Effect of longterm selection for number of mice in the first litter on size of subsequent litters

International audienc

Reproduction and bodyweight of mice after longterm selection for litter size

International audienc

Maximum Likelihood Estimation of the Negative Binomial Dispersion Parameter for Highly Overdispersed Data, with Applications to Infectious Diseases

BACKGROUND: The negative binomial distribution is used commonly throughout biology as a model for overdispersed count data, with attention focused on the negative binomial dispersion parameter, k. A substantial literature exists on the estimation of k, but most attention has focused on datasets that are not highly overdispersed (i.e., those with k≥1), and the accuracy of confidence intervals estimated for k is typically not explored. METHODOLOGY: This article presents a simulation study exploring the bias, precision, and confidence interval coverage of maximum-likelihood estimates of k from highly overdispersed distributions. In addition to exploring small-sample bias on negative binomial estimates, the study addresses estimation from datasets influenced by two types of event under-counting, and from disease transmission data subject to selection bias for successful outbreaks. CONCLUSIONS: Results show that maximum likelihood estimates of k can be biased upward by small sample size or under-reporting of zero-class events, but are not biased downward by any of the factors considered. Confidence intervals estimated from the asymptotic sampling variance tend to exhibit coverage below the nominal level, with overestimates of k comprising the great majority of coverage errors. Estimation from outbreak datasets does not increase the bias of k estimates, but can add significant upward bias to estimates of the mean. Because k varies inversely with the degree of overdispersion, these findings show that overestimation of the degree of overdispersion is very rare for these datasets

Anomalous ion diffusion within skeletal muscle transverse tubule networks

<p>Abstract</p> <p>Background</p> <p>Skeletal muscle fibres contain transverse tubular (t-tubule) networks that allow electrical signals to rapidly propagate into the fibre. These electrical signals are generated by the transport of ions across the t-tubule membranes and this can result in significant changes in ion concentrations within the t-tubules during muscle excitation. During periods of repeated high-frequency activation of skeletal muscle the t-tubule K⁺concentration is believed to increase significantly and diffusive K⁺transport from the t-tubules into the interstitial space provides a mechanism for alleviating muscle membrane depolarization. However, the tortuous nature of the highly branched space-filling t-tubule network impedes the diffusion of material through the network. The effective diffusion coefficient for ions in the t-tubules has been measured to be approximately five times lower than in free solution, which is significantly different from existing theoretical values of the effective diffusion coefficient that range from 2–3 times lower than in free solution. To resolve this discrepancy, in this paper we study the process of diffusion within electron microscope scanned sections of the skeletal muscle t-tubule network using mathematical modelling and computer simulation techniques. Our model includes t-tubule geometry, tautness, hydrodynamic and non-planar network factors.</p> <p>Results</p> <p>Using our model we found that the t-tubule network geometry reduced the K⁺diffusion coefficient to 19–27% of its value in free solution, which is consistent with the experimentally observed value of 21% and is significantly smaller than existing theoretical values that range from 32–50%. We also found that diffusion in the t-tubules is anomalous for skeletal muscle fibres with a diameter of less than approximately 10–20 μm as a result of obstructed diffusion. We also observed that the [K⁺] within the interior of the t-tubule network during high-frequency activation is greater for fibres with a larger diameter. Smaller skeletal muscle fibres are therefore more resistant to membrane depolarization. Because the t-tubule network is anisotropic and inhomogeneous, we also found that the [K⁺] distribution generated within the network was irregular for fibres of small diameter.</p> <p>Conclusion</p> <p>Our model explains the measured effective diffusion coefficient for ions in skeletal muscle t-tubules.</p

Regional differences in portion size consumption behaviour: Insights for the global food industry

Abstract: Given the influence of globalization on consumer food behaviour across the world, the purpose of this paper is to contribute to the theoretical discourse around food portion size as a global consumption-related symbol and its underlying socio-economic drivers for food industry strategy. Overall, 25,000 global food consumers were surveyed across 24 countries to elicit insight on portion size consumption behaviour as well as consumer perception on eating and drinking small portion size within selected socio-economic classes. The data was quantitatively analysed to answer the pertinent research objectives. In 20 out of the 24 global markets surveyed, large food portion size was statistically established as a prevalent consumption-related symbol. The paper found that there are regional differences in portion size food consumption behaviour, and further disparities exist across age, gender and income status in 24 countries covering all regions, including Australia, China, Mexico, South Africa, United Kingdom and United States of America. The outlined food industry implications reveal that adaptation and standardisation strategies are still relevant in global food and nutrition strategy as revealed by the variations in the preference for food portion sizes across various countries of the world