21 datasets found
  1. A

    ‘World Population Data’ analyzed by Analyst-2

    • analyst-2.ai
    Updated Jan 28, 2022
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2022). ‘World Population Data’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/kaggle-world-population-data-9453/0454f7ef/?iid=004-217&v=presentation
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    Dataset updated
    Jan 28, 2022
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    World
    Description

    Analysis of ‘World Population Data’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/kuntalmaity/world-population-data on 28 January 2022.

    --- Dataset description provided by original source is as follows ---

    Population in the world is currently (2020) growing at a rate of around 1.05% per year (down from 1.08% in 2019, 1.10% in 2018, and 1.12% in 2017). The current average population increase is estimated at 81 million people per year. Annual growth rate reached its peak in the late 1960s, when it was at around 2%.

    --- Original source retains full ownership of the source dataset ---

  2. A

    ‘World Population 1960-2018’ analyzed by Analyst-2

    • analyst-2.ai
    Updated Feb 13, 2022
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2022). ‘World Population 1960-2018’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/kaggle-world-population-1960-2018-57c0/d6bc3cb7/?iid=003-619&v=presentation
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    Dataset updated
    Feb 13, 2022
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    World
    Description

    Analysis of ‘World Population 1960-2018’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/imdevskp/world-population-19602018 on 13 February 2022.

    --- Dataset description provided by original source is as follows ---

    forthebadge forthebadge

    Content

    The dataset contains population data of different countries/regions from 1960 to 2018

    Acknowledgements

    https://data.worldbank.org/indicator/SP.POP.TOTL

    Note

    There are condensed and region-wise data in the population dataset.

    --- Original source retains full ownership of the source dataset ---

  3. A

    ‘World Population by Year’ analyzed by Analyst-2

    • analyst-2.ai
    Updated Jan 28, 2022
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2022). ‘World Population by Year’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/kaggle-world-population-by-year-3a4c/0a3c3ba0/?iid=001-049&v=presentation
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    Dataset updated
    Jan 28, 2022
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    World
    Description

    Analysis of ‘World Population by Year’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/sansuthi/world-population-by-year on 28 January 2022.

    --- Dataset description provided by original source is as follows ---

    Variables:

    • Year: 1951 to 2020
    • Population: World Population
    • ChangePerc: Yearly Change in Percentage
    • NetChange: Total Yearly Change
    • Density: Density in P/Km²
    • Urban: Urban Population
    • UrbanPerc: Urban Population Percentage

    Source of content: www.worldometers.info

    --- Original source retains full ownership of the source dataset ---

  4. b

    UK gridded population at 1 km resolution for 2021 based on Census 2021/2022...

    • hosted-metadata.bgs.ac.uk
    • catalogue.ceh.ac.uk
    • +2more
    zip
    Updated Feb 26, 2025
    + more versions
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    UK Centre for Ecology & Hydrology (2025). UK gridded population at 1 km resolution for 2021 based on Census 2021/2022 and Land Cover Map 2021 [Dataset]. https://hosted-metadata.bgs.ac.uk/geonetwork/srv/api/records/7beefde9-c520-4ddf-897a-0167e8918595
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    zipAvailable download formats
    Dataset updated
    Feb 26, 2025
    Dataset provided by
    UK Centre for Ecology & Hydrology
    NERC EDS Environmental Information Data Centre
    License

    https://eidc.ceh.ac.uk/licences/OGL/plainhttps://eidc.ceh.ac.uk/licences/OGL/plain

    http://purl.org/coar/access_right/c_abf2http://purl.org/coar/access_right/c_abf2

    Time period covered
    Jan 1, 2021 - Dec 31, 2022
    Area covered
    Description

    This dataset contains gridded human population with a spatial resolution of 1 km x 1 km for the UK based on Census 2021 (Census 2022 for Scotland) and Land Cover Map 2021 input data. Data on population distribution for the United Kingdom is available from statistical offices in England, Wales, Northern Ireland and Scotland and provided to the public e.g. via the Office for National Statistics (ONS). Population data is typically provided in tabular form or, based on a range of different geographical units, in file types for geographical information systems (GIS), for instance as ESRI Shapefiles. The geographical units reflect administrative boundaries at different levels of detail, from Devolved Administration to Output Areas (OA), wards or intermediate geographies. While the presentation of data on the level of these geographical units is useful for statistical purposes, accounting for spatial variability for instance of environmental determinants of public health requires a more spatially homogeneous population distribution. For this purpose, the dataset presented here combines 2021/2022 UK Census population data on Output Area level with Land Cover Map 2021 land-use classes 'urban' and 'suburban' to create a consistent and comprehensive gridded population data product at 1 km x 1 km spatial resolution. The mapping product is based on British National Grid (OSGB36 datum). Full details about this dataset can be found at https://doi.org/10.5285/7beefde9-c520-4ddf-897a-0167e8918595

  5. A

    ‘World Population’ analyzed by Analyst-2

    • analyst-2.ai
    Updated Feb 14, 2022
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2022). ‘World Population’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/kaggle-world-population-bb7e/3840d619/?iid=004-099&v=presentation
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    Dataset updated
    Feb 14, 2022
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    World
    Description

    Analysis of ‘World Population’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/vaishnavivenkatesan/world-population on 14 February 2022.

    --- Dataset description provided by original source is as follows ---

    Context

    This data set consist of population of each country from 1960 - 1966.

    Content

    This file consist of population of each country from 1960.It has 63 columns.

    Acknowledgements

    This is done during the internship at Tact Labs. Thanks to Aishwarya who aided me in collecting the data set.

    --- Original source retains full ownership of the source dataset ---

  6. Population of the United States 1610-2020

    • statista.com
    Updated Aug 12, 2024
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    Statista (2024). Population of the United States 1610-2020 [Dataset]. https://www.statista.com/statistics/1067138/population-united-states-historical/
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    Dataset updated
    Aug 12, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In the past four centuries, the population of the United States has grown from a recorded 350 people around the Jamestown colony of Virginia in 1610, to an estimated 331 million people in 2020. The pre-colonization populations of the indigenous peoples of the Americas have proven difficult for historians to estimate, as their numbers decreased rapidly following the introduction of European diseases (namely smallpox, plague and influenza). Native Americans were also omitted from most censuses conducted before the twentieth century, therefore the actual population of what we now know as the United States would have been much higher than the official census data from before 1800, but it is unclear by how much. Population growth in the colonies throughout the eighteenth century has primarily been attributed to migration from the British Isles and the Transatlantic slave trade; however it is also difficult to assert the ethnic-makeup of the population in these years as accurate migration records were not kept until after the 1820s, at which point the importation of slaves had also been illegalized. Nineteenth century In the year 1800, it is estimated that the population across the present-day United States was around six million people, with the population in the 16 admitted states numbering at 5.3 million. Migration to the United States began to happen on a large scale in the mid-nineteenth century, with the first major waves coming from Ireland, Britain and Germany. In some aspects, this wave of mass migration balanced out the demographic impacts of the American Civil War, which was the deadliest war in U.S. history with approximately 620 thousand fatalities between 1861 and 1865. The civil war also resulted in the emancipation of around four million slaves across the south; many of whose ancestors would take part in the Great Northern Migration in the early 1900s, which saw around six million black Americans migrate away from the south in one of the largest demographic shifts in U.S. history. By the end of the nineteenth century, improvements in transport technology and increasing economic opportunities saw migration to the United States increase further, particularly from southern and Eastern Europe, and in the first decade of the 1900s the number of migrants to the U.S. exceeded one million people in some years. Twentieth and twenty-first century The U.S. population has grown steadily throughout the past 120 years, reaching one hundred million in the 1910s, two hundred million in the 1960s, and three hundred million in 2007. In the past century, the U.S. established itself as a global superpower, with the world's largest economy (by nominal GDP) and most powerful military. Involvement in foreign wars has resulted in over 620,000 further U.S. fatalities since the Civil War, and migration fell drastically during the World Wars and Great Depression; however the population continuously grew in these years as the total fertility rate remained above two births per woman, and life expectancy increased (except during the Spanish Flu pandemic of 1918).

    Since the Second World War, Latin America has replaced Europe as the most common point of origin for migrants, with Hispanic populations growing rapidly across the south and border states. Because of this, the proportion of non-Hispanic whites, which has been the most dominant ethnicity in the U.S. since records began, has dropped more rapidly in recent decades. Ethnic minorities also have a much higher birth rate than non-Hispanic whites, further contributing to this decline, and the share of non-Hispanic whites is expected to fall below fifty percent of the U.S. population by the mid-2000s. In 2020, the United States has the third-largest population in the world (after China and India), and the population is expected to reach four hundred million in the 2050s.

  7. S

    CIESIN/CIAT: Population Density Grid, v3 (GPWv3) (1990, 2000, 2010) for...

    • dataportal.senckenberg.de
    zip
    Updated Dec 17, 2020
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    Bachmann (2020). CIESIN/CIAT: Population Density Grid, v3 (GPWv3) (1990, 2000, 2010) for UNDESERT study areas in Burkina Faso, Benin, Niger and Senegal [Dataset]. https://dataportal.senckenberg.de/de/dataset/ciesinciat-population-density-grid-v3-gpwv3-1990-2000-2010-for-undesert-study
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    zipAvailable download formats
    Dataset updated
    Dec 17, 2020
    Dataset provided by
    Senckenberg Biodiversitätsinformatik
    Authors
    Bachmann
    Time period covered
    1990 - 2010
    Area covered
    Benin, Burkina Faso, Senegal, Niger
    Description

    The population density maps presented here for the UNDESERT study areas in Burkina Faso, Benin, Niger and Senegal for 1990, 2000 and 2010 were produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with the Centro Internacional de Agricultura Tropical (CIAT). CIESIN/CIAT population density grids are available for the entire globe at a 2.5 arc-minutes resolution (http://sedac.ciesin.columbia.edu/data/collection/gpw-v3/sets/browse). The UNDESERT project (EU FP7 243906), financed by the European Commission, Directorate General for Research and Innovation, Environment Program, aims to improve the Understanding and Combating of Desertification to Mitigate its Impact on Ecosystem Services in West Africa. Humans originate and contribute significantly to desertification processes. Based on the CIESIN/CIAT population density grids we want to illustrate how population density changed in the UNDESERT study areas and countries during the last 20 years. Data for 1990 and 2000 were downloaded from the Gridded Population of the World, Version 3 (GPWv3) consisting of estimates of human population by 2.5 arc-minute grid cells and associated data sets dated circa 2000. Data for 2010 were copied from the Gridded Population of the World, Version 3 (GPWv3) consisting in a future estimate of human population by 2.5 arc-minute grid cells. The future estimate population values are extrapolated based on a combination of subnational growth rates from census dates and national growth rates from United Nations statistics.

    Source: http://sedac.ciesin.columbia.edu/data/set/gpw-v3-population-density Center for International Earth Science Information Network (CIESIN)/Columbia University, and Centro Internacional de Agricultura Tropical (CIAT). 2005. Gridded Population of the World, Version 3 (GPWv3): Population Density Grid. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). http://sedac.ciesin.columbia.edu/data/set/gpw-v3-population-density. Accessed 28/10/2013 And http://sedac.ciesin.columbia.edu/data/set/gpw-v3-population-density-future-estimates Center for International Earth Science Information Network (CIESIN)/Columbia University, and Centro Internacional de Agricultura Tropical (CIAT). 2005. Gridded Population of the World, Version 3 (GPWv3): Population Density Grid, Future Estimates. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). http://sedac.ciesin.columbia.edu/data/set/gpw-v3-population-density-future-estimates. Accessed 28/10/2013

  8. H

    Data from: The Potato's Contribution to Population and Urbanization:...

    • dataverse.harvard.edu
    Updated Sep 27, 2021
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    Nathan Nunn (2021). The Potato's Contribution to Population and Urbanization: Evidence from a Historical Experiment [Dataset]. http://doi.org/10.7910/DVN/4RUFZ0
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Sep 27, 2021
    Dataset provided by
    Harvard Dataverse
    Authors
    Nathan Nunn
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    We exploit regional variation in suitability for cultivating potatoes, together with time variation arising from their introduction to the Old World from the Americas, to estimate the impact of potatoes on Old World population and urbanization. Our results show that the introduction of the potato was responsible for a significant portion of the increase in population and urbaniza- tion observed during the eighteenth and nineteenth centuries. According to our most conservative estimates, the introduction of the potato accounts for approximately one-quarter of the growth in Old World population and urbanization between 1700 and 1900. Additional evidence from within-country comparisons of city populations and adult heights also confirms the cross-country findings.

  9. Data from: Global FAW population genomic signature supports complex...

    • data.csiro.au
    • researchdata.edu.au
    Updated Dec 10, 2021
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    Tek Tay; Rahul Rane; Tom Walsh; Amanda Padovan; Sharon Downes; Samia Elfekih; Darren Kriticos; Karl Gordon (2021). Global FAW population genomic signature supports complex introduction events across the Old World [Dataset]. http://doi.org/10.25919/y3nd-2903
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    Dataset updated
    Dec 10, 2021
    Dataset provided by
    CSIROhttp://www.csiro.au/
    Authors
    Tek Tay; Rahul Rane; Tom Walsh; Amanda Padovan; Sharon Downes; Samia Elfekih; Darren Kriticos; Karl Gordon
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 2020 - Dec 9, 2021
    Area covered
    World
    Dataset funded by
    CSIROhttp://www.csiro.au/
    Description

    Variant data for MS - "Global FAW population genomic signature supports complex introduction events across the Old World" Lineage: SNP calling using BBMAP for global FAW samples

  10. d

    International Data Base

    • dknet.org
    • rrid.site
    • +2more
    Updated Jan 29, 2022
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    (2022). International Data Base [Dataset]. http://identifiers.org/RRID:SCR_013139
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    Dataset updated
    Jan 29, 2022
    Description

    A computerized data set of demographic, economic and social data for 227 countries of the world. Information presented includes population, health, nutrition, mortality, fertility, family planning and contraceptive use, literacy, housing, and economic activity data. Tabular data are broken down by such variables as age, sex, and urban/rural residence. Data are organized as a series of statistical tables identified by country and table number. Each record consists of the data values associated with a single row of a given table. There are 105 tables with data for 208 countries. The second file is a note file, containing text of notes associated with various tables. These notes provide information such as definitions of categories (i.e. urban/rural) and how various values were calculated. The IDB was created in the U.S. Census Bureau''s International Programs Center (IPC) to help IPC staff meet the needs of organizations that sponsor IPC research. The IDB provides quick access to specialized information, with emphasis on demographic measures, for individual countries or groups of countries. The IDB combines data from country sources (typically censuses and surveys) with IPC estimates and projections to provide information dating back as far as 1950 and as far ahead as 2050. Because the IDB is maintained as a research tool for IPC sponsor requirements, the amount of information available may vary by country. As funding and research activity permit, the IPC updates and expands the data base content. Types of data include: * Population by age and sex * Vital rates, infant mortality, and life tables * Fertility and child survivorship * Migration * Marital status * Family planning Data characteristics: * Temporal: Selected years, 1950present, projected demographic data to 2050. * Spatial: 227 countries and areas. * Resolution: National population, selected data by urban/rural * residence, selected data by age and sex. Sources of data include: * U.S. Census Bureau * International projects (e.g., the Demographic and Health Survey) * United Nations agencies Links: * ICPSR: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/08490

  11. Data from: Genetic status and timing of a weevil introduction to Santa Cruz...

    • zenodo.org
    • datadryad.org
    txt
    Updated May 30, 2022
    + more versions
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    Hoi-Fei Mok; Courtney C. Stepien; Maryska Kaczmarek; Lázaro Roque Albelo; Andrea S. Sequeira; Hoi-Fei Mok; Courtney C. Stepien; Maryska Kaczmarek; Lázaro Roque Albelo; Andrea S. Sequeira (2022). Data from: Genetic status and timing of a weevil introduction to Santa Cruz Island, Galápagos [Dataset]. http://doi.org/10.5061/dryad.3ks4v
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    txtAvailable download formats
    Dataset updated
    May 30, 2022
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Hoi-Fei Mok; Courtney C. Stepien; Maryska Kaczmarek; Lázaro Roque Albelo; Andrea S. Sequeira; Hoi-Fei Mok; Courtney C. Stepien; Maryska Kaczmarek; Lázaro Roque Albelo; Andrea S. Sequeira
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Area covered
    Galápagos Islands, Santa Cruz Island
    Description

    Successful invasive species can overcome or circumvent the potential genetic loss caused by an introduction bottleneck through a rapid population expansion and admixture from multiple introductions. We explore the genetic makeup and the timing of a species introduction to Santa Cruz Island in the Galápagos archipelago. We investigate the presence of processes that can maintain genetic diversity in populations of the broad-nosed weevil Galapaganus howdenae howdenae. Analyses of combined genotypes for 8 microsatellite loci showed evidence of past population size reductions through moment and likelihood-based estimators. No evidence of admixture through multiple introductions was found, but substantial current population sizes (N0 298, 95% HPD 50-2300), genetic diversity comparable to long-established endemics (Mean number of alleles=3.875) and lack of genetic structure across the introduced range (ΦST = 0.01359) could suggest that foundations are in place for populations to rapidly recover any loss of genetic variability. The time estimates for the introduction into Santa Cruz support an accidental transfer during the colonization period (1832-1959) pre-dating the spurt in human population growth. Our evaluation of the genetic status of G. h. howdenae suggests potential for population growth in addition to our field observations of a concurrent expansion in range and feeding preferences towards protected areas and endemic host plants.

  12. World Factbook, 1989

    • icpsr.umich.edu
    • explore.openaire.eu
    ascii
    Updated Feb 17, 1992
    + more versions
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    United States Central Intelligence Agency (1992). World Factbook, 1989 [Dataset]. http://doi.org/10.3886/ICPSR09366.v1
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    asciiAvailable download formats
    Dataset updated
    Feb 17, 1992
    Dataset provided by
    Inter-university Consortium for Political and Social Researchhttps://www.icpsr.umich.edu/web/pages/
    Authors
    United States Central Intelligence Agency
    License

    https://www.icpsr.umich.edu/web/ICPSR/studies/9366/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/9366/terms

    Time period covered
    1989
    Area covered
    Global
    Description

    This annual survey contains the most current information on topics of interest to United States government officials. Data are presented in alphabetical order for 247 entities that include all countries, dependent areas, and other geographic entities. The entire surface of the world is represented without overlap or omission, and an additional entry for the world as a whole also is presented. Information provided covers the six major topic areas of geography, people, government, economy, communications, and defense forces.

  13. n

    Data from: Introduction history and population genetics of intracontinental...

    • data.niaid.nih.gov
    • search.dataone.org
    • +1more
    zip
    Updated Sep 6, 2019
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    Ursula Brandes; Beate Furevik; Lene Nielsen; Erik Kjær; Line Rosef; Siri Fjellheim (2019). Introduction history and population genetics of intracontinental scotch broom (Cytisus scoparius) invasion [Dataset]. http://doi.org/10.5061/dryad.33bp0m3
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    zipAvailable download formats
    Dataset updated
    Sep 6, 2019
    Authors
    Ursula Brandes; Beate Furevik; Lene Nielsen; Erik Kjær; Line Rosef; Siri Fjellheim
    License

    https://spdx.org/licenses/CC0-1.0.htmlhttps://spdx.org/licenses/CC0-1.0.html

    Description

    Aim Biological invasions at the intracontinental scale are poorly studied, and intracontinental invasions often remain cryptic. Here, we investigate the recent range expansion of scotch broom (Cytisus scoparius) into Norway and clarify whether the genetic patterns support a natural spread or human introduction. Furthermore, we investigate whether plants were moved within the native range and how this influences invasion success. We also infer the level and structuring of genetic diversity within and between the putative native and introduced range. Location Europe Methods We analysed the chloroplast sequence variation in 267 scotch broom samples from its northern expansion front and from its native range across Europe, including herbarium samples dating back to 1835. For 37 populations, we analysed variation in nuclear single-nucleotide polymorphic markers to study gene flow and genetic diversity. Results We identified 20 different haplotypes, which lacked spatial and temporal distribution patterns in the recent expansion range in Norway. These also mostly lacked patterns across the native European range of scotch broom. The genetic diversity of nuclear genomic SNP markers across populations in the introduced range was similar to that of populations in the native range, with limited differentiation among populations. Main conclusions Scotch broom is alien to Norway and was introduced by humans on multiple occasions from diverse origins over a long period of time. High propagule pressure has probably maintained the high genetic diversity in the novel range through a combination of genetically diverse source populations and high gene flow among them. Within the native European range, our results suggest the presence of cryptic intraspecific admixture, most likely mediated by humans moving genotypes among the regions occupied by distinct native genotypes. Intracontinental invasions may easily go unnoticed and revealing these invasions and the factors driving them may be of great importance for the management of alien species.

  14. f

    Table_1_Immunogenicity and Immune Silence in Human Cancer.XLSX

    • frontiersin.figshare.com
    • figshare.com
    xlsx
    Updated Jun 4, 2023
    + more versions
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    Mark Yarmarkovich; Alvin Farrel; Artemio Sison; Moreno di Marco; Pichai Raman; Joshua L. Parris; Dimitrios Monos; Hongzhe Lee; Stefan Stevanovic; John M. Maris (2023). Table_1_Immunogenicity and Immune Silence in Human Cancer.XLSX [Dataset]. http://doi.org/10.3389/fimmu.2020.00069.s008
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    xlsxAvailable download formats
    Dataset updated
    Jun 4, 2023
    Dataset provided by
    Frontiers
    Authors
    Mark Yarmarkovich; Alvin Farrel; Artemio Sison; Moreno di Marco; Pichai Raman; Joshua L. Parris; Dimitrios Monos; Hongzhe Lee; Stefan Stevanovic; John M. Maris
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Despite recent advances in cancer immunotherapy, the process of immunoediting early in tumorigenesis remains obscure. Here, we employ a mathematical model that utilizes the Cancer Genome Atlas (TCGA) data to elucidate the contribution of individual mutations and HLA alleles to the immunoediting process. We find that common cancer mutations including BRAF-V600E and KRAS-G12D are predicted to bind none of the common HLA alleles, and are thus “immunogenically silent” in the human population. We identify regions of proteins that are not presented by HLA at a population scale, coinciding with frequently mutated hotspots in cancer, and other protein regions broadly presented across the population in which few mutations occur. We also find that 9/29 common HLA alleles contribute disproportionately to the immunoediting of early oncogenic mutations. These data provide insights into immune evasion of common driver mutations and a molecular basis for the association of particular HLA genotypes with cancer susceptibility.

  15. i

    Population and Family Health Survey 1990 - Jordan

    • catalog.ihsn.org
    • dev.ihsn.org
    • +2more
    Updated Jul 6, 2017
    + more versions
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    Department of Statistics (DOS) (2017). Population and Family Health Survey 1990 - Jordan [Dataset]. https://catalog.ihsn.org/catalog/181
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    Dataset updated
    Jul 6, 2017
    Dataset authored and provided by
    Department of Statistics (DOS)
    Time period covered
    1990
    Area covered
    Jordan
    Description

    Abstract

    The JPFHS is part of the worldwide Demographic and Health Surveys (DHS) program, which is designed to collect data on fertility, family planning, and maternal and child health.

    The 1990 Jordan Population and Family Health Survey (JPFHS) was carried out as part of the Demographic and Health Survey (DHS) program. The Demographic and Health Surveys is assisting governments and private agencies in the implementation of household surveys in developing countries.

    The JPFIS was designed to provide information on levels and trends of fertility, infant and child mortality, and family planning. The survey also gathered information on breastfeeding, matemal and child health cam, the nutritional status of children under five, as well as the characteristics of households and household members.

    The main objectives of the project include: a) Providing decision makers with a data base and analyses useful for informed policy choices, b) Expanding the international population and health data base, c) Advancing survey methodology, and d) Developing skills and resources necessary to conduct high quality demographic and health surveys in the participating countries.

    Geographic coverage

    National

    Analysis unit

    • Household
    • Children under five years
    • Women age 15-49
    • Men

    Kind of data

    Sample survey data

    Sampling procedure

    The sample for the JPFHS survey was selected to be representative of the major geographical regions, as well as the nation as a whole. The survey adopted a stratified, multi-stage sampling design. In each governorate, localities were classified into 9 strata according to the estimated population size in 1989. The sampling design also allowed for the survey results to be presented according to major cities (Amman, Irbid and Zarqa), other urban localities, and the rural areas. Localities with fewer than 5,000 people were considered rural.

    For this survey, 349 sample units were drawn, containing 10,708 housing units for the individual interview. Since the survey used a separate household questionnaire, the Department of Statistics doubled the household sample size and added a few questions on labor force, while keeping the original individual sample intact. This yielded 21,172 housing units. During fieldwork for the household interview, it was found that 4,359 household units were ineligible either because the dwelling was vacant or destroyed, the household was absent during the team visit, or some other reason. There were 16,296 completed household interviews out of 16,813 eligible households, producing a response rate of 96.9 percent.

    The completed household interviews yielded 7,246 women eligible for the individual interview, of which 6,461 were successfully interviewed, producing a response rate of 89.2 percent.

    Note: See detailed description of sample design in APPENDIX A of the survey report.

    Mode of data collection

    Face-to-face

    Research instrument

    The 1990 JPFIS utilized two questionnaires, one for the household interview and the other for individual women. Both questionnaires were developed first in English and then translated into Arabic. The household questionnaire was used to list all members of the sample households, including usual residents as well as visitors. For each member of the household, basic demographic and socioeconomic characteristics were recorded and women eligible for the individual interview were identified. To be eligible for individual interview, a woman had to be a usual member of the household (part of the de jure population), ever-married, and between 15 and 49 years of age. The household questionnaire was expanded from the standard DHS-II model questionnaire to facilitate the estimation of adult mortality using the orphanhood and widowhood techniques. In addition, the questionnaire obtained information on polygamy, economic activity of persons 15 years of age and over, family type, type of insurance covering the household members, country of work in the summer of 1990 which coincided with the Gulf crisis, and basic data for the calculation of the crude birth rate and the crude death rate. Additional questions were asked about deceased women if they were ever-married and age 15-49, in order to obtain information for the calculation of materoal mortality indices.

    The individual questionnaire is a modified version of the standard DHS-II model "A" questionnaire. Experience gained from previous surveys, in particular the 1983 Jordan Fertility and Family Health Survey, and the questionnaire developed by the Pan Arab Project for Child Development (PAPCHILD), were useful in the discussions on the content of the JPFHS questionnaire. A major change from the DHS-II model questionnaire was the rearrangement of the sections so that the marriage section came before reproduction; this allowed the interview to flow more smoothly. Questions on children's cause of death based on verbal autopsy were added to the section on health, which, due to its size, was split into two parts. The first part focused on antenatal care and breastfeeding; the second part examined measures for prevention of childhood diseases and information on the morbidity and mortality of children loom since January 1985. As questions on sexual relations were considered too sensitive, they were replaced by questions about the husband's presence in the household during the specified time period; this served as a proxy for recent sexual activity.

    The JPFHS individual questionnaire consists of nine sections: - Respondent's background and household characteristics - Marriage - Reproduction - Contraception - Breastfeeding and health - Immunization, morbidity, and child mortality - Fertility preferences - Husband's background, residence, and woman's work - Height and weight of children

    Response rate

    For the individual interview, the number of eligible women found in the selected households and the number of women successfully interviewed are presented. The data indicate a high response rate for the household interview (96.9 percent), and a lower rate for the individual interview (89.2 percent). Women in large cities have a slightly lower response rate (88.6 percent) than those in other areas. Most of the non-response for the individual interview was due to the absence of respondents and the postponement of interviews which were incomplete.

    Note: See summarized response rates by place of residence in Table 1.1 of the survey report.

    Sampling error estimates

    The results from sample surveys are affected by two types of errors, non-sampling error and sampling error. Nonsampling error is due to mistakes made in carrying out field activities, such as failure to locate and interview the correct household, errors in the way the questions are asked, misunderstanding on the part of either the interviewer or the respondent, data entry errors, etc. Although efforts were made during the design and implementation of the JPFHS to minimize this type of error, non-sampling errors are impossible to avoid and difficult to evaluate statistically

    Sampling errors, on the other hand, can be measured statistically. The sample of women selected in the JPFHS is only one of many samples that could have been selected from the same population, using the same design and expected size. Each one would have yielded results that differed somewhat from the actual sample selected. The sampling error is a measure of the variability between all possible samples; although it is not known exactly, it can be estimated from the survey results.

    Sampling error is usually measured in terms of standard error of a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which one can reasonably assured that, apart from nonsampling errors, the true value of the variable for the whole population falls. For example, for any given statistic calculated from a sample survey, the value of that same statistic as measured in 95 percent of all possible samples with the same design (and expected size) will fall within a range of plus or minus two times the standard error of that statistic.

    If the sample of women had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the JPFI-IS sample design depended on stratification, stages and clusters. Consequently, it was necessary to utilize more complex formulas. The computer package CLUSTERS, developed by the International Statistical Institute for the World Fertility Survey, was used to assist in computing the sampling errors with the proper statistical methodology.

    Note: See detailed estimate of sampling error calculation in APPENDIX B of the survey report.

    Data appraisal

    Data Quality Tables - Household age distribution - Age distribution of eligible and interviewed women - Completeness of reporting - Births by calendar year since birth - Reporting of age at death in days - Reporting of age at death in months

    Note: See detailed tables in APPENDIX C of the report which is presented in this documentation.

  16. n

    Data from: A secure future? Human urban and agricultural land use benefits a...

    • data.niaid.nih.gov
    • search.dataone.org
    • +2more
    zip
    Updated Aug 1, 2023
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    Lucile Lévêque (2023). A secure future? Human urban and agricultural land use benefits a flightless island-endemic rail despite climate change [Dataset]. http://doi.org/10.5061/dryad.2jm63xsv8
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    zipAvailable download formats
    Dataset updated
    Aug 1, 2023
    Dataset provided by
    University of Tasmania
    Authors
    Lucile Lévêque
    License

    https://spdx.org/licenses/CC0-1.0.htmlhttps://spdx.org/licenses/CC0-1.0.html

    Description

    Identifying environmental characteristics that limit species’ distributions is important for contemporary conservation and inferring responses to future environmental change. The Tasmanian native hen is an island-endemic flightless rail and a survivor of a prehistoric extirpation event. Little is known about the regional-scale environmental characteristics influencing the distribution of native hens, or how their future distribution might be impacted by environmental shifts (e.g., climate change). Using a combination of local fieldwork and species distribution modelling, we assess environmental factors shaping the contemporary distribution of the native hen, and project future distribution changes under predicted climate change. We find 37.2% of Tasmania is currently suitable for the native hens, owing to low summer precipitation, low elevation, human-modified vegetation, and urban areas. Moreover, in unsuitable regions, urban areas can create ‘oases’ of habitat, able to support populations with high breeding activity by providing resources and buffering against environmental constraints. Under climate change predictions, native hens were predicted to lose only 5% of their occupied range by 2055. We conclude that the species is resilient to climate change and benefits overall from anthropogenic landscape modifications. As such, this constitutes a rare example of a flightless rail to have adapted to human activity. Methods Local-scale factors measurements (fieldwork) We selected geographically distant populations presenting different rainfall profiles during the late-autumn to spring period, April-November 2019, as rainfall is an important factor for native hens’ survival and reproduction (Ridpath, 1972a; Lévêque, 2022): ‘East’ (wukaluwikiwayna/Maria Island National park; 42°34'51"S 148°03'56"E), ‘North’ (Narawntapu National park; 41°08'53"S 146°36'52"E), and ‘West’ (adjacent to the town of Zeehan [712 inhabitants]; 41°53'03"S 145°19'56"E). The period April-November corresponds to the six-month period preceding the middle point of the breeding season, generally used for native hens’ surveys (Goldizen et al., 1998; Lévêque, 2022). All three populations were surveyed between the 10th and the 22nd of November 2019 (late spring, in the middle point of the breeding season) to determine population structure (total number of groups, group composition [number of adults and young], and breeding activity). Each population was monitored over two to five days, depending on habitat complexity and extent of the population area, until all native hens in the area had been surveyed, i.e., when the territories’ structure was found identical at least four times for populations with no previous data (‘North’ and ‘West’), and at least two times in well-known populations (‘East’; Lévêque, 2022), over two different half-day. To align with methods used by Lévêque (2022), we used territory mapping (Bibby et al., 2000; Gibbons & Gregory, 2006) as native-hens maintain year-round territories, and population sizes were measurable with our survey methodology. Territory mapping consists of establishing the location of birds over a number of visits to obtain distinct clusters representing each territory. Boundaries are determined by vocal disputes between neighbours, which are frequent in native hens. During each survey, a minimum of two observers conducted repeated group identification, based on location, neighbours’ location, and number of individuals per group (from two to five individuals per group in this study). The number of individuals and their age category (fledgling, juvenile, or adult) were recorded per territory. The total pasture area surveyed per population, and the total pasture area occupied by native hens were: North population: 2.0 km2 (1.3 km2 occupied); West population: 1.5 km2 (0.7 km2 occupied); East population: 1.5 km2 (0.6 km2 occupied). We measured environmental characteristics in the native-hens’ territory following methods established by Goldizen et al. (1998) to obtain quantitative measures of i) protection cover, ii) water availability, and iii) food availability; these parameters are important for native hen reproduction (Goldizen et al., 1998).

    Protection cover was determined as the length (m) of the interface between dense patches of bushes and pasture, used by native hens for hiding and protecting chicks against predators (Lévêque, 2022). It is an important parameter for breeding success (Goldizen et al., 1998). We measured the total protection cover available to native hens in each population using satellite data from Google Maps (www.google.com/maps, accessed on 09/12/2019). For measures of food availability (grass) on territories, we selected random transects of a total length of 1 m across all territories (East: n = 15, North: n = 26, West: n = 22). Measurements of vegetation characteristics were measured and recorded every 2 cm along each transect, including the percentage of i) total vegetation cover, ii) green vegetation, iii) vegetation cover that was grass, iv) vegetation cover that was moss, and v) the grass height (average length of grass blades). The same observer (LL) recorded all measures. Water availability on territories was recorded as territories that had access to water (running or stagnant) at the time the surveys were undertaken. Rainfall data was collected from the Bureau of Meteorology (B.O.M.; www.bom.gov.au/climate/data) at the three population sites: North population at Port Sorell (Narawntapu National Park – 4km away from the population site), West population at Zeehan (West Coast Pioneers Museum), East population at Maria Island (Darlington). Rainfall was reported as the amount of rainwater that had accumulated i) during the six months prior to breeding season midpoint (31/10/2019); following Goldizen et al. (1998)) and ii) during summer [December-February]. Information on recent droughts (on a 3- to 11-month period prior to 31/10/2019) was assessed using values on rainfall percentile deficiency (below the 10th percentile) from B.O.M. (http://www.bom.gov.au/climate/drought/#tabs=Rainfall-tracker). The 6-, 7-, and 12- month-periods were not accessible. B.O.M. defines the category ‘Serious deficiency’ as rainfall that “lies above the lowest five percent of recorded rainfall but below the lowest ten percent (decile range 1) for the period in question”, and ‘severe deficiency’ as “rainfall is among the lowest five percent for the period in question”.

    Species Distribution Modelling Data preparation We collected presence-point data for native hens across Tasmania from the Atlas of Living Australia (ALA: www.ala.org.au; accessed 19 February 2021). We additionally included data from BirdLife Tasmania, the Department of Primary Industries, Water and Environment (DPIPWE) reports, and our personal observations, resulting in a total of 23,923 occurrences. Our study area included the Tasmanian mainland and nearby islands, however a large area from the south-west of Tasmania was removed where native hen distribution is not well documented, however, they are thought to be rare or absent in this region due to large proportion of button grass vegetation creating unsuitable habitat (Fig. S2). All subsequent analyses were undertaken in Program R v4.0.4 (R Core Team, 2021). Duplicates were removed by converting presence points into grid presences at 1 km2 resolution and retaining one native hen observation per grid (n = 2447 grid points after this step). Occurrences were visually inspected for any potential errors/outliers from outside Tasmania and Tasmanian islands: this removed seven false occurrences on King and Flinders islands and two observations in freshwater inland lakes (Lake Crescent and Great Lake). As true-absence records were mostly unavailable, we generated pseudoabsences for sites where other land-bird species had been recorded (indicating observation effort at that point), but without native hen detections (Hanberry et al., 2012; Amin et al., 2021; Barlow et al., 2021). Native hens are large-bodied, ground-dwelling, active in the day, and have a loud, distinct call, all of which accounts for a high detectability, if present at a location. We extracted these data from ALA, with 780,499 possible observations on the Tasmanian mainland and all nearby islands. We then excluded all grid cells with a native hen presence and removed any records within 3 km of native hen records: this value was chosen because it is the dispersal distance under which a native hen can naturally move outside of its territory (Ridpath, 1972a). This process resulted in 3,222 pseudoabsence grid points. Citizen-science datasets offer unique opportunities to study a species distribution using ‘crowd-sourced’ effort, however, they tend to be access-biased and have non-random, clustered observations, leading to overrepresentation of certain regions and biases towards some environmental conditions (usually near urban areas; Steen et al., 2021). One way to reduce spatial autocorrelation is to selectively de-cluster occurrences in biased areas using a pre-defined (minimum linear) Nearest Minimum-neighbour Distance NMD (Pearson et al. 2007). As un-urbanised, sparsely populated areas have the least spatial point clustering (and hence spatial bias), the average number of observations in low human densities areas provides the threshold number of records that can be used to tune and select the optimal NMD (Amin et al., 2021). Therefore, we subdivided our data on a grid of 25 km2 cells to be relevant to the metric of human density and used the median of population density index (excluding cells < 1 human/km2) to define thresholds for low and high density. Population density was extracted from the ‘2011 Census of Population and Housing across Australia’ (bit.ly/3bth7W9). ‘Low density’ was defined as < 6 people/km2 and ‘High density’ as

  17. Estimated pre-colonization population of the Americas~1492

    • statista.com
    Updated Jan 1, 1983
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    Statista (1983). Estimated pre-colonization population of the Americas~1492 [Dataset]. https://www.statista.com/statistics/1171896/pre-colonization-population-americas/
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    Dataset updated
    Jan 1, 1983
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Americas
    Description

    Prior to the arrival of European explorers in the Americas in 1492, it is estimated that the population of the continent was around sixty million people. Over the next two centuries, most scholars agree that the indigenous population fell to just ten percent of its pre-colonization level, primarily due to the Old World diseases (namely smallpox) brought to the New World by Europeans and African slaves, as well as through violence and famine.

    Distribution

    It is thought that the most densely populated region of the Americas was in the fertile Mexican valley, home to over one third of the entire continent, including several Mesoamerican civilizations such as the Aztec empire. While the mid-estimate shows a population of over 21 million before European arrival, one estimate suggests that there were just 730,000 people of indigenous descent in Mexico in 1620, just one hundred years after Cortes' arrival. Estimates also suggest that the Andes, home to the Incas, was the second most-populous region in the Americas, while North America (in this case, the region north of the Rio Grande river) may have been the most sparsely populated region. There is some contention as to the size of the pre-Columbian populations in the Caribbean, as the mass genocides, forced relocation, and pandemics that followed in the early stages of Spanish colonization make it difficult to predict these numbers.

    Varying estimates Estimating the indigenous populations of the Americas has proven to be a challenge and point of contention for modern historians. Totals from reputable sources range from 8.4 million people to 112.55 million, and while both of these totals were published in the 1930s and 1960s respectively, their continued citation proves the ambiguity surrounding this topic. European settlers' records from the 15th to 17th centuries have also created challenges, due to their unrealistic population predictions and inaccurate methodologies (for example, many early settlers only counted the number of warriors in each civilization). Nonetheless, most modern historians use figures close to those given in the "Middle estimate" shown here, with similar distributions by region.

  18. m

    Data from: Conversion predictors of Clinically Isolated Syndrome to Multiple...

    • data.mendeley.com
    Updated May 16, 2023
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    Benjamin Pineda (2023). Conversion predictors of Clinically Isolated Syndrome to Multiple Sclerosis in Mexican patients: a prospective study. [Dataset]. http://doi.org/10.17632/8wk5hjx7x2.1
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    Dataset updated
    May 16, 2023
    Authors
    Benjamin Pineda
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Prospective cohort study was conducted in Mexican mestizo patients newly diagnosed with CIS who presented at the National Institute of Neurology and Neurosurgery (NINN) in Mexico City, Mexico, between 2006 and 2010.

  19. Cohort demographics.

    • plos.figshare.com
    xls
    Updated Jul 19, 2024
    + more versions
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    Marwah Al-kaabi; Pooja Deshpande; Martin Firth; Rebecca Pavlos; Abha Chopra; Hamed Basiri; Jennifer Currenti; Eric Alves; Spyros Kalams; Jacques Fellay; Elizabeth Phillips; Simon Mallal; Mina John; Silvana Gaudieri (2024). Cohort demographics. [Dataset]. http://doi.org/10.1371/journal.ppat.1012359.t001
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    xlsAvailable download formats
    Dataset updated
    Jul 19, 2024
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Marwah Al-kaabi; Pooja Deshpande; Martin Firth; Rebecca Pavlos; Abha Chopra; Hamed Basiri; Jennifer Currenti; Eric Alves; Spyros Kalams; Jacques Fellay; Elizabeth Phillips; Simon Mallal; Mina John; Silvana Gaudieri
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    A strong genetic predictor of outcome following untreated HIV-1 infection is the carriage of specific alleles of human leukocyte antigens (HLAs) that present viral epitopes to T cells. Residual variation in outcome measures may be attributed, in part, to viral adaptation to HLA-restricted T cell responses. Variants of the endoplasmic reticulum aminopeptidases (ERAPs) influence the repertoire of T cell epitopes presented by HLA alleles as they trim pathogen-derived peptide precursors to optimal lengths for antigen presentation, along with other functions unrelated to antigen presentation. We investigated whether ERAP variants influence HLA-associated HIV-1 adaptation with demonstrable effects on overall HIV-1 disease outcome. Utilizing host and viral data of 249 West Australian individuals with HIV-1 subtype B infection, we identified a novel association between two linked ERAP2 single nucleotide polymorphisms (SNPs; rs2248374 and rs2549782) with plasma HIV RNA concentration (viral load) (P adjusted = 0.0024 for both SNPs). Greater HLA-associated HIV-1 adaptation in the HIV-1 Gag gene correlated significantly with higher viral load, lower CD4+ T cell count and proportion; P = 0.0103, P = 0.0061, P = 0.0061, respectively). When considered together, there was a significant interaction between the two ERAP2 SNPs and HLA-associated HIV-1 adaptation on viral load (P = 0.0111). In a comprehensive multivariate model, addition of ERAP2 haplotypes and HLA associated adaptation as an interaction term to known HLA and CCR5 determinants and demographic factors, increased the explanatory variance of population viral load from 17.67% to 45.1% in this dataset. These effects were not replicated in publicly available datasets with comparably sized cohorts, suggesting that any true global epistasis may be dependent on specific HLA-ERAP allelic combinations. Our data raises the possibility that ERAP2 variants may shape peptide repertoires presented to HLA class I-restricted T cells to modulate the degree of viral adaptation within individuals, in turn contributing to disease variability at the population level. Analyses of other populations and experimental studies, ideally with locally derived ERAP genotyping and HLA-specific viral adaptations are needed to elucidate this further.

  20. f

    DataSheet_1_Influence of HLA Class II Polymorphism on Predicted Cellular...

    • frontiersin.figshare.com
    docx
    Updated May 30, 2023
    + more versions
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    Hannah C. Copley; Loren Gragert; Andrew R. Leach; Vasilis Kosmoliaptsis (2023). DataSheet_1_Influence of HLA Class II Polymorphism on Predicted Cellular Immunity Against SARS-CoV-2 at the Population and Individual Level.docx [Dataset]. http://doi.org/10.3389/fimmu.2021.669357.s001
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    docxAvailable download formats
    Dataset updated
    May 30, 2023
    Dataset provided by
    Frontiers
    Authors
    Hannah C. Copley; Loren Gragert; Andrew R. Leach; Vasilis Kosmoliaptsis
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Development of adaptive immunity after COVID-19 and after vaccination against SARS-CoV-2 is predicated on recognition of viral peptides, presented on HLA class II molecules, by CD4+ T-cells. We capitalised on extensive high-resolution HLA data on twenty five human race/ethnic populations to investigate the role of HLA polymorphism on SARS-CoV-2 immunogenicity at the population and individual level. Within populations, we identify wide inter-individual variability in predicted peptide presentation from structural, non-structural and accessory SARS-CoV-2 proteins, according to individual HLA genotype. However, we find similar potential for anti-SARS-CoV-2 cellular immunity at the population level suggesting that HLA polymorphism is unlikely to account for observed disparities in clinical outcomes after COVID-19 among different race/ethnic groups. Our findings provide important insight on the potential role of HLA polymorphism on development of protective immunity after SARS-CoV-2 infection and after vaccination and a firm basis for further experimental studies in this field.

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Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2022). ‘World Population Data’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/kaggle-world-population-data-9453/0454f7ef/?iid=004-217&v=presentation

‘World Population Data’ analyzed by Analyst-2

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Dataset updated
Jan 28, 2022
Dataset authored and provided by
Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Area covered
World
Description

Analysis of ‘World Population Data’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/kuntalmaity/world-population-data on 28 January 2022.

--- Dataset description provided by original source is as follows ---

Population in the world is currently (2020) growing at a rate of around 1.05% per year (down from 1.08% in 2019, 1.10% in 2018, and 1.12% in 2017). The current average population increase is estimated at 81 million people per year. Annual growth rate reached its peak in the late 1960s, when it was at around 2%.

--- Original source retains full ownership of the source dataset ---

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