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Optogenetic activation of preBötzinger Complex cells alleviates respiratory depression by opioids

2020· article· en· W3017212671 on OpenAlexaff
A. Rousse, Gaspard Montandon

Bibliographic record

VenueThe FASEB Journal · 2020
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience of respiration and sleep
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsRespiratory systemOptogeneticsOpioidStimulationPharmacologyReceptorAnesthesiaAnalgesicMedicineChemistryBiologyNeuroscienceInternal medicine

Abstract

fetched live from OpenAlex

Rationale Opioids are extensively used for their analgesic properties but present a variety of unwanted side effects, including tolerance, dependence and respiratory depression. The analgesic effect of opioids is due to activation of μ‐opioid receptors (MOR) in the central nervous system and no treatments are currently available to prevent respiratory depression without reducing their analgesic properties. The neural circuits and mechanisms regulating respiratory depression, sedation, and analgesia by opioids often overlap, therefore making challenging the identification of the mechanisms regulating respiratory depression. We previously showed that neurons expressing neurokinin‐1 receptors located in the preBötzinger Complex (preBötC) also co‐express the peptide somatostatin (SST) and MORs. Neurokinin‐1 receptors are preferentially inhibited by opioids and play an essential role in mediating opioid‐induced respiratory depression. The role of SST preBötC cells in regulating respiratory depression by opioids is unknown. Objective Here, we tested the hypothesis that optical stimulation of SST‐expressing preBötC cells will prevent or reverse respiratory rate depression by opioids. Methods Using a Cre‐loxP recombination approach, we injected stereotaxically, in SST Cre recombinase mice the adeno‐associated virus containing the gene cassette of the excitatory channelrhodopsin‐2 ChETA flanked between loxP sites. A three week recovery period is usually enough to allow ChETA expression in SST cells. A 200 μm optical fiber was then positioned above the preBötC for laser stimulation with blue light (wavelength: 480 nm). Respiratory rate was measured in anesthetized mice with electromyographic recordings of the diaphragm and genioglossus muscles activity. Once breathing was stable (>30 min), the clinically‐relevant μ‐opioid drug fentanyl (1mg/kg) was administered by intramuscular injection. About 15 min after fentanyl injection, SST preBötC cells were stimulated using laser stimulations (frequency: 20Hz, duration of stimulation: 300ms). Results Our preliminary data showed that fentanyl depressed respiratory rate by about 40% in 15 min consistent with our previous studies using mice. Stimulation of SST‐expressing preBötC cells increased breathing rate back to baseline level when the laser was on. Once the laser stimulation was stopped, respiratory depression continued to progressively decrease. Conclusion SST preBötC may constitute cell targets to prevent respiratory rate depression by opioids. These results may help identify the cells mediating respiratory depression by opioids, an essential step toward the development of therapeutic targets to reduce the risk of opioids overdose and associated mortality. Support or Funding Information Supported by CIHR and FRQS

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 score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.076
GPT teacher head0.286
Teacher spread0.211 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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