28 datasets found
  1. Population density in Tokyo Prefecture, Japan 2000-2020

    • statista.com
    • ai-chatbox.pro
    Updated Jul 11, 2025
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    Statista (2025). Population density in Tokyo Prefecture, Japan 2000-2020 [Dataset]. https://www.statista.com/statistics/673679/japan-population-density-toyko/
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    Dataset updated
    Jul 11, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Japan
    Description

    In 2020, the population of Tokyo Metropolis amounted to over ***** inhabitants per square kilometer. The number increased from approximately ***** inhabitants per square kilometer in 2000.

  2. Population density in the Greater Tokyo Area 1985-2015

    • statista.com
    Updated Dec 1, 2016
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    Statista (2016). Population density in the Greater Tokyo Area 1985-2015 [Dataset]. https://www.statista.com/statistics/673621/japan-population-density-greater-toyko/
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    Dataset updated
    Dec 1, 2016
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    1985 - 2015
    Area covered
    Japan
    Description

    The statistic presents the population density in the Greater Tokyo Area in Japan from 1985 to 2015. In 1985, Greater Tokyo's population amounted to ***** inhabitants per square kilometer. This number increased to almost ***** inhabitants per square kilometer in 2015.

  3. e

    Japan - Population density - Dataset - ENERGYDATA.INFO

    • energydata.info
    Updated Jul 23, 2024
    + more versions
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    (2024). Japan - Population density - Dataset - ENERGYDATA.INFO [Dataset]. https://energydata.info/dataset/japan--population-density-2015
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    Dataset updated
    Jul 23, 2024
    License

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

    Area covered
    Japan
    Description

    Population density per pixel at 100 metre resolution. WorldPop provides estimates of numbers of people residing in each 100x100m grid cell for every low and middle income country. Through ingegrating cencus, survey, satellite and GIS datasets in a flexible machine-learning framework, high resolution maps of population counts and densities for 2000-2020 are produced, along with accompanying metadata. DATASET: Alpha version 2010 and 2015 estimates of numbers of people per grid square, with national totals adjusted to match UN population division estimates (http://esa.un.org/wpp/) and remaining unadjusted. REGION: Africa SPATIAL RESOLUTION: 0.000833333 decimal degrees (approx 100m at the equator) PROJECTION: Geographic, WGS84 UNITS: Estimated persons per grid square MAPPING APPROACH: Land cover based, as described in: Linard, C., Gilbert, M., Snow, R.W., Noor, A.M. and Tatem, A.J., 2012, Population distribution, settlement patterns and accessibility across Africa in 2010, PLoS ONE, 7(2): e31743. FORMAT: Geotiff (zipped using 7-zip (open access tool): www.7-zip.org) FILENAMES: Example - AGO10adjv4.tif = Angola (AGO) population count map for 2010 (10) adjusted to match UN national estimates (adj), version 4 (v4). Population maps are updated to new versions when improved census or other input data become available.

  4. a

    Growth of Megacities-Tokyo

    • gis-for-secondary-schools-schools-be.hub.arcgis.com
    • hub.arcgis.com
    • +1more
    Updated Sep 8, 2014
    + more versions
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    ArcGIS StoryMaps (2014). Growth of Megacities-Tokyo [Dataset]. https://gis-for-secondary-schools-schools-be.hub.arcgis.com/maps/1fa848e239a34889b0f943b3891be736
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    Dataset updated
    Sep 8, 2014
    Dataset authored and provided by
    ArcGIS StoryMaps
    Area covered
    Description

    The Global Human Footprint dataset of the Last of the Wild Project, version 2, 2005 (LWPv2) is the Human Influence Index (HII) normalized by biome and realm. The HII is a global dataset of 1 km grid cells, created from nine global data layers covering human population pressure (population density), human land use and infraestructure (built-up areas, nighttime lights, land use/land cover) and human access (coastlines, roads, navigable rivers).The Human Footprint Index (HF) map, expresses as a percentage the relative human influence in each terrestrial biome. HF values from 0 to 100. A value of zero represents the least influence -the "most wild" part of the biome with value of 100 representing the most influence (least wild) part of the biome.

  5. d

    Japan Point of Interest (POI) & Mobility Data | 15M+ Businesses & Places

    • datarade.ai
    .json, .csv
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    dataplor, Japan Point of Interest (POI) & Mobility Data | 15M+ Businesses & Places [Dataset]. https://datarade.ai/data-products/japan-point-of-interest-poi-data-15m-places-cpg-sale-dataplor
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    .json, .csvAvailable download formats
    Dataset authored and provided by
    dataplor
    Area covered
    Japan
    Description

    dataplor specializes in delivering highly precise, actionable intelligence tailored for businesses operating within the complex Japanese market. Our in-depth Point of Interest and foot traffic dataset for Japan is a cornerstone for businesses seeking to optimize operations and expand their footprint across the country.

    Unlocking Japan's Potential with dataplor's POI Data Third-party Logistics / Order Fulfillment: Leverage our dataset to optimize delivery routes, identify optimal warehouse locations in bustling cities like Tokyo, Osaka, and Nagoya, and enhance last-mile delivery efficiency in densely populated urban areas.

    Consumer Product Goods (CPGs): Gain a competitive edge by identifying ideal store locations in high-traffic areas, understanding consumer preferences across different regions and optimizing product distribution strategies. Telecommunication: Identify areas with high smartphone penetration, analyze competitor tower locations, and optimize network coverage in major cities and rural prefectures.

    Finance and Investment: Evaluate potential investment opportunities by analyzing POI density and distribution in different regions (Tokyo, Osaka, Fukuoka), identifying affluent neighborhoods, and assessing the competitive landscape.

    Store Location Data: Identify ideal store locations based on factors such as population density, competition, and consumer spending patterns in cities like Tokyo, Osaka, and Nagoya. Real Estate Intelligence: Assess property values based on location and surrounding amenities in major cities and regional areas.

    Audience Targeting Data: Create highly targeted marketing campaigns through targeted marketing placement in high-density POI areas across Tokyo, Osaka, and Kyoto.

    Travel Booking Data: Identify popular tourist destinations, analyze hotel and accommodation availability, and optimize travel itineraries for domestic and international visitors. dataplor's Japan POI dataset offers unparalleled granularity and accuracy, empowering businesses to make informed decisions and achieve sustainable growth in this dynamic market.

  6. Urbanization in Japan 2023

    • statista.com
    Updated Jun 13, 2025
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    Statista (2025). Urbanization in Japan 2023 [Dataset]. https://www.statista.com/statistics/270086/urbanization-in-japan/
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    Dataset updated
    Jun 13, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Japan
    Description

    In the past decade, Japan’s degree of urbanization has leveled off at around 92.04 percent. This means that less than 10 percent of Japan’s population of 126 million inhabitants do not live in an urban setting. Japan is well above the degree of urbanization worldwide, which is 55 percent. Japan is also known for its high population density: In 2017, it amounted to an eye-watering 347.78 inhabitants per square kilometer - however, it is not even among the top twenty countries with the highest population density worldwide. That ranking is lead by Monaco, followed by China, and Singapore. Japan’s aging population The main demographic challenge that Japan currently faces is an aging population, as the number of inhabitants over 65 years old is an increasing percentage of the population. As of 2018, Japan is the country with the largest percentage of total population over 65 years, and life expectancy at birth there is about 84 years. Simultaneously, the birth rate in Japan is declining, resulting in negative population growth in recent years. One method Japan is using to address these demographic shifts is by investing in automated work processes; it's one of the top countries interested in collaborative robots.

  7. Estimation results for detailed periods.

    • plos.figshare.com
    xls
    Updated Jun 4, 2023
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    Kazufumi Tsuboi; Naoya Fujiwara; Ryo Itoh (2023). Estimation results for detailed periods. [Dataset]. http://doi.org/10.1371/journal.pone.0276741.t002
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    xlsAvailable download formats
    Dataset updated
    Jun 4, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Kazufumi Tsuboi; Naoya Fujiwara; Ryo Itoh
    License

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

    Description

    Estimation results for detailed periods.

  8. f

    Estimation results for the weekend afternoon.

    • figshare.com
    xls
    Updated May 31, 2023
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    Kazufumi Tsuboi; Naoya Fujiwara; Ryo Itoh (2023). Estimation results for the weekend afternoon. [Dataset]. http://doi.org/10.1371/journal.pone.0276741.t003
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    xlsAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Kazufumi Tsuboi; Naoya Fujiwara; Ryo Itoh
    License

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

    Description

    Estimation results for the weekend afternoon.

  9. f

    Tokyo Vulerability and Healthcare Accessibility

    • figshare.com
    zip
    Updated Jul 8, 2022
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    Siqin Wang (2022). Tokyo Vulerability and Healthcare Accessibility [Dataset]. http://doi.org/10.6084/m9.figshare.20268738.v1
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    zipAvailable download formats
    Dataset updated
    Jul 8, 2022
    Dataset provided by
    figshare
    Authors
    Siqin Wang
    License

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

    Area covered
    Tokyo
    Description

    The ongoing multi-wave COVID-19 pandemic has disproportional impacts on people with different demographic and socioeconomic background, and their access to healthcare facilities. Vulnerable neighborhoods with low healthcare access are places most needed for the enhancement of medical resources and services. Measuring vulnerability to COVID-19 and healthcare accessibility at the fine-grained level serves as the foundation for spatially explicit health planning and policy making in response to future public health crisis. Despite of its importance, the evaluation of vulnerability and healthcare accessibility is insufficient in Japan—a nation with high population density and super-aging challenge. Drawing on the latest 2022 census data at the smallest statistical unit, as well as transport network, medical and digital cadastral data, land use maps, and points of interest data, our study reformulates the concept of vulnerability in the context of COVID-19 and constructs the first fine-grained measure of vulnerability and healthcare accessibility in Tokyo Metropolis, Japan—the most popular metropolitan region in the world. We delineate the vulnerable neighborhoods with low healthcare access and further evaluate the disparity in healthcare access and built environment of areas at different levels of vulnerability. Our outcome datasets and findings provide nuanced and timely evidence to government and health authorities to have a holistic and latest understanding of social vulnerability to COVID-19 and healthcare access at a fine-grained level. Our analytical framework can be employed to different geographic contexts, guiding through the place-based health planning and policy making in the post-COVID era and beyond.

  10. f

    Comparison of the resultsa,b of the conditional quantile regression models...

    • plos.figshare.com
    xls
    Updated Oct 11, 2023
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    Hongjik Kim; Hiroki Baba; Chihiro Shimizu; Kimihiro Hino (2023). Comparison of the resultsa,b of the conditional quantile regression models (50% quantile) between central and other cities. [Dataset]. http://doi.org/10.1371/journal.pone.0292657.t003
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    xlsAvailable download formats
    Dataset updated
    Oct 11, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Hongjik Kim; Hiroki Baba; Chihiro Shimizu; Kimihiro Hino
    License

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

    Description

    Comparison of the resultsa,b of the conditional quantile regression models (50% quantile) between central and other cities.

  11. Global megacity populations 2025

    • statista.com
    • ai-chatbox.pro
    Updated May 27, 2025
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    Statista (2025). Global megacity populations 2025 [Dataset]. https://www.statista.com/statistics/912263/population-of-urban-agglomerations-worldwide/
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    Dataset updated
    May 27, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2025
    Area covered
    World
    Description

    As of 2025, Tokyo-Yokohama in Japan was the largest world urban agglomeration, with 37 million people living there. Delhi ranked second with more than 34 million, with Shanghai in third with more than 30 million inhabitants.

  12. f

    Comparison of the resultsa,b of the conditional quantile regression models...

    • plos.figshare.com
    xls
    Updated Oct 11, 2023
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    Hongjik Kim; Hiroki Baba; Chihiro Shimizu; Kimihiro Hino (2023). Comparison of the resultsa,b of the conditional quantile regression models by price range (N = 71,289). [Dataset]. http://doi.org/10.1371/journal.pone.0292657.t004
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    xlsAvailable download formats
    Dataset updated
    Oct 11, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Hongjik Kim; Hiroki Baba; Chihiro Shimizu; Kimihiro Hino
    License

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

    Description

    Comparison of the resultsa,b of the conditional quantile regression models by price range (N = 71,289).

  13. n

    Tokyo Bay measurements from 1982-1984

    • cmr.earthdata.nasa.gov
    • s.cnmilf.com
    • +3more
    Updated Apr 6, 2023
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    (2023). Tokyo Bay measurements from 1982-1984 [Dataset]. http://doi.org/10.5067/SeaBASS/TOKYO_BAY/DATA001
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    Dataset updated
    Apr 6, 2023
    Time period covered
    Nov 25, 1982 - Present
    Area covered
    Earth
    Description

    Measurements taken in the Tokyo Bay between 1982 and 1984.

  14. f

    Characteristicsa of single-family detached houses sold between 2015 and...

    • plos.figshare.com
    xls
    Updated Oct 11, 2023
    + more versions
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    Hongjik Kim; Hiroki Baba; Chihiro Shimizu; Kimihiro Hino (2023). Characteristicsa of single-family detached houses sold between 2015 and 2020. [Dataset]. http://doi.org/10.1371/journal.pone.0292657.t001
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    xlsAvailable download formats
    Dataset updated
    Oct 11, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Hongjik Kim; Hiroki Baba; Chihiro Shimizu; Kimihiro Hino
    License

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

    Description

    Characteristicsa of single-family detached houses sold between 2015 and 2020.

  15. Population of Japan 1800-2020

    • statista.com
    Updated Aug 9, 2024
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    Statista (2024). Population of Japan 1800-2020 [Dataset]. https://www.statista.com/statistics/1066956/population-japan-historical/
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    Dataset updated
    Aug 9, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Japan
    Description

    In 1800, the population of Japan was just over 30 million, a figure which would grow by just two million in the first half of the 19th century. However, with the fall of the Tokugawa shogunate and the restoration of the emperor in the Meiji Restoration of 1868, Japan would begin transforming from an isolated feudal island, to a modernized empire built on Western models. The Meiji period would see a rapid rise in the population of Japan, as industrialization and advancements in healthcare lead to a significant reduction in child mortality rates, while the creation overseas colonies would lead to a strong economic boom. However, this growth would slow beginning in 1937, as Japan entered a prolonged war with the Republic of China, which later grew into a major theater of the Second World War. The war was eventually brought to Japan's home front, with the escalation of Allied air raids on Japanese urban centers from 1944 onwards (Tokyo was the most-bombed city of the Second World War). By the war's end in 1945 and the subsequent occupation of the island by the Allied military, Japan had suffered over two and a half million military fatalities, and over one million civilian deaths.

    The population figures of Japan were quick to recover, as the post-war “economic miracle” would see an unprecedented expansion of the Japanese economy, and would lead to the country becoming one of the first fully industrialized nations in East Asia. As living standards rose, the population of Japan would increase from 77 million in 1945, to over 127 million by the end of the century. However, growth would begin to slow in the late 1980s, as birth rates and migration rates fell, and Japan eventually grew to have one of the oldest populations in the world. The population would peak in 2008 at just over 128 million, but has consistently fallen each year since then, as the fertility rate of the country remains below replacement level (despite government initiatives to counter this) and the country's immigrant population remains relatively stable. The population of Japan is expected to continue its decline in the coming years, and in 2020, it is estimated that approximately 126 million people inhabit the island country.

  16. Population density of Singapore 2005-2024

    • statista.com
    Updated Feb 21, 2025
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    Statista (2025). Population density of Singapore 2005-2024 [Dataset]. https://www.statista.com/statistics/778525/singapore-population-density/
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    Dataset updated
    Feb 21, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Singapore
    Description

    In 2024, the population density of Singapore was 8,207 people per square kilometers. The population of Singapore had been increasing over the years within a very limited space, posing challenges such as housing shortages and land scarcity. Limited land, expanding population With an urban population of around 5.69 million people in 2020 and a land area of approximately 720 square kilometers, Singapore was the third most densely populated territory in the world. This was not expected to ease in the near future, with the population of Singapore estimated to grow to 6.52 million people in 2035. While this might not come close to the population size of other Asian metropolises such as Tokyo or Bangkok, the lack of land available for development poses a great challenge to the island city-state. Since its independence in 1965, Singapore has increased its land area from 581.5 square kilometers to its current size through land reclamation. However, Singapore’s proximity to Malaysia and the Riau Islands in Indonesia effectively limit the available area for reclamation to its maritime borders. The importance of urban planning Urban planning in Singapore must therefore make effective use of what little land is available without compromising livability. Most residents live in apartments situated in high-rise buildings, with a large majority of the population living in public housing provided by the Housing Development Board. Rooftop gardens, tree-lined roads and green innovations such as vertical farming and “breathing walls” help soften the presence of all that glass and concrete, earning Singapore its moniker of “Garden City”. Whether and how well Singapore can sustain the quality of life that its residents are used to with an ever-increasing population density in the next twenty years is, however, to be seen.

  17. m

    Ionospheric parameters scaled manually from Tokyo ionosonde

    • meta.meteo.ru
    Updated Apr 21, 2019
    + more versions
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    (2019). Ionospheric parameters scaled manually from Tokyo ionosonde [Dataset]. http://meta.meteo.ru/geonetwork/static/search?format=TXT
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    Dataset updated
    Apr 21, 2019
    Area covered
    Tokyo
    Description

    Some parameters which are manually scaled from ionosondes obtained at Kokubunji station in Tokyo, Japan. The ionosonde sweeps HF radio pulses from 1MHz to 30MHz, basically every 15 minutes. The transmitted radio pulses travel more slowly within the ionosphere, depending on the ionospheric plasma density. The apparent height, that is, virtual height of the reflection point is recorded for each frequency of the transmitted HF radio wave in ionograms. When the frequencies become higher than the maximum plasma frequency of the ionospheric layer, the radio wave pass through the layer and be lost in space. The frequency which corresponds to the maximum plasma frequency of each layer is called critical frequency. Some parameters such as critical frequency (e.g., foF2, foEs) and virtual heights (h’F2, h’Es) are manually scaled basically every 1 hour. Time is Japanese Standard Time (JST), which is UTC + 9.

  18. Number of dental clinics Japan 2019, by prefecture

    • statista.com
    Updated Jan 9, 2024
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    Statista (2024). Number of dental clinics Japan 2019, by prefecture [Dataset]. https://www.statista.com/statistics/1182104/japan-number-dental-clinics-by-prefecture/
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    Dataset updated
    Jan 9, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Japan
    Description

    There was a total number of 68.5 thousand dental clinics in Japan as of October 2019, of which around 10.7 thousand were located in Tokyo Prefecture. That year, the prefecture with the highest density of dental practices was also Tokyo, with around 76.6 facilities per 100 thousand inhabitants.

  19. o

    An eQTL study in the Japanese population [gene expression_3]

    • omicsdi.org
    Updated Nov 27, 2012
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    (2012). An eQTL study in the Japanese population [gene expression_3] [Dataset]. https://www.omicsdi.org/dataset/biostudies/E-GEOD-42229
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    Dataset updated
    Nov 27, 2012
    Area covered
    Japan
    Variables measured
    Unknown
    Description

    A genome-wide eQTL analysis was performed in whole blood samples collected from 76 Japanese subjects. RNA microarray analysis was performed for 3 independent samples that were genotyped in a genome-wide scan. The correlations between the genotypes of 534,404 autosomal single nucleotide polymorphisms (SNPs) and the expression levels of 30,465 probes were examined for each sample. The SNP-probe pairs with combined correlation coefficients of all 3 samples corresponding to P < 3.10 × 10-12 (i.e., Bonferroni-corrected P < 0.05) were considered significant. SNP-probe pairs with a high likelihood of cross-hybridization and SNP-in-probe effects were excluded to exclude false positive results. We identified 102 cis-acting and 5 trans-acting eQTL regions. The cis-eQTL regions were widely distributed both upstream and downstream of the gene, as well as within the gene. RNA microarray data obtained from 3 independent samples originally recruited for other studies investigating the gene expression levels in psychiatric disorders were used in the present study. For the purpose of the present analyses, genomic DNA was collected from 24 subjects (13 men and 11 women, mean age [SD] = 39.9 [7.6] years) in sample 1, 24 subjects in sample 2 (12 men and 12 women, 34.1 [11.5] years), and 28 subjects (14 men and 14 women, 41.4 [11.8] years) in sample 3. Some of the subjects had depressive symptoms, but all were physically healthy and without clinically significant systemic disease (e.g., malignant disease, diabetes mellitus, hypertension, renal failure, or endocrine disorders). Subjects were recruited from the outpatient clinic of the National Center of Neurology and Psychiatry Hospital, Tokyo, Japan, through advertisements in free local information magazines or through our website announcement. All the subjects were biologically unrelated Japanese individuals who resided in the same geographical area (western Tokyo). The study protocol was approved by the ethics committee at the National Center of Neurology and Psychiatry, Japan. Written informed consent was obtained from every subject after the study was explained to them. Venous blood was collected between 1100 and 1200 h in PAXgene tubes (Qiagen, Valencia) from each subject and was incubated at room temperature for 24 h for RNA stabilization. RNA was extracted from whole blood according to the manufacturer’s guidelines by using the PAXgene Blood RNA System Kit (PreAnalytix GmbH, Hombrechtikon, Switzerland). The RNA was quantified by optical density readings at A260nm by using the NanoDrop ND-1000 (Thermo Scientific, Rockford). Gene expression analysis was performed using Agilent Human Genome 4 × 44 K arrays (Agilent Technologies, Santa Clara). Raw signal data for each of the 3 independent samples were analyzed separately by the GeneSpring GX software (Agilent Technologies). Data were filtered according to the expression level for quality control to eliminate genes that were below the 20th percentile threshold. The expression value of each gene was normalized to the median expression value of all genes in each chip. A total of 30,465 probes were included in the analysis. Genomic DNA was obtained from venous blood samples. Genotyping was performed by Riken Genesis (Yokohama, Japan) using the Illumina HumanOmni1-Quad BeadChip (Illumina, Inc., San Diego). A total of 713,495 autosomal SNPs were assessed for quality using the PLINK v1.07 software. All SNPs with a call rate below 95%, a deviation from Hardy-Weinberg equilibrium at an error level of P < 0.001, or a minor allele frequency of less than 10% were excluded. The remaining 534,404 SNPs were used for further analysis.

  20. R

    Japan Cardiac Surgery Instruments Market Size | Growth Analysis 2036

    • researchnester.com
    Updated Jan 6, 2025
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    Research Nester (2025). Japan Cardiac Surgery Instruments Market Size | Growth Analysis 2036 [Dataset]. https://www.researchnester.com/reports/japan-cardiac-surgery-instruments-market/6927
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    Dataset updated
    Jan 6, 2025
    Dataset authored and provided by
    Research Nester
    License

    https://www.researchnester.comhttps://www.researchnester.com

    Area covered
    Japan
    Description

    The cardiac surgery instruments market in Japan size was valued at USD 141.3 million in 2024 and is anticipated to surpass USD 357.1 million by the end of 2036, expanding at a CAGR of 8% during the forecast period, i.e., 2025-2036. Tokyo is the largest healthcare market in Japan due to the high population density that puts pressure on the healthcare delivery systems for cardiac surgery instruments.

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Statista (2025). Population density in Tokyo Prefecture, Japan 2000-2020 [Dataset]. https://www.statista.com/statistics/673679/japan-population-density-toyko/
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Population density in Tokyo Prefecture, Japan 2000-2020

Explore at:
Dataset updated
Jul 11, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Area covered
Japan
Description

In 2020, the population of Tokyo Metropolis amounted to over ***** inhabitants per square kilometer. The number increased from approximately ***** inhabitants per square kilometer in 2000.

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