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6,569 results for “Long-term”
Data from: Plant, soil and microbial controls on grassland diversity restoration: a long-term, multi-site mesocosm experiment
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Data from: Mercury exposure in an endangered seabird: long-term changes and relationships with trophic ecology and breeding success
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Data from: Hypogonadism and low bone mineral density in patients on long-term intrathecal opioid delivery therapy
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Verification of the accuracy of the recent 50 years of tree growth and long-term change in intrinsic water-use efficiency using xylem Δ14C and δ13C in trees in an aseasonal tropical rainforest
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Data set for: Long-term Perfluorooctanesulfonic acid (PFOS) exposure alters anxiety-like behaviour but not boldness in zebrafish (Danio rerio)
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Long-term trends in the phylogenetic and functional diversity of Anatidae in South China coastal wetlands
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Temporal trends in case fatality, discharge destination, and admission to long-term care after acute stroke
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Data from: Transcriptome analysis of Drosophila melanogaster laboratory strains of different geographical origin after long-term laboratory maintenance
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As the Wind Blows: The Effects of Long-Term Exposure to Air Pollution on Mortality
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Long-term study reveals top-down effect of crabs on a California salt marsh
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Meiobenthos abundance. Long-term variability and dynamics of estuarine meiobenthic populations for North Inlet Estuary, South Carolina, from 1972 to 1992, North Inlet LTER
The original purpose of this research was to determine if natural meiobenthic assemblages exhibited continuity over time and to monitor several physical variables to determine if these influenced long-term temporal patterns. The most recent study focused on variation and the relations of meiobenthos abundance with environmental factors over 11 years. Typically marine benthic community studies are limited temporally and the majority of previously published 'longterm' meiofauna results (all taxa) were based on about a year's duration.
LBA-ECO TG-07 Long-Term Soil Gas Flux and Root Mortality, Tapajos National Forest
This data set reports measurements of trace gas fluxes of methane (CH4), nitric oxide (N2O), nitrous oxide (NO), carbon dioxide (CO2) from soils at a study site in the Tapajos National Forest (TNF), near the km 83 on the Santarem-Cuiaba Highway south of Santarem, Para, Brazil. Data for root mass and carbon content, soil nitrogen (N), nitrification, and moisture content are also provided. There are five comma-delimited data files with this data set.The research was conducted to test the effects of root mortality on the soil-atmosphere trace-gas fluxes over the course of one year. Root mortality was induced by isolating blocks of land to 1 m depth using trenching and root exclusion screening. Gas fluxes were measured weekly for ten weeks following the trenching treatment and monthly for the remainder of the year.Note: The related data set LBA-ECO TG-07 Soil Trace Gas Flux and Root Mortality, Tapajos National Forest contains the same flux data that were measured weekly for ten weeks following the trenching treatment. This data set also provides the monthly data for the remainder of the year.
Multi-Satellite Volcanic Sulfur Dioxide L4 Long-Term Global Database V4 (MSVOLSO2L4) at GES DISC
Version 4 is the current version of the data set. Older versions are no longer available and have been superseded by Version 4.These data are a part of MEaSUREs 2012 projects. The particular project, "Multi-Decadal Sulfur Dioxide Climatology from Satellite Instruments", is expected to produce SO2 Earth Science Data Record by means of combining measurements from backscatter Ultraviolet (BUV), thermal infrared (IR) and microwave (MLS) instruments on multiple satellites. The data represent best estimates of the volcanic and anthropogenic contribution to global atmospheric SO2 concentrations. Since SO2 is the major precursor of sulfate aerosol, which has climate and air quality impact, SO2 measurements will contribute to better understanding of the sulfate aerosol distributions and its atmospheric impact."The released data file is a long-term database of volcanic SO2 emission derived from ultraviolet satellite measurements from October 31, 1978, to present.Data are in a table format in simple ASCII format:Column Descriptions:Column 1 = Name of volcano.Column 2 = Latitude of volcano.Column 3 = Longitude of volcano.Column 4 = Altitude of volcano (km).Column 5 = Eruption year.Column 6 = Eruption month of year.Column 7 = Eruption day of month.Column 8 = Eruption style: exp = explosive, eff = effusive.Column 9 = Eruption volcanic explosivity index (nd = no data or undetermined).Column 10 = Observed plume altitude (km) where known.Column 11 = Estimated plume altitude (km) above vent: 10 km for explosive, 5 km for effusive.Column 12 = Measured SO2 mass in kilotons (= 1000 metric tons).
Multi-Satellite Air Quality Sulfur Dioxide (SO2) Database Long-Term L4 Global V2 (MSAQSO2L4) at GES DISC
These data are a part of Multi-Decadal Sulfur Dioxide (SO2) Climatology from Satellite Instruments (MEaSUREs-12-0022 project). Version 2 of the global catalogue of emissions from large SO2 point sources combines data from the Ozone Monitoring Instrument (OMI) on NASA's EOS Aura spacecraft, the Ozone Mapping and Profiler Suite (OMPS) on the NASA-NOAA Suomi National Polar-orbiting Partnership (SNPP), and the TROPOspheric Monitoring Instrument (TROPOMI) on the ESA/Copernicus Sentinel-5 Precursor (S-5P) spacecraft.The catalogue MSAQSO2L4 file contains the site coordinates, source type, country, source name, annual SO2 emissions, annual emission uncertainties, and the number of satellite pixels in the fitting area for three satellite instruments as well as for their weighted average.The emission estimates are based on operational version 2 OMI and OMPS Principal Component Analysis (PCA) retrieval algorithm SO2 slant column density (SCD) data (Li et al., 2020) as well as on new TROPOMI Covariance-Based Retrieval Algorithm (COBRA) SCD data (Theys et al., 2021). A single time-independent site-specific Air-Mass Factor (AMF) value for each site was calculated (McLinden et al., 2014) and applied consistently to each satellite SCD dataset to derive SO2 vertical column densities (VCDs=SCDs/AMFs). The emission estimate method is based on a fit of satellite VCDs to an empirical plume model developed to describe the SO2 spatial distribution near emission point sources. The plume model assumes that the SO2 concentrations emitted from a point source decline exponentially with distance and that they are affected by turbulent diffusion that can be described by a two-dimensional (2D) exponentially modified Gaussian function. The total SO2 mass is derived from the fit and the annual emission rate is calculated as the ratio between the total mass and the prescribed SO2 lifetime.
Long-Term Arctic Growing Season NDVI Trends from GIMMS 3g, 1982-2012
This data set provides normalized difference vegetation index (NDVI) data for the arctic growing season derived primarily with data from Advanced Very High Resolution Radiometer (AVHRR) sensors onboard several NOAA satellites over the years 1982 through 2012. The NDVI data, which show vegetation activity, were averaged annually for the arctic growing season (GS; June, July and August). The products include the annual GS-NDVI values and the results of a cumulative GS-NDVI time series trends analysis. The data are circumpolar in coverage at 8-km resolution and limited to greater than 20 degrees N.These normalized difference vegetation index (NDVI) trends were calculated using the third generation data set from the Global Inventory Modeling and Mapping Studies (GIMMS 3g). GIMMS 3g improves on its predecessor (GIMMS g) in three important ways. First, GIMMS 3g integrates data from NOAA-17 and 18 satellites to lengthen its record. Second, it addresses the spatial discontinuity north of 72 degrees N, by using SeaWiFS, in addition to SPOT VGT, to calibrate between the second and third versions of the AVHRR sensor (AVHRR/2 and AVHRR/3). Finally, the GIMMS 3g algorithm incorporates improved snowmelt detection and is calibrated based on data from the shorter, arctic growing season (May-September) rather than the entire year (January-December).
Plasticity of the human IgM repertoire in response to a long-term spaceflight
Immune dysregulation is among the main adverse outcomes of spaceflight. Despite its crucial role in host protection effects on the human antibody repertoire are unknown. Consequently we examined the IgM repertoire of five cosmonauts 25 days before launch after 64 and 129 days spent on the International Space Station (ISS) and after 1 7 and 30 days of Earth reambulation using high-throughput sequencing. This is the first study of this kind. Our data revealed that the IgM repertoire of cosmonauts was different from the one of control subjects already prior to launch and that 2 out the 5 analyzed cosmonauts presented significant changes of their IgM repertoire during the mission. These modifications persisted up to 30 days after landing likely affected the specificities of IgM binding sites correlated with changes of the V(D)J recombination process in charge of creating functional antibody genes and coincided with a higher stress response. These data confirm that about half of the astronauts who spent six months on the ISS are subjected to immunological changes contribute to explain increased susceptibility to infection reveal individual responses and consequently that personalized approaches should be implemented during future deep-space exploration missions that will endure for an unprecedented amount of time.
RNA-Seq transcriptome analysis of reactive oxygen species gene network in Mizuna plants grown in long-term space flight
Space environment is suspected to generate reactive oxygen species (ROS) and induce oxidative stress in plants however little is known about the gene expression of ROS gene network in plants grown in long-term space flight. RNA-Seq was used to define the large-scale gene expression profiles of Mizuna harvested after 27 days cultivation in the international space station to understand the molecular response and adaptation to space environment.Results: Total reads of transcripts from the Mizuna grown in the international space station as well as on the ground by RNA-Seq using next generation sequencing technology showed 8,258 and 14,170 transcripts up- and down-regulated in the space-grown Mizuna respectively when compared with those from the ground-grown Mizuna. A total of 20 in 32 ROS oxidative marker genes were up-regulated including high expression of 4 hallmarks and preferentially expressed gene associated with ROS-scavenging genes was thioredoxin glutaredoxin and alternative oxidase genes. In the transcription factors of ROS gene network MEKK1-MKK4-MPK3 OXI1-MKK4-MPK3 and OXI1-MPK3 of MAP cascades induction of WRKY22 by MEKK1-MKK4-MPK3 cascade induction of WRKY25 and repression of ZAT7 by Zat12 were suggested. RbohD and RbohF genes were up-regulated preferentially in NADPH oxidase genes which produce ROS.Conclusions: Our large-scale transcriptome analysis demonstrated that the space environment induced oxidative stress and ROS gene network was activated in the space-grown Mizuna some of which were common genes up-regulated by abiotic and biotic stress and were preferentially up-regulated genes by the space environment even though Mizuna grew in the space as well as on the ground showing that plants could acclimate to the space environment by reprograming the expression of ROS gene network.
Gene responses in mouse brain to long-term exposure to microgravity
The spaceflight experiment was carried out using male C57BL/10J mice (8 weeks old at launch). Wild type mice (n=3) were launched by Space Shuttle Discovery and housed on the International Space Station (ISS) for 91 days. They returned to the Earth by Space Shuttle Atlantis. But only one mouse returned to the Earth alive. Whole brain was sampled from the mouse killed by inhalation of carbon dioxide at the Life Sciences Support Facility of Kennedy Space Center within 3-4 hours after landing. After the spaceflight experiment the on-ground experiment was also carried out at the Advanced Biotechnology Center in Genova Italy. A mouse with the same species sex and age was housed in mice drawer system (MDS) which was utilized for the spaceflight (SF) mice for 3 months as the ground control (GC). Another mouse was housed in normal vivarium cage as the laboratory control (LC). Amount of food and water supplementation and environmental conditions were simulated as the flight group. After 3 months brain was sampled from one mouse in group GC and LC respectively. Comprehensive analyses of gene expression were performed in the right brain. Total of 4,000 genes were analyzed. The expression levels of 60 genes significantly changed in response to SF compared with LC and/or GC. The 15 and 16 genes were up- (> 2 folds) and down-regulated (< 0.5 folds) respectively following SF vs. GC. The levels of 58 genes were significantly altered by housing in MDS in space and/or on the ground. Forty seven and 11 genes were significantly up- and down-regulated vs. LC. Twenty seven out of these genes responded to caging in MDS both in space and on the ground. Further 31 genes were influenced by housing in MDS on the Earth. Responses of the characteristics of brain to long-term gravitational unloading were investigated in mice.
['"Proteome profiling of the exhaled breath condensate after long-term spaceflights"']
['"The aim of the study was to analyze exhaled breath condensate (EBC) proteome changes due to the effects of spaceflight factors. All the protocols were approved at the Institute of Biomedical Problems – Russian Federation State Scientific Research Center in the frame of Protocon experiment. EBC samples were collected by commercial devices RTube one month before flight (background) at the Yu. A. Gagarin Research and Test Cosmonaut Training Center, immediately after landing of the landing modules in the field (R0), and on the seventh day after landing as a part of medical examination (R+7). Semi-quantitative label-free proteomic analysis of 13 EBC samples collected from 5 Russian cosmonauts before and after long-term (169–199 days) spaceflights were performed and resulted in 164 different proteins. The highest number of proteins was detected in EBC after landing (R0). Pathways enrichment analysis via GO database large group of proteins that take part in keratinization processes (CASP14, DSG1, DSP, JUP, and etc). Nine proteins were KRT2, KRT9, KRT1, KRT10, KRT14, DCD, KRT6C, KRT6A, KRT5 were detected in all groups (background, R0, R+1). A two-sample Welch’s t-test identified the significant changing of KRT2 and KRT9 levels after landing. Enrichment analysis via KEGG database revealed significant participation (2,07E-06) of detected proteins in pathogenic E. coli infection (ACTG1, TUBA1C, TUBA4A, TUBB, TUBB8, YWHAZ). Presumably, presents of this proteins can associated with changing of cosmonauts’ microbial composition. Thus EBC can be used for noninvasive monitoring of health status and respiratory tract pathologies during the spaceflight. The obtained data are important for the development of medicine in extreme situations."']
Moderate long-term drought stress in rice
GEO Series GSE7766. Oryza sativa. 14 samples. Type: Expression profiling by array.
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.