Browsing by Subject "Population"

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    Mediators of Fine-Scale Population Genetic Structure in the Black Blow Fly, Phormia regina (Meigen) (Diptera: Calliphoridae)
    (2019-08) Owings, Charity Grace; Picard, Christine J.; Walsh, Susan; Wang, Xianzhong; Holland, Jeffery D.; Gilhooly, William, III
    Population genetic structure is difficult to assess in blow flies (Diptera: Calliphoridae) due to high connectivity and genetic diversity of subpopulations. Previous studies revealed high relatedness among individuals within wild samples of blow fly populations, however broad geographic structure was absent. The aim of this research was to determine if blow fly genetic structure exists at a fine spatiotemporal resolution and, if so, to elucidate the influence of environmental factors and resource availability on fly genetics. Specifically, blow fly population genetic patterns were tested against a null hypothesis that flies adhere to a patchy population model with high genetic diversity (i.e. no structure) and high resource availability. Samples of the black blow fly, Phormia regina Meigen (Diptera: Calliphoridae), were collected at six urban parks in Indiana, USA (=urban) in 2016 and 2017 (N = 14 and 16 timepoints, respectively). Additional sampling in different ecoregions was performed to determine if trends observed at a high-resolution scale were also present at a broad geographic scale. Therefore, P. regina were also collected at four sites within two national parks (the Great Smoky Mountains and Yellowstone National Parks) over a three-day period. Randomly selected females (N = 10) from each sample underwent the following analyses: 1) gut DNA extraction, 2) molecular analysis at 6 microsatellite loci, 3) vertebrate-specific 12S and 16S rRNA sequencing, and, 4) vertebrate fecal metabolite screening. Flies from the national parks and a comparable subset of urban data also underwent stable isotope analysis (SIA) to determine larval food source. Overall, strong seasonal population genetic structure was observed over both years in the urban environment (2016 F’ST = 0.47, 2017 F’ST 0.34), however spatial structure was lacking, as seen in previous studies (2016 F’ST = 0.04, 2017 F’ST 0.03). Weather conditions prior to and on the day of blow fly collections, interspecific competition, and resource availability greatly impacted the genetic diversity and kinship of P. regina. A total of 17 and 19 vertebrate species were detected by flies in 2016 and 2017, respectively, and many flies tested positive for vertebrate feces, suggesting that many varied resources are important for maintaining high gene flow among geographic locations. Genetic diversity was non-existent in flies collected from the Smokies (F’ST = 0.00), while very slight spatial structure existed in the Yellowstone populations (F’ST = 0.07). Environmental factors such as temperature, humidity, and wind speed were all statistically relevant in maximizing fly collections with vertebrate resources. In 720 min of total sampling time in the national parks and a subset of urban data, 28 vertebrate species were identified, and fecal resources appeared to be the most abundant in Yellowstone. Stable isotope analysis revealed a majority of larval resources in the national parks were herbivores, with a more even distribution of carnivore and herbivore carcasses present in the urban environment, which likely explains the high genetic diversity of adult flies in these regions. Overall, the null hypothesis that P. regina adheres to a patchy population model could not be rejected for the Smokies populations. However, the urban and Yellowstone populations appear to adhere to a Levins metapopulation model in which variable availability in resources leads to random bottleneck events in the local populations. Overall, environmental conditions, competition, and resource availability are all important factors influencing P. regina population genetic structure in different environments.
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    Prognostic Value of Phase Analysis for Predicting Adverse Cardiac Events beyond Conventional SPECT Variables: Results from the REFINE SPECT Registry
    (American Heart Association, 2021) Kuronuma, Keiichiro; Miller, Robert J. H.; Otaki, Yuka; Van Kriekinge, Serge D.; Diniz, Marcio A.; Sharir, Tali; Hu, Lien-Hsin; Gransar, Heidi; Liang, Joanna X.; Parekh, Tejas; Kavanagh, Paul; Einstein, Andrew J.; Fish, Mathews B.; Ruddy, Terrence D.; Kaufmann, Philipp A.; Sinusas, Albert J.; Miller, Edward J.; Bateman, Timothy M.; Dorbala, Sharmila; Di Carli, Marcelo; Tamarappoo, Balaji K.; Dey, Damini; Berman, Daniel S.; Slomka, Piotr J.; Radiation Oncology, School of Medicine
    Background: Phase analysis of single-photon emission computed tomography myocardial perfusion imaging provides dyssynchrony information which correlates well with assessments by echocardiography, but the independent prognostic significance is not well defined. This study assessed the independent prognostic value of single-photon emission computed tomography-myocardial perfusion imaging phase analysis in the largest multinational registry to date across all modalities. Methods: From the REFINE SPECT (Registry of Fast Myocardial Perfusion Imaging With Next Generation SPECT), a total of 19 210 patients were included (mean age 63.8±12.0 years and 56% males). Poststress total perfusion deficit, left ventricular ejection fraction, and phase variables (phase entropy, bandwidth, and SD) were obtained automatically. Cox proportional hazards analyses were performed to assess associations with major adverse cardiac events (MACE). Results: During a follow-up of 4.5±1.7 years, 2673 (13.9%) patients experienced MACE. Annualized MACE rates increased with phase variables and were ≈4-fold higher between the second and highest decile group for entropy (1.7% versus 6.7%). Optimal phase variable cutoff values stratified MACE risk in patients with normal and abnormal total perfusion deficit and left ventricular ejection fraction. Only entropy was independently associated with MACE. The addition of phase entropy significantly improved the discriminatory power for MACE prediction when added to the model with total perfusion deficit and left ventricular ejection fraction (P<0.0001). Conclusions: In a largest to date imaging study, widely representative, international cohort, phase variables were independently associated with MACE and improved risk stratification for MACE beyond the prediction by perfusion and left ventricular ejection fraction assessment alone. Phase analysis can be obtained fully automatically, without additional radiation exposure or cost to improve MACE risk prediction and, therefore, should be routinely reported for single-photon emission computed tomography-myocardial perfusion imaging studies.