Assesment of Analytical Performance of HbA1C Test by Six Sigma Methodology

Background and Objective: The HbA1 c test is a biomarker used to evaluate the long-term outcomes of diabetes, and therefore its role in diabetes management is important Analytical reliability of clinical laboratories may be obtained by Internal Quality Control (IQC), External Quality Control (EQC) etc. by analyzing the data with statistical methods. In six sigma methodology, which is one of these methods, the analytical performance can be evaluated with a single number named "process sigma value". This study aimed to compare the six sigma levels in line with the results of IQC and EQC of HbA1c tests which is one of the most commonly used tests in our laboratory.Material and Methods: IQC and EQC data between May 2015-August 2015 were collected. Monthly process sigma levels were calculated by using formula "(TEa% - Bias%)/CV%. For Bias; values that the firm provided from IQC results and the standard deviation index (SDI) values in EQC reports were used. 6% were basis for the allowed total error values (NGSP).Results: Process sigma level were determined according to IQC1, IQC2 and EQC results by month as May (3.4-8.4-9.6), June (3.9-5.2-4.5), July (5.9-8.4-4.7), August (8.7-8.4-8.2), respectively in 2015.Conclusions: In our study it was observed that HbA1C test is in conformity with the process sigma levels according to IQC and EQC data. HbA1 c test was found to be compatible with internal quality control and external quality control results in accordance with process sigma levels and it was also evaluated as favorable considering our laboratory performance

Modeling Structure and Dynamics of Protein Complexes with SAXS Profiles.

Small-angle X-ray scattering (SAXS) is an increasingly common and useful technique for structural characterization of molecules in solution. A SAXS experiment determines the scattering intensity of a molecule as a function of spatial frequency, termed SAXS profile. SAXS profiles can be utilized in a variety of molecular modeling applications, such as comparing solution and crystal structures, structural characterization of flexible proteins, assembly of multi-protein complexes, and modeling of missing regions in the high-resolution structure. Here, we describe protocols for modeling atomic structures based on SAXS profiles. The first protocol is for comparing solution and crystal structures including modeling of missing regions and determination of the oligomeric state. The second protocol performs multi-state modeling by finding a set of conformations and their weights that fit the SAXS profile starting from a single-input structure. The third protocol is for protein-protein docking based on the SAXS profile of the complex. We describe the underlying software, followed by demonstrating their application on interleukin 33 (IL33) with its primary receptor ST2 and DNA ligase IV-XRCC4 complex