کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
7233832 | 1470981 | 2013 | 8 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Non-invasive measurement of glucose uptake of skeletal muscle tissue models using a glucose nanobiosensor
ترجمه فارسی عنوان
اندازه گیری غیر تهاجمی از جذب گلوکز از مدل های بافت ماهیچه اسکلتی با استفاده از نانوبوسنسور گلوکز
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کلمات کلیدی
دیابت نانو بوسنسور گلوکز، بافت عضلانی اسکلتی مهندسی، جذب گلوکز، تحریک الکتریکی،
موضوعات مرتبط
مهندسی و علوم پایه
شیمی
شیمی آنالیزی یا شیمی تجزیه
چکیده انگلیسی
Skeletal muscle tissues play a significant role to maintain the glucose level of whole body and any dysfunction of this tissue leads to the diabetes disease. A culture medium was created in which the muscle cells could survive for a long time and meanwhile it did not interfere with the glucose sensing. We fabricated a model of skeletal muscle tissues in vitro to monitor its glucose uptake. A nanoporous gold as a high sensitive nanobiosensor was then successfully developed and employed to detect the glucose uptake of the tissue models in this medium upon applying the electrical stimulation in a rapid, and non-invasive approach. The response of the glucose sensor was linear in a wide concentration range of 1-50 mM, with a detection limit of 3 μM at a signal-to-noise ratio of 3.0. The skeletal muscle tissue was electrically stimulated during 24 h and glucose uptake was monitored during this period. During the first 3 h of stimulation, electrically stimulated muscle tissue consumed almost twice the amount of glucose than counterpart non-stimulated sample. In total, the glucose consumption of muscle tissues was higher for the electrically stimulated tissues compared to those without applying the electrical field.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Biosensors and Bioelectronics - Volume 50, 15 December 2013, Pages 194-201
Journal: Biosensors and Bioelectronics - Volume 50, 15 December 2013, Pages 194-201
نویسندگان
Raquel Obregón, Samad Ahadian, Javier Ramón-Azcón, Luyang Chen, Takeshi Fujita, Hitoshi Shiku, Mingwei Chen, Tomokazu Matsue,