Sensitivity of single-molecule array assays to detect Clostridium difficile toxins in comparison to conventional laboratory testing algorithms.

Guidelines recommend the use of an algorithm for the laboratory diagnosis of Clostridium difficile infection (CDI). Enzyme immunoassays (EIAs) detecting C. difficile toxins cannot be used as standalone tests due to suboptimal sensitivity, and molecular tests suffer from nonspecificity by detecting colonization. Sensitive immunoassays have recently been developed to improve and simplify CDI diagnosis. Assays detecting CD toxins have been developed using single-molecule array (SIMOA) technology. SIMOA performance was assessed relative to a laboratory case definition of CDI defined by positive glutamate dehydrogenase (GDH) screen and cell cytotoxicity neutralizing assay (CCNA). Samples were tested with SIMOA assays and a commercial toxin EIA to compare performance, with discrepancy resolution using a commercial nucleic acid-based test and a second cell cytotoxicity assay. The SIMOA toxin A and toxin B assays showed limits of detection of 0.6 and 2.9 pg/ml, respectively, and intra-assay coefficients of variation of less than 10%. The optimal clinical thresholds for the toxin A and toxin B assays were determined to be 22.1 and 18.8 pg/ml, respectively, with resultant sensitivities of 84.8 and 95.5%. In contrast, a high-performing EIA toxin test had a sensitivity of 71.2%. Thus, the SIMOA assays detected toxins in 24% more samples with laboratory-defined CDI than the high performing toxin EIA (95% [63/66] versus 71% [47/66]). This study shows that SIMOA C. difficile toxin assays have a higher sensitivity than currently available toxin EIA and have the potential to improve CDI diagnosis

Localization of hepatitis B surface antigen epitopes present on variants and specifically recognised by anti-hepatitis B surface antigen monoclonal antibodies

Small hepatitis B surface antigen (HBsAg) is considered to be the best marker for the diagnosis of Hepatitis B virus infection. However, HBsAg variants with mutations within the "a" determinant may be poorly or not detected by diagnostic assays. Three anti-HBsAg monoclonal antibodies (6H6B6, 27E7F10, and 2G2G10), directed against conformational epitopes, were tested for their ability to detect the wild-type HBsAg as well as variant forms and their respective epitopes were localised on the HBsAg sequence by using the phage-displayed peptide library technology. Whereas 6H6B6 did not detect mutations T123N, S143L, D144A and G145R, 27E7F10 binding was affected by mutations P120T and G145R. In contrast, 2G2G10 reacted strongly with all tested variants including variant with the G145R mutation. Part of the 6H6B6 epitope was located in the major hydrophilic region (MHR) at residues 101-105, the 27E7F10 epitope (residues 214-219) was located near the C-terminal end of the antigen and the 2G2G10 epitope at residues 199-208, within the theoretical fourth transmembrane helix. The 2G2G10 epitope localisation brings information about the HBsAg structure and the validity of established topological models. Finally, 2G2G10 is a valuable tool for HBsAg variant detection that is used as capture phase in a new bioMérieux diagnostic assay, which is currently in development

Critical failure OPC: Improving model accuracy through enhanced model generation

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Critical failure ORC: Improving model accuracy through enhanced model generation

Ensuring robust patterning after OPC is becoming more and more difficult due to the continuous reduction of layout dimensions and diminishing process windows associated with each successive lithographic generation. Lithographers must guarantee high imaging fidelity throughout the entire range of normal process variations. As a result, post-OPC verification methods have become indispensable tools for avoiding pattern printing issues. A post-OPC verification technique known as critical failure optical rule checking (CFORC) was recently introduced and has proven its efficiency for detecting potential printing issues through the entire process window [S.D. Shang et al., Proc. SPIE 5040 (2003); J. Belledent et al., Proc. SPIE 5377 (2004); A. previous termBorjonnext term et al., Proc. SPIE 5754 (2005)]. This methodology uses optical parameters from aerial image simulations at single process condition. A numerical model, build using support vector machine (SVM) principle [The Nature of Statistical Learning Theory, second ed., Springer, (1995)], correlates these optical parameters with experimental data taken throughout the process window to predict printing failures. This statistical method however leads to some false predictions. Although false predictions may be unavoidable in statistical methodologies, it is possible to lower their rate of occurrence. In this study, concentrated on contact layer patterning for the 90 nm node and the poly layer patterning for the 65 nm node, the accuracy of CFORC models is improved through several approaches: enhancing the normalization algorithm, optimization of fitting parameters and optimizing the parameter space coverage

Impact of modelisation pixel size on OPC consistency

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Analysis of the diffraction pattern for optimal assist feature placement

International audienceAssist features (AF) are an essential component of reticle enhancement techniques. Their use is indispensable in sub-100 nm technologies to ensure a maximum process window (PW) across chip, especially for critical levels. Indeed, AF, which can be binary, attenuated or phase-shifted, help in providing a larger PW to the features they assist when they are used in conjunction with off-axis illumination. The depth of focus (DOF) of an isolated structure is improved by the presence of AF by providing to the optical system a diffraction pattern close to the diffraction pattern of a dense structure. The resulting DOF and exposure latitude (EL) are dependent on the relative position of the AF from the main feature. Moreover, the PW varies while inserting one, two or more AF. The relative position of each influences the results. In this paper, a method will be detailed to optimise the placement of the AF. For the purpose of this study, the diffraction pattern induced by the insertion of one or several AF is analysed in frequency space. This analysis details the evolution of the intensity of even and odd orders during the insertion of AF. The calculation of the optimum placement is detailed, and the DOF resulting from the insertion of one or more AF is also presented