Effects of glutenin and gliadin on the surface tackiness of frozen cooked noodles.

The mechanism of glutenin and gliadin on the surface tackiness of recooked frozen cooked noodles (FCNs) is unclear. In this study, the effects of glutenin and gliadin addition on the surface tackiness of FCNs were investigated. The addition of glutenin and gliadin reduced the surface tackiness (3.60 and 3.50 N) of recooked FCNs stored for 0 min. The addition of glutenin increased the rigidity of the gluten network and the compactness of FCNs and made the FCNs have a moisture-distribution with multilayers. The addition of gliadin increased the tensile distance of FCNs, restricted water migration during frozen storage, and increased the membranous structure of the gluten network to wrap starch particles. Glutenin had a stronger effect on reducing the surface tackiness of FCNs than gliadin. In the future, the synergistic effects of different proportions of glutenin and gliadin on the gluten network of FCNs could be further studied.

Moderate Dose Irradiation Induces DNA Damage and Impairments of Barrier and Host Defense in Nasal Epithelial Cells in vitro.

Purpose: Radiotherapy (RT) is the mainstay treatment for head and neck cancers. However, chronic and recurrent upper respiratory tract infections and inflammation have been commonly reported in patients post-RT. The underlying mechanisms remain poorly understood. Method and Materials: We used a well-established model of human nasal epithelial cells (hNECs) that forms a pseudostratified layer in the air-liquid interface (ALI) and exposed it to single or repeated moderate dose γ-irradiation (1Gy). We assessed the DNA damage and evaluated the biological properties of hNECs at different time points post-RT. Further, we explored the host immunity alterations in irradiated hNECs with polyinosinic-polycytidylic acid sodium salt (poly [I:C]) and lipopolysaccharides (LPS). Results: IR induced DNA double strand breaks (DSBs) and triggered DNA damage response in hNECs. Repeated IR significantly reduced basal cell proliferation with low expression of p63/KRT5 and Ki67, induced cilia loss and inhibited mucus secretion. In addition, IR decreased ZO-1 expression and caused a significant decline in the transepithelial electrical resistance (TEER). Moreover, hyperreactive response against pathogen invasion and disrupted epithelial host defense can be observed in hNECs exposed to repeated IR. Conclusion: Our study suggests that IR induced prolonged structural and functional impairments of hNECs may contribute to patients post-RT with increased risk of developing chronic and recurrent upper respiratory tract infection and inflammation.

Optimal convex combination bounds of geometric and Neuman means for Toader-type mean.

In this paper, we prove that the double inequalities [Formula: see text] hold for all [Formula: see text] with [Formula: see text] if and only if [Formula: see text], [Formula: see text] , [Formula: see text] and [Formula: see text] , where [Formula: see text], [Formula: see text], [Formula: see text] and [Formula: see text], [Formula: see text] are the Toader, geometric, arithmetic and two Neuman means of a and b, respectively.

[Association between ion channel subtype and its gene co-expression].

Association between ion channel functional subtype and its genes expression is important for exploring function of ion channel, annotating function of an unknown subtype and probing into molecular mechanism of ion channel diseases. In this study, we began with noise reduction by standardizing original micro-array data, which consisted of human and mouse gene expression profiles, and then we employed principle component analysis (PCA) together with fuzzy C-mean clustering algorithm to analyze the pre-processed gene expression profiles. PCA is applied to rebuild the feature space of human gene in 21 dimensions as well as the feature space of mouse gene in 26 dimensions. Using this method we largely reduced computational complexity without losing much information involved in the original data. Subsequently, fuzzy C-mean clustering was used to classify the ion channel genes of human and mouse in their reduced feature space. In the end, four ion channel functional subtypes, such as potassium ion channels, calcium ion channel, chloride ion channel, and receptor-mediated ion channel were clustered in both human and mouse gene feature space. We applied two statistic ways to conduct significance test of the findings. In one way, we randomly sampled the data for each functional subtype of the ion channel genes and recorded the true positive rate. As a result, in both human and mouse gene feature spaces, genes that belong to one functional subtype were more likely to be clustered together than expected by chance. In the other way, we performed Kappa test and used the functional subtypes as gold standard. The result showed that consistency between the ion channel gene clusters and the ion channel gene subtypes was significantly high for both human and mouse. These results indicate that ion channel genes within the same functional subtype tend to be co-expressed at least at the mRNA-level.

Familial aggregation analysis of gene expressions.

Traditional studies of familial aggregation are aimed at defining the genetic (and non-genetic) causes of a disease from physiological or clinical traits. However, there has been little attempt to use genome-wide gene expressions, the direct phenotypic measures of genes, as the traits to investigate several extended issues regarding the distributions of familially aggregated genes on chromosomes or in functions. In this study we conducted a genome-wide familial aggregation analysis by using the in vitro cell gene expressions of 3300 human autosome genes (Problem 1 data provided to Genetic Analysis Workshop 15) in order to answer three basic genetics questions. First, we investigated how gene expressions aggregate among different types (degrees) of relative pairs. Second, we conducted a bioinformatics analysis of highly familially aggregated genes to see how they are distributed on chromosomes. Third, we performed a gene ontology enrichment test of familially aggregated genes to find evidence to support their functional consensus. The results indicated that 1) gene expressions did aggregate in families, especially between sibs. Of 3300 human genes analyzed, there were a total of 1105 genes with one or more significant (empirical p < 0.05) familial correlation; 2) there were several genomic hot spots where highly familially aggregated genes (e.g., the chromosome 6 HLA genes cluster) were clustered; 3) as we expected, gene ontology enrichment tests revealed that the 1105 genes were aggregating not only in families but also in functional categories.