Nutrient supply affects the mRNA expression profile of the porcine skeletal muscle

Background: The genetic basis of muscle fat deposition in pigs is not well known. So far, we have only identified a limited number of genes involved in the absorption, transport, storage and catabolism of lipids. Such information is crucial to interpret, from a biological perspective, the results of genome-wide association analyses for intramuscular fat content and composition traits. Herewith, we have investigated how the ingestion of food changes gene expression in the gluteus medius muscle of Duroc pigs. Results: By comparing the muscle mRNA expression of fasted pigs (T0) with that of pigs sampled 5 h (T1) and 7 h (T2) after food intake, we have detected differential expression (DE) for 148 (T0-T1), 520 (T0-T2) and 135 (T1-T2) genes (q-value of 1.5). Many of these DE genes were transcription factors, suggesting that we have detected the coordinated response of the skeletal muscle to nutrient supply. We also found DE genes with a dual role in oxidative stress and angiogenesis (THBS1, THBS2 and TXNIP), two biological processes that are probably activated in the post-prandial state. Finally, we have identified several loci playing a key role in the modulation of circadian rhythms (ARNTL, PER1, PER2, BHLHE40, NR1D1, SIK1, CIART and CRY2), a result that indicates that the porcine muscle circadian clock is modulated by nutrition. Conclusion: We have shown that hundreds of genes change their expression in the porcine skeletal muscle in response to nutrient intake. Many of these loci do not have a known metabolic role, a result that suggests that our knowledge about the genetic basis of muscle energy homeostasis is still incomplete

Colorectal cancer stages transcriptome analysis

Colorectal cancer (CRC) is the third most common cancer and the second leading cause of cancer-related deaths in the United States. The purpose of this study was to evaluate the gene expression differences in different stages of CRC. Gene expression data on 433 CRC patient samples were obtained from The Cancer Genome Atlas (TCGA). Gene expression differences were evaluated across CRC stages using linear regression. Genes with p 0.001 in expression differences were evaluated further in principal component analysis and genes with p 0.0001 were evaluated further in gene set enrichment analysis. A total of 377 patients with gene expression data in 20,532 genes were included in the final analysis. The numbers of patients in stage I through IV were 59, 147, 116 and 55, respectively. NEK4 gene, which encodes for NIMA related kinase 4, was differentially expressed across the four stages of CRC. The stage I patients had the highest expression of NEK4 genes, while the stage IV patients had the lowest expressions (p = 9*10−6 ). Ten other genes (RNF34, HIST3H2BB, NUDT6, LRCh4, GLB1L, HIST2H4A, TMEM79, AMIGO2, C20orf135 and SPSB3) had p value of 0.0001 in the differential expression analysis. Principal component analysis indicated that the patients from the 4 clinical stages do not appear to have distinct gene expression pattern. Network-based and pathway-based gene set enrichment analyses showed that these 11 genes map to multiple pathways such as meiotic synapsis and packaging of telomere ends, etc. Ten of these 11 genes were linked to Gene Ontology terms such as nucleosome, DNA packaging complex and protein-DNA interactions. The protein complex-based gene set analysis showed that four genes were involved in H2AX complex II. This study identified a small number of genes that might be associated with clinical stages of CRC. Our analysis was not able to find a molecular basis for the current clinical staging for CRC based on the gene expression patterns

Obtención y caracterización de pectina a partir de la cáscara de parchita (Passiflora edulis f. flavicarpa Degener)

Se analizó la influencia del estado de coloración (verde-blanco, verde-amarillo y amarillo) y del agente de extracción (HCl, H3PO4, H3PO4-(NaPO3)6) sobre la pectina de la corteza seca de parchita. El contenido de pectina se determinó por el método de hidrólisis ácida, a las condiciones de extracción pH: 3.0, temperatura: 90-95ºC y tiempo de calentamiento: 90 minutos. La calidad de la pectina se evaluó mediante análisis de humedad, cenizas, peso equivalente, metoxilo, ácido anhidrourónico, grado de esterificación, tiempo de gelificación, viscosidad relativa, espectros de infrarrojo y los minerales calcio (Ca), magnesio (Mg) y sodio (Na). El rendimiento máximo de pectina obtenido fue 18,45% al usarse como extractante H3PO4-(NaPO3)6; mientras que la pectina de mejor calidad fue extraída con HCl, con un contenido de ácido anhidrourónico y de metoxilo de 78% y 9,9%, respectivamente. La corteza de la parchita en el estado de madurez amarillo presentó el mayor contenido de pectina, mientras que la extraída en el estado de madurez verde-blanco exhibió las mejores propiedades gelificantes. La espectrometría de IR confirmó que la pectina tiene alto contenido de metoxilo. El análisis de los minerales arrojó los siguientes resultados: calcio 0,10 a 0,15%, magnesio 0,05 a 0,08% y sodio 0,02 a 0,04%. La pectina de la corteza de parchita no presenta características inusuales que indiquen alguna desventaja potencial comercial

Producción de proteína microbiana a partir de los desechos del procesamiento de la caña de azúcar (bagacillo)(Microbial protein production from waste of sugar cane processing (bagasse pith))

A study was undertaken of microbial biomass production using hydrolyzed pith bagasse acid as a growth medium. Hydrolysis was carried out using diluted (6%v/v) sulfuric acid in a reaction time of four hours. The equipment used operated at boiling conditions with atmospheric pressure reflux, and with a liquid/solid relation of 30. The concentration of sugars in the hydrolyzed solution was carried out by a rotational evaporator. The Candida utilis (ATCC 9256) and Saccharomyces cerevisiae (ATCC 26603) yeasts were cultivated in the hydrolyzed concentrate at a pH of 5.00, 30 °C and 200 rpm. The greatest production of biomass was 4.90 ± 0,03 kg/m3 in S. cerevisiae and 9.45 ± 0,01 kg/m3 in C. utilis. The yield of biomass was 1.19 ± 0,012 kg/kg in S. cerevisiae and 1.86 ± 0,040 kg/kg in C. utilis. The specific rate of growth was 0.0141 ± 0,0001 and 0.0544 ± 0,0001 h-1 for S. cerevisiae and C. utilis, respectively. The biotechnological process utilized is an important fundamental alternative for the industrial usage of pith bagasse from sugar cane through the production of a protein concentrate for animal feeds

Mobility in Collaborative Alert Systems: Building Trust through Reputation

Part 3: - WCNS 2011 WorkshopInternational audienceCollaborative Intrusion Detection Networks (CIDN) are usually composed by a set of nodes working together to detect distributed intrusions that cannot be easily recognized with traditional intrusion detection architectures. In this approach every node could potentially collaborate to provide its vision of the system and report the alarms being detected at the network, service and/or application levels. This approach includes considering mobile nodes that will be entering and leaving the network in an ad hoc manner. However, for this alert information to be useful in the context of CIDN networks, certain trust and reputation mechanisms determining the credibility of a particular mobile node, and the alerts it provides, are needed. This is the main objective of this paper, where an inter-domain trust and reputation model, together with an architecture for inter-domain collaboration, are presented with the main aim of improving the detection accuracy in CIDN systems while users move from one security domain to another

Ruin probabilities for a discrete time risk model with non-homogeneous conditions

This paper is concerned with a non-homogeneous discrete time risk model where premiums are fixed but non-uniform, and claim amounts are independent but non-stationary. It allows one to account for the influence of inflation and interest and the effect of variability in the claims. Our main purpose is to develop an algorithm for calculating the finite time ruin probabilities and the associated ruin severity distributions. The ruin probabilities are shown to rely on an underlying algebraic structure of Appell type. That property makes the computational method proposed quite simple and efficient. Its application is illustrated through some numerical examples of ruin problems. The well known Lundberg bound for ultimate ruin probabilities is also reexamined within such a non-homogeneous framework.info:eu-repo/semantics/publishe