Accurate QT correction method from transfer entropy.

Background: The QT interval in the electrocardiogram (ECG) is a fundamental risk measure for arrhythmic adverse cardiac events. However, the QT interval depends on the heart rate and must be corrected accordingly. The present QT correction (QTc) methods are either simple models leading to under- or overcorrection, or impractical in requiring long-term empirical data. In general, there is no consensus on the best QTc method. Objective: We introduce a model-free QTc method-AccuQT-that computes QTc by minimizing the information transfer from R-R to QT intervals. The objective is to establish and validate a QTc method that provides superior stability and reliability without models or empirical data. Methods: We tested AccuQT against the most commonly used QT correction methods by using long-term ECG recordings of more than 200 healthy subjects from PhysioNet and THEW databases. Results: AccuQT overperforms the previously reported correction methods: the proportion of false-positives is reduced from 16% (Bazett) to 3% (AccuQT) for the PhysioNet data. In particular, the QTc variance is significantly reduced and thus the RR-QT stability is increased. Conclusion: AccuQT has significant potential to become the QTc method of choice in clinical studies and drug development. The method can be implemented in any device recording R-R and QT intervals.

Prevalence and risk factors of frailty among home care clients.

BACKGROUND: Frailty is a common problem among older people and it is associated with an increased risk of death and long-term institutional care. Early identification of frailty is necessary to prevent a further decline in the health status of home care clients. The aims of the present study were to determine the prevalence of frailty and associated factors among 75-year-old or older home care clients. METHODS: The study participants were 75-year-old or older home care clients living in three cities in Eastern and Central Finland. Home care clients who had completed the abbreviated Comprehensive Geriatric Assessment (aCGA) for frailty (n = 257) were included in the present study. Baseline data were obtained on functional status, cognitive status, depressive symptoms, self-rated health, ability to walk 400 m, nutritional status, drug use and comorbidities. RESULTS: Most of the home care clients (90%) were screened for frailty using the aCGA. Multivariate analysis showed that the risk of malnutrition or malnutrition (OR = 4.27, 95% CI = 1.56, 11.68) and a low level of education (OR = 1.14, 95% CI = 1.07, 1.23) were associated with frailty. CONCLUSION: Frailty is a prevalent problem among home care clients. The risk of malnutrition or malnourishment and a lower level of education increase the risk of frailty. Screening for frailty should be done to detect the most vulnerable older people for further intervention to prevent adverse health problems. TRIAL REGISTRATION: ClinicalTrials.gov: NCT02214758 .

Parallel independent evolution of pathogenicity within the genus Yersinia.

The genus Yersinia has been used as a model system to study pathogen evolution. Using whole-genome sequencing of all Yersinia species, we delineate the gene complement of the whole genus and define patterns of virulence evolution. Multiple distinct ecological specializations appear to have split pathogenic strains from environmental, nonpathogenic lineages. This split demonstrates that contrary to hypotheses that all pathogenic Yersinia species share a recent common pathogenic ancestor, they have evolved independently but followed parallel evolutionary paths in acquiring the same virulence determinants as well as becoming progressively more limited metabolically. Shared virulence determinants are limited to the virulence plasmid pYV and the attachment invasion locus ail. These acquisitions, together with genomic variations in metabolic pathways, have resulted in the parallel emergence of related pathogens displaying an increasingly specialized lifestyle with a spectrum of virulence potential, an emerging theme in the evolution of other important human pathogens.

Identification of genetic markers with synergistic survival effect in cancer.

BACKGROUND: Cancers are complex diseases arising from accumulated genetic mutations that disrupt intracellular signaling networks. While several predisposing genetic mutations have been found, these individual mutations account only for a small fraction of cancer incidence and mortality. With large-scale measurement technologies, such as single nucleotide polymorphism (SNP) microarrays, it is now possible to identify combinatorial effects that have significant impact on cancer patient survival. RESULTS: The identification of synergetic functioning SNPs on genome-scale is a computationally daunting task and requires advanced algorithms. We introduce a novel algorithm, Geninter, to identify SNPs that have synergetic effect on survival of cancer patients. Using a large breast cancer cohort we generate a simulator that allows assessing reliability and accuracy of Geninter and logrank test, which is a standard statistical method to integrate genetic and survival data. CONCLUSIONS: Our results show that Geninter outperforms the logrank test and is able to identify SNP-pairs with synergetic impact on survival.

Do allopatric male Calopteryx virgo damselflies learn species recognition?

There is a growing amount of empirical evidence that premating reproductive isolation of two closely related species can be reinforced by natural selection arising from avoidance of maladaptive hybridization. However, as an alternative for this popular reinforcement theory, it has been suggested that learning to prefer conspecifics or to discriminate heterospecifics could cause a similar pattern of reinforced premating isolation, but this possibility is much less studied. Here, we report results of a field experiment in which we examined (i) whether allopatric Calopteryx virgo damselfly males that have not encountered heterospecific females of the congener C. splendens initially show discrimination, and (ii) whether C. virgo males learn to discriminate heterospecifics or learn to associate with conspecifics during repeated experimental presentation of females. Our experiment revealed that there was a statistically nonsignificant tendency for C. virgo males to show initial discrimination against heterospecific females but because we did not use sexually naïve individuals in our experiment, we were not able to separate the effect of innate or associative learning. More importantly, however, our study revealed that species discrimination might be further strengthened by learning, especially so that C. virgo males increase their association with conspecific females during repeated presentation trials. The role of learning to discriminate C. splendens females was less clear. We conclude that learning might play a role in species recognition also when individuals are not naïve but have already encountered potential conspecific mates.

Large-scale data integration framework provides a comprehensive view on glioblastoma multiforme.

BACKGROUND: Coordinated efforts to collect large-scale data sets provide a basis for systems level understanding of complex diseases. In order to translate these fragmented and heterogeneous data sets into knowledge and medical benefits, advanced computational methods for data analysis, integration and visualization are needed. METHODS: We introduce a novel data integration framework, Anduril, for translating fragmented large-scale data into testable predictions. The Anduril framework allows rapid integration of heterogeneous data with state-of-the-art computational methods and existing knowledge in bio-databases. Anduril automatically generates thorough summary reports and a website that shows the most relevant features of each gene at a glance, allows sorting of data based on different parameters, and provides direct links to more detailed data on genes, transcripts or genomic regions. Anduril is open-source; all methods and documentation are freely available. RESULTS: We have integrated multidimensional molecular and clinical data from 338 subjects having glioblastoma multiforme, one of the deadliest and most poorly understood cancers, using Anduril. The central objective of our approach is to identify genetic loci and genes that have significant survival effect. Our results suggest several novel genetic alterations linked to glioblastoma multiforme progression and, more specifically, reveal Moesin as a novel glioblastoma multiforme-associated gene that has a strong survival effect and whose depletion in vitro significantly inhibited cell proliferation. All analysis results are available as a comprehensive website. CONCLUSIONS: Our results demonstrate that integrated analysis and visualization of multidimensional and heterogeneous data by Anduril enables drawing conclusions on functional consequences of large-scale molecular data. Many of the identified genetic loci and genes having significant survival effect have not been reported earlier in the context of glioblastoma multiforme. Thus, in addition to generally applicable novel methodology, our results provide several glioblastoma multiforme candidate genes for further studies.Anduril is available at http://csbi.ltdk.helsinki.fi/anduril/The glioblastoma multiforme analysis results are available at http://csbi.ltdk.helsinki.fi/anduril/tcga-gbm/