Synthesis and Expression in Escherichia coli of a Human Neutrophil Activating Protein-1/Interleukin-8 Gene

The complete gene coding for human neutrophilactivating protein-1/interleukin-8 was synthesized using a semi-chemical semi-enzymatic method. The synthetic gene was then overexpressed in Escherichia coli under the temperature-regulated control of the P_RP_L tandem promoters. As determined by SDS-PAGE and densitometry, the overexpressed protein comprised up to 18.5% and 10.9% of the total soluble protein in E. coli cells grown in shake flasks and in batch fermentation, respectively. The recombinant NAP-1/IL-8 was then purified to>95% homogeneity by gel filtration and cation exchange chromatography. The purified protein appeared as a single band on the SDS-PAGE gel and possessed potent chemotactic activity in the concentration of <10 ng/ml, as assayed by the agarose plate method. An early skin reactivity was also observed when the pure NAP-1/IL-8 was injected subcutaneously into the rabbits. The N-terminal 36 amino acid sequence of the recombinant NAP1/IL-8 was determined using the Edman method and was sho     

QUANTITATIVE EXPLANATION ON STRUCTURE-CARCINOGENIC ACTIVITY RELATIONSHIP OF AROMATIC AMINES BY DI-REGION THEORY

Di-region theory, the theory for the mechanism of carcinogenesis, has been extendedsuccessfully on the quantitative Structure-carcinogenic activity relationship (QSCAR) of 63aromatic amines. A quantitative equation for the QSCAR of aromatic amines has been estab-lished by the mechanism conception of the specialized di- functional alkylation between thenitrenium ion of the amino group and the epoxide of the aromatic ring. The agreementbetween calculation and experiment comes up to 98%. Thus, it can now express the puzzlingvariation of the carcinogenicity of aromatic amines, as a comprehensible structure-chemicalreactivity relationship.     

Bipartite network analysis reveals metabolic gene expression profiles that are highly associated with the clinical outcomes of acute myeloid leukemia

Dysregulated and reprogrammed metabolism are one of the most important characteristics of cancer, and exploiting cancer cell metabolism can aid in understanding the diverse clinical outcomes for patients. To investigate the differences in metabolic pathways among patients with acute myeloid leukemia (AML) and differential survival outcomes, we systematically conducted microarray data analysis of the metabolic gene expression profiles from 384 patients available from the Gene Expression Omnibus and Cancer Genome Atlas databases. Pathway enrichment analysis of differentially expressed genes (DEGs) showed that the metabolic differences between low-risk and high-risk patients mainly existed in two pathways: biosynthesis of unsaturated fatty acids and oxidative phosphorylation. Using the gene-pathway bipartite network, 62 metabolic genes were identified from 272 DEGs involved in 88 metabolic pathways. Based on the expression patterns of the 62 genes, patients with shorter overall survival (OS) durations in the training set (hazard ratio (HR) = 1.58, p = 0.038) and in two test sets (HR = 1.69 and 1.56 and p = 0.089 and 0.029, respectively) were well discriminated by hierarchical clustering analysis. Notably, the expression profiles of ALAS2, BCAT1, BLVRB, and HK3 showed distinct differences between the low-risk and high-risk patients. In addition, models for predicting the OS outcome of AML from the 62 gene signatures achieved improved performance compared with previous studies. In conclusion, our findings reveal significant differences in metabolic processes of patients with AML with diverse survival durations and provide valuable information for clinical translation.     

DEVELOPMENT AND IDENTIFICATION OF CHINESE SPRING Ta1 kr ph1b PLANTS AND THEIR USE ON GENETIC TRANSFER OF DESIRABLE GENES FROM Aegilops

Chinese Spring Tal kr phlb plants were developed by hybridizing Tal common wheat and Chinese Spring phlb mutant and backcrosses. When Chinese Spring Tal kr phlb plants were crossed with some wild species of Triticeae, much more seeds of wide hybridization can be obtained without artificial emasculation and pollination because of the existence of Tat and kr genes. The homoeologous chromosomes between common wheat and the wild species of Triticeae can also pair and exhibit cross-over in the hybrid F1 plants because of the existence of the phlb gene. So that more alien desirable genes can be transferred to common wheat rapidly. Therefore, Chinese Spring Tal kr phlb plants become a powerful tool for wide hybridization and transferring alien desirable genes to common wheat.     

A new method for resolving combinatorial ambiguities at hadron colliders

We present a new method for resolving combinatorial ambiguities that arise in multi-particle decay chains at hadron colliders where the assignment of visible particles to the different decay chains has ambiguities. Our method, based on selection cuts favoring high transverse momentum and low invariant mass pairings, is shown to be significantly superior to the more traditional hemisphere method for a large class of decay chains, producing an increase in signal retention of up to a factor of 2. This new method can thus greatly reduce the combinatorial ambiguities of decay chain assignments.     

Selective alterations of the antibody response to HIV-1

HIV infection leads to progressive alterations of humoral immune functions, including B-cell hyperplasia, hypergammaglobulinemia, elevated autoantibody titers, a poor response to neoantigens and mitogens, polyclonal B-cell activation, monoclonal gammopathies, and a significant deterioration of the antigen-specific humoral response. There is also an important isotypic imbalance of the antibody (Ab) response in the systemic compartment and a profound modification of mucosal immune functions. These abnormalities may contribute to disease progression and development of opportunistic infections, despite the presence of serum-neutralizing anti-HIV Abs. Equally important are the abnormal selection mechanisms of the Ab repertoire that seem to be responsible for B-cell clonal deletions. The V_H3 gene family, which encodes for approx 50% of immunoglobulins expressed by peripheral B-cells from normal adults, is underrepresented in human monoclonal antibodies to HIV-1 and in the peripheral B-cells of AIDS patients. These abnormalities, together with features of germinal center alteration, could be responsible for the clonal elimination of a subset of B-cells, and could contribute to HIV pathogenesis.     

Missing value imputation strategies for metabolomics data

The origin of missing values can be caused by different reasons and depending on these origins missing values should be considered differently and dealt with in different ways. In this research, four methods of imputation have been compared with respect to revealing their effects on the normality and variance of data, on statistical significance and on the approximation of a suitable threshold to accept missing data as truly missing. Additionally, the effects of different strategies for controlling familywise error rate or false discovery and how they work with the different strategies for missing value imputation have been evaluated. Missing values were found to affect normality and variance of data and k‐means nearest neighbour imputation was the best method tested for restoring this. Bonferroni correction was the best method for maximizing true positives and minimizing false positives and it was observed that as low as 40% missing data could be truly missing. The range between 40 and 70% missing values was defined as a “gray area” and therefore a strategy has been proposed that provides a balance between the optimal imputation strategy that was k‐means nearest neighbor and the best approximation of positioning real zeros.     

Differentially expressed genes selection via Laplacian regularized low-rank representation method

With the rapid development of DNA microarray technology and next-generation technology, a large number of genomic data were generated. So how to extract more differentially expressed genes from genomic data has become a matter of urgency. Because Low-Rank Representation (LRR) has the high performance in studying low-dimensional subspace structures, it has attracted a chunk of attention in recent years. However, it does not take into consideration the intrinsic geometric structures in data.In this paper, a new method named Laplacian regularized Low-Rank Representation (LLRR) has been proposed and applied on genomic data, which introduces graph regularization into LRR. By taking full advantages of the graph regularization, LLRR method can capture the intrinsic non-linear geometric information among the data. The LLRR method can decomposes the observation matrix of genomic data into a low rank matrix and a sparse matrix through solving an optimization problem. Because the significant genes can be considered as sparse signals, the differentially expressed genes are viewed as the sparse perturbation signals. Therefore, the differentially expressed genes can be selected according to the sparse matrix. Finally, we use the GO tool to analyze the selected genes and compare the P-values with other methods.The results on the simulation data and two real genomic data illustrate that this method outperforms some other methods: in differentially expressed gene selection.