Prevalence of Enteropathogens in Dogs Attending 3 Regional Dog Parks in Northern California.

BackgroundThe prevalence and risk factors for infection with enteropathogens in dogs frequenting dog parks have been poorly documented, and infected dogs can pose a potential zoonotic risk for owners.Hypothesis/objectivesTo determine the prevalence and risk factors of infection with enteropathogens and zoonotic Giardia strains in dogs attending dog parks in Northern California and to compare results of fecal flotation procedures performed at a commercial and university parasitology laboratory.AnimalsThree-hundred dogs attending 3 regional dog parks in Northern California.MethodsProspective study. Fresh fecal specimens were collected from all dogs, scored for consistency, and owners completed a questionnaire. Specimens were analyzed by fecal centrifugation flotation, DFA, and PCR for detection of 11 enteropathogens. Giardia genotyping was performed for assemblage determination.ResultsEnteropathogens were detected in 114/300 dogs (38%), of which 62 (54%) did not have diarrhea. Frequency of dog park attendance correlated significantly with fecal consistency (P = .0039), but did not correlate with enteropathogen detection. Twenty-seven dogs (9%) were infected with Giardia, and genotyping revealed nonzoonotic assemblages C and D. The frequency of Giardia detection on fecal flotation was significantly lower at the commercial laboratory versus the university laboratory (P = .013), and PCR for Giardia was negative in 11/27 dogs (41%) that were positive on fecal flotation or DFA.Conclusions and clinical importanceEnteropathogens were commonly detected in dogs frequenting dog parks, and infection with Giardia correlated with fecal consistency. PCR detection of Giardia had limited diagnostic utility, and detection of Giardia cysts by microscopic technique can vary among laboratories

Development of statistical methods for the analysis of single-cell RNA-seq data

Single-cell RNA-sequencing profiles the transcriptome of cells from diverse populations. A popular intermediate data format is a large count matrix of genes x cells. This type of data brings several analytical challenges. Here, I present three projects that I worked on during my PhD that address particular aspects of working with such datasets: - The large number of cells in the count matrix is a challenge for fitting gamma-Poisson generalized linear models with existing tools. I developed a new R package called glmGamPoi to address this gap. I optimized the overdispersion estimation procedure to be quick and robust for datasets with many cells and small counts. I compared the performance against two popular tools (edgeR and DESeq2) and find that my inference is 6x to 13x faster and achieves a higher likelihood for a majority of the genes in four single-cell datasets. - The variance of single-cell RNA-seq counts depends on their mean but many existing statistical tools have optimal performance when the variance is uniform. Accordingly, variance-stabilizing transformations are applied to unlock the large number of methods with such an requirement. I compared four approaches to variance-stabilize the data based on the delta method, model residuals, inferred latent expression state or count factor analysis. I describe the theoretical strength and weaknesses, and compare their empirical performance in a benchmark on simulated and real single-cell data. I find that none of the mathematically more sophisticated transformations consistently outperform the simple log(y/s+1) transformation. - Multi-condition single-cell data offers the opportunity to find differentially expressed genes for individual cell subpopulations. However, the prevalent approach to analyze such data is to start by dividing the cells into discrete populations and then test for differential expression within each group. The results are interpretable but may miss interesting cases by (1) choosing the cluster size too small and lacking power to detect effects or (2) choosing the cluster size too large and obscuring interesting effects apparent on a smaller scale. I developed a new statistical framework for the analysis of multi-condition single-cell data that avoids the premature discretization. The approach performs regression on the latent subspaces occupied by the cells in each condition. The method is implemented as an R package called lemur

Стадии экономической оценки месторождения

The cAMP response element modulator (CREM)α is a widely expressed transcriptional repressor that is important for the termination of the T cell immune response and contributes to the abnormal T cell function in patients with systemic lupus erythematosus. We present evidence that APCs of Crem(−/−) mice express increased amounts of the costimulatory molecule CD86 and induce enhanced Ag-dependent and Ag-independent T cell proliferation. Similarly, human APCs in which CREMα was selectively suppressed expressed more CD86 on the surface membrane. CREMα was found to bind to the CD86 promoter and suppressed its activity. Transfer of APCs from Crem(−/−) mice into naive mice facilitated a significantly stronger contact dermatitis response compared with mice into which APCs from Crem(+/+) mice had been transferred. We conclude that CREMα is an important negative regulator of costimulation and APC-dependent T cell function both in vitro and in vivo

Determination of cobalt and copper concentration in technological flows of oxidation process of cyclohexane by method of MP-AES

In this paper, we propose a method for quantifying Co and Cu in the range 0,5-20,000 ppm in the process streams of cyclohexane oxidation products using MP-AES

BBF RFC 105: The Intein standard - a universal way to modify proteins after translation

This Request for Comments (RFC) proposes a new standard that allows for easy and flexible cloning of intein constructs and thus makes this technology accessible to the synthetic biology community

Mechanische und elektrische Eigenschaften von Ionenleitern

The current global interest in energy storage has triggered the development of new composite materials and, consequently, new methodologies for manufacturing and testing these products. In the energy storage research field their mechanical behavior is less investigated, despite of their high both fundamental and technological relevance. To assess the interplay between charge and mass transport, this thesis focusses on a large variety of electrolytes using shear rheology and dielectric spectroscopy as examination methods. Tailoring the mechanical behavior of these materials, this work investigates the impact of their local and macroscopic viscoelasticity on their conductivity, with the ultimate goal of finding new recipes for improving the latter. Our investigations from a series of mixtures with an ionic liquid and a dipolar one shows an unusual shifting in the coupling between the mechanical and conductvity processes. A survey of ionogels demonstrate that the interaction of charge carriers with their gel-like matrix can affect conductivity even in the presence of a strong dynamical disparity between its macroscopic mechanical and electrical parameters. Finally, comparing ionic and proton conductors, it is shown that this decoupling significantly enhances the conductivity in acid hydrates. Our results and their analysis show that enhancing the degree of decoupling between the mechanical and electrical degrees of freedom, combined with a reduction of charge correlations in highly concentrated electrolytes are essential for the development of the next generation of energy storage materials.Das derzeitige weltweite Interesse an der Energiespeicherung hat zur Entwicklung neuer Verbundwerkstoffe und folglich zu neuen Methoden für die Herstellung und Prüfung dieser Produkte geführt. In der Energiespeicherforschung wird das mechanische Verhalten jedoch weniger untersucht, obwohl es sowohl von grundlegender als auch technologischer Bedeutung ist. Um das Zusammenspiel von Ladungs- und Massentransport zu bewerten, konzentriert sich diese Arbeit auf eine Vielzahl von Elektrolyten, wobei Scherrheologie und dielektrische Spektroskopie als Untersuchungsmethoden eingesetzt werden. Indem wir das mechanische Verhalten dieser Materialien anpassen, untersuchen wir den Einfluss ihrer lokalen und makroskopischen Viskoelastizität auf ihre Leitfähigkeit, mit dem Ziel, neue Ansätze zur Verbesserung der Leitfähigkeit zu finden. Unsere Untersuchungen an einer Reihe von Mischungen mit einer ionischen und einer dipolaren Flüssigkeit zeigen eine ungewöhnliche Verschiebung in der Kopplung zwischen mechanischem und Leitfähigkeits-Prozess. Eine Untersuchung von Ionengelen zeigt, dass die Wechselwirkung von Ladungsträgern mit ihrer gelartigen Matrix die Leitfähigkeit auch dann beeinflussen kann, wenn eine starke dynamische Diskrepanz zwischen den makroskopischen mechanischen und elektrischen Parametern besteht. Schließlich wird durch den Vergleich von Ionen- und Protonenleitern gezeigt, dass diese Entkopplung die Leitfähigkeit in Säurehydraten signifikant erhöht. Unsere Ergebnisse und deren Analysen zeigen, dass die Verbesserung des Entkopplungsgrades zwischen den mechanischen und elektrischen Freiheitsgraden in Verbindung mit einer Reduzierung der Ladungskorrelationen in hochkonzentrierten Elektrolyten für die Entwicklung der nächsten Generation von Energiespeichermaterialien von essentieller Bedeutung ist