O-005 Mesenchymal stem cell-derived extracellular vesicles as a coiling adjunct to improve intracranial aneurysmal healing in a rabbit model
Notice bibliographique
Résumé
Background Although endovascular coiling has become a standard of care for treatment of intracranial aneurysms, up to 30% of treated aneurysms will recur. Using mesenchymal stem cells (MSCs) as an adjunctive therapy can potentially improve aneurysm healing, but the injection of cells may be impractical for routine use. Moreover, increasing evidence has found that the therapeutic effects of MSCs may be due to their release of a heterogeneous population of lipid membrane-bound nanoparticles called extracellular vesicles (EVs). Similar to MSCs, EVs can also localize to areas of inflammation, but have many advantages over a cell-based therapy including a better safety profile, reduced immunogenicity, and simplified production and storage. (Yuana et al., 2013, Bang&Kim 2019; Natasha et al., 2014, Gonzalez-Gonzalez et al., 2020) The purpose of this study, therefore, was to determine the effect of MSC-derived EVs in an in vivo aneurysm model. Methods Aneurysms were created as previously described in two female New Zealand White rabbits (Belanger et al., 2021). Four weeks after creation, animals underwent digital subtraction angiography (DSA) to determine aneurysm size and patency. After the deployment of one to two framing coils in the aneurysm to stagnate flow, EVs from 6x107 adipose-derived MSCs were injected directly into the aneurysm sac using the same SL-10 catheter. Aneurysms were then coiled to completion with a goal packing density between 20% and 30%. Ninety days later, animals were sacrificed for histological processing and were compared to historical controls (Herting et al., 2019) in terms of aneurysm size, coil length per aneurysm, packing density, neointimal thickness, and histological healing score (Dai et al., 2006). Results For the experimental group, aneurysm size, coil length per aneurysm volume, and packing density were 61.78 mm3±22.11, 0.52 cm/mm3±0.036, and 26.24%±1.75 while Herting et al. reported 119.3 mm3±114.9, 0.417 cm/mm3±0.18, and 24.3%±7.8, respectively (mean±SD). There was no significant differences in these metrics between the two groups (p=0.53, 0.76, 0.50, respectively (Student’s T-test)). Comparison of neointimal thickness between the experimental group and historical controls was also not significantly different (0.03um±0.029 vs. 0.03um±0.01, p=0.99 (Student’s T-test)), although histological healing score was significantly higher in the experimental group (11.5±2.12 vs. 4.5±2.4, p=0.02) (figure 1). Conclusions MSC-derived EVs as an adjunct to endovascular coiling may improve the histological healing scores of aneurysms, potentially reducing the risk of aneurysm recurrence after endovascular coiling. Additional studies are needed to more rigorously investigate this effect. Disclosures B. Belanger: 1; C; NSERC Brain CREATE Program. J. Phelps: None. A. Bromley: None. A. Sen: 1; C; Natural Sciences and Engineering Research Council of Canada (NSERC), Office of the Vice President (Research), University of Calgary. A. Mitha: 1; C; Stryker Neurovascular, Fluid Biomedical. 2; C; Cerus Endovascular. 4; C; Fluid Biomedical.
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) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| 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 ».