cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.13148758
title: Assessment of the association of new biomarkers (GDF15, ST2, galectin-3, TIMP-1, MMP-9, NfL) and plasma prothrombotic potential in the course of cardiac transthyretin amyloidosis.
title: Ocena asocjacji nowych biomarkerów (GDF15, ST2, galektyna-3, TIMP-1, MMP-9, NfL) oraz potencjału prozakrzepowego osocza w przebiegu amyloidozy transtyretynowej serca.

description: The development of cardiac amyloidosis (ATTR) is caused by the deposition of misfolded, insoluble proteins in the extracellular matrix of tissues. An important element of the clinical presentation of the disease is the increased risk of thromboembolic complications. Currently, there is limited published data on the potential role of new heart failure biomarkers in the assessment of ATTR cardiomyopathy, particularly in the assessment of asymptomatic carriers of pathogenic transthyretin (TTR) variants.

Purpose of the study: To assess the diagnostic value of biomarkers related to heart failure (growth differentiation factor-15 (GDF15), soluble suppression of tumorigenicity-2 (ST2), galectin-3), amyloidosis ( retinol binding protein 4 (RBP4, transthyretin) , tissue inhibitor of metalloproteinase-1 (TIMP-1), matrix metalloproteinase-9 (MMP-9, matrix metalloproteinase-9), neurofilament light chain (NfL)) and the generation potential thrombin as a marker of the prothrombotic state in the course of ATTR.

Methods: This prospective, single-center study included consecutive patients diagnosed with ATTR, asymptomatic carriers of pathogenic TTR variants, and a matched control group of healthy volunteers.   The values of these biomarkers were evaluated using the ELISA method from peripheral blood (enzyme-linked immunosorbent assay) GDF15, ST2, RBP4 (TTR), TIMP-1, MMP-9, galectin-3, NfL. Additionally, the prothrombotic potential of plasma was tested using the calibrated automatic thrombogram (CAT) method. Results are presented in Table 1. Baseline demographic, clinical and laboratory characteristics of the study population are presented in Table 2.

Conclusions: The project provides information on the value of novel biomarkers in the assessment of ATTR cardiomyopathy, especially in the assessment of asymptomatic carriers of pathogenic TTR variants. Moreover, it evaluated prothrombotic state in the course of ATTR.
DOI: 10.5281/zenodo.13132167
title: Assessment of the association of new biomarkers (GDF15, ST2, galectin-3, TIMP-1, MMP-9, NfL) and plasma prothrombotic potential in the course of cardiac transthyretin amyloidosis.
title: Ocena asocjacji nowych biomarkerów (GDF15, ST2, galektyna-3, TIMP-1, MMP-9, NfL) oraz potencjału prozakrzepowego osocza w przebiegu amyloidozy transtyretynowej serca.

description: The development of cardiac amyloidosis (ATTR) is caused by the deposition of misfolded, insoluble proteins in the extracellular matrix of tissues. An important element of the clinical presentation of the disease is the increased risk of thromboembolic complications. Currently, there is limited published data on the potential role of new heart failure biomarkers in the assessment of ATTR cardiomyopathy, particularly in the assessment of asymptomatic carriers of pathogenic transthyretin (TTR) variants.

Purpose of the study: To assess the diagnostic value of biomarkers related to heart failure (growth differentiation factor-15 (GDF15), soluble suppression of tumorigenicity-2 (ST2), galectin-3), amyloidosis ( retinol binding protein 4 (RBP4, transthyretin) , tissue inhibitor of metalloproteinase-1 (TIMP-1), matrix metalloproteinase-9 (MMP-9, matrix metalloproteinase-9), neurofilament light chain (NfL)) and the generation potential thrombin as a marker of the prothrombotic state in the course of ATTR.

Methods: This prospective, single-center study included consecutive patients diagnosed with ATTR, asymptomatic carriers of pathogenic TTR variants, and a matched control group of healthy volunteers.   The values of these biomarkers were evaluated using the ELISA method from peripheral blood (enzyme-linked immunosorbent assay) GDF15, ST2, RBP4 (TTR), TIMP-1, MMP-9, galectin-3, NfL. Additionally, the prothrombotic potential of plasma was tested using the calibrated automatic thrombogram (CAT) method. Results are presented in Table 1. The demographic  and clinical characteristics of the study population are presented in Table 2 and Table 3.

Conclusions: The project provides information on the value of novel biomarkers in the assessment of ATTR cardiomyopathy, especially in the assessment of asymptomatic carriers of pathogenic TTR variants. Moreover, it evaluated prothrombotic state in the course of ATTR.
DOI: 10.5281/zenodo.13150289
title: Assessment of the association of new biomarkers (GDF15, ST2, galectin-3, TIMP-1, MMP-9, NfL) and plasma prothrombotic potential in the course of cardiac transthyretin amyloidosis.
title: Ocena asocjacji nowych biomarkerów (GDF15, ST2, galektyna-3, TIMP-1, MMP-9, NfL) oraz potencjału prozakrzepowego osocza w przebiegu amyloidozy transtyretynowej serca.

description: The development of cardiac amyloidosis (ATTR) is caused by the deposition of misfolded, insoluble proteins in the extracellular matrix of tissues. An important element of the clinical presentation of the disease is the increased risk of thromboembolic complications. Currently, there is limited published data on the potential role of new heart failure biomarkers in the assessment of ATTR cardiomyopathy, particularly in the assessment of asymptomatic carriers of pathogenic transthyretin (TTR) variants.

Purpose of the study: To assess the diagnostic value of biomarkers related to heart failure (growth differentiation factor-15 (GDF15), soluble suppression of tumorigenicity-2 (ST2), galectin-3), amyloidosis ( retinol binding protein 4 (RBP4, transthyretin) , tissue inhibitor of metalloproteinase-1 (TIMP-1), matrix metalloproteinase-9 (MMP-9, matrix metalloproteinase-9), neurofilament light chain (NfL)) and the generation potential thrombin as a marker of the prothrombotic state in the course of ATTR.

Methods: This prospective, single-center study included consecutive patients diagnosed with ATTR, asymptomatic carriers of pathogenic TTR variants, and a matched control group of healthy volunteers.   The values of these biomarkers were evaluated using the ELISA method from peripheral blood (enzyme-linked immunosorbent assay) GDF15, ST2, RBP4 (TTR), TIMP-1, MMP-9, galectin-3, NfL. Additionally, the prothrombotic potential of plasma was tested using the calibrated automatic thrombogram (CAT) method. Results are presented in Table 1. The demographic  and clinical characteristics of the study population are presented in Table 2 and Table 3.

Conclusions: The project provides information on the value of novel biomarkers in the assessment of ATTR cardiomyopathy, especially in the assessment of asymptomatic carriers of pathogenic TTR variants. Moreover, it evaluated prothrombotic state in the course of ATTR.
DOI: 10.5281/zenodo.13150298
title: Binary black-hole simulation SXS:BBH:1526

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.13150299
title: Binary black-hole simulation SXS:BBH:1526

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.13150303
title: Binary black-hole simulation SXS:BBH:1961

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.13150304
title: Binary black-hole simulation SXS:BBH:1961

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.15468/dl.bw8b7v
title: Occurrence Download

description: A dataset containing 181 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Country is one of (Oman, Yemen, Saudi Arabia, Qatar, United Arab Emirates, Bahrain, Kuwait, Jordan, Iran (Islamic Republic of), Iraq, Syrian Arab Republic)",
 "TaxonKey is Acalypha L."
 ]
}

 The dataset includes 181 records from 21 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0044205-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.13150307
title: Binary black-hole simulation SXS:BBH:1988

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.13150308
title: Binary black-hole simulation SXS:BBH:1988

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.13150313
title: Binary black-hole simulation SXS:BBH:2035

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.13150314
title: Binary black-hole simulation SXS:BBH:2035

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.13144354
title: Multimodal omics data fusion for cancer prognosis with co-attention-based variational autoencoder
DOI: 10.5281/zenodo.13144355
title: Multimodal omics data fusion for cancer prognosis with co-attention-based variational autoencoder
DOI: 10.5281/zenodo.13150316
title: Multimodal omics data fusion for cancer prognosis with co-attention-based variational autoencoder
DOI: 10.5281/zenodo.13150319
title: Binary black-hole simulation SXS:BBH:1905

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.13150320
title: Binary black-hole simulation SXS:BBH:1905

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.12799455
title: 2021_Veterinary_Hospital_FacilityDistributions

description: Veterinary and Hospital distributions. 

Abstract:

These maps of veterinary facilities and hospital health care locations are derived from the open-source Open Street Maps (OSM). These are large datasets that underlie most of the satnav utilities, and are continuously updated by members of the public. They are compiled by GEOFABRIK, and can be downloaded from https://www.geofabric.de. Healthcare data have been further enhanced by the Global Health Sites Mapping Project (https://healthsites.io).  The data consist of locations (“points of interest”) and building outlines, and are made up of points and polygons that are stored separately in the OSM files. Each record has a series of descriptors (“tags”) such as ‘amenity’ which may include descriptions of a hospital or veterinary clinic. These tags are provided by the people who add the data to the maps and are multilingual and very variable. Most records contain additional more generic tags that can be used to identify classes of locations like hospitals or pharmacies.   ERGO has taken the IO and OSM datasets, combined the polygon and point data, converted the polygons to points, and removed any duplicates (where building outlines also have point location records), to produce and global datasets for healthcare and regional datasets for healthcare and veterinary locations covering Europe and its neighboring countries. 

 

File naming scheme:  

Full descriptions in Maps of Healthcare and Veterinary Locations.pptx.  

ESRI point shapefiles are as follows:  Healthcare Global: Ionodewaynodupallmay21.shp  Healthcare Regional: MONODWAYALLnodupMAY21.shp  Veterinary Regional: afeupolypointsnondupmergemay21.shp  The regional maps are produced by tabulating the number of each healthcare amenity or veterinary locations within administrative zones, normalising by the administrative unit areas. The maps are produced from the following shape files:  Healthcare Regional: MOiohealthamenitycountadmin2may21.shp  Veterinary Regional: MONODWATALLVETSNODUPMAY21.shp  An arcGS 10.4 MPK project file (ERGOhealthvetforweb.mpk) has been provided to display the spatial data provided

 

Projection + EPSG code:Latitude-Longitude/WGS84 (EPSG: 4326)

Spatial extent:Extent    -73.2621536249999394,18.9632860000000392 : 69.0703202920000336,83.6274185180000842

Spatial resolution:Shp files

Temporal Resolution:

Year 2021

Values:

Per Units (Number of facilities ): the number of each healthcare amenity or veterinary locations within administrative zones,

Source: 

Open Street Maps (OSM):

GEOFABRIK  https://www.geofabric.de

Health care data https://healthsites.io

Software used:ArcMap 10.4

License: CC-BY-SA 4.0

Processed by:ERGO (Environmental Research Group Oxford) https://ergoonline.co.uk/ for the H2020 MOOD project
DOI: 10.5281/zenodo.12917423
title: A Nonlinear Flow Model and Criterion for 3D Natural Fracture Intersections: Effects of Surface Roughness and Mechanical Aperture

description: The present repository includes the raw data of flow rate ~ hydraulic gradient presented in the manuscript submitted for publication in Water Resources Research entitled A Nonlinear Flow Model and Criterion for 3D Natural Fracture Intersections: Effects of Surface Roughness and Mechanical Aperture.

The repository is presented as CSV files,and all other results including the linear and nonlinear coefficients in Forchheimer equation and Permeability of fracture intersections can be calculated employing this basic data.
DOI: 10.5281/zenodo.12799454
title: 2021_Veterinary_Hospital_FacilityDistributions

description: Veterinary and Hospital distributions. 

Abstract:

These maps of veterinary facilities and hospital health care locations are derived from the open-source Open Street Maps (OSM). These are large datasets that underlie most of the satnav utilities, and are continuously updated by members of the public. They are compiled by GEOFABRIK, and can be downloaded from https://www.geofabric.de. Healthcare data have been further enhanced by the Global Health Sites Mapping Project (https://healthsites.io).  The data consist of locations (“points of interest”) and building outlines, and are made up of points and polygons that are stored separately in the OSM files. Each record has a series of descriptors (“tags”) such as ‘amenity’ which may include descriptions of a hospital or veterinary clinic. These tags are provided by the people who add the data to the maps and are multilingual and very variable. Most records contain additional more generic tags that can be used to identify classes of locations like hospitals or pharmacies.   ERGO has taken the IO and OSM datasets, combined the polygon and point data, converted the polygons to points, and removed any duplicates (where building outlines also have point location records), to produce and global datasets for healthcare and regional datasets for healthcare and veterinary locations covering Europe and its neighboring countries. 

 

File naming scheme:  

Full descriptions in Maps of Healthcare and Veterinary Locations.pptx.  

ESRI point shapefiles are as follows:  Healthcare Global: Ionodewaynodupallmay21.shp  Healthcare Regional: MONODWAYALLnodupMAY21.shp  Veterinary Regional: afeupolypointsnondupmergemay21.shp  The regional maps are produced by tabulating the number of each healthcare amenity or veterinary locations within administrative zones, normalising by the administrative unit areas. The maps are produced from the following shape files:  Healthcare Regional: MOiohealthamenitycountadmin2may21.shp  Veterinary Regional: MONODWATALLVETSNODUPMAY21.shp  An arcGS 10.4 MPK project file (ERGOhealthvetforweb.mpk) has been provided to display the spatial data provided

 

Projection + EPSG code:Latitude-Longitude/WGS84 (EPSG: 4326)

Spatial extent:Extent    -73.2621536249999394,18.9632860000000392 : 69.0703202920000336,83.6274185180000842

Spatial resolution:Shp files

Temporal Resolution:

Year 2021

Values:

Per Units (Number of facilities ): the number of each healthcare amenity or veterinary locations within administrative zones,

Source: 

Open Street Maps (OSM):

GEOFABRIK  https://www.geofabric.de

Health care data https://healthsites.io

Software used:ArcMap 10.4

License: CC-BY-SA 4.0

Processed by:ERGO (Environmental Research Group Oxford) https://ergoonline.co.uk/ for the H2020 MOOD project
DOI: 10.15468/dl.txkcy8
title: Occurrence Download

description: A dataset containing 1980 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is EOD – eBird Observation Dataset",
 "Geometry POLYGON((8.11334 40.65038,8.30992 40.65038,8.30992 40.88021,8.11334 40.88021,8.11334 40.65038))",
 "HasCoordinate is true",
 "PublishingCountry is Italy"
 ]
}

 The dataset includes 1980 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0044207-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.13150327
title: Binary black-hole simulation SXS:BBH:1718

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.13150328
title: Binary black-hole simulation SXS:BBH:1718

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.12799469
title: MOOD_2021_FloodRisk_JRC

description: Floodrisk, 10 year return period, 1km.  

Abstract:

The flood risk dataset downloaded from https://data.jrc.ec.europa.eu/collection/id-0054 has been windowed to the MOOD extent for access by project partners. According to JRC "The maps have been developed using hydrological and hydrodynamic models, driven by the climatological data of the European and Global Flood Awareness Systems (EFAS and GloFAS). European-scale maps comprise most of the geographical Europe and all the river basins entering the Mediterranean and Black Seas in the Caucasus, Middle East and Northern Africa countries."

 

File naming scheme:  

flood risk in TIF format for 10 years : erfloodMapGL_rp10y1km.tif 

JRC Guide:   JRC cdatafloodrisk.pdf 

Projection + EPSG code:Latitude-Longitude/WGS84 (EPSG: 4326)

Spatial extent:Extent    -32.0000000000000000,10.0000000000000000 : 68.9999999999999574,81.9999999999999716

Spatial resolution:0.0083333 deg (approx. 1000 m)

Temporal Resolution:

10 year period

Pixel values:unit: meter

Source: 

 JRC: https://data.jrc.ec.europa.eu/collection/id-0054

Software used:ArcMap 10.8

License: CC-BY-SA 4.0

Processed by:ERGO (Environmental Research Group Oxford) https://ergoonline.co.uk/ for the H2020 MOOD project
DOI: 10.5281/zenodo.12799470
title: MOOD_2021_FloodRisk_JRC

description: Floodrisk, 10 year return period, 1km.  

Abstract:

The flood risk dataset downloaded from https://data.jrc.ec.europa.eu/collection/id-0054 has been windowed to the MOOD extent for access by project partners. According to JRC "The maps have been developed using hydrological and hydrodynamic models, driven by the climatological data of the European and Global Flood Awareness Systems (EFAS and GloFAS). European-scale maps comprise most of the geographical Europe and all the river basins entering the Mediterranean and Black Seas in the Caucasus, Middle East and Northern Africa countries."

 

File naming scheme:  

flood risk in TIF format for 10 years : erfloodMapGL_rp10y1km.tif 

JRC Guide:   JRC cdatafloodrisk.pdf 

Projection + EPSG code:Latitude-Longitude/WGS84 (EPSG: 4326)

Spatial extent:Extent    -32.0000000000000000,10.0000000000000000 : 68.9999999999999574,81.9999999999999716

Spatial resolution:0.0083333 deg (approx. 1000 m)

Temporal Resolution:

10 year period

Pixel values:unit: meter

Source: 

 JRC: https://data.jrc.ec.europa.eu/collection/id-0054

Software used:ArcMap 10.8

License: CC-BY-SA 4.0

Processed by:ERGO (Environmental Research Group Oxford) https://ergoonline.co.uk/ for the H2020 MOOD project
DOI: 10.5281/zenodo.13150334
title: Binary black-hole simulation SXS:BBH:2076

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.13150335
title: Binary black-hole simulation SXS:BBH:2076

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.13150342
title: Binary black-hole simulation SXS:BBH:1807

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.13150343
title: Binary black-hole simulation SXS:BBH:1807

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.15468/dl.755ck5
title: Occurrence Download

description: A dataset containing 1169 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((19.86328 -37.09959,49.74609 -26.67757,53.26172 -12.4802,53.26172 13.31408,44.47265 11.25312,34.98047 27.12694,34.6289 32.01677,22.32422 34.07936,11.42578 37.221,-6.15235 34.94839,-18.8086 24.59641,-19.51172 11.94188,-9.31641 2.53628,2.98828 3.23851,11.42578 -11.10367,9.66797 -20.23196,15.29297 -33.66096,19.86328 -37.09959))",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Bemisia tabaci (Gennadius, 1889)"
 ]
}

 The dataset includes 1169 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0303906-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.98jqqy
title: Occurrence Download

description: A dataset containing 1422 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((20.33203 -36.1497,50.56641 -26.71875,53.26172 -15.11719,53.37891 -6.67969,51.62109 13.09731,44.58984 11.03466,35.09765 27.55374,34.39453 31.82779,23.49609 32.42325,8.73047 37.04349,-5.33203 35.34127,-10.60547 31.22846,-17.28516 23.75183,-18.33985 14.80321,-15.99609 2.8125,1.93359 1.75781,7.55859 -2.10937,11.89453 -13.04024,10.83984 -18.11801,20.33203 -36.1497))",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Manihot esculenta Crantz",
 "Year 1502-2021"
 ]
}

 The dataset includes 1422 records from 56 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0301500-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.13150350
title: Binary black-hole simulation SXS:BBH:1843

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.13150351
title: Binary black-hole simulation SXS:BBH:1843

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.15468/dl.dskayg
title: Occurrence Download

description: A dataset containing 5393373 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "Year 2004-2024"
 ]
}

 The dataset includes 5393373 records from 3369 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0044206-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.24355/dbbs.084-202409230712-0
title: Haplotype-resolved genome sequence of Cassava (Manihot esculenta) cultivar COL40

description: A high quality genome assembly of Cassava COL40 cultivar (completeness &gt; 98 %; QV &gt; 57) is presented together with predicted polypeptide sequences (completeness &gt; 96 %) and functional annoation. The genome sequence of Cassava COL40 was assembled with Hifiasm from PacBio HiFi sequencing data. The assembly was scaffolded into pseudochromosomes and gene models were predicted with BRAKER3 by incorporating RNA-Seq hints of the COL40 cultivar and other Cassava cultivars and polypeptide sequences from Manihot esculenta and Viridiplantae as external hints. The predicted polypeptide sequences were functionally annotated by InterProScan5 and transposable elements (TEs) were predicted by EDTA (TE proportion &gt; 58 %).
DOI: 10.15468/dl.42wuy1
title: Occurrence Download

description: A dataset containing 569 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Datura suaveolens Humb. & Bonpl. ex Willd."
 ]
}

 The dataset includes 569 records from 78 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001688-191105090559680/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.