Uterine Synchronization Analysis During Pregnancy and Labor Using Graph Theory,Classification Based on Neural Network and Deep Learning

1) ObjectivesPreterm birth caused by preterm labor is one of the major health problems in the world. In this article, we present a new framework for dealing with this problem through the processing of electrohysterographic signals (EHG) that are recorded during labor and pregnancy. The objective in this research is to improve the classification between labor and pregnancy contractions by using a new approach that focuses on the connectivity analysis based on graph parameters, representative of uterine synchronization, and comparing neural network and machine learning methods in order to classify between labor and pregnancy.2) Material and methodsafter denoising of the 16 EHG signals recorded from pregnant women abdomen, we applied different connectivity methods to obtain connectivity matrices; then by using the graph theory, we extracted some graph parameters from the connectivity matrices; finally, we tested different neural network and machine learning methods on the features obtained from both graph and connectivity methods in order to classify between labor and pregnancy.3) ResultsThe best results were obtained by using the logistic regression method. We also evidence the power of graph parameters extracted from the connectivity matrices to improve the classification results.4) ConclusionThe use of graph analysis associated with machine learning methods can be a powerful tool to improve labor and pregnancy classification based on the analysis of EHG signals.     

Phytostructural characterization of several vegetation types in northern Portugal. II. The structural expressivity and the resistance of the vegetation

Abstract

The encouraging results obtained in a previous work induced the authors to pursue here the characterization of the structure of the vegetation in northern Portugal, using the phytostructural methodology proposed earlier by the authors. With this objective, eight different types of vegetal communities, representative of the apparent states of the successional process present in this area, and representing the diversity of plant community types in the same area, were selected. The phytostructural method was elaborated on the basis of three types of structural basic matrices regarding diversity, abundance and cover. The data obtained were collected in a contingency matrix, which was then treated by means of a statistical multivariate analysis. Three structural tendencies emerged from this analysis. With the aim of studying their stability, the results are discussed in terms of resistance and resilience, according to the Highest Expressive Amplitude (HEA) concept, and by considering the intra- and inter-community structural dynamics as structural parameters. The data obtained suggest structural situations with different degrees of non-equilibrium that reflect resistance to environmental factors. The resistance of the vegetation is correlated with the apparent functional connectivity detected for the communities analysed.     

Character coupling for taxa discrimination: a critical appraisal of quadratic assignment procedures (QAP)1

Taxa can be characterized by character coupling represented in similarity matrices. The customary methods of testing equality of variance-covariance matrices are based upon the multinormality assumption which is, however, frequently unacceptable in reality. Quadratic assignment procedures (QAP) have proved to be an alternative. They represent a type of computer-based test and utilize a random-permutation strategy to discover significant pattern correspondences between matrices. A comparison of the applicability of both testing methods requires an example with underlying multinormality. The samples of two species of land snails (Pulmonata, Helicidae), i. e. Arianta arbustorum (n = 104) and Arianta chamaeleon (n = 36), fulfil this requirement. Four parameters of shape and two parameters of spiral change were determined in each shell. The data serve as the basis for similarity matrices (variance-covariance, product-moment and rank order correlations). The inspection of methods reveals that QAP are suitable for correlation matrices, but can be applied for variance-covariance matrices with limitations only. Nevertheless, they are recommended procedures in taxonomy and evolutionary biology. Straightforward application, independence from distributional assumptions, and the possibility to test hypotheses of character coupling are advantageous features. The snail species are significantly discriminated by character coupling. Also, their parameters of shape and spiral change are morphologically integrated in a different way.     

Adaptive strategy for the statistical analysis of connectomes

We study an adaptive statistical approach to analyze brain networks represented by brain connection matrices of interregional connectivity (connectomes). Our approach is at a middle level between a global analysis and single connections analysis by considering subnetworks of the global brain network. These subnetworks represent either the inter-connectivity between two brain anatomical regions or by the intra-connectivity within the same brain anatomical region. An appropriate summary statistic, that characterizes a meaningful feature of the subnetwork, is evaluated. Based on this summary statistic, a statistical test is performed to derive the corresponding p-value. The reformulation of the problem in this way reduces the number of statistical tests in an orderly fashion based on our understanding of the problem. Considering the global testing problem, the p-values are corrected to control the rate of false discoveries. Finally, the procedure is followed by a local investigation within the significant subnetworks. We contrast this strategy with the one based on the individual measures in terms of power. We show that this strategy has a great potential, in particular in cases where the subnetworks are well defined and the summary statistics are properly chosen. As an application example, we compare structural brain connection matrices of two groups of subjects with a 22q11.2 deletion syndrome, distinguished by their IQ scores.     

Quantifying the link between anatomical connectivity, gray matter volume and regional cerebral blood flow: an integrative MRI study

Background

In the graph theoretical analysis of anatomical brain connectivity, the white matter connections between regions of the brain are identified and serve as basis for the assessment of regional connectivity profiles, for example, to locate the hubs of the brain. But regions of the brain can be characterised further with respect to their gray matter volume or resting state perfusion. Local anatomical connectivity, gray matter volume and perfusion are traits of each brain region that are likely to be interdependent, however, particular patterns of systematic covariation have not yet been identified.

Methodology/Principal Findings

We quantified the covariation of these traits by conducting an integrative MRI study on 23 subjects, utilising a combination of Diffusion Tensor Imaging, Arterial Spin Labeling and anatomical imaging. Based on our hypothesis that local connectivity, gray matter volume and perfusion are linked, we correlated these measures and particularly isolated the covariation of connectivity and perfusion by statistically controlling for gray matter volume. We found significant levels of covariation on the group- and regionwise level, particularly in regions of the Default Brain Mode Network.

Conclusions/Significance

Connectivity and perfusion are systematically linked throughout a number of brain regions, thus we discuss these results as a starting point for further research on the role of homology in the formation of functional connectivity networks and on how structure/function relationships can manifest in the form of such trait interdependency.     

Measuring Evolutionary Constraints Through the Dimensionality of the Phenotype: Adjusted Bootstrap Method to Estimate Rank of Phenotypic Covariance Matrices

The potential and direction of phenotypic evolution is constrained by the distribution of genetic variation for the traits as described by the phenotypic (P) and genetic covariance matrices (G). The rank of the covariance matrix reflects the number of independent variational dimensions of the phenotype. Covariance matrices with less than full rank indicate lack of variation in some directions of the phenotype space and thus are an indication of absolute evolutionary constraints. Because selection acts upon phenotypic variation, the rank of P represents the upper limit of the dimensionality in G, relevant for selection response. The limitations of current methods to estimate matrix rank motivated us to analyze and adjust a bootstrap method and evaluate its performance by simulation. The results show that the modified bootstrap method (ABRE) gives reliable and rather conservative rank estimates when the sample size is sufficient for the number of variables studied (the sample size is at least five-fold the number of variables). Applying the method to various datasets suggests high phenotypic dimensionality in all cases. The analysis thus provides no evidence for absolute evolutionary constraints. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

A mechanistic damage model for ligaments

PurposeThe accuracy of biomechanical models is predicated on the realism by which they represent their biomechanical tissues. Unfortunately, most models use phenomenological ligament models that neglect the behaviour in the failure region. Therefore, the purpose of this investigation was to test whether a mechanistic model of ligamentous tissue portrays behaviour representative of actual ligament failure tests.ModelThe model tracks the time-evolution of a population of collagen fibres in a theoretical ligament. Each collagen fibre is treated as an independent linear cables with constant stiffness. Model equations were derived by assuming these fibres act as a continuum and applying a conservation law akin to Huxley’s muscle model. A breaking function models the rate of collagen fibre breakage at a given displacement, and was chosen to be a linear function for this preliminary analysis.MethodsThe model was fitted to experimental average curves for the cervical anterior longitudinal ligament. In addition, the model was cyclically loaded to test whether the tissue model behaves similarly.ResultsThe model agreed very well with experiment with an RMS error of 14.23 N and an R² of 0.995. Cyclic loading exhibited a reduction in force similar to experimental data.Discussion and conclusionThe proposed model showcases behaviour reminiscent of actual ligaments being strained to failure and undergoing cyclic load. Future work could incorporate viscous effects, or validate the model further by testing it in various loading conditions. Characterizing the breaking function more accurately would also lead to better results.     

Shotgun Crystallization Strategy for Structural Genomics II: Crystallization Conditions that Produce High Resolution Structures for T. maritima Proteins

Currently, 119 high resolution structures of Thermotoga maritima proteins have been determined by the Joint Center for Structural Genomics (JCSG, www.jcsg.org). Sixty-seven of these were solved using the first implementation of the multi-tiered crystallization strategy at the JCSG for the efficient crystallization of large numbers of protein targets. Previously, we reported the analysis of all proteins crystallized using this multi-tiered strategy [Lesley, S.A. et al. (2002) Proc. Natl. Acad. Sci. USA 99, 11664–11669; Page, R. et al. (2003) Acta Crystallogr. D Biol. Crystallogr. 59, 1028–1037]. Here, we extend the analysis and describe the crystallization characteristics of those proteins that produced diffraction quality crystals, ultimately resulting in high resolution structures. First, we found that over 77% (52) of the crystals used for structure determination were produced directly from high-throughput coarse screens, indicating that less than one quarter of the crystals (15) required fine screening. In addition, as observed for the proteome screen [Page, R. et al. (2003) Acta Crystallogr. D Biol. Crystallogr. 59, 1028–1037], the majority of conditions that produced crystals for natively expressed proteins, whose structures have been determined, were distinct from those of their more extensively purified and selenomethionine-labeled counterparts. Finally, 99% of the proteins whose structures were solved crystallized in conditions contained in the JCSG Minimal Core Screen [Page, R. et al. (2003) Acta Crystallogr. D Biol. Crystallogr. 59, 1028–1037; Page, R. and Stevens, R.C. (2004) Methods 34, 373–389], a set of 67 conditions previously identified as those most likely to produce crystals of a diverse set of proteins, confirming its success for rapid identification of proteins with a natural propensity to crystallize.     

Effective Connectivity Extracted from Resting-State fMRI Images Using Transfer Entropy

Background and objectiveBased on magnetic resonance imaging (MRI), macroscopic structural and functional connectivity of human brain has been widely explored in the last decade. However, little work has been done on effective connectivity between individual brain parcels. In this preliminary study, we aim to investigate whole-brain effective connectivity networks from resting-state functional MRI (rs-fMRI) images.Material and methodsAfter the functional connectivity networks of 26 healthy subjects (aged from 25 to 35 years old) from Human Connectome Project database were derived from rs-fMRI images with dynamic time warping, proportional thresholding (PT) was performed on the functional connectivity matrices by retaining the PT% strongest functional connections. PT% ranges from 40% to 10% in steps of 5%. Then, effective connections corresponding to the PT% strongest functional connections, both bi-directional and unidirectional, were estimated with Renyi's 2-order transfer entropy (TE) method. Topological metrics of the built functional and effective connectivity networks were further characterized, including clustering coefficient, transitivity, and modularity.ResultsIt is found that the effective connectivity networks exhibit small world attributes, and that the networks contain a subset of highly interactive regions, including right frontal pole (in-degree 6), left middle frontal gyrus (in-degree 8, out-degree 1), right precentral gyrus (out-degree 9), left precentral gyrus (out-degree 7), right posterior division of supramarginal gyrus (in-degree 2, out-degree 3), left angular gyrus (out-degree 6), left inferior division of lateral occipital cortex (out-degree 6), right occipital pole (in-degree 5), right cerebellum 7b parcel (in-degree 15), and right cerebellum 8 parcel (in-degree 7, out-degree 1).ConclusionsThe observations in this study provide information about the casual interactions among brain parcels in resting state, helping reveal how different subregions of large-scale distributed neural networks are coupled together in performing cognitive functions.     

The taxa of Scottish bracken in a European perspective

Summary

In contrast to the traditional view that Scottish Bracken (Pteridium Scop., Hypolepidaceae sensu Page, 1976) is a single, uniform taxon, evidence is presented that two species, each represented by multiple subspecies, are present in Scotland. These belong to two different species complexes within Pteridium, the P. aquilinum complex and the P. latiusculum complex. The P. aquilinum complex is represented by P. aquilinum (L.) Kuhn, with at least three subspecies: subsp. aquilinum, subsp. atlanticum C.N. Page and subsp. fulvum C.N. Page. The P. latiusculum complex is represented by P. pinetorum C.N. Page & R.R. Mill with at least two subspecies, subsp. pinetorum and subsp. osmundaceum (Christ) C.N. Page. Only P. aquilinum subsp. aquilinum is an aggressive weed which is a widespread problem to man; the others are rare. The paper establishes the nomenclatural priorities, typification, taxonomy, morphology, known distribution and ecology of all bracken taxa so far known from Scotland. The typification of P. aquilinum is discussed. There is no conflict between the two lectotypifications of Try on (1941) and Sheffield et al. (1989); both relate to the common bracken of the mid- and southern-latitudes of Europe, for which the existing epithet aquilinum must therefore be retained. It is pointed out that some of the other European taxa of bracken might well also yet be found within the British Isles, as well as, perhaps, other (especially possible diploid) taxa as yet undescribed.     

Scottish bracken (Pteridium): New taxa and a new combination

Summary

In advance of two forthcoming works in which the names will be used, one new species of Pteridium (P. pinetorum C.N. Page & R.R. Mill) and one new subspecies (P. aquilinum (L.) Kuhn subsp. fulvum C.N. Page) are formally described, and one new combination made (P. pinetorum C.N. Page & R .R. Mill subsp. osmundaceum (Christ) C. N. Page, comb, et stat. nov.).     

偏头痛患者体感刺激下脑电信号的功能连接（英文）

目的 偏头痛是一种复杂的脑功能障碍性疾病,全球范围内患病率为14.4%。功能连接测量两个神经信号之间的统计学相互依赖性,不同的功能连接反映了大脑区域协同工作的不同模式。因此,研究不同脑区的功能连接对于理解偏头痛的病理生理机制具有十分重要的意义。以往基于脑电图对偏头痛患者脑功能连接的分析主要集中在视觉和疼痛刺激。本文尝试研究偏头痛患者在发作间期对体感刺激的皮质反应,以进一步了解偏头痛的神经功能障碍,为偏头痛的预防和治疗提供线索。方法 招募23例无先兆偏头痛患者,10例有先兆偏头痛患者,28名健康对照者。所有受试者均进行详细的基本资料和病史采集,完善量表评估,在正中神经体感刺激下进行脑电图记录。计算68个脑区的相干性作为功能连接,并评估功能连接与临床参数的相关性。结果 在正中神经体感刺激下,无先兆偏头痛和有先兆偏头痛患者的脑电功能连接与对照组相比存在差异,异常的脑电功能连接主要位于感觉辨别、疼痛调节、情绪认知和视觉处理等区域。无先兆偏头痛和有先兆偏头痛患者的大脑皮层对体感刺激可能具有相同的反应方式。偏头痛患者的功能连接异常与临床特征之间存在相关性,可以部分反映偏头痛的严重程度。结论 本研究...     

Bacterial Protein Interaction Networks: Connectivity is Ruled by Gene Conservation,Essentiality and Function

BackgroundProtein-protein interaction (PPI) networks are the backbone of all processes in living cells. In this work, we relate conservation, essentiality and functional repertoire of a gene to the connectivity k (i.e. the number of interactions, links) of the corresponding protein in the PPI network.MethodsOn a set of 42 bacterial genomes of different sizes, and with reasonably separated evolutionary trajectories, we investigate three issues: i) whether the distribution of connectivities changes between PPI subnetworks of essential and nonessential genes; ii) how gene conservation, measured both by the evolutionary retention index (ERI) and by evolutionary pressures, is related to the connectivity of the corresponding protein; iii) how PPI connectivities are modulated by evolutionary and functional relationships, as represented by the Clusters of Orthologous Genes (COGs).ResultsWe show that conservation, essentiality and functional specialisation of genes constrain the connectivity of the corresponding proteins in bacterial PPI networks. In particular, we isolated a core of highly connected proteins (connectivities k≥40), which is ubiquitous among the species considered here, though mostly visible in the degree distributions of bacteria with small genomes (less than 1000 genes).ConclusionThe genes that support this highly connected core are conserved, essential and, in most cases, belong to the COG cluster J, related to ribosomal functions and the processing of genetic information.     

A dinosaur ichnocoenosis from the middle jurassic of Yorkshire,UK

An assemblage of dinosaur tracks from the undersurface of a sandstone bed in the Saltwick Formation (Middle Jurassic) of Yorkshire shows a range of morphological types, preservational variants and behavioral styles. The tracks are combinations of transmitted prints and underprints and include three distinct trackways. One trackway was made by an animal walking on exposed damp sand, another was left by an animal swimming diagonally across a current and being swept down current, while the third may have been made by an animal either running or pushing off with its feet as it drifted down current. Environmental conditions that existed during the formation of the trackways varied between crevasse splay floods and exposed damp sand. The morphology of the swimming tracks is sufficiently distinctive to warrant the erection of a new ichnogenus and ichnospecies—Characichnos tridactylus. Previously described material from Kansas, Wyoming and New Mexico can be attributed to this new ichnogenus, while specimens from Germany and Utah are only provisionally referred to it. This indicates a known range from Triassic to Cretaceous.     

Parsimony analysis of endemicity as a panbiogeographical tool: an analysis of Caribbean plant taxa

To demonstrate that parsimony analysis of endemicity (PAE) can be a method implementing the panbiogeographic approach, we analyzed two data matrices of 40/38 biogeographic provinces × 148 plant species from the Caribbean subregion of the Neotropical region, one where taxa are represented by individual tracks and the other where taxa are represented by single sample localities. We obtained six generalized tracks resulted from the PAE of the areas × individual tracks matrix, and one generalized track from the PAE of the areas × single sample localities matrix, with the latter nested within the former tracks. The results obtained show that PAE works as a panbiogeographical tool if it is based on an areas × individual tracks matrix. When performed in this way, PAE retrieves spatial information that is lost when it is based on an areas × single sample localities matrix, raising doubts regarding the conclusions derived from this latter type of analysis. © 2010 The Linnean Society of London, Biological Journal of the Linnean Society, 2010, 101 , 961–976.     

Connectivity,reproduction number,and mobility interact to determine communities’ epidemiological superspreader potential in a metapopulation network

Disease epidemic outbreaks on human metapopulation networks are often driven by a small number of superspreader nodes, which are primarily responsible for spreading the disease throughout the network. Superspreader nodes typically are characterized either by their locations within the network, by their degree of connectivity and centrality, or by their habitat suitability for the disease, described by their reproduction number (R). Here we introduce a model that considers simultaneously the effects of network properties and R on superspreaders, as opposed to previous research which considered each factor separately. This type of model is applicable to diseases for which habitat suitability varies by climate or land cover, and for direct transmitted diseases for which population density and mitigation practices influences R. We present analytical models that quantify the superspreader capacity of a population node by two measures: probability-dependent superspreader capacity, the expected number of neighboring nodes to which the node in consideration will randomly spread the disease per epidemic generation, and time-dependent superspreader capacity, the rate at which the node spreads the disease to each of its neighbors. We validate our analytical models with a Monte Carlo analysis of repeated stochastic Susceptible-Infected-Recovered (SIR) simulations on randomly generated human population networks, and we use a random forest statistical model to relate superspreader risk to connectivity, R, centrality, clustering, and diffusion. We demonstrate that either degree of connectivity or R above a certain threshold are sufficient conditions for a node to have a moderate superspreader risk factor, but both are necessary for a node to have a high-risk factor. The statistical model presented in this article can be used to predict the location of superspreader events in future epidemics, and to predict the effectiveness of mitigation strategies that seek to reduce the value of R, alter host movements, or both.     

Mind the gaps: overlooking inaccessible regions confounds statistical testing in genome analysis

Background

The current versions of reference genome assemblies still contain gaps represented by stretches of Ns. Since high throughput sequencing reads cannot be mapped to those gap regions, the regions are depleted of experimental data. Moreover, several technology platforms assay a targeted portion of the genomic sequence, meaning that regions from the unassayed portion of the genomic sequence cannot be detected in those experiments. We here refer to all such regions as inaccessible regions, and hypothesize that ignoring these regions in the null model may increase false findings in statistical testing of colocalization of genomic features.

Results

Our explorative analyses confirm that the genomic regions in public genomic tracks intersect very little with assembly gaps of human reference genomes (hg19 and hg38). The little intersection was observed only at the beginning and end portions of the gap regions. Further, we simulated a set of synthetic tracks by matching the properties of real genomic tracks in a way that nullified any true association between them. This allowed us to test our hypothesis that not avoiding inaccessible regions (as represented by assembly gaps) in the null model would result in spurious inflation of statistical significance. We contrasted the distributions of test statistics and p-values of Monte Carlo-based permutation tests that either avoided or did not avoid assembly gaps in the null model when testing colocalization between a pair of tracks. We observed that the statistical tests that did not account for assembly gaps in the null model resulted in a distribution of the test statistic that is shifted to the right and a distribution of p-values that is shifted to the left (indicating inflated significance). We observed a similar level of inflated significance in hg19 and hg38, despite assembly gaps covering a smaller proportion of the latter reference genome.

Conclusion

We provide empirical evidence demonstrating that inaccessible regions, even when covering only a few percentages of the genome, can lead to a substantial amount of false findings if not accounted for in statistical colocalization analysis.

     

Spatial heterogeneity stabilizes predator–prey interactions at the microscale while patch connectivity controls their outcome

Natural landscapes are both fragmented and heterogeneous, affecting the distribution of organisms, and their interactions. While predation in homogeneous environments increases the probability of population extinction, fragmentation/heterogeneity promotes coexistence and enhances community stability as shown by experimentation with animals and microorganisms, and supported by theory. Patch connectivity can modulate such effects but how microbial predatory interactions are affected by water-driven connectivity is unknown. In soil, patch habitability by microorganisms, and their connectivity depend upon the water saturation degree (SD). Here, using the obligate bacterial predator Bdellovibrio bacteriovorus, and a Burkholderia prey, we show that soil spatial heterogeneity profoundly affects predatory dynamics, enhancing long-term co-existence of predator and prey in a SD-threshold dependent-manner. However, as patches and connectors cannot be distinguished in these soil matrices, metapopulations cannot be invoked to explain the dynamics of increased persistence. Using a set of experiments combined with statistical and physical models we demonstrate and quantify how under full connectivity, predation is independent of water content but depends on soil microstructure characteristics. In contrast, the SD below which predation is largely impaired corresponds to a threshold below which the water network collapses and water connectivity breaks down, preventing the bacteria to move within the soil matrix.     

Comparison of Populations Based on Attribute Data,when Covariance Matrices are Unequal

Mahalanobis—like distance indices B² and G² of BALAKRISHNAN and SANGHVI (1968) are employed to compare multinomial populations of proportions in human data. Recently, BOWERING and MISRA (1982) employed these methods, with modifications, in a different field viz. to compare fish stocks, based on meristic characters. The method of BALAKRISHNAN and SANGHVI (1968), however, assumes equality of covariance matrices, which is doubtful with multinomial populations of proportions. In this paper a statistical method for comparing such populations (where covariance matrices are not equal) is presented. Also, a feature of the G² method of BALAKRISHNAN and SANGHVI (1968) is discussed, which makes its statistical status a little more clear.