کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5760512 1623996 2017 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A new data-driven model for post-transplant antibody dynamics in high risk kidney transplantation
ترجمه فارسی عنوان
یک مدل داده مبتنی بر داده ها برای پویایی آنتی بادی پس از پیوند در پیوند کلیه با ریسک بالا
کلمات کلیدی
پیوند کلیه، دینامیک آنتیبادی، معادلات دیفرانسیل معمولی، مدل داده رانده شده، مقدار خاص، استنتاج بیزی گری اختیاری،
موضوعات مرتبط
علوم زیستی و بیوفناوری علوم کشاورزی و بیولوژیک علوم کشاورزی و بیولوژیک (عمومی)
چکیده انگلیسی
The dynamics of donor specific human leukocyte antigen antibodies during early stage after kidney transplantation are of great clinical interest as these antibodies are considered to be associated with short and long term clinical outcomes. The limited number of antibody time series and their diverse patterns have made the task of modelling difficult. Focusing on one typical post-transplant dynamic pattern with rapid falls and stable settling levels, a novel data-driven model has been developed for the first time. A variational Bayesian inference method has been applied to select the best model and learn its parameters for 39 time series from two groups of graft recipients, i.e. patients with and without acute antibody-mediated rejection (AMR) episodes. Linear and nonlinear dynamic models of different order were attempted to fit the time series, and the third order linear model provided the best description of the common features in both groups. Both deterministic and stochastic parameters are found to be significantly different in the AMR and no-AMR groups showing that the time series in the AMR group have significantly higher frequency of oscillations and faster dissipation rates. This research may potentially lead to better understanding of the immunological mechanisms involved in kidney transplantation.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Mathematical Biosciences - Volume 284, February 2017, Pages 3-11
نویسندگان
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