دورية أكاديمية

Automated, High-Throughput Assays for Evaluation of Human Pancreatic Islet Function

التفاصيل البيبلوغرافية
العنوان: Automated, High-Throughput Assays for Evaluation of Human Pancreatic Islet Function
المؤلفون: Cabrera, Over, Jacques-Silva, M. Caroline, Berman, Dora M., Fachado, Alberto, Echeverri, Felipe, Poo, Ramon, Khan, Aisha, Kenyon, Norma S., Ricordi, Camillo, Berggren, Per-Olof, Caicedo, Alejandro
المصدر: Cell Transplantation ; volume 16, issue 10, page 1039-1048 ; ISSN 0963-6897 1555-3892
بيانات النشر: SAGE Publications
سنة النشر: 2007
مصطلحات موضوعية: Transplantation, Cell Biology, Biomedical Engineering
الوصف: An important challenge in pancreatic islet transplantation in association with type 1 diabetes is to define automatic high-throughput assays for evaluation of human islet function. The physiological techniques presently used are amenable to small-scale experimental samples and produce descriptive results. The postgenomic era provides an opportunity to analyze biological processes on a larger scale, but the transition to high-throughput technologies is still a challenge. As a first step to implement high-throughput assays for the study of human islet function, we have developed two methodologies: multiple automated perifusion to determine islet hormone secretion and high-throughput kinetic imaging to examine islet cellular responses. Both technologies use fully automated devices that allow performing simultaneous experiments on multiple islet preparations. Our results illustrate that these technologies can be applied to study the functional status and explore the pharmacological profiles of islet cells. These methodologies will enable functional characterization of human islet preparations before transplantation and thereby provide the basis for the establishment of predictive tests for β-cell potency.
نوع الوثيقة: article in journal/newspaper
اللغة: English
DOI: 10.3727/000000007783472408
الإتاحة: https://doi.org/10.3727/000000007783472408Test
حقوق: http://journals.sagepub.com/page/policies/text-and-data-mining-licenseTest
رقم الانضمام: edsbas.21ED6B71
قاعدة البيانات: BASE