cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.27940243
title: Assessing the Causal Role of Walking Pace and Hand Grip Strength with Chronic Obstructive Pulmonary Disease Hospital: A Mendelian Randomization Study

description: Chronic obstructive pulmonary disease(COPD) hospitalization heightens risks for patients, including mortality, reduced quality of life, and financial strain. Walking pace (WP) and hand grip strength (HGS) are key indicators, their direct connection to COPD hospitalization is uncertain. To investigate the relationship between genetic determinants of walking pace, hand grip strength, and the risk of COPD hospitalization as well as lung function. The data pertaining to WP (<i>n</i> = 459,915), HGS (<i>n</i> = 922,115), COPD hospitalizations (<i>n</i> = 309,154), and lung function (<i>n</i> = 79,055) were procured from comprehensive large-scale genome-wide association studies. In carrying out the causal inference analysis, robust statistical methods were utilized, encompassing inverse variance weighted (IVW), MR-Egger, weighted median, simple median and Weighted mode. To address issues of heterogeneity, pleiotropy, and outliers, we incorporated sensitivity analyses and Mendelian randomization (MR) techniques. The IVW analysis suggests that a faster WP reduces the risk of COPD hospitalization (OR = 0.3559, 95% CI: 0.22-0.52; <i>p</i> = 5.197 × 10<sup>−5</sup>). It also reveals a potential association between gait speed and the likelihood of developing early-onset COPD (OR = 0.189, 95% CI 0.09 to 0.39; <i>p</i> = 8.89 × 10-6) as well as late-onset COPD (OR = 0.44, 95% CI 0.25 to 0.76; <i>p</i> = 0.0036). The IVW analysis further indicates a potential correlation between an increased WP and enhanced peak expiratory flow (PEF) (OR = 1.699, 95% CI: 1.23 to 2.35; <i>p</i> = 0.0014), forced expiratory volume in 1 s(FEV1, OR = 1.557, 95% CI 1.24 to 1.95; <i>p</i> = 0.0001), and forced vital capacity(FVC, OR = 1.584, 95% CI 1.26 to 1.99; <i>p</i> = 8.89 × 10-5). The IVW analysis suggests a possible causal link between stronger left-hand grip strength and elevated levels of FVC (OR = 1.29, 95% CI: 1.15 to 1.46; <i>p</i> = 1.68 × 10-5), FEV1 (OR = 1.24, 95% CI: 1.11 to 1.39; <i>p</i> = 1.63 × 10-4), and PEF (OR = 1.2, 95% CI: 1.07 to 1.36; <i>p</i> = 2.67 × 10-3). Similarly, right-hand grip strength exhibits a comparable causal relationship with FVC and PEF as left-hand grip strength. Our research shows a link between slower walking pace and higher COPD hospitalization risk, as well as decreased lung function (PEF, FEV1, FVC). We also found a significant correlation between weaker hand grip and reduced lung function, especially FVC. These findings have the potential to improve risk assessment approaches, intervention strategies, and management methods for COPD patients, while simultaneously enhancing their overall quality of life and health status.
DOI: 10.6084/m9.figshare.27940243.v1
title: Assessing the Causal Role of Walking Pace and Hand Grip Strength with Chronic Obstructive Pulmonary Disease Hospital: A Mendelian Randomization Study

description: Chronic obstructive pulmonary disease(COPD) hospitalization heightens risks for patients, including mortality, reduced quality of life, and financial strain. Walking pace (WP) and hand grip strength (HGS) are key indicators, their direct connection to COPD hospitalization is uncertain. To investigate the relationship between genetic determinants of walking pace, hand grip strength, and the risk of COPD hospitalization as well as lung function. The data pertaining to WP (<i>n</i> = 459,915), HGS (<i>n</i> = 922,115), COPD hospitalizations (<i>n</i> = 309,154), and lung function (<i>n</i> = 79,055) were procured from comprehensive large-scale genome-wide association studies. In carrying out the causal inference analysis, robust statistical methods were utilized, encompassing inverse variance weighted (IVW), MR-Egger, weighted median, simple median and Weighted mode. To address issues of heterogeneity, pleiotropy, and outliers, we incorporated sensitivity analyses and Mendelian randomization (MR) techniques. The IVW analysis suggests that a faster WP reduces the risk of COPD hospitalization (OR = 0.3559, 95% CI: 0.22-0.52; <i>p</i> = 5.197 × 10<sup>−5</sup>). It also reveals a potential association between gait speed and the likelihood of developing early-onset COPD (OR = 0.189, 95% CI 0.09 to 0.39; <i>p</i> = 8.89 × 10-6) as well as late-onset COPD (OR = 0.44, 95% CI 0.25 to 0.76; <i>p</i> = 0.0036). The IVW analysis further indicates a potential correlation between an increased WP and enhanced peak expiratory flow (PEF) (OR = 1.699, 95% CI: 1.23 to 2.35; <i>p</i> = 0.0014), forced expiratory volume in 1 s(FEV1, OR = 1.557, 95% CI 1.24 to 1.95; <i>p</i> = 0.0001), and forced vital capacity(FVC, OR = 1.584, 95% CI 1.26 to 1.99; <i>p</i> = 8.89 × 10-5). The IVW analysis suggests a possible causal link between stronger left-hand grip strength and elevated levels of FVC (OR = 1.29, 95% CI: 1.15 to 1.46; <i>p</i> = 1.68 × 10-5), FEV1 (OR = 1.24, 95% CI: 1.11 to 1.39; <i>p</i> = 1.63 × 10-4), and PEF (OR = 1.2, 95% CI: 1.07 to 1.36; <i>p</i> = 2.67 × 10-3). Similarly, right-hand grip strength exhibits a comparable causal relationship with FVC and PEF as left-hand grip strength. Our research shows a link between slower walking pace and higher COPD hospitalization risk, as well as decreased lung function (PEF, FEV1, FVC). We also found a significant correlation between weaker hand grip and reduced lung function, especially FVC. These findings have the potential to improve risk assessment approaches, intervention strategies, and management methods for COPD patients, while simultaneously enhancing their overall quality of life and health status.
DOI: 10.6084/m9.figshare.26776708.v1
title: HPV-16 E6 mutation and viral integration related host DNA methylation implicate the development and progression of cervical cancer

description: HPV-16 infection and viral-host integration are the most important risk factors for cervical cancer (CC). The aim of this study is to develop a new molecular strategy integrated both the viral and host genome variations identifying and monitoring CC. A total of 312 methylation and 538 RNA-seq datasets were collected from public databases to identify differentially methylated and expressed genes. HPV associated virus integration sites (VISs) were analysed using the ViMIC database. From September 2020 to August 2021, the 70 HPV-16 positive cases retrospectively collected from multi-centre cohorts were subjected to HPV-16 E6 deep sequencing and PCR-based host gene (ASTN1, DLX1, ITGA4, RXFP3, SOX17, ZNF671) methylation detection. RNAseq and expression validation (NNF671) were performed in C-33A cell line harbouring HPV D32E. Lasso and logistic regression algorithm were used to construct the CC diagnostic model. A positive correlation was observed between the average methylation level of CC patients and their pathological features including tumour stage (<i>p</i> = 0.0077) and HPV subtype (<i>p</i> &lt; 0.001). ZNF671 was identified as a CC-specific methylation marker, with an impressive 93% sensitivity. Both HPV-16 D32E mutation and integration of HPV-16 down-regulated the ZNF671 expression. Finally, a CC diagnostic nomogram was developed by integrating ZNF671 methylation level and HPV E6 mutation feature, yielding an exceptional AUC of 0.997 (95% CI: 0.934–1.000). Our study demonstrated HPV viral mutations are closely related to host gene epigenetic alterations in CC. Integration of the viral and host genetic information might be a new promising strategy for CC screening.
DOI: 10.6084/m9.figshare.26776708
title: HPV-16 E6 mutation and viral integration related host DNA methylation implicate the development and progression of cervical cancer

description: HPV-16 infection and viral-host integration are the most important risk factors for cervical cancer (CC). The aim of this study is to develop a new molecular strategy integrated both the viral and host genome variations identifying and monitoring CC. A total of 312 methylation and 538 RNA-seq datasets were collected from public databases to identify differentially methylated and expressed genes. HPV associated virus integration sites (VISs) were analysed using the ViMIC database. From September 2020 to August 2021, the 70 HPV-16 positive cases retrospectively collected from multi-centre cohorts were subjected to HPV-16 E6 deep sequencing and PCR-based host gene (ASTN1, DLX1, ITGA4, RXFP3, SOX17, ZNF671) methylation detection. RNAseq and expression validation (NNF671) were performed in C-33A cell line harbouring HPV D32E. Lasso and logistic regression algorithm were used to construct the CC diagnostic model. A positive correlation was observed between the average methylation level of CC patients and their pathological features including tumour stage (<i>p</i> = 0.0077) and HPV subtype (<i>p</i> &lt; 0.001). ZNF671 was identified as a CC-specific methylation marker, with an impressive 93% sensitivity. Both HPV-16 D32E mutation and integration of HPV-16 down-regulated the ZNF671 expression. Finally, a CC diagnostic nomogram was developed by integrating ZNF671 methylation level and HPV E6 mutation feature, yielding an exceptional AUC of 0.997 (95% CI: 0.934–1.000). Our study demonstrated HPV viral mutations are closely related to host gene epigenetic alterations in CC. Integration of the viral and host genetic information might be a new promising strategy for CC screening.
DOI: 10.6084/m9.figshare.26790440
title: Interferon gene expression declines over time post-COVID infection and in long COVID patients

description: Interferons (IFNs) represent a first-line defense against viruses and other pathogens. It has been shown that an impaired and uncontrolled release of these glycoproteins can result in tissue damage and explain severe progression of coronavirus disease 2019 (COVID-19). However, their potential role in Long-COVID syndrome (LC) remains debateable. The objective of the present study is to shed further light on the possible role of IFNs (and related genes) gene expression patterns in the progression of COVID-19 and LC patients. We carried out a multi-cohort study by analyzing the IFN gene expression patterns (using different IFN gene signatures) in five cohorts of acute COVID-19 (<i>n</i> = 541 samples) and LC patients (<i>n</i> = 188), and compared them to patterns observed in three autoimmune diseases (systemic lupus erythematous [<i>n</i> = 242], systemic sclerosis [<i>n</i> = 91], and Sjögren’s syndrome [<i>n</i> = 282]). The data show that, while the interferon signatures are strongly upregulated in severe COVID-19 patients and autoimmune diseases, it decays with the time from symptoms onset and in LC patients. Differential pathway analysis of IFN-related terms indicates an over activation in autoimmune diseases (IFN-I/II) and severe COVID-19 (IFN-I/II/III), while these pathways are mostly inactivated or downregulated in LC (IFN-I/III). By analyzing six proteomic LC datasets, we did not find evidence of a role of IFNs in this condition. Our findings suggest a potential role of cytokine exhaustion mediated by IFN gene expression inactivation as a possible driver of LC.
DOI: 10.6084/m9.figshare.26790440.v1
title: Interferon gene expression declines over time post-COVID infection and in long COVID patients

description: Interferons (IFNs) represent a first-line defense against viruses and other pathogens. It has been shown that an impaired and uncontrolled release of these glycoproteins can result in tissue damage and explain severe progression of coronavirus disease 2019 (COVID-19). However, their potential role in Long-COVID syndrome (LC) remains debateable. The objective of the present study is to shed further light on the possible role of IFNs (and related genes) gene expression patterns in the progression of COVID-19 and LC patients. We carried out a multi-cohort study by analyzing the IFN gene expression patterns (using different IFN gene signatures) in five cohorts of acute COVID-19 (<i>n</i> = 541 samples) and LC patients (<i>n</i> = 188), and compared them to patterns observed in three autoimmune diseases (systemic lupus erythematous [<i>n</i> = 242], systemic sclerosis [<i>n</i> = 91], and Sjögren’s syndrome [<i>n</i> = 282]). The data show that, while the interferon signatures are strongly upregulated in severe COVID-19 patients and autoimmune diseases, it decays with the time from symptoms onset and in LC patients. Differential pathway analysis of IFN-related terms indicates an over activation in autoimmune diseases (IFN-I/II) and severe COVID-19 (IFN-I/II/III), while these pathways are mostly inactivated or downregulated in LC (IFN-I/III). By analyzing six proteomic LC datasets, we did not find evidence of a role of IFNs in this condition. Our findings suggest a potential role of cytokine exhaustion mediated by IFN gene expression inactivation as a possible driver of LC.
DOI: 10.34740/kaggle/dsv/10303014
title: Global Genomic Neurofibromatosis Neoplasia
DOI: 10.7910/dvn/3lor3r/cpxtyp
title: analysis_code_revised.do

description: main analysis script producing the tables and statistics of the resubmission (July 2020)
DOI: 10.7910/dvn/3lor3r/zfodsy
title: analysis_code_v10.do

description: script to produce the tables and other statistics reported in the paper
DOI: 10.7910/dvn/3lor3r/fhtbng
title: asylum.tab

description: Cleaned asylum data ready for analysis, produced by asylum_data_cleaning_and_checking.do
DOI: 10.7910/dvn/3lor3r/td5mbb
title: asylum_data_cleaning_and_checking.do

description: script to produce data/EOIR_asylum/asylum.dta from raw EOIR files in data/EOIR_asylum/rawdata
DOI: 10.7910/dvn/3lor3r/ksjgys
title: master.do

description: calls data assembly scripts and analysis script
DOI: 10.7910/dvn/3lor3r/dkn5ap
title: readme_analysis_output_folder.txt

description: a placeholder file whose only purpose is to force the creation of an analysis/analysis_output folder
DOI: 10.5281/zenodo.14557829
title: Global Renewable Methanol Market 2024 To 2033

description: Renewable Methanol Market Size, Trends and Insights By Feedstock (Agriculture Waste, Municipal Waste, Renewable Energy, Others), By Application (Gasoline, Formaldehyde, MTBE, Dimethyl Ether, MTO, Acetic Acid, Others), and By Region - Global Industry Overview, Statistical Data, Competitive Analysis, Share, Outlook, and Forecast 2024–2033.

Reports Description

Global Renewable Methanol Market was valued at USD 2.7 Billion in 2024 and is expected to reach USD 26.7 Billion by 2033, at a CAGR of 54.7% during the forecast period 2024 – 2033.

Low-carbon methanol produced from sustainable biomass (also called bio-methanol) or from carbon dioxide and hydrogen produced by renewable energy sources is called renewable methanol. Biomass and industrial waste are examples of renewable resources that are used to make renewable methanol.

For more information, DOWNLOAD FREE SAMPLE Now at https://www.custommarketinsights.com/request-for-free-sample/?reportid=52609
DOI: 10.5281/zenodo.14557830
title: Global Renewable Methanol Market 2024 To 2033

description: Renewable Methanol Market Size, Trends and Insights By Feedstock (Agriculture Waste, Municipal Waste, Renewable Energy, Others), By Application (Gasoline, Formaldehyde, MTBE, Dimethyl Ether, MTO, Acetic Acid, Others), and By Region - Global Industry Overview, Statistical Data, Competitive Analysis, Share, Outlook, and Forecast 2024–2033.

Reports Description

Global Renewable Methanol Market was valued at USD 2.7 Billion in 2024 and is expected to reach USD 26.7 Billion by 2033, at a CAGR of 54.7% during the forecast period 2024 – 2033.

Low-carbon methanol produced from sustainable biomass (also called bio-methanol) or from carbon dioxide and hydrogen produced by renewable energy sources is called renewable methanol. Biomass and industrial waste are examples of renewable resources that are used to make renewable methanol.

For more information, DOWNLOAD FREE SAMPLE Now at https://www.custommarketinsights.com/request-for-free-sample/?reportid=52609
DOI: 10.15468/dl.6wacfr
title: Occurrence Download

description: A dataset containing 444 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Sparidae, 209454778, Sparidae, Sparidae, Sparidae, Sparidae, 205993695, Sparidae, Sparidae, Sparidae, 205986161, Sparidae, Sparidae, Sparidae, 209346469, Sparidae, Sparidae, Sparidae, Sparidae, Sparidae, Sparidae, Sparidae, 205973273, 204357656, 209667199, Sparidae, Sparidae, Sparidae, Sparidae, Sparidae, Sparidae, Sparidae, Sparidae, Sparidae, Sparidae, Sparidae, 209459667, Sparidae, Sparidae, Sparidae, Sparidae, Sparidae, Sparidae, Sparidae, Sparidae, 205939152, Sparidae, Sparidae, Sparidae, 212108397, Sparidae, Sparidae, Sparidae, 157073718, Sparidae, 204227584, Sparidae, Sparidae, Sparidae, Sparidae, 208592787, Sparidae, Sparidae, Sparidae, 197286779, 209286643, 212282735, 205227323, Sparidae, Sparidae, Sparidae, Sparidae, Sparidae, Sparidae, Sparidae, 197875183, Sparidae, 204865177, 205889059, Sparidae, Sparidae, Sparidae, 158144640, 210656586, Sparidae, 212386582, Sparidae, Sparidae, Sparidae, Sparidae, 209458958, 204985412, 210655459, Sparidae, 211762849, 212360712, Sparidae, 206013982, Sparidae, Sparidae, Sparidae, Sparidae, Sparidae, 205982173, Sparidae, Sparidae, Sparidae, 205986158, 212101300, Sparidae, Sparidae, Sparidae, Sparidae, Sparidae, Sparidae, Sparidae, Sparidae, Sparidae, SPARIDAE, Sparidae, Sparidae, Sparidae, 187337877, 210218628, Sparidae, Sparidae, Sparidae, Sparidae, Sparidae, Sparidae, Sparidae, 212276927, Sparidae, Sparidae, Sparidae, Sparidae, Sparidae, Sparidae, Sparidae, Sparidae, Sparidae, Sparidae , Sparidae, Sparidae, Sparidae, Sparidae, Sparidae Bonaparte, 161427290, Sparidae Rafinesque 1818, Sparidae Rafinesque, 1810, Sparidae Rafinesque, 1818, Sparidae Cuvier, 1817, Sparidae Bonaparte, 1832, Sparidae Rafinesque, 1818, Sparidae Rafinesque, 1818, Sparidae Rafinesque, 1818, Sparidae Bonaparte 1851, Sparidae Rafinesque, 1818, Sparidae Rafinesque, 1810, Sparidae Rafinesque 1818, Sparidae Rafinesque, 1818, Characidae Latreille 1825, Lethrinidae Bonaparte, 1838, Nemipteridae Regan, 1913, Eunicidae Berthold, 1827, Haemulidae, Centracanthidae Gill, 1893, 161428090, Maenidae, Centracanthidae, Centracanthidae Gill, 1893)",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Living Specimen, Machine Observation, Literature Occurrence)",
 "Geometry POLYGON((109.5 20.15,117.25 20.15,117.25 24,109.5 24,109.5 20.15))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 444 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0049125-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5mxru4
title: Occurrence Download

description: A dataset containing 444 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Sparidae, 209454778, Sparidae, Sparidae, Sparidae, Sparidae, 205993695, Sparidae, Sparidae, Sparidae, 205986161, Sparidae, Sparidae, Sparidae, 209346469, Sparidae, Sparidae, Sparidae, Sparidae, Sparidae, Sparidae, Sparidae, 205973273, 204357656, 209667199, Sparidae, Sparidae, Sparidae, Sparidae, Sparidae, Sparidae, Sparidae, Sparidae, Sparidae, Sparidae, Sparidae, 209459667, Sparidae, Sparidae, Sparidae, Sparidae, Sparidae, Sparidae, Sparidae, Sparidae, 205939152, Sparidae, Sparidae, Sparidae, 212108397, Sparidae, Sparidae, Sparidae, 157073718, Sparidae, 204227584, Sparidae, Sparidae, Sparidae, Sparidae, 208592787, Sparidae, Sparidae, Sparidae, 197286779, 209286643, 212282735, 205227323, Sparidae, Sparidae, Sparidae, Sparidae, Sparidae, Sparidae, Sparidae, 197875183, Sparidae, 204865177, 205889059, Sparidae, Sparidae, Sparidae, 158144640, 210656586, Sparidae, 212386582, Sparidae, Sparidae, Sparidae, Sparidae, 209458958, 204985412, 210655459, Sparidae, 211762849, 212360712, Sparidae, 206013982, Sparidae, Sparidae, Sparidae, Sparidae, Sparidae, 205982173, Sparidae, Sparidae, Sparidae, 205986158, 212101300, Sparidae, Sparidae, Sparidae, Sparidae, Sparidae, Sparidae, Sparidae, Sparidae, Sparidae, SPARIDAE, Sparidae, Sparidae, Sparidae, 187337877, 210218628, Sparidae, Sparidae, Sparidae, Sparidae, Sparidae, Sparidae, Sparidae, 212276927, Sparidae, Sparidae, Sparidae, Sparidae, Sparidae, Sparidae, Sparidae, Sparidae, Sparidae, Sparidae , Sparidae, Sparidae, Sparidae, Sparidae, Sparidae Bonaparte, 161427290, Sparidae Rafinesque 1818, Sparidae Rafinesque, 1810, Sparidae Rafinesque, 1818, Sparidae Cuvier, 1817, Sparidae Bonaparte, 1832, Sparidae Rafinesque, 1818, Sparidae Rafinesque, 1818, Sparidae Rafinesque, 1818, Sparidae Bonaparte 1851, Sparidae Rafinesque, 1818, Sparidae Rafinesque, 1810, Sparidae Rafinesque 1818, Sparidae Rafinesque, 1818, Characidae Latreille 1825, Lethrinidae Bonaparte, 1838, Nemipteridae Regan, 1913, Eunicidae Berthold, 1827, Haemulidae, Centracanthidae Gill, 1893, 161428090, Maenidae, Centracanthidae, Centracanthidae Gill, 1893)",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Living Specimen, Machine Observation, Literature Occurrence)",
 "Geometry POLYGON((109.5 20.15,117.25 20.15,117.25 24,109.5 24,109.5 20.15))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 444 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0049126-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rfpnd6
title: Occurrence Download

description: A dataset containing 38 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Africa",
 "Country is Algeria",
 "Geometry POLYGON((-1.14663 35.75082,-1.24758 35.59443,-1.22201 35.55522,-0.89835 35.75217,-0.87805 35.78532,-1.14663 35.75082))",
 "TaxonKey is Scleractinia"
 ]
}

 The dataset includes 38 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0049127-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5t6982
title: Occurrence Download

description: A dataset containing 296859 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is iNaturalist Research-grade Observations",
 "GadmGid is one of (FRA, ITA, ESP, PRT)",
 "License is one of (CC-BY 4.0, CC0 1.0)",
 "PublishingOrg is one of (da86174a-a605-43a4-a5e8-53d484152cd3, 2cd829bb-b713-433d-99cf-64bef11e5b3e, 1928bdf0-f5d2-11dc-8c12-b8a03c50a862, 10980920-6dad-11da-ad13-b8a03c50a862, 28eb1a3f-1c15-4a95-931a-4af90ecb574d)",
 "TaxonKey is Plantae"
 ]
}

 The dataset includes 296859 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0049124-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.43r78u
title: Occurrence Download

description: A dataset containing 50556 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Lynx lynx (Linnaeus, 1758)",
 "Continent is Europe",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "Year is greater than or equal to 1900"
 ]
}

 The dataset includes 50556 records from 97 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0049128-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.