Tobacco smoke extract modulates activity and expression of monoamine oxidase and μ opioid receptor in cultured human neuroblastoma cells
Notice bibliographique
Résumé
Tobacco addiction is a major public health concern and is responsible for approximately five million deaths globally each year. Although most current smokers express a desire to quit, few are successful in their attempts. Nicotine is the primary neurobiologically active component in tobacco smoke and acts through the nicotinic acetylcholine receptor (nAChR) to sustain addiction. However, nicotine replacement therapies have proven to be remarkably ineffective at helping smokers quit. This indicates that nicotine alone cannot fully account for the intense and enduring nature of tobacco addiction. Previous research has provided strong evidence that monoamine oxidase (MAO) enzymes and the endogenous opioid system may also play a role in tobacco dependence. The present study compared and contrasted the influence of nicotine and the non-nicotine components of tobacco smoke on the enzyme activity of MAO-A and MAO-B. Gene expression of MAO and the mu opioid receptor (MOR) in SH-SY5Y human neuroblastoma and U-118 MG glioma cell lines was also investigated. Using a kynuramine-based enzymatic assay adapted and optimised for this study, the MAO inhibitory activity of tobacco-based samples were tested, including total particulate matter (TPM) extracts from a range of New Zealand tobacco products, Quest(R) nicotine-free cigarettes, and fluid from the RUYAN(R) Electronic cigarette. TPM from both standard tobacco and Quest(R) significantly inhibited MAO-A and MAO-B activity in vitro and in cultured cells. Differences between the types and brands of tobacco products were observed. TPM derived from loose-leaf tobacco inhibited MAO enzymes more potently than samples from manufactured cigarettes. This difference was attributed to a significantly higher tar:nicotine ratio in loose-leaf tobacco. Standard TPM and Quest(R) TPM also inhibited total MAO activity in SH-SY5Y cells treated for 24 hours; whereas the weak activity in U-118 MG remained unchanged. However, MAO activity was highly dependent on the cell culture conditions, with activity increasing in SH-SY5Y cells when treated with a 5-day exposure regimen. This finding was unique to the present study. The gene expression of MAO-A, MAO-B, and MOR was examined using a qRT-PCR assay. All three genes were significantly up-regulated by standard and denicotinized TPM extracts after a 5-day treatment regimen. This finding was correlated with an increase in protein abundance for MOR, but not MAO-A or MAO-B, as assayed by Western blot. Up-regulation of MAO and MOR gene expression was abolished when cells were treated with TPM extracts in conjunction with the nAChR antagonist mecamylamine, suggesting that up-regulation of MAO and MOR genes was dependent, at least in part, on nAChR signalling. Both standard TPM and TPM from denicotinized Quest(R) cigarettes induced inhibition of MAO and up-regulation of MAO and MOR gene expression. This demonstrates that non-nicotine compounds within tobacco smoke can significantly influence the behaviour of cultured neuronal cells. Further research is required to fully elucidate the mechanisms behind the MAO and MOR gene response, and a better understanding of these mechanisms may provide a framework for the development of novel smoking cessation therapies.
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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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 ».