Optimization Of Off-Null Ellipsometry For Air/Solid Interfaces

The optimization of off-null ellipsometry is described with emphasis on the improvement of sample thickness sensitivity. Optimal conditions are dependent on azimuth angle settings of the polarizer, compensator, and analyzer in a polarizer-compensator-sample-analyzer ellipsometer arrangement. Numerical simulation utilized offers an approach to present the dependence of the sensitivity on the azimuth angle settings, from which optimal settings corresponding to the best sensitivity are derived. For a series of samples of SiO2 layer (thickness in the range of 1.8-6.5 nm) on silicon substrate, the theory analysis proves that sensitivity at the optimal settings is increased 20 times compared to that at null settings used in most works, and the relationship between intensity and thickness is simplified as a linear type instead of the original nonlinear type, with the relative error reduced to similar to 1/100 at the optimal settings. Furthermore the discussion has been extended toward other factors affecting the sensitivity of the practical system, such as the linear dynamic range of the detector, the signal-to-noise ratio and the intensity from the light source, etc. Experimental results from the investigation Of SiO2 layer on silicon substrate are chosen to verify the optimization. (c) 2007 Optical Society of America.

Optimization of Off-Null Ellipsometry for Optical Biosensor Applications

The optimization of off-null ellipsometry is described with emphasis on the improvement of resolution for visualizing biomolecule layers. For optical biosensor with layer thickness below 6.5 nm, a numerical simulation for the dependence of resolution on the azimuth settings of polarizer and analyzer is presented first. For comparison, three different resolutions are given at three azimuth settings which are near null and far away from null condition, respectively. Furthermore, the square or linear approximation relationship between the intensity and the layer thickness are also given at these settings. The difference among their accuracy is up to 100 times or so. Experimental results of the biosensor sample verify the optimization.

Simulated pathogenic conformational switch regions matched well with the biochemical findings

Pathogenic conformational conversion is a general causation of many disease, such as transmissible spon- giform encephalopathy (TSE) caused by misfolding of prion, sickle cell anemia, and etc. In such structural changes, misfolding occurs in regions important for the stability of native structure firstly. This destabi- lizes the normal conformation and leads to subsequent errors in folding pathway. Sites involved in the first stage can be deemed switch regions of the protein, and are vital for conformational conversion. Namely it could be a switch of disease at residue level. Here we report an algorithm that can identify such sites computationally with an accuracy of 93%, by calculating the probability of the native structure of a short segment jumping to a mistake one. Knowledge of such switch sites could be used to target clinical therapy, study physiological and pathologic mechanism of protein, and etc.

Short and long peptidoglycan recognition proteins (PGRPs) in zebrafish, with findings of multiple PGRP homologs in teleost fish

Peptidoglycan recognition protein (PGRP) specifically binds to peptidoglycan and is considered to be one of the pattern recognition proteins in the innate immunity of insect and mammals. Using a database mining approach and RT-PCR, multiple peptidoglycan recognition protein (PGRP) like genes have been discovered in fish including zebrafish Danio rerio, Japanese pufferfish TakiFugu rubripes and spotted green pufferfish Tetraodon nigroviridis. They share the common features of those PGRPs in arthropod and mammals, by containing a conserved PGRP domain. Based on the predicted structures, the identified zebrafish PGRP homologs resemble short and long PGRP members in arthropod and mammals. The identified PGRP genes in T. nigroviridis and TakiFugu rubripes resemble the long PGRPs, and the short PGRP genes have not been found in T. nigroviridis and TakiFugu rubripes databases. Computer modelling of these molecules revealed the presence of three alpha-helices and five or six beta-strands in all fish PGRPs reported in the present study. The long PGRP in teleost fish have multiple alternatively spliced forms, and some of the identified spliced variants, e.g., tnPGRP-L3 and tnPGRP-L4 (in: Tetraodon nigroviridis), exhibited no characters present in the PGRP homologs domain. The coding regions of zfPGRP6 (zf: zebrafish), zfPGRP2-A, zfPGRP2-B and zfPGRP-L contain five exons and four introns; however, the other PGRP-like genes including zfPGRPSC1a, zfPGRPSC2, tnPGRP-L1-, tnPGRP-L2 and frPGRP-L (fr: Takifugu rubripes) contain four exons and three introns. In zebrafish, long and short PGRP genes identified are located in different chromosomes, and an unknown locus containing another long PGRP-like gene has also been found in zebrafish, demonstrating that multiple PGRP loci may be present in fish. In zebrafish, the constitutive expressions of zfPGRP-L, zfPGRP-6 and zfPGRP-SC during ontogeny from unfertilized eggs to larvae, in different organs of adult, and the inductive expression following stimulation by Flavobacterium columnare, were detected by real-time PCR, but the levels and patterns varied for different PGRP genes, implying that different short and long PGRPs may play different roles in innate immune response. (c) 2007 Elsevier Ltd. All rights reserved.

Inheritance of 15 microsatellites in the Pacific oyster Crassostrea gigas: segregation and null allele identification for linkage analysis

Microsatellites were screened in a backcross family of the Pacific oyster, Crassostrea gigas. Fifteen microsatellite loci were distinguishable and polymorphic with 6 types of allele-combinations. Null alleles were detected in 46.7% of loci, accounting for 11.7% of the total alleles. Four loci did not segregate in Mendelian Ratios. Three linkage groups were identified among 7 of the 15 segregating loci. Fluorescence-based automated capillary electrophoresis (ABI 310 Genetic Analyzer) that used to detect the microsatellite loci, has been proved a fast, precise, and reliable method in microsatellite genotyping.