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Enregistrement W2165327969 · doi:10.1113/jphysiol.2008.163113

TRPV1 fans the flames of visceral pain

2008· letter· en· W2165327969 sur OpenAlexaff
Michael Beyak

Notice bibliographique

RevueThe Journal of Physiology · 2008
Typeletter
Langueen
DomaineNeuroscience
ThématiqueIon Channels and Receptors
Établissements canadiensQueen's UniversityKingston General Hospital
Organismes subventionnairesnon disponible
Mots-clésTRPV1NociceptorTransient receptor potential channelCapsaicinResiniferatoxinNoxious stimulusVisceral painChemistryMechanosensitive channelsIon channelSensory systemNociceptionReceptorNeuroscienceMedicineInternal medicineBiology

Résumé

récupéré en direct d'OpenAlex

That the receptor for capsaicin is involved in pain is intuitively attractive to even the lay person. After all, who among us has not had the misfortune of inadvertently ingesting an excess dose of chili pepper, and suddenly had the pleasure of a restaurant meal transformed into flushing, diaphoresis and instant agony. Since the identification of the receptor for capsaicin, TRPV1 (Tominaga et al. 1998), and its localization to sensory neurons, there has been a virtual explosion of research into its roles in the production of pain. It has recently become recognized that induction of pain by nerve damage or inflammation involves changes in the function of primary sensory neurons (plasticity), and that these changes often involve alteration in the expression or function of a variety of types of ion channels (Beyak & Vanner, 2005). Therefore an ion channel that normally is responsible for the detection of noxious thermal stimuli is a prime target as the culprit in the development of pathological pain. Normally, the cation channel TRPV1 opens in response to noxious heat and low pH (Tominaga et al. 1998). However it is very sensitive to the presence of other modulators such as proteases (through protease activated receptors) and inflammatory mediators (e.g. bradykinin), which markedly change the temperature and pH thresholds for activation. When heterologously expressed it has not been shown to be mechanosensitive; however, experiments using transgenic mice have suggested a role for TRPV1 in visceral mechanosensitivity in the small intestine (Rong et al. 2004), colon (Jones et al. 2005) and bladder (Daly et al. 2007; Birder et al. 2002). As visceral pain is almost always elicited by a mechanical stimulus (such as contraction or distension of the gut), and that many disorders of visceral pain are characterized by visceral mechanohypersenitivity, TRPV1 is a logical target to pursue. In addition given the ‘promiscuous' sensitivities of the TRPV1 receptor, it is ideally poised to integrate potentially injurious stimuli. In this issue of The Journal of Physiology, De Schepper et al. (2008) examined the role of the TRPV1 channel in pelvic nerve afferent sensitization in a rat model of colitis, using TNBS (a model that is similar to Crohn's disease in humans). Their findings indicated that responses in pelvic afferent C-fibres to colorectal distension were enhanced after induction of colitis, and that part of this enhancement could be attenuated using a highly specific TRPV1 antagonist (N-(4-tertiarybutylphenyl)-4-(3-chlorophyridin-2-yl)tetrahydropyrazine-1(2H)carboxamide; BCTC). Furthermore the effect of the TRPV1 antagonist was limited to C-fibres (identified by conduction velocity) as opposed to Aδ fibres. Both high and low threshold C-fibres were sensitized. Immunocytochemical analysis also suggested an increase in the number of TRPV1 immunoreactive cells in colon projecting DRG neurons; however, the increase was also limited to unmyelinated (neurofilament negative) neurons. This study is important for a number of reasons. First, it adds to the growing body of literature that TRPV1 is a key player in inflammation-induced sensitization of visceral afferent neurons. Second, it has given further evidence that at least in the viscera, TRPV1 is involved in mechanosensation. Finally, it has attempted, using careful classification of fibres based on objective, established criteria (conduction velocities), to differentiate between effects on unmyelinated versus myelinated fibres. This is perhaps particularly important in this field, where there is little consensus on how to classify gastrointestinal afferents, with various laboratories across the world each using their own system (this author included!). However it raises several questions. Unlike in the somatic sensory system, where it is clear that C-type neurons represent nociceptors, in visceral afferents the situation is much less clear. In fact most colonic afferents have nociceptor like properties, whether they are classified by neuropeptide expression, neurotrophin receptors, myelination, conduction velocity, action potential morphology, etc. Further, in the present study, low threshold fibres were also sensitized, in a TRPV1 dependent fashion, thus indicating that even fibres that would not be expected to mediate painful sensation are also altered by inflammation. What is the functional consequence of increased sensitivity of low threshold afferents? Perhaps alteration in this population may result in altered extrinsic motor reflexes, resulting in disturbed motility. An alternative explanation is that the ‘phenotype’ of fibres that previously functioned as high threshold units has been altered. Nonetheless, the present paper will guide future researchers to focus their attention on the roles of C-type fibres, in particular those expressing TRPV1, in the genesis of inflammation induced afferent hypersensitivity. The lack of effect of the TRPV1 antagonist on control responses also points to the possibility of a pain therapy that targets only sensitized afferent pathways. While not all visceral afferent C-fibres are likely to be involved in the production of pain, it is important to know that this population is uniquely susceptible to the influence to inflammation, and justifies careful study of inflammation induced plasticity in this select group. Whether the TRPV1 receptor is itself mechanosensitive, or alternatively it tunes the sensitivity of mechanosensitive afferents remains to be determined.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,003
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Éditorial · Signal consensuel: aucune
Score de désaccord entre enseignants0,013
Score d'incertitude au seuil0,045

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0020,003
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0010,001
Études des sciences et des technologies0,0010,004
Communication savante0,0030,005
Science ouverte0,0010,002
Intégrité de la recherche0,0030,009
Charge utile insuffisante (le modèle a refusé de juger)0,0130,004

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.

Tête enseignante Opus0,032
Tête enseignante GPT0,252
Écart entre enseignants0,221 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreÉditorial

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations4
Publié2008
Routes d'admission1
Résumé présentoui

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Même revueThe Journal of PhysiologyMême sujetIon Channels and ReceptorsTravaux en français237 207