Monitoring of Eschericia. Coli O157 From Raw Cow\u27s Milk in the Storage Tank in Sleman District, YOGYAKARTA

Escherichia coli O157 is a member of Enterobacteriaceae which has somatic antigen O157. E. coli O157 isassociated with life threatening diseases such as hemorrhagic colitis (HC), hemolytic uremic syndrome(HUS) and thrombotic thrombocytopenic purpura (TTP). Raw milk is considered a high risk food as it ishighly nutritious and serves as an ideal medium for bacterial growth. The aim of this study was to monitorE. coli O157 contamination in the storage tank before distribution in Sleman district, Yogyakarta. Totalof 30 raw milk samples were collected from the storage tank in Sleman district. Tryptic Soy Broth (TSB)media added with novobiocin was used as enrichment medium, while Chromocult Coliform Agar (CCA)and Chromagar O157 medium for screening test. Additional analysis including serologic and moleculartest of isolates obtained. Based on the screening result, 11,428 colonies were considered as E. coli O157 suspectthat produced red colour in CCA medium. Further screening employing Chromagar O157 mediumresulted in 3 potential colonies which produce mauve colour. These colonies were later tested with LatexTest O157 for serological reason, showing that none were E. coli O157. Molecular analysis with primer pairsfor detection of Stx1 and Stx2 genes confirm that none of the suspected strains have genes that encodedthe toxin, Stx1 and Stx2. These results showed that the presence of STEC (Shiga toxin E. coli) hasn\u27t foundin the tested samples of raw cow\u27s milk

Spinal release of tumour necrosis factor activates c-Jun N-terminal kinase and mediates inflammation-induced hypersensitivity.

BackgroundMounting evidence points to individual contributions of tumour necrosis factor-alpha (TNF) and the c-Jun N-terminal kinase (JNK) pathway to the induction and maintenance of various pain states. Here we explore the role of spinal TNF and JNK in carrageenan-induced hypersensitivity. As links between TNF and JNK have been demonstrated in vitro, we investigated if TNF regulates spinal JNK activity in vivo.MethodsTNF levels in lumbar cerebrospinal fluid (CSF) were measured by enzyme-linked immunosorbent assay, spinal TNF gene expression by real-time polymerase chain reaction and TNF protein expression, JNK and c-Jun phosphorylation by western blotting. The role of spinal TNF and JNK in inflammation-induced mechanical and thermal hypersensitivity was assessed by injecting the TNF inhibitor etanercept and the JNK inhibitors SP600125 and JIP-1 intrathecally (i.t.). TNF-mediated regulation of JNK activity was examined by assessing the effect of i.t. etanercept on inflammation-induced spinal JNK activity.ResultsTNF levels were increased in CSF and spinal cord following carrageenan-induced inflammation. While JNK phosphorylation followed the same temporal pattern as TNF, c-jun was only activated at later time points. Intrathecal injection of TNF and JNK inhibitors attenuated carrageenan-induced mechanical and thermal hypersensitivity. TNF stimulation induced JNK phosphorylation in cultured spinal astrocytes and blocking the spinal actions of TNF in vivo by i.t. injection of etanercept reduced inflammation-induced spinal JNK activity.ConclusionsHere we show that spinal JNK activity is dependent on TNF and that both TNF and the JNK signalling pathways modulate pain-like behaviour induced by peripheral inflammation

On Vague Computers

Vagueness is something everyone is familiar with. In fact, most people think that vagueness is closely related to language and exists only there. However, vagueness is a property of the physical world. Quantum computers harness superposition and entanglement to perform their computational tasks. Both superposition and entanglement are vague processes. Thus quantum computers, which process exact data without "exploiting" vagueness, are actually vague computers

Compressibility of titanosilicate melts

The effect of composition on the relaxed adiabatic bulk modulus (K0) of a range of alkali- and alkaline earth-titanosilicate [X 2 n/n+ TiSiO5 (X=Li, Na, K, Rb, Cs, Ca, Sr, Ba)] melts has been investigated. The relaxed bulk moduli of these melts have been measured using ultrasonic interferometric methods at frequencies of 3, 5 and 7 MHz in the temperature range of 950 to 1600°C (0.02 Pa s < s < 5 Pa s). The bulk moduli of these melts decrease with increasing cation size from Li to Cs and Ca to Ba, and with increasing temperature. The bulk moduli of the Li-, Na-, Ca- and Ba-bearing metasilicate melts decrease with the addition of both TiO2 and SiO2 whereas those of the K-, Rb- and Cs-bearing melts increase. Linear fits to the bulk modulus versus volume fraction of TiO2 do not converge to a common compressibility of the TiO2 component, indicating that the structural role of TiO2 in these melts is dependent on the identity of the cation. This proposition is supported by a number of other property data for these and related melt compositions including heat capacity and density, as well as structural inferences from X-ray absorption spectroscopy (XANES). The compositional dependence of the compressibility of the TiO2 component in these melts explains the difficulty incurred in previous attempts to incorporate TiO2 in calculation schemes for melt compressibility. The empirical relationship KV-4/3 for isostructural materials has been used to evaluate the compressibility-related structural changes occurring in these melts. The alkali metasilicate and disilicate melts are isostructural, independent of the cation. The addition of Ti to the metasilicate composition (i.e. X2TiSiO5), however, results in a series of melts which are not isostructural. The alkaline-earth metasilicate and disilicate compositions are not isostructural, but the addition of Ti to the metasilicate compositions (i.e. XTiSiO5) would appear, on the basis of modulus-volume systematics, to result in the melts becoming isostructural with respect to compressibility

Monsoon circulation induced variability in total column ozone over India

The intra-seasonal variability of daily total column ozone (TCO) over 12 Indian stations has been studied. Total Ozone Mapping Spectrometer daily data from May to September for five years (1998-2002) have been utilized in the study. The power spectrum analysis of daily TCO data showed three dominant modes of period 3-8 days (synoptic), 10-20 days (quasi biweekly, qbw) and 30-60 days (Madden Julian Oscillation, MJO), similar to that found in the Indian Summer Monsoon Rainfall. Mean spatial distribution of the activities of these intra-seasonal modes in TCO variability over the Indian region has been studied. The spatial distribution of the synoptic mode shows the strongest activity over central India. The qbw mode shows strongest activity over northwest India. The MJO mode shows strongest activity over northern most and southern most parts of India

Muscle Fatigue Analysis Using OpenSim

In this research, attempts are made to conduct concrete muscle fatigue analysis of arbitrary motions on OpenSim, a digital human modeling platform. A plug-in is written on the base of a muscle fatigue model, which makes it possible to calculate the decline of force-output capability of each muscle along time. The plug-in is tested on a three-dimensional, 29 degree-of-freedom human model. Motion data is obtained by motion capturing during an arbitrary running at a speed of 3.96 m/s. Ten muscles are selected for concrete analysis. As a result, the force-output capability of these muscles reduced to 60%-70% after 10 minutes' running, on a general basis. Erector spinae, which loses 39.2% of its maximal capability, is found to be more fatigue-exposed than the others. The influence of subject attributes (fatigability) is evaluated and discussed

On the Growth of Al_2 O_3 Scales

Understanding the growth of Al2O3 scales requires knowledge of the details of the chemical reactions at the scale–gas and scale–metal interfaces, which in turn requires specifying how the creation/annihilation of O and Al vacancies occurs at these interfaces. The availability of the necessary electrons and holes to allow for such creation/annihilation is a crucial aspect of the scaling reaction. The electronic band structure of polycrystalline Al2O3 thus plays a decisive role in scale formation and is considered in detail, including the implications of a density functional theory (DFT) calculation of the band structure of a Σ7 View the MathML source bicrystal boundary, for which the atomic structure of the boundary was known from an independent DFT energy-minimization calculation and comparisons with an atomic-resolution transmission electron micrograph of the same boundary. DFT calculations of the formation energy of O and Al vacancies in bulk Al2O3 in various charge states as a function of the Fermi energy suggested that electronic conduction in Al2O3 scales most likely involves excitation of both electrons and holes, which are localized on singly charged O vacancies, View the MathML source and doubly charged Al vacancies, View the MathML source, respectively. We also consider the variation of the Fermi level across the scale and bending (“tilting”) of the conduction band minimum and valence band maximum due to the electric field developed during the scaling reaction. The band structure calculations suggest a new mechanism for the “reactive element” effect—a consequence of segregation of Y, Hf, etc., to grain boundaries in Al2O3 scales, which results in improved oxidation resistance—namely, that the effect is due to the modification of the near-band edge grain-boundary defect states rather than any blocking of diffusion pathways, as previously postulated. Secondly, Al2O3 scale formation is dominated by grain boundary as opposed to lattice diffusion, and there is unambiguous evidence for both O and Al countercurrent transport in Al2O3 scale-forming alloys. We postulate that such transport is mediated by migration of grain boundary disconnections containing charged jogs, rather than by jumping of isolated point defects in random high-angle grain boundaries

Novel Bayesian Networks for Genomic Prediction of Developmental Traits in Biomass Sorghum.

The ability to connect genetic information between traits over time allow Bayesian networks to offer a powerful probabilistic framework to construct genomic prediction models. In this study, we phenotyped a diversity panel of 869 biomass sorghum (Sorghum bicolor (L.) Moench) lines, which had been genotyped with 100,435 SNP markers, for plant height (PH) with biweekly measurements from 30 to 120 days after planting (DAP) and for end-of-season dry biomass yield (DBY) in four environments. We evaluated five genomic prediction models: Bayesian network (BN), Pleiotropic Bayesian network (PBN), Dynamic Bayesian network (DBN), multi-trait GBLUP (MTr-GBLUP), and multi-time GBLUP (MTi-GBLUP) models. In fivefold cross-validation, prediction accuracies ranged from 0.46 (PBN) to 0.49 (MTr-GBLUP) for DBY and from 0.47 (DBN, DAP120) to 0.75 (MTi-GBLUP, DAP60) for PH. Forward-chaining cross-validation further improved prediction accuracies of the DBN, MTi-GBLUP and MTr-GBLUP models for PH (training slice: 30-45 DAP) by 36.4-52.4% relative to the BN and PBN models. Coincidence indices (target: biomass, secondary: PH) and a coincidence index based on lines (PH time series) showed that the ranking of lines by PH changed minimally after 45 DAP. These results suggest a two-level indirect selection method for PH at harvest (first-level target trait) and DBY (second-level target trait) could be conducted earlier in the season based on ranking of lines by PH at 45 DAP (secondary trait). With the advance of high-throughput phenotyping technologies, our proposed two-level indirect selection framework could be valuable for enhancing genetic gain per unit of time when selecting on developmental traits

Exposure to benzene at work and the risk of leukemia: a systematic review and meta-analysis

Background A substantial number of epidemiologic studies have provided estimates of the relation between exposure to benzene at work and the risk of leukemia, but the results have been heterogeneous. To bridge this gap in knowledge, we synthesized the existing epidemiologic evidence on the relation between occupational exposure to benzene and the risk of leukemia, including all types combined and the four main subgroups acute myeloid leukemia (AML), acute lymphocytic leukemia (ALL), chronic lymphocytic leukemia (CLL), and chronic myeloid leukemia (CML). Methods A systematic literature review was carried out using two databases 'Medline' and 'Embase' from 1950 through to July 2009. We selected articles which provided information that can be used to estimate the relation between benzene exposure and cancer risk (effect size). Results In total 15 studies were identified in the search, providing 16 effect estimates for the main analysis. The summary effect size for any leukemia from the fixed-effects model was 1.40 (95% CI, 1.23-1.57), but the study-specific estimates were strongly heterogeneous (I2 = 56.5%, Q stat = 34.47, p = 0.003). The random-effects model yielded a summary- effect size estimate of 1.72 (95% CI, 1.37-2.17). Effect estimates from 9 studies were based on cumulative exposures. In these studies the risk of leukemia increased with a dose-response pattern with a summary-effect estimate of 1.64 (95% CI, 1.13-2.39) for low (< 40 ppm-years), 1.90 (95% CI, 1.26-2.89) for medium (40-99.9 ppm-years), and 2.62 (95% CI, 1.57-4.39) for high exposure category (> 100 ppm-years). In a meta-regression, the trend was statistically significant (P = 0.015). Use of cumulative exposure eliminated heterogeneity. The risk of AML also increased from low (1.94, 95% CI, 0.95-3.95), medium (2.32, 95% CI, 0.91-5.94) to high exposure category (3.20, 95% CI, 1.09-9.45), but the trend was not statistically significant. Conclusions Our study provides consistent evidence that exposure to benzene at work increases the risk of leukemia with a dose-response pattern. There was some evidence of an increased risk of AML and CLL. The meta-analysis indicated a lack of association between benzene exposure and the risk of CML