An entropy-based improved k-top scoring pairs (TSP) method for classifying human cancers

Classification and prediction of different cancers based on gene-expression profiles are important for cancer diagnosis, cancer treatment and medication discovery. However, most data in the gene expression profile are not able to make a contribution to cancer classification and prediction. Hence, it is important to find the key genes that are relevant. An entropy-based improved k-top scoring pairs (TSP) (Ik-TSP) method was presented in this study for the classification and prediction of human cancers based on gene-expression data. We compared Ik-TSP classifiers with 5 different machine learning methods and the k-TSP method based on 3 different feature selection methods on 9 binary class gene expression datasets and 10 multi-class gene expression datasets involving human cancers. Experimental results showed that the Ik-TSP method had higher accuracy. The experimental results also showed that the proposed method can effectively find genes that are important for distinguishing different cancer and cancer subtype.Key words: Cancer classification, gene expression, k-TSP, information entropy, gene selection

Chicken-eaters and pork-eaters have different gut microbiota and tryptophan metabolites

This study was aimed to evaluate the differences in the composition of gut microbiota, tryptophan metabolites and short-chain fatty acids in feces between volunteers who frequently ate chicken and who frequently ate pork. Twenty male chicken-eaters and 20 male pork-eaters of 18 and 30 years old were recruited to collect feces samples for analyses of gut microbiota composition, short-chain fatty acids and tryptophan metabolites. Chicken-eaters had more diverse gut microbiota and higher abundance of Prevotella 9, Dialister, Faecalibacterium, Megamonas, and Prevotella 2. However, pork-eaters had higher relative abundance of Bacteroides, Faecalibacterium, Roseburia, Dialister, and Ruminococcus 2. In addition, chicken-eaters had high contents of skatole and indole in feces than pork-eaters, as well as higher contents of total short chain fatty acids, in particular for acetic acid, propionic acid, and branched chain fatty acids. The Spearman's correlation analysis revealed that the abundance of Prevotella 2 and Prevotella 9 was positively correlated with levels of fecal skatole, indole and short-chain fatty acids. Thus, intake of chicken diet may increase the risk of skatole- and indole-induced diseases by altering gut microbiota

Laboratory-based Surveillance of Extensively Drug-Resistant Tuberculosis, China

To estimate the prevalence of extensively drug-resistant tuberculosis (XDR TB) in China, we retrospectively analyzed drug-resistance profiles of 989 clinical Mycobacterium tuberculosis isolates. We found 319 (32.3%) isolates resistant to >1 first-line drugs; 107 (10.8%) isolates were multidrug resistant, of which 20 (18.7%) were XDR. XDR TB is of major concern in China

Prediction Method of the Fuel Consumption of Wheel Loaders in the V-Type Loading Cycle

Wheel loaders in the V-type loading cycle are characterized by complicated loading conditions, nonlinear power-train system, and time-variable engine power distribution. Therefore, it is difficult to predict the fuel consumption of wheel loaders in the V-type loading cycle. The static matching methods cannot provide fuel consumption prediction for the loading cycle. In this paper, the prediction method and model of the fuel consumption for wheel loaders in the V-type loading cycle were proposed. Firstly, the hydraulic system data were tested when a wheel loader loaded three different materials in a typical V-type loading cycle. Secondly, the tested data were filtered by the 8th-order Butterworth filter and the dimensionless power deduction equations of hydraulic power system for loading three different materials were obtained by Gaussian and linear fitting based on the filtered data in the loading cycle. Finally, fuel consumption was obtained with the compiling dynamic calculation program as well as input parameters of tested vehicle speed, throttle parameter, and the dimensionless equation. The simulation results agreed well with experiment results. Dynamic calculation program is applicable to calculate loading economy and can provide academic guidance for wheel loader’s design and optimization

Interplay between residual protease activity in commercial lactases and the subsequent digestibility of β-casein in a model system

One of the conventional ways to produce lactose-hydrolyzed (LH) milk is via the addition of commercial lactases into heat-treated milk in which lactose is hydrolyzed throughout storage. This post-hydrolysis method can induce proteolysis in milk proteins due to protease impurities remaining in commercial lactase preparations. In this work, the interplay between lactose hydrolysis, proteolysis, and glycation was studied in a model system of purified β-casein (β-CN), lactose, and lactases using peptidomic methods. With a lactase presence, the proteolysis of β-CN was found to be increased during storage. The protease side-activities mainly acted on the hydrophobic C-terminus of β-CN at Ala, Pro, Ile, Phe, Leu, Lys, Gln, and Tyr positions, resulting in the formation of peptides, some of which were N-terminal glycated or potentially bitter. The proteolysis in β-CN incubated with a lactase was shown to act as a kind of “pre-digestion”, thus increasing the subsequent in vitro digestibility of β-CN and drastically changing the peptide profiles of the in vitro digests. This model study provides a better understanding of how the residual proteases in commercial lactase preparations affect the quality and nutritional aspects of β-CN itself and could be related to its behavior in LH milk

High-Salt Diet Has a Certain Impact on Protein Digestion and Gut Microbiota: A Sequencing and Proteome Combined Study

High-salt diet has been considered to cause health problems, but it is still less known how high-salt diet affects gut microbiota, protein digestion, and passage in the digestive tract. In this study, C57BL/6J mice were fed low- or high-salt diets (0.25 vs. 3.15% NaCl) for 8 weeks, and then gut contents and feces were collected. Fecal microbiota was identified by sequencing the V4 region of 16S ribosomal RNA gene. Proteins and digested products of duodenal, jejunal, cecal, and colonic contents were identified by LC-MS-MS. The results indicated that the high-salt diet increased Firmicutes/Bacteroidetes ratio, the abundances of genera Lachnospiraceae and Ruminococcus (P < 0.05), but decreased the abundance of Lactobacillus (P < 0.05). LC-MS-MS revealed a dynamic change of proteins from the diet, host, and gut microbiota alongside the digestive tract. For dietary proteins, high-salt diet seemed not influence its protein digestion and absorption. For host proteins, 20 proteins of lower abundance were identified in the high-salt diet group in duodenal contents, which were involved in digestive enzymes and pancreatic secretion. However, no significant differentially expressed proteins were detected in jejunal, cecal, and colonic contents. For bacterial proteins, proteins secreted by gut microbiota were involved in energy metabolism, sodium transport, and protein folding. Five proteins (cytidylate kinase, trigger factor, 6-phosphogluconate dehydrogenase, transporter, and undecaprenyl-diphosphatase) had a higher abundance in the high-salt diet group than those in the low-salt group, while two proteins (acetylglutamate kinase and PBSX phage manganese-containing catalase) were over-expressed in the low-salt diet group than in the high-salt group. Consequently, high-salt diet may alter the composition of gut microbiota and has a certain impact on protein digestion