Identification of normalization factors for quantitative realtime RT-PCR analysis of gene expression in Pacific abalone Haliotis discus hannai

Quantitative real-time reverse transcription-polymerase chain reaction （qRT-PCR） is widely used in studies of gene expression. In most of these studies, housekeeping genes are used as internal references without validation. To identify appropriate reference genes for qRT-PCR in Pacific abalone Haliotis discus hannai, we examined the transcription stability of six housekeeping genes in abalone tissues in the presence and absence of bacterial infection. For this purpose, abalone were infected with the bacterial pathogen Fibrio anguillarum for 12 h and 48 h. The mRNA levels of the housekeeping genes in five tissues （digestive glands, foot muscle, gill, hemocyte, and mantle） were determined by qRT-PCR. The PCR data was subsequently analyzed with the geNorm and NormFinder algorithms. The results show that in the absence of bacterial infection, elongation factor-l-alpha and beta-actin were the most stably expressed genes in all tissues, and thus are suitable as cross-tissue type normalization factors. However, we did not identify any universal reference genes post infection because the most stable genes varied between tissue types. Furthermore, for most tissues, the optimal reference genes identified by both algorithms at 12 h and 48 h post-infection differed. These results indicate that bacterial infection induced significant changes in the expression of abalone housekeeping genes in a manner that is dependent on tissue type and duration of infection. As a result, different normalization factors must be used for different tissues at different infection points.

Role of Soluble Factors in Immune and Normal Sera in the Control of Giardiasis Due to Giardia Iamblia

Hyperimmune sera (HIS), raised against crude giardia antigen, on in vitro interaction, caused more agglutination of Giardia lamblia trophozoites. Heat inactivated HIS possessed a comparable agglutinating activity as the non-inactivated controls. Non-inactivated normal (unimmunized) serum caused immobilization of Giardia trophozoite, which was checked on heat inactivation. Antibodies in immune sera are mainly responsible for agglutination, whereas the heat labile non-immune components control the mobility of the intestinal parasite.

Selection of reference genes for qRT-PCR analysis of gene expression in sea cucumber Apostichopus japonicus during aestivation

Quantitative real-time reverse transcription-polymerase chain reaction （qRT-PCR） is a technique that is widely used for gene expression analysis, and its accuracy depends on the expression stability of the internal reference genes used as normalization factors. However, many applications of qRT-PCR used housekeeping genes as internal controls without validation. In this study, the expression stability of eight candidate reference genes in three tissues （intestine, respiratory tree, and muscle） of the sea cucumber Apostichopus japonicus was assessed during normal growth and aestivation using the geNorm, NormFinder, delta CT, and RefFinder algorithms. The results indicate that the reference genes exhibited significantly different expression patterns among the three tissues during aestivation. In general, the β-tubulin （TUBB） gene was relatively stable in the intestine and respiratory tree tissues. The optimal reference gene combination for intestine was 40S ribosomal protein S18 （RPSI 8）, TUBB, and NADH dehydrogenase （NADH）; for respiratory tree, it was β-actin （ACTB）, TUBB, and succinate dehydrogenase cytochrome B small subunit （SDHC）; and for muscle it was α-tubulin （TUBA） and NADH dehydrogenase [ubiquinone] 1α subcomplex subunit 13 （NDUFA13）. These combinations of internal control genes should be considered for use in further studies of gene expression in A.japonicus during aestivation.

A novel algorithm of adaptive IIR lattice notch filter and performance analysis

A novel adaptive algorithm of IIR lattice notch filter realized by all-pass filter is presented. The time-averaged estimation of cross correlation of the present instantaneous input signal and the past output signal is used to update the step-size, leading to a considerably improved convergence rate in a low SNR situation and reduced steady-state bias and MSE. The theoretical expression for steady-state bounds on the step-size is derived, and the influence factors on the stable performance of the algorithm theoretically are analyzed. A normalized power factor is then introduced to control variation of step-size in its steady-state bounds. This technique prevents divergence due to the influence of large power input signal and improves robustness. Numerical experiments are performed to demonstrate superiority of the proposed method.

Normalization strategy of microarray gene expression data

Objective： To discuss strategies and methods of normalization on how to deal with and analyze data for different chips with the combination of statistics, mathematics and bioinformatics in order to find significant difference genes. Methods： With Excel and SPSS software, high or low density chips were analyzed through total intensity normalization （TIN） and locally weighted linear regression normalization （LWLRN）. Results： These methods effectively reduced systemic errors and made data more comparable and reliable. Conclusion： These methods can search the genes of significant difference, although normalization methods are being developed and need to be improved further. Great breakthrough will be obtained in microarray data normalization analysis and transformation with the development of non-linear technology, software and hardware of computer.

L-two-optimal identification of errors-in-variables models:a frequency-domain approach

This paper proposes an L-two-optimal identification approach to cope with errors-in-variables model （EIVM） identification. With normalized coprime factor model （NCFM） representations, L-two-optimal approximate models are derived from the framework of an EIVM according to the kernel and image representations of related signals. Based on the optimal approximate models, the v-gap metric is employed as a minimization criterion to optimize the parameters of a system model, and thus the resulting optimization problem can be solved by linear matrix inequalities （LMIs）. In terms of the optimized system model, the noise model （NM） can be readily obtained by right multiplication of an inner. Compared with other EIVM identification methods, the proposed one has a wider scope of applications because the statistical properties of disturbing noises are not demanded. It is also capable of giving identifiabiUty. Finally, a numerical simulation is used to verify the effectiveness of the proposed method.

NUMERICAL ANALYSIS OF WATER SURFACE PROFILE IN RIVER AFFECTED BY TIDE FLUCTUATION

A Finite Difference Method with four points weighted implicit scheme and Newton-Raphson iteration method are introduced to complete the flood routing in the tidal river. The problems related to normalization of cross-sectional area and optimization of weighting factor α are discussed and α = 0. 5 - 0. 7 is suggested. With such a α, high accuracy, stable and convergence results and flexible time step will be expected. The computational example of a tidal river in Liaoning Province shows the good agreement with the measuring data on prototype.