Improvement of androgenic alopecia by extracellular vesicles secreted from hyaluronic acid-stimulated induced mesenchymal stem cells
Notice bibliographique
Résumé
BACKGROUND: Androgenetic alopecia (AGA) is a common form of hair loss. Androgens, such as testosterone and dihydrotestosterone, are the main causes of AGA. Extracellular vesicles (EVs) derived from mesenchymal stem cells (MSCs) can reduce AGA. However, preparing therapeutic doses of MSCs for clinical use is challenging. Induced pluripotent stem cell-derived MSCs (iMSCs) are homogenous and easily expandable, enabling scalable production of EVs. Hyaluronic acid (HA) can exert various functions including free radical scavenging, immune regulation, and cell migration. Herein, we examined whether hyaluronic acid (HA) stimulation of iMSCs could produce EVs with enhanced therapeutic outcomes for AGA. METHODS: EVs were collected from iMSCs primed with HA (HA-iMSC-EVs) or without HA (iMSC-EVs). The characteristics of EVs were examined using dynamic light scattering, cryo-transmission electron microscopy, immunoblotting, flow cytometry, and proteomic analysis. In vitro, we compared the potential of EVs in stimulating the survival of hair follicle dermal papilla cells undergoing testosterone-mediated AGA. Additionally, the expression of androgen receptor (AR) and relevant growth factors as well as key proteins of Wnt/β-catenin signaling pathway (β-catenin and phosphorylated GSK3β) was analyzed. Subsequently, AGA was induced in male C57/BL6 mice by testosterone administration, followed by repeated injections of iMSC-EVs, HA-iMSC-EVs, finasteride, or vehicle. Several parameters including hair growth, anagen phase ratio, reactivation of Wnt/β-catenin pathway, and AR expression was examined using qPCR, immunoblotting, and immunofluorescence analysis. RESULTS: Both types of EVs showed typical characteristics for EVs, such as size distribution, markers, and surface protein expression. In hair follicle dermal papilla cells, the mRNA levels of AR, TGF-β, and IL-6 increased by testosterone was blocked by HA-iMSC-EVs, which also contributed to the augmented expression of trophic genes related to hair regrowth. However, no notable changes were observed in the iMSC-EVs. Re-activation of Wnt/β-catenin was observed in HA-iMSC-EVs but not in iMSC-EVs, as shown by β-catenin stabilization and an increase in phosphorylated GSK3β. Restoration of hair growth was more significant in HA-iMSC-EVs than in iMSC-EVs, and was comparable to that in mice treated with finasteride. Consistently, the decreased anagen ratio induced by testosterone was reversed by HA-iMSC-EVs, but not by iMSC-EVs. An increased expression of hair follicular β-catenin protein, as well as the reduction of AR was observed in the skin tissue of AGA mice receiving HA-iMSC-EVs, but not in those treated with iMSC-EVs. CONCLUSIONS: Our results suggest that HA-iMSC-EVs have potential to improve AGA by regulating growth factors/cytokines and stimulating AR-related Wnt/β-catenin signaling.
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 ».