Effect of predictive sign of acceleration on heart rate variability in passive translation situation: preliminary evidence using visual and vestibular stimuli in VR environment

<p>Abstract</p> <p>Objective</p> <p>We studied the effects of the presentation of a visual sign that warned subjects of acceleration around the yaw and pitch axes in virtual reality (VR) on their heart rate variability.</p> <p>Methods</p> <p>Synchronization of the immersive virtual reality equipment (CAVE) and motion base system generated a driving scene and provided subjects with dynamic and wide-ranging depth information and vestibular input. The heart rate variability of 21 subjects was measured while the subjects observed a simulated driving scene for 16 minutes under three different conditions.</p> <p>Results</p> <p>When the predictive sign of the acceleration appeared 3500 ms before the acceleration, the index of the activity of the autonomic nervous system (low/high frequency ratio; LF/HF ratio) of subjects did not change much, whereas when no sign appeared the LF/HF ratio increased over the observation time. When the predictive sign of the acceleration appeared 750 ms before the acceleration, no systematic change occurred.</p> <p>Conclusion</p> <p>The visual sign which informed subjects of the acceleration affected the activity of the autonomic nervous system when it appeared long enough before the acceleration. Also, our results showed the importance of the interval between the sign and the event and the relationship between the gradual representation of events and their quantity.</p

Comparative Membranome Expression Analysis in Primary Tumors and Derived Cell Lines

Despite the wide use of cell lines in cancer research, the extent to which their surface properties correspond to those of primary tumors is poorly characterized. The present study addresses this problem from a transcriptional standpoint, analyzing the expression of membrane protein genes - the Membranome – in primary tumors and immortalized in-vitro cultured tumor cells. 409 human samples, deriving from ten independent studies, were analyzed. These comprise normal tissues, primary tumors and tumor derived cell lines deriving from eight different tissues: brain, breast, colon, kidney, leukemia, lung, melanoma, and ovary. We demonstrated that the Membranome has greater power than the remainder of the transcriptome when used as input for the automatic classification of tumor samples. This feature is maintained in tumor derived cell lines. In most cases primary tumors show maximal similarity in Membranome expression with cell lines of same tissue origin. Differences in Membranome expression between tumors and cell lines were analyzed also at the pathway level and biological themes were identified that were differentially regulated in the two settings. Moreover, by including normal samples in the analysis, we quantified the degree to which cell lines retain the Membranome up- and down- regulations observed in primary tumors with respect to their normal counterparts. We showed that most of the Membranome up-regulations observed in primary tumors are lost in the in-vitro cultured cells. Conversely, the majority of Membranome genes down-regulated upon tumor transformation maintain lower expression levels also in the cell lines. This study points towards a central role of Membranome genes in the definition of the tumor phenotype. The comparative analysis of primary tumors and cell lines identifies the limits of cell lines as a model for the study of cancer-related processes mediated by the cell surface. Results presented allow for a more rational use of the cell lines as a model of cancer

Assessing the Value of DNA Barcodes and Other Priority Gene Regions for Molecular Phylogenetics of Lepidoptera

BACKGROUND: Despite apparently abundant amounts of observable variation and species diversity, the order Lepidoptera exhibits a morphological homogeneity that has provided only a limited number of taxonomic characters and led to widespread use of nucleotides for inferring relationships. This study aims to characterize and develop methods to quantify the value of priority gene regions designated for Lepidoptera molecular systematics. In particular, I assess how the DNA barcode segment of the mitochondrial COI gene performs across a broad temporal range given its number one position of priority, most sequenced status, and the conflicting opinions on its phylogenetic performance. METHODOLOGY/PRINCIPAL FINDINGS: Gene regions commonly sequenced for lepidoptera phylogenetics were scored using multiple measures across three categories: practicality, which includes universality of primers and sequence quality; phylogenetic utility; and phylogenetic signal. I found that alternative measures within a category often appeared correlated, but high scores in one category did not necessarily translate into high scores in another. The DNA barcode was easier to sequence than other genes, and had high scores for utility but low signal above the genus level. CONCLUSIONS/SIGNIFICANCE: Given limited financial resources and time constraints, careful selection of gene regions for molecular phylogenetics is crucial to avoid wasted effort producing partially informative data. This study introduces an approach to assessing the value of gene regions prior to the initiation of new studies and presents empirical results to help guide future selections

Gene-Based Tests of Association

Genome-wide association studies (GWAS) are now used routinely to identify SNPs associated with complex human phenotypes. In several cases, multiple variants within a gene contribute independently to disease risk. Here we introduce a novel Gene-Wide Significance (GWiS) test that uses greedy Bayesian model selection to identify the independent effects within a gene, which are combined to generate a stronger statistical signal. Permutation tests provide p-values that correct for the number of independent tests genome-wide and within each genetic locus. When applied to a dataset comprising 2.5 million SNPs in up to 8,000 individuals measured for various electrocardiography (ECG) parameters, this method identifies more validated associations than conventional GWAS approaches. The method also provides, for the first time, systematic assessments of the number of independent effects within a gene and the fraction of disease-associated genes housing multiple independent effects, observed at 35%–50% of loci in our study. This method can be generalized to other study designs, retains power for low-frequency alleles, and provides gene-based p-values that are directly compatible for pathway-based meta-analysis

Targeted sequencing of lung function loci in chronic obstructive pulmonary disease cases and controls

Chronic obstructive pulmonary disease (COPD) is the third leading cause of death worldwide; smoking is the main risk factor for COPD, but genetic factors are also relevant contributors. Genome-wide association studies (GWAS) of the lung function measures used in the diagnosis of COPD have identified a number of loci, however association signals are often broad and collectively these loci only explain a small proportion of the heritability. In order to examine the association with COPD risk of genetic variants down to low allele frequencies, to aid fine-mapping of association signals and to explain more of the missing heritability, we undertook a targeted sequencing study in 300 COPD cases and 300 smoking controls for 26 loci previously reported to be associated with lung function. We used a pooled sequencing approach, with 12 pools of 25 individuals each, enabling high depth (30x) coverage per sample to be achieved. This pooled design maximised sample size and therefore power, but led to challenges during variant-calling since sequencing error rates and minor allele frequencies for rare variants can be very similar. For this reason we employed a rigorous quality control pipeline for variant detection which included the use of 3 independent calling algorithms. In order to avoid false positive associations we also developed tests to detect variants with potential batch effects and removed them before undertaking association testing. We tested for the effects of single variants and the combined effect of rare variants within a locus. We followed up the top signals with data available (only 67% of collapsing methods signals) in 4,249 COPD cases and 11,916 smoking controls from UK Biobank. We provide suggestive evidence for the combined effect of rare variants on COPD risk in TNXB and in sliding windows within MECOM and upstream of HHIP. These findings can lead to an improved understanding of the molecular pathways involved in the development of COPD

TRAM (Transcriptome Mapper): database-driven creation and analysis of transcriptome maps from multiple sources

<p>Abstract</p> <p>Background</p> <p>Several tools have been developed to perform global gene expression profile data analysis, to search for specific chromosomal regions whose features meet defined criteria as well as to study neighbouring gene expression. However, most of these tools are tailored for a specific use in a particular context (e.g. they are species-specific, or limited to a particular data format) and they typically accept only gene lists as input.</p> <p>Results</p> <p>TRAM (Transcriptome Mapper) is a new general tool that allows the simple generation and analysis of quantitative transcriptome maps, starting from any source listing gene expression values for a given gene set (e.g. expression microarrays), implemented as a relational database. It includes a parser able to assign univocal and updated gene symbols to gene identifiers from different data sources. Moreover, TRAM is able to perform intra-sample and inter-sample data normalization, including an original variant of quantile normalization (scaled quantile), useful to normalize data from platforms with highly different numbers of investigated genes. When in 'Map' mode, the software generates a quantitative representation of the transcriptome of a sample (or of a pool of samples) and identifies if segments of defined lengths are over/under-expressed compared to the desired threshold. When in 'Cluster' mode, the software searches for a set of over/under-expressed consecutive genes. Statistical significance for all results is calculated with respect to genes localized on the same chromosome or to all genome genes. Transcriptome maps, showing differential expression between two sample groups, relative to two different biological conditions, may be easily generated. We present the results of a biological model test, based on a meta-analysis comparison between a sample pool of human CD34+ hematopoietic progenitor cells and a sample pool of megakaryocytic cells. Biologically relevant chromosomal segments and gene clusters with differential expression during the differentiation toward megakaryocyte were identified.</p> <p>Conclusions</p> <p>TRAM is designed to create, and statistically analyze, quantitative transcriptome maps, based on gene expression data from multiple sources. The release includes FileMaker Pro database management runtime application and it is freely available at <url>http://apollo11.isto.unibo.it/software/</url>, along with preconfigured implementations for mapping of human, mouse and zebrafish transcriptomes.</p

Pure phase-locking of beta/gamma oscillation contributes to the N30 frontal component of somatosensory evoked potentials

BACKGROUND: Evoked potentials have been proposed to result from phase-locking of electroencephalographic (EEG) activities within specific frequency bands. However, the respective contribution of phasic activity and phase resetting of ongoing EEG oscillation remains largely debated. We here applied the EEGlab procedure in order to quantify the contribution of electroencephalographic oscillation in the generation of the frontal N30 component of the somatosensory evoked potentials (SEP) triggered by median nerve electrical stimulation at the wrist. Power spectrum and intertrial coherence analysis were performed on EEG recordings in relation to median nerve stimulation. RESULTS: The frontal N30 component was accompanied by a significant phase-locking of beta/gamma oscillation (25-35 Hz) and to a lesser extent of 80 Hz oscillation. After the selection in each subject of the trials for which the power spectrum amplitude remained unchanged, we found pure phase-locking of beta/gamma oscillation (25-35 Hz) peaking about 30 ms after the stimulation. Transition across trials from uniform to normal phase distribution revealed temporal phase reorganization of ongoing 30 Hz EEG oscillations in relation to stimulation. In a proportion of trials, this phase-locking was accompanied by a spectral power increase peaking in the 30 Hz frequency band. This corresponds to the complex situation of 'phase-locking with enhancement' in which the distinction between the contribution of phasic neural event versus EEG phase resetting is hazardous. CONCLUSION: The identification of a pure phase-locking in a large proportion of the SEP trials reinforces the contribution of the oscillatory model for the physiological correlates of the frontal N30. This may imply that ongoing EEG rhythms, such as beta/gamma oscillation, are involved in somatosensory information processing.Comparative StudyJournal ArticleResearch Support, Non-U.S. Gov'tinfo:eu-repo/semantics/publishe

Complex systems and the technology of variability analysis

Characteristic patterns of variation over time, namely rhythms, represent a defining feature of complex systems, one that is synonymous with life. Despite the intrinsic dynamic, interdependent and nonlinear relationships of their parts, complex biological systems exhibit robust systemic stability. Applied to critical care, it is the systemic properties of the host response to a physiological insult that manifest as health or illness and determine outcome in our patients. Variability analysis provides a novel technology with which to evaluate the overall properties of a complex system. This review highlights the means by which we scientifically measure variation, including analyses of overall variation (time domain analysis, frequency distribution, spectral power), frequency contribution (spectral analysis), scale invariant (fractal) behaviour (detrended fluctuation and power law analysis) and regularity (approximate and multiscale entropy). Each technique is presented with a definition, interpretation, clinical application, advantages, limitations and summary of its calculation. The ubiquitous association between altered variability and illness is highlighted, followed by an analysis of how variability analysis may significantly improve prognostication of severity of illness and guide therapeutic intervention in critically ill patients

Extracting key information from historical data to quantify the transmission dynamics of smallpox

<p>Abstract</p> <p>Background</p> <p>Quantification of the transmission dynamics of smallpox is crucial for optimizing intervention strategies in the event of a bioterrorist attack. This article reviews basic methods and findings in mathematical and statistical studies of smallpox which estimate key transmission parameters from historical data.</p> <p>Main findings</p> <p>First, critically important aspects in extracting key information from historical data are briefly summarized. We mention different sources of heterogeneity and potential pitfalls in utilizing historical records. Second, we discuss how smallpox spreads in the absence of interventions and how the optimal timing of quarantine and isolation measures can be determined. Case studies demonstrate the following. (1) The upper confidence limit of the 99th percentile of the incubation period is 22.2 days, suggesting that quarantine should last 23 days. (2) The highest frequency (61.8%) of secondary transmissions occurs 3–5 days after onset of fever so that infected individuals should be isolated before the appearance of rash. (3) The U-shaped age-specific case fatality implies a vulnerability of infants and elderly among non-immune individuals. Estimates of the transmission potential are subsequently reviewed, followed by an assessment of vaccination effects and of the expected effectiveness of interventions.</p> <p>Conclusion</p> <p>Current debates on bio-terrorism preparedness indicate that public health decision making must account for the complex interplay and balance between vaccination strategies and other public health measures (e.g. case isolation and contact tracing) taking into account the frequency of adverse events to vaccination. In this review, we summarize what has already been clarified and point out needs to analyze previous smallpox outbreaks systematically.</p

Scrub typhus ecology: a systematic review of Orientia in vectors and hosts

Abstract Scrub typhus, caused by Orientia tsutsugamushi, is an important and neglected vector-borne zoonotic disease with an expanding known distribution. The ecology of the disease is complex and poorly understood, impairing discussion of public health interventions. To highlight what we know and the themes of our ignorance, we conducted a systematic review of all studies investigating the pathogen in vectors and non-human hosts. A total of 276 articles in 7 languages were included, with 793 study sites across 30 countries. There was no time restriction for article inclusion, with the oldest published in 1924. Seventy-six potential vector species and 234 vertebrate host species were tested, accounting for over one million trombiculid mites (‘chiggers’) and 83,000 vertebrates. The proportion of O. tsutsugamushi positivity was recorded for different categories of laboratory test and host species. Vector and host collection sites were geocoded and mapped. Ecological data associated with these sites were summarised. A further 145 articles encompassing general themes of scrub typhus ecology were reviewed. These topics range from the life-cycle to transmission, habitats, seasonality and human risks. Important gaps in our understanding are highlighted together with possible tools to begin to unravel these. Many of the data reported are highly variable and inconsistent and minimum data reporting standards are proposed. With more recent reports of human Orientia sp. infection in the Middle East and South America and enormous advances in research technology over recent decades, this comprehensive review provides a detailed summary of work investigating this pathogen in vectors and non-human hosts and updates current understanding of the complex ecology of scrub typhus. A better understanding of scrub typhus ecology has important relevance to ongoing research into improving diagnostics, developing vaccines and identifying useful public health interventions to reduce the burden of the disease.</jats:p