Modeling epidemic spread with awareness and heterogeneous transmission rates in networks

During an epidemic outbreak in a human population, susceptibility to infection can be reduced by raising awareness of the disease. In this paper, we investigate the effects of three forms of awareness (i.e., contact, local, and global) on the spread of a disease in a random network. Connectivity-correlated transmission rates are assumed. By using the mean-field theory and numerical simulation, we show that both local and contact awareness can raise the epidemic thresholds while the global awareness cannot, which mirrors the recent results of Wu et al. The obtained results point out that individual behaviors in the presence of an infectious disease has a great influence on the epidemic dynamics. Our method enriches mean-field analysis in epidemic models.     

Mixed-model of ANOVA for measurement reproducibility in proteomics

This work is a statistical analysis of reproducibility of a MALDI-TOF mass spectrometry experiment. Its aim is to evaluate measurement variability and compare peak intensities from two types of MALDI-TOF platforms. We compared and commented on the abilities of Principal Component Analysis and mixed-model analysis of variance to evaluate the biological variability and the technical variability of peak intensities in different patients. The properties and hypotheses of both methods are summarized and applied to spectra from plasma of patients with Hodgkin lymphoma. Principal Component Analysis checks rapidly the balance between the two variabilities; however, a mixed-model analysis of variance is necessary to quantify the biological and technical components of the experimental variance as well as their interactions and to split the total variance into between-subjects and within-subject components. The latter method helped to assess the reproducibility of measurements from two MALDI-TOF platforms and to decompose the technical variability according to the experimental design.     

Can transposable element copy number distribution parameters be estimated from natural populations of Drosophila melanogaster?

The copy frequency distribution of a transposable element family in a Drosophila melanogaster natural population is generally characterised by the values of the Charlesworths' model parameters α and β (Charlesworth & Charlesworth, 1983). The estimation of these parameters is made using the observed distribution of the occupied sites in a population sample. Several results have been interpreted as due either to the influence of stochastic factors or to deterministic factors (transposition, excision, selection…). The accuracy of this method was tested by estimations performed on samples from simulated populations. The results show that with the sample size usually used for natural population studies, the confidence intervals are too large to reasonably deduce either the element copy number distribution or the values of transposition and excision rate and selective coefficients.     

Protein structure prediction using mutually orthogonal Latin squares and a genetic algorithm

We combine a new, extremely fast technique to generate a library of low energy structures of an oligopeptide (by using mutually orthogonal Latin squares to sample its conformational space) with a genetic algorithm to predict protein structures. The protein sequence is divided into oligopeptides, and a structure library is generated for each. These libraries are used in a newly defined mutation operator that, together with variation, crossover, and diversity operators, is used in a modified genetic algorithm to make the prediction. Application to five small proteins has yielded near native structures.     

Distribution of RNA binding protein MOEP19 in the oocyte cortex and early embryo indicates pre-patterning related to blastomere polarity and trophectoderm specification

We report the cloning and characterization of MOEP19, a novel 19 kDa RNA binding protein that marks a defined cortical cytoplasmic domain in oocytes and provides evidence of mammalian oocyte polarity and a form of pre-patterning that persists in zygotes and early embryos through the morula stage. MOEP19 contains a eukaryotic type KH-domain, typical of the KH-domain type I superfamily of RNA binding proteins, and both recombinant and native MOEP19 bind polynucleotides. By immunofluorescence, MOEP19 protein was first detected in primary follicles throughout the ooplasm. As oocytes expanded in size during oogenesis, MOEP19 increased in concentration. MOEP19 localized in the ovulated egg and early zygote as a symmetrical spherical cortical domain underlying the oolemma, deep to the zone of cortical granules. MOEP19 remained restricted to a cortical cytoplasmic crescent in blastomeres of 2-, 4- and 8-cell embryos. The MOEP19 domain was absent in regions underlying cell contacts. In morulae, the MOEP19 domain was found at the apex of outer, polarized blastomeres but was undetectable in blastomeres of the inner cell mass. In early blastocysts, MOEP19 localized in both mural and polar trophectoderm and a subset of embryos showed inner cell mass localization. MOEP19 concentration dramatically declined in late blastocysts. When blastomeres of 4- to 8-cell stages were dissociated, the polarized MOEP19 domain assumed a symmetrically spherical localization, while overnight culture of dissociated blastomeres resulted in formation of re-aggregated embryos in which polarity of the MOEP19 domain was re-established at the blastomere apices. MOEP19 showed no evidence of translation in ovulated eggs, indicating that MOEP19 is a maternal effect gene. The persistence during early development of the MOEP19 cortical oocyte domain as a cortical crescent in blastomers suggests an intrinsic pre-patterning in the egg that is related to the apical-basolateral polarity of the embryo. Although the RNAs bound to MOEP19 are presently unknown, we predict that the MOEP19 domain directs RNAs essential for normal embryonic development to specific locations in the oocyte and early embryo.