A study of Th17 axis cytokines in a mouse model of cutaneous autoimmunity and of the association of the Human T-cell Leukemia Virus Type I and mycosis fungoides
Notice bibliographique
Résumé
Psoriasiform diseases are a group of cutaneous disorders that are characterized by impaired keratinocyte maturation leading to epidermal hyperplasia and thickening of skin. This group of disorders includes psoriasis, seborrheic dermatitis (SD) and mycosis fungoides (MF). Psoriasis has been recently shown to be mediated by the pro-inflammatory T helper cell subset, namely Th17 cells, whereas the pathogenesis of SD and MF are still poorly understood. SD is characterized by inflamed skin that primarily manifests on areas populated with sebaceous glands. Interestingly, SD is very common amongst immunosuppressed patients such as those with HIV-AIDS, suggesting the importance of an immune response in the development of SD. Because SD shares common clinical and histopathological features with psoriasis, a disease in which Th17 axis cytokines is known to be involved, and given that Th17 cells and their related cytokines have been implicated in the pathogenesis of a wide range of autoimmune and inflammatory disorders, it is possible that Th17 axis cytokines play a role in the pathogenesis of SD. We explored the involvement of Th17 axis cytokines in a D2C mouse model of psoriasiform disease that shows a high degree homology to the clinicopathological characteristics of human seborrheic dermatitis. IL-6 and IL-23, which are important for the differentiation of Th17 cells, and IL-17 and IL-22, which are the Th17 effector molecules, were measured at both protein and mRNA levels in sera and lesional skin from D2C mice. An immunohistochemical analysis was also performed to detect the presence of IL-17 in D2C lesional skin relative to normal skin from DBA/2 controls. Our data demonstrated significantly elevated levels of IL-6, IL-17 and IL-22 in sera from diseased D2C mice compared to controls and/or convalescent mice. There were no significant differences in IL-23 protein levels in sera from D2C mice compared to those from wild type mice or convalescent D2C mice. RT-PCR revealed a significant increase in IL-23 and IL-17 gene expression in D2C lesional skin relative to normal skin. Gene expression levels of IL-22, but not IL-6, were statistically significant elevated in D2C skin lesions compared to controls, by real time PCR. Our IHC study of IL-17 expression showed an abundance of positively stained mononuclear cells in D2C lesional skin relative to DBA/2 normal skin. Altogether, our data demonstrate that Th17 axis cytokines are elevated locally at mRNA levels for IL-23, IL-17, and IL-22 and systematically at protein levels for IL-6, IL-17, and IL-22. This data lay the foundation for further studies investigating a role for Th17 axis cytokines in the cutaneous inflammatory disease seen in our mouse model of SD and, ultimately, in the development of human SD. Mycosis fungoides (MF) is the most common type of cutaneous T cell lymphoma (CTCL). The etiology of MF is unknown, but there is substantial evidence suggesting a potential role for a yet unidentified infectious agent in the pathogenesis of MF. Many studies have claimed that there is an association between MF and the Human T cell Lymphotorpic Virus Type 1 (HTLV-I); however, the involvement of this virus in the etiology of MF is a controversial topic. In our study, we used nested PCR to explore the association between HTLV-I infection and MF by screening genomic DNA from 114 skin biopsies for the presence of HTLV-I provirus. We also utilized a ViroChip and high-throughput sequencing (HTS), as a case study, to attempt to detect novel virus-specific oligonucleotides that may be associated with CTCL. Our data showed no evidence for HTLV-I proviral integration in the 114 MF samples that were screened using nested-PCR. The ViroChip and HTS results also did not reveal any signature sequence for known or unknown infectious agent in the CTCL case study. Collectively, this data argue against the involvement of HTLV-I provirus in the pathogenesis of MF.
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 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,002 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
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 ».