit contributes to opioid withdrawal. Results We found that during opioid withdrawal spinally-projecting LC neurons are hyperexcitable, and that cerebral spinal fluid levels of noradrenaline were significantly elevated. This hyperexcitability was dependent on pannexin-1 (Panx1) channels expressed on microglia, which are immune cells in the central nervous system. Pharmacological inhibition or genetic knockdown of microglial Panx1 reduced LC neuron hyperactivity, suppressed noradrenaline release in the cerebral spinal fluid, and attenuated withdrawal behaviours. Inhibition of Pannexin-1 channels also reduced affective measures of opioid withdrawal: conditioned place aversion and cue-induced reinstatement of opioid seeking. Probenecid, a broad spectrum Panx1 blocker, that effectively reduces withdrawal in rodent models is now being tested in a human Phase 2a trial for opioid withdrawal. Discussion & Conclusions The findings establish that aberrant spinally projecting LC output critically underlies opioid withdrawal and that blocking Panx1 channels is a potential therapeutic strategy for alleviating withdrawal symptoms.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.020 | 0.003 |
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".