Superiority of Classification Tree versus Cluster,Fuzzy and Discriminant Models in a Heartbeat Classification System

This study presents a 2-stage heartbeat classifier of supraventricular (SVB) and ventricular (VB) beats. Stage 1 makes computationally-efficient classification of SVB-beats, using simple correlation threshold criterion for finding close match with a predominant normal (reference) beat template. The non-matched beats are next subjected to measurement of 20 basic features, tracking the beat and reference template morphology and RR-variability for subsequent refined classification in SVB or VB-class by Stage 2. Four linear classifiers are compared: cluster, fuzzy, linear discriminant analysis (LDA) and classification tree (CT), all subjected to iterative training for selection of the optimal feature space among extended 210-sized set, embodying interactive second-order effects between 20 independent features. The optimization process minimizes at equal weight the false positives in SVB-class and false negatives in VB-class. The training with European ST-T, AHA, MIT-BIH Supraventricular Arrhythmia databases found the best performance settings of all classification models: Cluster (30 features), Fuzzy (72 features), LDA (142 coefficients), CT (221 decision nodes) with top-3 best scored features: normalized current RR-interval, higher/lower frequency content ratio, beat-to-template correlation. Unbiased test-validation with MIT-BIH Arrhythmia database rates the classifiers in descending order of their specificity for SVB-class: CT (99.9%), LDA (99.6%), Cluster (99.5%), Fuzzy (99.4%); sensitivity for ventricular ectopic beats as part from VB-class (commonly reported in published beat-classification studies): CT (96.7%), Fuzzy (94.4%), LDA (94.2%), Cluster (92.4%); positive predictivity: CT (99.2%), Cluster (93.6%), LDA (93.0%), Fuzzy (92.4%). CT has superior accuracy by 0.3–6.8% points, with the advantage for easy model complexity configuration by pruning the tree consisted of easy interpretable ‘if-then’ rules.     

Genomic Ancestry,Self-Rated Health and Its Association with Mortality in an Admixed Population: 10 Year Follow-Up of the Bambui-Epigen (Brazil) Cohort Study of Ageing

Background

Self-rated health (SRH) has strong predictive value for mortality in different contexts and cultures, but there is inconsistent evidence on ethnoracial disparities in SRH in Latin America, possibly due to the complexity surrounding ethnoracial self-classification.

Materials/Methods

We used 370,539 Single Nucleotide Polymorphisms (SNPs) to examine the association between individual genomic proportions of African, European and Native American ancestry, and ethnoracial self-classification, with baseline and 10-year SRH trajectories in 1,311 community dwelling older Brazilians. We also examined whether genomic ancestry and ethnoracial self-classification affect the predictive value of SRH for subsequent mortality.

Results

European ancestry predominated among participants, followed by African and Native American (median = 84.0%, 9.6% and 5.3%, respectively); the prevalence of Non-White (Mixed and Black) was 39.8%. Persons at higher levels of African and Native American genomic ancestry, and those self-identified as Non-White, were more likely to report poor health than other groups, even after controlling for socioeconomic conditions and an array of self-reported and objective physical health measures. Increased risks for mortality associated with worse SRH trajectories were strong and remarkably similar (hazard ratio ~3) across all genomic ancestry and ethno-racial groups.

Conclusions

Our results demonstrated for the first time that higher levels of African and Native American genomic ancestry—and the inverse for European ancestry—were strongly correlated with worse SRH in a Latin American admixed population. Both genomic ancestry and ethnoracial self-classification did not modify the strong association between baseline SRH or SRH trajectory, and subsequent mortality.     

Reconstruction of the Evolutionary Dynamics of A(H3N2) Influenza Viruses Circulating in Italy from 2004 to 2012

Background

Influenza A viruses are characterised by their rapid evolution, and the appearance of point mutations in the viral hemagglutinin (HA) domain causes seasonal epidemics. The A(H3N2) virus has higher mutation rate than the A(H1N1) virus. The aim of this study was to reconstruct the evolutionary dynamics of the A(H3N2) viruses circulating in Italy between 2004 and 2012 in the light of the forces driving viral evolution.

Methods

Phylodinamic analyses were made using a Bayesian method, and codon-specific positive selection acting on the HA coding sequence was evaluated.

Results

Global and local phylogenetic analyses showed that the Italian strains collected between 2004 and 2012 grouped into five significant Italian clades that included viral sequences circulating in different epidemic seasons. The time of the most recent common ancestor (tMRCA) of the tree root was between May and December 2003. The tMRCA estimates of the major clades suggest that the origin of a new viral strain precedes the effective circulation of the strain in the Italian population by 6–31 months, thus supporting a central role of global migration in seeding the epidemics in Italy. The study of selection pressure showed that four codons were under positive selection, three of which were located in antigenic sites. Analysis of population dynamics showed the alternation of periods of exponential growth followed by a decrease in the effective number of infections corresponding to epidemic and inter-epidemic seasons.

Conclusions

Our analyses suggest that a complex interaction between the immune status of the population, migrations, and a few selective sweeps drive the influenza A(H3N2) virus evolution. Our findings suggest the possibility of the year-round survival of local strains even in temperate zones, a hypothesis that warrants further investigation.     

Resistance to change and vulnerability to stress: autistic‐like features of GAP43‐deficient mice

There is an urgent need for animal models of autism spectrum disorder (ASD) to understand the underlying pathology and facilitate development and testing of new treatments. The synaptic growth‐associated protein‐43 (GAP43) has recently been identified as an autism candidate gene of interest. Our previous studies show many brain abnormalities in mice lacking one allele for GAP43 [GAP43 (+/?)] that are consistent with the disordered connectivity theory of ASD. Thus, we hypothesized that GAP43 (+/?) mice would show at least some autistic‐like behaviors. We found that GAP43 (+/?) mice, relative to wild‐type (+/+) littermates, displayed resistance to change, consistent with one of the diagnostic criteria for ASD. GAP43 (+/?) mice also displayed stress‐induced behavioral withdrawal and anxiety, as seen in many autistic individuals. In addition, both GAP43 (+/?) mice and (+/+) littermates showed low social approach and lack of preference for social novelty, consistent with another diagnostic criterion for ASD. This low sociability is likely because of the mixed C57BL/6J 129S3/SvImJ background. We conclude that GAP43 deficiency leads to the development of a subset of autistic‐like behaviors. As these behaviors occur in a mouse that displays disordered connectivity, we propose that future anatomical and functional studies in this mouse may help uncover underlying mechanisms for these specific behaviors. Strain‐specific low sociability may be advantageous in these studies, creating a more autistic‐like environment for study of the GAP43‐mediated deficits of resistance to change and vulnerability to stress.     

Tissue- and stimulus-dependent role of phosphatidylinositol 3-kinase isoforms for neutrophil recruitment induced by chemoattractants in vivo

PI3K plays a fundamental role in regulating neutrophil recruitment into sites of inflammation but the role of the different isoforms of PI3K remains unclear. In this study, we evaluated the role of PI3Kgamma and PI3Kdelta for neutrophil influx induced by the exogenous administration or the endogenous generation of the chemokine CXCL1. Administration of CXCL1 in PI3Kgamma(-/-) or wild-type (WT) mice induced similar increases in leukocyte rolling, adhesion, and emigration in the cremaster muscle when examined by intravital microscopy. The induction of neutrophil recruitment into the pleural cavity or the tibia-femoral joint induced by the injection of CXCL1 was not significantly different in PI3Kgamma(-/-) or WT mice. Neutrophil influx was not altered by treatment of WT mice with a specific PI3Kdelta inhibitor, IC87114, or a specific PI3Kgamma inhibitor, AS605240. The administration of IC87114 prevented CXCL1-induced neutrophil recruitment only in presence of the PI3Kgamma inhibitor or in PI3Kgamma(-/-) mice. Ag challenge of immunized mice induced CXCR2-dependent neutrophil recruitment that was inhibited by wortmannin or by blockade of and PI3Kdelta in PI3Kgamma(-/-) mice. Neutrophil recruitment to bronchoalveolar lavage induced by exogenously added or endogenous production of CXCL1 was prevented in PI3Kgamma(-/-) mice. The accumulation of the neutrophils in lung tissues was significantly inhibited only in PI3Kgamma(-/-) mice treated with IC87114. Neutrophil recruitment induced by exogenous administration of C5a or fMLP appeared to rely solely on PI3Kgamma. Altogether, our data demonstrate that there is a tissue- and stimulus-dependent role of PI3Kgamma and PI3Kdelta for neutrophil recruitment induced by different chemoattractants in vivo.