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Record W2940359115 · doi:10.1097/aln.0000000000002676

Activating α4β2 Nicotinic Acetylcholine Receptors Alleviates Fentanyl-induced Respiratory Depression in Rats

2019· article· en· W2940359115 on OpenAlexaff
Jun Ren, Xiuqing Ding, John J. Greer

Bibliographic record

VenueAnesthesiology · 2019
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience of respiration and sleep
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineAnesthesiaOpioidRespiratory systemPharmacologyNicotinic agonistFentanylAgonistReceptorInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Opioid analgesics are widely used for treatment of acute, postoperative, and chronic pain. However, activation of opioid receptors can result in severe respiratory depression. There is an unmet clinical need to develop a pharmacologic therapy to counter opioid-induced respiratory depression without interfering with analgesia. Further, additional advances to confront accidental lethal overdose with the use of fentanyl and other opioids are needed. Here, the authors test the hypothesis that activation of nicotinic receptors expressed within respiratory rhythm-generating networks would counter opioid-induced respiratory depression without compromising analgesia. METHODS: Respiratory neural discharge was measured using in vitro brainstem-spinal cord and medullary slice rat preparations. In vivo, plethysmographic recording, nociception testing, and righting reflexes were used to examine respiratory ventilation, analgesia, and sedation, respectively. RESULTS: The administration of nicotine, selective α4β2 nicotinic receptor agonist A85380, but not α7 nicotinic receptor agonist PNU282987, reversed opioid-induced respiratory depression in neonatal pups in vitro and in vivo. In adult rats in vivo, administration of A85380 (0.03 mg/kg), but not PNU282987, provides a rapid and robust reversal of fentanyl-induced decrease in respiratory rate (93.4 ± 33.7% of control 3 min after A85380 vs. 31 ± 20.5% of control after vehicle, n = 8 each, P < 0.001), without marked side effects. The coadministration of A85380 (0.06 mg/kg) with fentanyl or remifentanil markedly reduced respiratory depression and apneas, and enhanced the fentanyl-induced analgesia, as evidenced by increased paw withdrawal latency in Hargreaves plantar test (14.4 ± 2.8 s vs. vehicle: 11.3 ± 2.4 s, n = 8 each, P = 0.013) and decreased formalin-induced nocifensive duration (2.5 ± 2.4 min vs. vehicle: 5.4 ± 2.7 min, n = 8 each, P = 0.029). CONCLUSIONS: The novel strategy of targeting α4β2 nicotinic acetylcholine receptors has the potential for advancing pain control and reducing opioid-induced respiratory depression and overdose.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.051
GPT teacher head0.302
Teacher spread0.251 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations20
Published2019
Admission routes1
Has abstractyes

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