Regionally selective atrophy of subcortical structures in prodromal HD as revealed by statistical shape analysis

Huntington disease (HD) is a neurodegenerative disorder that involves preferential atrophy in the striatal complex and related subcortical nuclei. In this article, which is based on a dataset extracted from the PREDICT‐HD study, we use statistical shape analysis with deformation markers obtained through “Large Deformation Diffeomorphic Metric Mapping” of cortical surfaces to highlight specific atrophy patterns in the caudate, putamen, and globus pallidus, at different prodromal stages of the disease. On the basis of the relation to cortico‐basal ganglia circuitry, we propose that statistical shape analysis, along with other structural and functional imaging studies, may help expand our understanding of the brain circuitry affected and other aspects of the neurobiology of HD, and also guide the most effective strategies for intervention. Hum Brain Mapp 35:792–809, 2014. © 2012 Wiley Periodicals, Inc.     

Optimal needle design for minimal insertion force and bevel length

This research presents a methodology for optimal design of the needle geometry to minimize the insertion force and bevel length based on mathematical models of cutting edge inclination and rake angles and the insertion force. In brachytherapy, the needle with lower insertion force typically is easier for guidance and has less deflection. In this study, the needle with lancet point (denoted as lancet needle) is applied to demonstrate the model-based optimization for needle design. Mathematical models to calculate the bevel length and inclination and rake angles for lancet needle are presented. A needle insertion force model is developed to predict the insertion force for lancet needle. The genetic algorithm is utilized to optimize the needle geometry for two cases. One is to minimize the needle insertion force. Using the geometry of a commercial lancet needle as the baseline, the optimized needle has 11% lower insertion force with the same bevel length. The other case is to minimize the bevel length under the same needle insertion force. The optimized design can reduce the bevel length by 46%. Both optimized needle designs were validated experimentally in ex vivo porcine liver needle insertion tests and demonstrated the methodology of the model-based optimal needle design.     

Bacterial taxa associated with the hematophagous mite Dermanyssus gallinae detected by 16S rRNA PCR amplification and TTGE fingerprinting

Dermanyssus gallinae (Arthropoda, Mesostigmata) is suspected to be involved in the transmission of a wide variety of pathogens, but nothing is known about its associated non-pathogenic bacterial community. To address this question, we examined the composition of bacterial communities in D. gallinae collected from standard poultry farms in Brittany, France. Genetic fingerprints of bacterial communities were generated by temporal temperature gradient gel electrophoresis (TTGE) separation of individual polymerase chain reaction (PCR)-amplified 16S rRNA gene fragments, followed by DNA sequence analysis. Most of the sequences belonged to the Proteobacteria and Firmicute phyla, with a majority of sequences corresponding to the Enterobacteriales order and the Staphylococcus genus. By using statistical analysis, we showed differences in biodiversity between poultry farms. We also determined the major phylotypes that compose the characteristic microbiota associated with D. gallinae. Saprophytes, opportunistic pathogens and pathogenic agents such as Pasteurella multocida, Erysipelothrix rhusiopathiae and sequences close to the genus Aerococcus were identified. Endosymbionts such as Schineria sp., Spiroplasma sp. Anistosticta, “Candidatus Cardinium hertigii” and Rickettsiella sp. were also present in the subdominant bacterial community. Identification of potential targets within the symbiont community may be considered in the future as a means of ectoparasite control.     

An appeal for the presentation of detailed human derived data for dose–response calculations in nutritional science

If a diet, food or food constituent is recognised to have both health benefits and health risks, the benefits have to be compared with the risks to develop coherent scientific evidence-based dietary advice. This means that both risk and benefit assessment should follow a similar paradigm and that benefits and risks are expressed in a common currency. Dose–response functions are vital for that purpose. However, the construction of these functions is often of second interest in the currently available (epidemiological) literature. In order to bring forward the potential of epidemiological studies for the construction of the dose–response functions for benefit–risk purposes, the scientific (nutrition and health) community is asked to expand on their data presentation, either by presenting more detailed data focusing on dose–response necessities, and/or by sharing primary data.     

The Power and Robustness of Maximum LOD Score Statistics

The maximum LOD score statistic is extremely powerful for gene mapping when calculated using the correct genetic parameter value. When the mode of genetic transmission is unknown, the maximum of the LOD scores obtained using several genetic parameter values is reported. This latter statistic requires higher critical value than the maximum LOD score statistic calculated from a single genetic parameter value.
In this paper, we compare the power of maximum LOD scores based on three fixed sets of genetic parameter values with the power of the LOD score obtained after maximizing over the entire range of genetic parameter values. We simulate family data under nine generating models. For generating models with non-zero phenocopy rates, LOD scores maximized over the entire range of genetic parameters yielded greater power than maximum LOD scores for fixed sets of parameter values with zero phenocopy rates. No maximum LOD score was consistently more powerful than the others for generating models with a zero phenocopy rate. The power loss of the LOD score maximized over the entire range of genetic parameters, relative to the maximum LOD score calculated using the correct genetic parameter value, appeared to be robust to the generating models.