کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
5827330 | 1558922 | 2015 | 8 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
The utility of animal models in developing immunosuppressive agents
ترجمه فارسی عنوان
استفاده از مدل های حیوانی در پیشگیری از عوامل سرکوب کننده ایمنی
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کلمات کلیدی
سوء هاضمه ی ایمنی، مدل حیوانی، پیوند ایمونولوژی، دارو،
موضوعات مرتبط
علوم زیستی و بیوفناوری
علم عصب شناسی
علوم اعصاب سلولی و مولکولی
چکیده انگلیسی
The immune system comprises an integrated network of cellular interactions. Some responses are predictable, while others are more stochastic. While in vitro the outcome of stimulating a single type of cell may be stereotyped and reproducible, in vivo this is often not the case. This phenomenon often merits the use of animal models in predicting the impact of immunosuppressant drugs. A heavy burden of responsibility lies on the shoulders of the investigator when using animal models to study immunosuppressive agents. The principles of the three R׳s: refine (less suffering,), reduce (lower animal numbers) and replace (alternative in vitro assays) must be applied, as described elsewhere in this issue. Well designed animal model experiments have allowed us to develop all the immunosuppressive agents currently available for treating autoimmune disease and transplant recipients. In this review, we examine the common animal models used in developing immunosuppressive agents, focusing on drugs used in transplant surgery. Autoimmune diseases, such as multiple sclerosis, are covered elsewhere in this issue. We look at the utility and limitations of small and large animal models in measuring potency and toxicity of immunosuppressive therapies.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: European Journal of Pharmacology - Volume 759, 15 July 2015, Pages 295-302
Journal: European Journal of Pharmacology - Volume 759, 15 July 2015, Pages 295-302
نویسندگان
James McDaid, Christopher J. Scott, Adrien Kissenpfennig, Huifang Chen, Paulo N. Martins,