tailieunhanh - Báo cáo y học: " Variance in multiplex suspension array assays: A distribution generation machine for multiplex counts"

Tuyển tập các báo cáo nghiên cứu về y học được đăng trên tạp chí y học quốc tế cung cấp cho các bạn kiến thức về ngành y đề tài: " Variance in multiplex suspension array assays: A distribution generation machine for multiplex counts | Theoretical Biology and Medical Modelling BioMed Central Research Variance in multiplex suspension array assays A distribution generation machine for multiplex counts Brian P Hanley1 2 Open Access Address Microbiology Graduate Group University of California Davis CA 95616 USA and 2BW Education and Forensics 2710 Thomes Avenue Cheyenne Wyoming 82001 USA Email Brian P Hanley - bphanley@ Published 28 January 2008 Received 13 December 2007 Theoretical Biology and Medical Modelling 2008 5 3 doi 1742-4682-5-3 Accepted 28 January 2008 This article is available from http content 5 1 3 2008 Hanley licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License http licenses by which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. Abstract Background This study attempted to replicate Luminex experimental results for large numbers of beads per classifier using multiplexed assays and routine instrument use conditions. Conclusion Using larger numbers of microspheres per classifier highlights a fundamental stochastic distribution of bead counts issue complicated by other factors. The more classifiers and the higher the count required per classifier there are the more apparent the distribution of counts per classifier will be and the more microspheres are required. Additional problems have been identified. Alternate methods of improving precision and reliability are recommended such as intraplexing and multi-well sample replicates to improve precision and confidence. Background In a study by Jacobson et al. 1 up to 1000 microspheres were acquired for a single classifier. Those results showed improved confidence intervals and more reliable mean values for 1000 microspheres. The current study attempted to replicate .