Impaired motor facilitation during action observation in individuals with autism spectrum disorder

It has been suggested that social impairments observed in individuals with autism spectrum disorder (ASD) can be partly explained by an abnormal mirror neuron system (MNS) 1., 2.. Studies on monkeys have shown that mirror neurons are cells in premotor area F5 that discharge when a monkey executes or sees a specific action or when it hears the corresponding action-related sound 3., 4., 5.. Evidence for the presence of a MNS in humans comes in part from studies using transcranial magnetic stimulation (TMS), where a change in the amplitude of the TMS-induced motor-evoked potentials (MEPs) during action observation has been demonstrated 6., 7., 8., 9.. These data suggest that actions are understood when the representation of that action is mapped onto the observer's own motor structures [10]. To determine if the neural mechanism matching action observation and execution is anomalous in individuals with ASD, TMS was applied over the primary motor cortex (M1) during observation of intransitive, meaningless finger movements. We show that overall modulation of M1 excitability during action observation is significantly lower in individuals with ASD compared with matched controls. In addition, we find that basic motor cortex abnormalities do not underlie this impairment.     

Spectral signal-to-noise ratio and resolution assessment of 3D reconstructions

Measuring the quality of three-dimensional (3D) reconstructed biological macromolecules by transmission electron microscopy is still an open problem. In this article, we extend the applicability of the spectral signal-to-noise ratio (SSNR) to the evaluation of 3D volumes reconstructed with any reconstruction algorithm. The basis of the method is to measure the consistency between the data and a corresponding set of reprojections computed for the reconstructed 3D map. The idiosyncrasies of the reconstruction algorithm are taken explicitly into account by performing a noise-only reconstruction. This results in the definition of a 3D SSNR which provides an objective indicator of the quality of the 3D reconstruction. Furthermore, the information to build the SSNR can be used to produce a volumetric SSNR (VSSNR). Our method overcomes the need to divide the data set in two. It also provides a direct measure of the performance of the reconstruction algorithm itself; this latter information is typically not available with the standard resolution methods which are primarily focused on reproducibility alone.     

Proteomic analysis of amniotic fluid in pregnancies with Klinefelter syndrome foetuses

Klinefelter syndrome is a sex chromosomal abnormality (47, XXY karyotype), occurring approximately in 1 in 1000 male live births. In the present study proteomic analysis was performed in twelve 2nd trimester amniotic fluid samples, eight coming from pregnancies with normal males and four with Klinefelter syndrome foetuses, as shown by routine prenatal cytogenetic analysis. Samples were analysed by 2-DE, coupled with MALDI-TOF-MS analysis. Three proteins (Ceruloplasmin, Alpha-1-antitrypsin and Zinc-alpha-2-glycoprotein) were found to be up-regulated in samples obtained from pregnancies with Klinefelter syndrome foetuses, whereas four proteins (Apolipoprotein A-I, Plasma retinol-binding protein, Gelsolin, and Vitamin D-binding protein) were down regulated when compared to proteins detected in samples from normal foetuses. The differential expression of Ceruloplasmin, Apolipoprotein A-I and Plasma retinol-binding protein was further confirmed by immunoblotting. Since these proteins are likely to cross the placenta barrier and be detected in maternal plasma they could be used as biomarkers for the non-invasive prenatal diagnosis of Klinefelter syndrome.     

Une lettre inédite de Alexander von Humboldt sur les termites du Pérou

Sans résumé     

Book reviews

Ohne Zusammenfassung

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Book reviews

     

Metabolic discrimination of Catharanthus roseus leaves infected by phytoplasma using 1H-NMR spectroscopy and multivariate data analysis

A comprehensive metabolomic profiling of Catharanthus roseus L. G. Don infected by 10 types of phytoplasmas was carried out using one-dimensional and two-dimensional NMR spectroscopy followed by principal component analysis (PCA), an unsupervised clustering method requiring no knowledge of the data set and used to reduce the dimensionality of multivariate data while preserving most of the variance within it. With a combination of these techniques, we were able to identify those metabolites that were present in different levels in phytoplasma-infected C. roseus leaves than in healthy ones. The infection by phytoplasma in C. roseus leaves causes an increase of metabolites related to the biosynthetic pathways of phenylpropanoids or terpenoid indole alkaloids: chlorogenic acid, loganic acid, secologanin, and vindoline. Furthermore, higher abundance of Glc, Glu, polyphenols, succinic acid, and Suc were detected in the phytoplasma-infected leaves. The PCA of the (1)H-NMR signals of healthy and phytoplasma-infected C. roseus leaves shows that these metabolites are major discriminating factors to characterize the phytoplasma-infected C. roseus leaves from healthy ones. Based on the NMR and PCA analysis, it might be suggested that the biosynthetic pathway of terpenoid indole alkaloids, together with that of phenylpropanoids, is stimulated by the infection of phytoplasma.     

Socio-economic and Climate Factors Associated with Dengue Fever Spatial Heterogeneity: A Worked Example in New Caledonia

Background/Objectives

Understanding the factors underlying the spatio-temporal distribution of infectious diseases provides useful information regarding their prevention and control. Dengue fever spatio-temporal patterns result from complex interactions between the virus, the host, and the vector. These interactions can be influenced by environmental conditions. Our objectives were to analyse dengue fever spatial distribution over New Caledonia during epidemic years, to identify some of the main underlying factors, and to predict the spatial evolution of dengue fever under changing climatic conditions, at the 2100 horizon.

Methods

We used principal component analysis and support vector machines to analyse and model the influence of climate and socio-economic variables on the mean spatial distribution of 24,272 dengue cases reported from 1995 to 2012 in thirty-three communes of New Caledonia. We then modelled and estimated the future evolution of dengue incidence rates using a regional downscaling of future climate projections.

Results

The spatial distribution of dengue fever cases is highly heterogeneous. The variables most associated with this observed heterogeneity are the mean temperature, the mean number of people per premise, and the mean percentage of unemployed people, a variable highly correlated with people''s way of life. Rainfall does not seem to play an important role in the spatial distribution of dengue cases during epidemics. By the end of the 21st century, if temperature increases by approximately 3°C, mean incidence rates during epidemics could double.

Conclusion

In New Caledonia, a subtropical insular environment, both temperature and socio-economic conditions are influencing the spatial spread of dengue fever. Extension of this study to other countries worldwide should improve the knowledge about climate influence on dengue burden and about the complex interplay between different factors. This study presents a methodology that can be used as a step by step guide to model dengue spatial heterogeneity in other countries.