In vitro oxygen imaging of acellular and cell-loaded beta cell replacement devices
Notice bibliographique
Résumé
Abstract Type 1 diabetes (T1D) is an autoimmune disease that leads to the loss of insulin-producing beta cells. Bioartificial pancreas (BAP) or beta cell replacement strategies have shown promise in curing T1D and providing long-term insulin independence. Hypoxia (low oxygen concentration) that may occur in the BAP devices due to cell oxygen consumption at the early stages after implantation damages the cells, in addition to imposing limitations to device dimensions when translating promising results from rodents to humans. Finding ways to provide cells with sufficient oxygenation remains the major challenge in realizing BAP devices’ full potential. Therefore, in vitro oxygen imaging assessment of BAP devices is crucial for predicting the devices’ in vivo efficiency. Electron paramagnetic resonance oxygen imaging (EPROI, also known as electron MRI or eMRI) is a unique imaging technique that delivers absolute partial pressure of oxygen (pO2) maps and has been used for cancer hypoxia research for decades. However, its applicability for assessing BAP devices has not been explored. EPROI utilizes low magnetic fields in the mT range, static gradients, and the linear relationship between the spin–lattice relaxation rate (R1) of oxygen-sensitive spin probes such as trityl OX071 and pO2 to generate oxygen maps in tissues. With the support of the Juvenile Diabetes Research Foundation (JDRF), an academic-industry partnership consortium, the “Oxygen Measurement Core” was established at O2M to perform oxygen imaging assessment of BAP devices originated from core members’ laboratories. This article aims to establish the protocols and demonstrate a few examples of in vitro oxygen imaging of BAP devices using EPROI. All pO2 measurements were performed using a recently introduced 720 MHz/25 mT preclinical oxygen imager instrument, JIVA-25™. We began by performing pO2 calibration of the biomaterials used in BAPs at 25 mT magnetic field since no such data exist. We compared the EPROI pO2 measurement with a single-point probe for a few selected materials. We also performed trityl OX071 toxicity studies with fibroblasts, as well as insulin-producing cells (beta TC6, MIN6, and human islet cells). Finally, we performed proof-of-concept in vitro pO2 imaging of five BAP devices that varied in size, shape, and biomaterials. We demonstrated that EPROI is compatible with commonly used biomaterials and that trityl OX071 is nontoxic to cells. A comparison of the EPROI with a fluorescent-based point oxygen probe in selected biomaterials showed higher accuracy of EPROI. The imaging of typically heterogenous BAP devices demonstrated the utility of obtaining oxygen maps over single-point measurements. In summary, we present EPROI as a quality control tool for developing efficient cell transplantation devices and artificial tissue grafts. Although the focus of this work is encapsulation systems for diabetes, the techniques developed in this project are easily transferable to other biomaterials, tissue grafts, and cell therapy devices used in the field of tissue engineering and regenerative medicine (TERM). In summary, EPROI is a unique noninvasive tool to experimentally study oxygen distribution in cell transplantation devices and artificial tissues, which can revolutionize the treatment of degenerative diseases like T1D.
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 ».