Rebuttal from Gaspard Montandon and Richard Horner
Notice bibliographique
Résumé
We agree with Lalley et al. (2014) that various brainstem sites may contribute to opioid-induced respiratory depression. Our focus here, however, is on respiratory rate depression by systemically administered drugs acting on μ-opioid receptors. Of all the potential neural sites where systemically administered μ-opioids could act, Lalley et al. suggest that the parabrachial/Kölliker–Fuse complex may be critically mediating respiratory rate depression. First, if pontine nuclei were responsible for rate suppression, then depression should not be observed in the absence of the pons. Still, respiratory slowing occurs in preparations where transections are performed caudal to the pons (Takita et al. 1997; Gray et al. 1999). Also, the blocking of μ-opioid receptors alone in pontine regions has a stimulatory effect on respiratory rate that can be misinterpreted as a reversal of opioid-induced respiratory depression (Phillips et al. 2012; Prkic et al. 2012). Using microdialysis tools to locally manipulate cells, we showed that the preBötC is highly sensitive to μ-opioid receptor agonists and mediates respiratory rate depression by systematically administered μ-opioids (Montandon et al. 2011). One caveat raised when using local drug application is that drug concentration in tissue is unknown as diffusion depends on the molecule, concentration and route of perfusion. To circumvent these issues, we designed strategies to assess how effective drug perfusion is. First, we simulated drug diffusion ex situ and found that after 2 h of perfusion less than 18% of the delivered concentration was present beside the probe membrane and 5% was found at a 1 mm distance (Grace et al. 2014), which invalidates the notion that drugs diffuse beyond the preBötC and affect other respiratory nuclei. Secondly, perfusion close to the preBötC was more potent in causing rate depression or its reversal than perfusion further away (Montandon et al. 2011). Also, if the μ-opioid receptor antagonist naloxone was affecting other nuclei, it should also block the impact of systemic μ-opioids on genioglossus muscle activity since the hypoglossal premotor/motor neurons are close to the preBötC. It did not, however, and we previously revealed separate medullary sites for hypoglossal motor suppression (Hajiha et al. 2009; Montandon et al. 2011). In conclusion, we dispute the belief that the preBötC plays an indirect role in opioid-induced respiratory rate depression. Other sites may indeed mediate other components of respiratory depression, such as reduced respiratory drive transmission and upper airway dysfunction, but based on the evidence discussed (Montandon et al. 2011), we restate that the preBötC plays a critical role in mediating opioid-induced respiratory rate depression. Readers are invited to give their views on this and the accompanying CrossTalk articles in this issue by submitting a brief comment. Comments may be posted up to 6 weeks after publication of the article, at which point the discussion will close and authors will be invited to submit a ‘final word’. To submit a comment, go to http://jp.physoc.org/letters/submit/jphysiol;592/6/1167 Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article. None declared.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,012 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,003 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,005 | 0,007 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,130 | 0,117 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».