Isolation and characterization of endoglucanases produced by microbes residing in the gut of Coptotermes curvignathus termite

Bacteria and enzymes in the gut of termites play an important role to digest lignocellulosic material. Coptotermes curvignathus is one of the very few destructive species that can infest living plants. In this study, five bacteria isolated from C. curvignathus gut; four aerobic Bacillus spp. and an anaerobic uncultured bacterium were identified to produce endoglucanase with molecular size of 11 kDa which is significantly smaller than the endoglucanase produced by Reticulitermes speratus. Biolog reader identification showed that TG117 and N45/1 were Bacillus cereus/thuringiensis, TG111 was Bacillus pseudomycoides and TG005 was Bacillus mycoides. Endoglucanase produced by aerobic isolate NA45/1 showed promising potential as an industrial enzyme with significantly higher enzymtic activity than the commercial cellulase from Aspergillus Niger (C1184 Sigma). Endoglucanase NA45/1 displayed enzymatic activity 0.3961 U at pH 9 and 45°C. The endoglucanase TG111 acted optimally at alkaline condition with 0.2294 U whereas endoglucanase TG117 functioned best at slightly acidic condition. This study showed that the termite gut has a wide range of endoglucanase enzymes with various optimum temperatures and pH

A Close Binary Star Resolved from Occultation by 87 Sylvia

The star BD+29 1748 was resolved to be a close binary from its occultation by the asteroid 87 Sylvia on 2006 December 18 UT. Four telescopes were used to observe this event at two sites separated by some 80 km apart. Two flux drops were observed at one site, whereas only one flux drop was detected at the other. From the long-term variation of Sylvia, we inferred the probable shape of the shadow during the occultation, and this in turn constrains the binary parameters: the two components of BD+29 1748 have a projected separation of 0.097" to 0.110" on the sky with a position angle 104 deg to 107 deg. The asteroid was clearly resolved with a size scale ranging from 130 to 290 km, as projected onto the occultation direction. No occultation was detected for either of the two known moonlets of 87 Sylvia.Comment: 12 pages, 4 figures, 2 tables; submitted to the PAS

Statistical identification of gene association by CID in application of constructing ER regulatory network

<p>Abstract</p> <p>Background</p> <p>A variety of high-throughput techniques are now available for constructing comprehensive gene regulatory networks in systems biology. In this study, we report a new statistical approach for facilitating <it>in silico </it>inference of regulatory network structure. The new measure of association, coefficient of intrinsic dependence (CID), is model-free and can be applied to both continuous and categorical distributions. When given two variables X and Y, CID answers whether Y is dependent on X by examining the conditional distribution of Y given X. In this paper, we apply CID to analyze the regulatory relationships between transcription factors (TFs) (X) and their downstream genes (Y) based on clinical data. More specifically, we use estrogen receptor α (ERα) as the variable X, and the analyses are based on 48 clinical breast cancer gene expression arrays (48A).</p> <p>Results</p> <p>The analytical utility of CID was evaluated in comparison with four commonly used statistical methods, Galton-Pearson's correlation coefficient (GPCC), Student's <it>t</it>-test (STT), coefficient of determination (CoD), and mutual information (MI). When being compared to GPCC, CoD, and MI, CID reveals its preferential ability to discover the regulatory association where distribution of the mRNA expression levels on X and Y does not fit linear models. On the other hand, when CID is used to measure the association of a continuous variable (Y) against a discrete variable (X), it shows similar performance as compared to STT, and appears to outperform CoD and MI. In addition, this study established a two-layer transcriptional regulatory network to exemplify the usage of CID, in combination with GPCC, in deciphering gene networks based on gene expression profiles from patient arrays.</p> <p>Conclusion</p> <p>CID is shown to provide useful information for identifying associations between genes and transcription factors of interest in patient arrays. When coupled with the relationships detected by GPCC, the association predicted by CID are applicable to the construction of transcriptional regulatory networks. This study shows how information from different data sources and learning algorithms can be integrated to investigate whether relevant regulatory mechanisms identified in cell models can also be partially re-identified in clinical samples of breast cancers.</p> <p>Availability</p> <p>the implementation of CID in R codes can be freely downloaded from <url>http://homepage.ntu.edu.tw/~lyliu/BC/</url>.</p

Particle spectrum in the modified NMSSM in the strong Yukawa coupling limit

A theoretical analysis of solutions of renormalisation group equations in the MSSM corresponding to the quasi-fixed point conditions shows that the mass of the lightest Higgs boson in this case does not exceed $94\pm 5\text{GeV}$. It means that a substantial part of the parameter space of the MSSM is practically excluded by existing experimental data from LEP II. In the NMSSM the upper bound on the lightest Higgs boson mass reaches its maximum in the strong Yukawa coupling regime, when Yukawa constants are considerably larger the gauge ones on the Grand Unification scale. In this paper a particle spectrum in a simple modification of NMSSM which leads to a self-consistent solution in the considered region of the parameter space is studied. This model allows one to get $m_h\sim 125\text{GeV}$ even for comparatively low values of $\tan\beta\ge 1.9$. For an analysis of the Higgs boson spectrum and neutralino spectrum a method for diagonalisation of mass matrices proposed formerly is used. The mass of the lightest Higgs boson in this model does not exceed $130.5\pm 3.5\text{GeV}$.Comment: 34 pages, 5 figures included, LaTeX 2

Development, implementation, and evaluation of the Apollo model of pediatric rehabilitation service delivery

This article presents the experience of a rehabilitation program that un- dertook the challenge to reorganize its services to address accessibility issues and im- prove service quality. The context in which the reorganization process occurred, along with the relevant literature justifying the need for a new service delivery model, and an historical perspective on the planning; implementation; and evaluation phases of the process are described. In the planning phase, the constitution of the working committee, the data collected, and the information found in the literature are presented. Apollo, the new service delivery model, is then described along with each of its components (e.g., community, group, and individual interventions). Actions and lessons learnt during the implementation of each component are presented. We hope by sharing our experiences that we can help others make informed decisions about service reorganization to im- prove the quality of services provided to children with disabilities, their families, and their communities

Model Selection in Time Series Studies of Influenza-Associated Mortality

Background: Poisson regression modeling has been widely used to estimate influenza-associated disease burden, as it has the advantage of adjusting for multiple seasonal confounders. However, few studies have discussed how to judge the adequacy of confounding adjustment. This study aims to compare the performance of commonly adopted model selection criteria in terms of providing a reliable and valid estimate for the health impact of influenza. Methods: We assessed four model selection criteria: quasi Akaike information criterion (QAIC), quasi Bayesian information criterion (QBIC), partial autocorrelation functions of residuals (PACF), and generalized cross-validation (GCV), by separately applying them to select the Poisson model best fitted to the mortality datasets that were simulated under the different assumptions of seasonal confounding. The performance of these criteria was evaluated by the bias and root-mean-square error (RMSE) of estimates from the pre-determined coefficients of influenza proxy variable. These four criteria were subsequently applied to an empirical hospitalization dataset to confirm the findings of simulation study. Results: GCV consistently provided smaller biases and RMSEs for the influenza coefficient estimates than QAIC, QBIC and PACF, under the different simulation scenarios. Sensitivity analysis of different pre-determined influenza coefficients, study periods and lag weeks showed that GCV consistently outperformed the other criteria. Similar results were found in applying these selection criteria to estimate influenza-associated hospitalization. Conclusions: GCV criterion is recommended for selection of Poisson models to estimate influenza-associated mortality and morbidity burden with proper adjustment for confounding. These findings shall help standardize the Poisson modeling approach for influenza disease burden studies. © 2012 Wang et al.published_or_final_versio

Parallel sequencing of extrachromosomal circular DNAs and transcriptomes in single cancer cells

Extrachromosomal DNAs (ecDNAs) are common in cancer, but many questions about their origin, structural dynamics and impact on intratumor heterogeneity are still unresolved. Here we describe single-cell extrachromosomal circular DNA and transcriptome sequencing (scEC&T-seq), a method for parallel sequencing of circular DNAs and full-length mRNA from single cells. By applying scEC&T-seq to cancer cells, we describe intercellular differences in ecDNA content while investigating their structural heterogeneity and transcriptional impact. Oncogene-containing ecDNAs were clonally present in cancer cells and drove intercellular oncogene expression differences. In contrast, other small circular DNAs were exclusive to individual cells, indicating differences in their selection and propagation. Intercellular differences in ecDNA structure pointed to circular recombination as a mechanism of ecDNA evolution. These results demonstrate scEC&T-seq as an approach to systematically characterize both small and large circular DNA in cancer cells, which will facilitate the analysis of these DNA elements in cancer and beyond

Asymmetry of Early Endosome Distribution in C. elegans Embryos

development, we examined the distribution and dynamics of early endosomes (EEs) in embryos.EEs are primarily found at the cell periphery with an initially uniform distribution after fertilization. Strikingly, we find that during the first cell cycle, EEA-1 positive EEs become enriched at the anterior cortex. In contrast, the Golgi compartment shows no asymmetry in distribution. Asymmetric enrichment of EEs depends on acto-myosin contractility and embryonic PAR polarity. In addition to their localization at the cortex, EEs are also found around the centrosome. These EEs move rapidly (1.3um/s) from the cortex directly to the centrosome, a speed comparable to that of the minus end directed motor dynein.We speculate that the asymmetry of early endosomes might play a role in cell asymmetries or fate decisions