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A fixed-ratio combination of the basal insulin analogue insulin degludec and the glucagon-like peptide-1 (GLP-1) analogue liraglutide has been developed as a once-daily injection for the treatment of type 2 diabetes. We aimed to compare combined insulin degludec–liraglutide (IDegLira) with its components given alone in insulin-naive patients.

This paper deals with Bayesian inferences of animal models using Gibbs sampling. First, we suggest a general and efficient method for updating additive genetic effects, in which the computational cost is independent of the pedigree depth and increases linearly only with the size of the pedigree. Second, we show how this approach can be used to draw inferences from a wide range of animal models using the computer package Winbugs. Finally, we illustrate the approach in a simulation study, in which the data are generated and analyzed using Winbugs according to a linear model with i.i.d errors having Student's tdistributions. In conclusion, Winbugs can be used to make inferences in small-sized, quantitative, genetic data sets applying a wide range of animal models that are not yet standard in the animal breeding literature.

The objective of this study was, by means of simulation, to quantify the effect of ignoring individual heterogeneity in Weibull sire frailty models on parameter estimates and to address the consequences for genetic inferences. Three simulation studies were evaluated, which included 3 levels of individual heterogeneity combined with 4 levels of censoring (0, 25, 50, or 75%). Data were simulated according to balanced half-sib designs using Weibull log-normal animal frailty models with a normally distributed residual effect on the log-frailty scale. The 12 data sets were analyzed with 2 models: the sire model, equivalent to the animal model used to generate the data (complete sire model), and a corresponding model in which individual heterogeneity in log-frailty was neglected (incomplete sire model). Parameter estimates were obtained from a Bayesian analysis using Gibbs sampling, and also from the software Survival Kit for the incomplete sire model. For the incomplete sire model, the Monte Carlo and Survival Kit parameter estimates were similar. This study established that when unobserved individual heterogeneity was ignored, the parameter estimates that included sire effects were biased toward zero by an amount that depended in magnitude on the level of censoring and the size of the ignored individual heterogeneity. Despite the biased parameter estimates, the ranking of sires, measured by the rank correlations between true and estimated sire effects, was unaffected. In comparison, parameter estimates obtained using complete sire models were consistent with the true values used to simulate the data. Thus, in this study, several issues of concern were demonstrated for the incomplete sire model.

We present a formulation of the method of stochastic quantization of Parisi and W that reveals its intimate connection with supersymmetry. The crucial ingredient of this analysis is the Nicolai map. By using supersymmetric Ward identities, we derive relations between two Fokker-Planck-type Hamiltonians which arise naturally in this formalism.

Four strains of Bacillus thuringiensiswere isolated from infections in burn wounds and from water used in the treatment of burn wounds. The strains produced large parasporal inclusion bodies composed of 141, 83, and 81 kDa protoxins. The four strains were tested for insecticidal activity against larvae of Pieris brassicaeand Aedes aegyptibut showed no activity; Vero cell assays for the production of enterotoxins were also negative. Attempts to classify the strains according to flagellar H‐serotype showed them all to be non‐flagellated. Apart from two occupational health accidents that occurred during the handling of highly concentrated B. thuringiensisfluids, this is the first report of B. thuringiensiscausing non‐gastrointestinal clinical infection in immunosuppressed patients.

The notion of Langevin processes with anticommuting numbers, defined in straight-forward analogy with the ordinary description of Brownian motion, is briefly discussed. Applications of this formalism to stochastic quantization of field theories involving fermions is then reviewed. We comment on the existence of suitable kernels to ensure convergence to equilibrium in the general case.