126 research outputs found

    Effects of Epinephrine and Phenylephrine on QT Interval Dispersion in Congenital Long QT Syndrome 11This study was supported by a grant from the Finnish Cardiac Research Foundation, Helsinki.

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    AbstractObjectives. Measurement of QT interval dispersion during pharmacologic adrenergic stimulation was used to assess the effect of alpha- and beta-adrenergic stimulation on arrhythmic vulnerability in familial long QT syndrome (LQTS).Background. Nonhomogeneity in the ventricular action potential duration causes electrical instability leading to life-threatening ventricular arrhythmias and is markedly increased in LQTS. QT interval dispersion measured from the electrocardiogram (ECG) can be used as an index of nonhomogeneous ventricular repolarization.Methods. Sixteen symptomatic patients with LQTS and nine healthy control subjects were examined at baseline and during epinephrine (mainly beta-adrenergic agonist, 0.05 μg/kg body weight per min) and phenylephrine infusions (alpha-adrenergic agonist, mean 1.4 μg/kg per min). QT interval dispersion was determined from a 12-lead ECG as interlead range and coefficient of variation measured to the end (QTend) and apex (QTapex) of the T wave.Results. At baseline QTenddispersion was greater in patients with LQTS compared with control subjects (mean [±SD] 68 ± 34 vs. 36 ± 7 ms, p = 0.001). QTenddispersion was markedly increased in patients with LQTS by use of epinephrine (from 68 ± 34 to 90 ± 36 ms, p = 0.002), but remained unchanged in control subjects. Phenylephrine did not affect QT dispersion in either group (all p = NS). Atrial pacing to achieve comparable heart rates during baseline and epinephrine and phenylephrine infusions did not influence the magnitude of QT dispersion in either group. QTapexdispersion analysis gave congruent results.Conclusions. Epinephrine but not phenylephrine increased QT dispersion, suggesting that beta-adrenergic stimulation provokes arrhythmias in patients with LQTS by aggravating nonhomogeneity of ventricular repolarization, whereas alpha-adrenergic stimulation is less important for arrhythmic vulnerability. The results also suggest that rapid pacing may not reduce vulnerability to arrhythmias in congenital LQTS

    Mapping urban linguistic diversity with social media and population register data

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    Globalization, urbanization and international mobility have led to increasingly diverse urban populations. Compared to traditional traits for measuring urban diversity, such as ethnicity and country of origin, the role of language remains underexplored in understanding diversity, interactions between different groups and socio-spatial segregation. In this article, we analyse language use in the Helsinki Metropolitan Area by combining individual-level register data, socio-economic grid database, mobile phone and social media data to understand spatio-temporal patterns of linguistic diversity better. We measured linguistic diversity using metrics developed in the fields of ecology and information theory, and performed spatial clustering and regression analyses to explore the spatio-temporal patterns of linguistic diversity. We found spatial and temporal differences between register and social media data, show that linguistic diversity is influenced by the physical and socio-economic environment, and identified areas where different linguistic groups are likely to interact. Our results provide insights for urban planning and understanding urban diversity through linguistic information. As global urbanization, international migration and refugee flows and climate change drive diverse populations into cities, understanding urban diversity and its implications for urban planning and sustainability become increasingly important.Peer reviewe

    Exploring human–nature interactions in national parks with social media photographs and computer vision

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    Understanding the activities and preferences of visitors is crucial for managing protected areas and planning conservation strategies. Conservation culturomics promotes the use of user-generated online content in conservation science. Geotagged social media content is a unique source of in situ information on human presence and activities in nature. Photographs posted on social media platforms are a promising source of information, but analyzing large volumes of photographs manually remains laborious. We examined the application of state-of-the-art computer-vision methods to studying human-nature interactions. We used semantic clustering, scene classification, and object detection to automatically analyze photographs taken in Finnish national parks by domestic and international visitors. Our results showed that human-nature interactions can be extracted from user-generated photographs with computer vision. The different methods complemented each other by revealing broad visual themes related to level of the data set, landscape photogeneity, and human activities. Geotagged photographs revealed distinct regional profiles for national parks (e.g., preferences in landscapes and activities), which are potentially useful in park management. Photographic content differed between domestic and international visitors, which indicates differences in activities and preferences. Information extracted automatically from photographs can help identify preferences among diverse visitor groups, which can be used to create profiles of national parks for conservation marketing and to support conservation strategies that rely on public acceptance. The application of computer-vision methods to automatic content analysis of photographs should be explored further in conservation culturomics, particularly in combination with rich metadata available on social media platforms.Peer reviewe

    Comparison of Ventricular Refractory Periods Determined by Incremental and Decremental Scanning of an Extrastimulus

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    Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/73345/1/j.1540-8159.1989.tb02699.x.pd
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