cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.14552059
title: Prioritisation of the most vulnerable regions to climate change and outputs of the analysis

description: Output data along with the deliverable report that focuses on identifying and prioritizing regions in Europe most vulnerable to climate change impacts. It introduces a comprehensive Climate Risk Index (CRI), which integrates multiple dimensions of risk, including climate hazards, exposure, and socio-economic vulnerability, at the NUTS-3 regional level. The analysis is informed by the latest IPCC methodologies and frameworks, incorporating data from sources like Eurostat, ESPON, and climate modeling projections for 2050 under two emissions scenarios (RCP 2.6 and RCP 8.5).

The CRI evaluates four specific impact chains: labor productivity, tourism, agriculture, and water scarcity. Each impact chain combines a hazard (e.g., heat stress, water imbalance) with its socio-economic consequences (e.g., reduced labor productivity or agricultural output). Indicators for exposure (e.g., population, employment), vulnerability (e.g., adaptive capacity, sensitivity), and hazards are normalized and weighted to calculate the CRI for each region.

Results highlight a clear spatial pattern of climate risk, with Southern and Eastern Europe (e.g., Spain, Italy, Greece, Romania) facing higher risks due to stronger hazards and socio-economic vulnerabilities. Key regions are identified for each impact chain, with agricultural-intensive and highly touristic areas, as well as urban regions, at greater risk. The report emphasizes the importance of using such indices to guide EU policy decisions, focusing on supporting regions most vulnerable to climate change impacts.

The methodology and findings aim to assist policymakers in prioritizing adaptation efforts and fostering resilience in the most affected regions. The CRI framework is adaptable, allowing integration of new data and indicators as they become available, making it a vital tool for future climate resilience planning across Europe.
DOI: 10.5281/zenodo.14552060
title: Prioritisation of the most vulnerable regions to climate change and outputs of the analysis

description: Output data along with the deliverable report that focuses on identifying and prioritizing regions in Europe most vulnerable to climate change impacts. It introduces a comprehensive Climate Risk Index (CRI), which integrates multiple dimensions of risk, including climate hazards, exposure, and socio-economic vulnerability, at the NUTS-3 regional level. The analysis is informed by the latest IPCC methodologies and frameworks, incorporating data from sources like Eurostat, ESPON, and climate modeling projections for 2050 under two emissions scenarios (RCP 2.6 and RCP 8.5).

The CRI evaluates four specific impact chains: labor productivity, tourism, agriculture, and water scarcity. Each impact chain combines a hazard (e.g., heat stress, water imbalance) with its socio-economic consequences (e.g., reduced labor productivity or agricultural output). Indicators for exposure (e.g., population, employment), vulnerability (e.g., adaptive capacity, sensitivity), and hazards are normalized and weighted to calculate the CRI for each region.

Results highlight a clear spatial pattern of climate risk, with Southern and Eastern Europe (e.g., Spain, Italy, Greece, Romania) facing higher risks due to stronger hazards and socio-economic vulnerabilities. Key regions are identified for each impact chain, with agricultural-intensive and highly touristic areas, as well as urban regions, at greater risk. The report emphasizes the importance of using such indices to guide EU policy decisions, focusing on supporting regions most vulnerable to climate change impacts.

The methodology and findings aim to assist policymakers in prioritizing adaptation efforts and fostering resilience in the most affected regions. The CRI framework is adaptable, allowing integration of new data and indicators as they become available, making it a vital tool for future climate resilience planning across Europe.
DOI: 10.26302/sshade/bandlist_raman_n2_alpha-n2
title: Raman band list of N2 in solid N2 (phase alpha)

description: FIR-MIR Raman band list of the isotopes of $N_2$ in solid $\alpha-N2$
DOI: 10.26302/sshade/bandlist_abs_n2_alpha-n2
title: Absorption band list of N2 in solid N2 (phase alpha)

description: FIR-MIR-NIR absorption band list of the isotopes of $N_2$ in solid $\alpha-N2$
DOI: 10.26302/sshade/bandlist_abs_n2_beta-n2
title: Absorption band list of N2 in solid N2 (phase beta)

description: MIR-NIR absorption band list of the isotopes of $N_2$ in solid $\beta-N2$
DOI: 10.26302/sshade/bandlist_raman_n2_beta-n2
title: Raman band list of N2 in solid N2 (phase beta)

description: MIR Raman band list of the isotopes of $N_2$ in solid $\beta-N2$
DOI: 10.6084/m9.figshare.27264298
title: Cold ischemia time alters cell-type specific senescence leading to loss of cellular integrity in mouse lungs

description: <b>Purpose:</b> Ischemia-reperfusion injury (IRI) is a major challenge in lung transplantation often causing graft dysfunction and chronic airway illnesses in recipients. To prevent potential transplant related complications, strict guidelines were put in place to choose viable donor lungs with minimal risk of IRI. These regulations deem most of the donor organs unfit for transplant which then are donated for research to understand the mechanisms of health and diseases in human. However, resected organs that are being transported undergo cold ischemia that can negatively affect the tissue architecture and other cellular functions under study. Thus, it is important to assess how cold ischemia time (CIT) affects the physiological mechanism. In this respect, we are interested in studying how CIT affects cellular senescence in normal aging and various pulmonary pathologies. We thus hypothesized that prolonged CIT exhibits cell-type specific changes in lung cellular senescence in mice. <b>Methods:</b> Lung lobes from C57BL/6J (<i>n</i> = 5–8) mice were harvested and stored in UW Belzer cold storage solution for 0, 4-, 9-, 12-, 24-, and 48-h CIT. Lung cellular senescence was determined using fluorescence (C<sub>12</sub>FdG) assay and co-immunolabelling was performed to identify changes in individual cell types. <b>Results:</b> We found a rapid decline in the overall lung cellular senescence after 4-h of CIT in our study. Co-immunolabelling revealed the endothelial cells to be most affected by cold ischemia, demonstrating significant decrease in the endothelial cell senescence immediately after harvest. Annexin V-PI staining further revealed a prominent increase in the number of necrotic cells at 4-h CIT, thus suggesting that most of the cells undergo cell death within a few hours of cold ischemic injury. <b>Conclusions:</b> We thus concluded that CIT significantly lowers the cellular senescence in lung tissues and must be considered as a confounding factor for mechanistic studies in the future.
DOI: 10.6084/m9.figshare.27264298.v1
title: Cold ischemia time alters cell-type specific senescence leading to loss of cellular integrity in mouse lungs

description: <b>Purpose:</b> Ischemia-reperfusion injury (IRI) is a major challenge in lung transplantation often causing graft dysfunction and chronic airway illnesses in recipients. To prevent potential transplant related complications, strict guidelines were put in place to choose viable donor lungs with minimal risk of IRI. These regulations deem most of the donor organs unfit for transplant which then are donated for research to understand the mechanisms of health and diseases in human. However, resected organs that are being transported undergo cold ischemia that can negatively affect the tissue architecture and other cellular functions under study. Thus, it is important to assess how cold ischemia time (CIT) affects the physiological mechanism. In this respect, we are interested in studying how CIT affects cellular senescence in normal aging and various pulmonary pathologies. We thus hypothesized that prolonged CIT exhibits cell-type specific changes in lung cellular senescence in mice. <b>Methods:</b> Lung lobes from C57BL/6J (<i>n</i> = 5–8) mice were harvested and stored in UW Belzer cold storage solution for 0, 4-, 9-, 12-, 24-, and 48-h CIT. Lung cellular senescence was determined using fluorescence (C<sub>12</sub>FdG) assay and co-immunolabelling was performed to identify changes in individual cell types. <b>Results:</b> We found a rapid decline in the overall lung cellular senescence after 4-h of CIT in our study. Co-immunolabelling revealed the endothelial cells to be most affected by cold ischemia, demonstrating significant decrease in the endothelial cell senescence immediately after harvest. Annexin V-PI staining further revealed a prominent increase in the number of necrotic cells at 4-h CIT, thus suggesting that most of the cells undergo cell death within a few hours of cold ischemic injury. <b>Conclusions:</b> We thus concluded that CIT significantly lowers the cellular senescence in lung tissues and must be considered as a confounding factor for mechanistic studies in the future.
DOI: 10.6084/m9.figshare.27045651
title: Exosomes derived from hypoxic alveolar epithelial cells promote the phenotypic transformation of pulmonary artery smooth muscle cells via the Rap1 pathway

description: <b>Background:</b> Hypoxic pulmonary hypertension (HPH) is one of the important pathophysiological changes in chronic pulmonary heart disease. Hypoxia promotes the phenotypic transformation of pulmonary artery smooth muscle cells (PASMCs). Extracellular exosomes regulate vascular smooth muscle cell (VSMC) phenotypic switch. <b>Aim:</b> Given the importance of exosomes and alveolar epithelial cells (AECs) in HPH, the present study aimed to address the issue of whether AEC-derived exosomes promote HPH by triggering PASMC phenotypic switch. <b>Methods:</b> Cell Counting Kit-8 (CCK-8), TRITC-phalloidin staining, and Western blotting were used to examine the effects of AEC-derived exosomes on cell proliferation, intracellular actin backbone distribution, and expression of phenotypic marker proteins in PASMCs. Transcriptomics sequencing was used to analyze differentially expressed genes (DEGs) between groups. <b>Results:</b> Hypoxia-induced exosomes (H-exos) could promote the proliferation of PASMCs, cause the reduction of cellular actin microfilaments, promote the expression of synthetic marker proteins (ELN and OPN), reduce the expression of contractile phenotypic marker proteins (SM22-α and α-SMA), and induce the phenotypic transformation of PASMCs. Transcriptomics sequencing analysis showed that the Rap1 signaling pathway was involved in the phenotypic transformation of PASMCs induced by H-exos. <b>Conclusion:</b> The present study identified that hypoxia-induced AEC-derived exosomes promote the phenotypic transformation of PASMCs and its mechanism is related to the Rap1 signaling pathway.
DOI: 10.6084/m9.figshare.27045651.v1
title: Exosomes derived from hypoxic alveolar epithelial cells promote the phenotypic transformation of pulmonary artery smooth muscle cells via the Rap1 pathway

description: <b>Background:</b> Hypoxic pulmonary hypertension (HPH) is one of the important pathophysiological changes in chronic pulmonary heart disease. Hypoxia promotes the phenotypic transformation of pulmonary artery smooth muscle cells (PASMCs). Extracellular exosomes regulate vascular smooth muscle cell (VSMC) phenotypic switch. <b>Aim:</b> Given the importance of exosomes and alveolar epithelial cells (AECs) in HPH, the present study aimed to address the issue of whether AEC-derived exosomes promote HPH by triggering PASMC phenotypic switch. <b>Methods:</b> Cell Counting Kit-8 (CCK-8), TRITC-phalloidin staining, and Western blotting were used to examine the effects of AEC-derived exosomes on cell proliferation, intracellular actin backbone distribution, and expression of phenotypic marker proteins in PASMCs. Transcriptomics sequencing was used to analyze differentially expressed genes (DEGs) between groups. <b>Results:</b> Hypoxia-induced exosomes (H-exos) could promote the proliferation of PASMCs, cause the reduction of cellular actin microfilaments, promote the expression of synthetic marker proteins (ELN and OPN), reduce the expression of contractile phenotypic marker proteins (SM22-α and α-SMA), and induce the phenotypic transformation of PASMCs. Transcriptomics sequencing analysis showed that the Rap1 signaling pathway was involved in the phenotypic transformation of PASMCs induced by H-exos. <b>Conclusion:</b> The present study identified that hypoxia-induced AEC-derived exosomes promote the phenotypic transformation of PASMCs and its mechanism is related to the Rap1 signaling pathway.
DOI: 10.6084/m9.figshare.27906949
title: Whole transcriptome sequencing identifies key lncRNAs, circRNAs and miRNAs in sepsis-associated acute lung injury

description: <b>Purpose:</b> In this study, we identified differentially expressed genes (DEGs) and signaling pathways to gain insight into the pathogenesis of acute lung injury (ALI). <b>Methods:</b> C57BL/6 mice were intravenously injected with lipopolysaccharide (LPS) to establish a sepsis-induced ALI model. Hematoxylin-eosin (H&E) and enzyme-linked immunosorbent assays (ELISAs) were used to evaluate the model. Whole transcriptome sequencing was performed to identify the expression changes in lncRNAs, circRNAs, miRNAs and mRNAs in lung tissues. The crucial RNAs and the biological function of the target genes were confirmed and annotated based on bioinformatics analysis. Real-time quantitative reverse transcription-polymerase chain reaction (qRT–PCR) was employed to verify the expression levels of key lncRNAs, circRNAs, miRNAs and mRNAs in the lung tissues and human bronchoalveolar lavage (BALF). <b>Results:</b> A total of 3304 (1632 upregulated and 1672 downregulated) differentially expressed mRNAs, 794 (397 up and 397 down) differentially expressed lncRNAs, 89 (58 up and 31 down) differentially expressed circRNAs, and 14 (11 up and 3 down) differentially expressed miRNAs were identified between the control and LPS lung tissues. The lncRNA ceRNA subnetwork and circRNA ceRNA subnetwork were constructed based on the observed interaction and co-expression among the differentially expressed RNAs. An analysis of the protein–protein interaction (PPI) network and hub genes revealed crucial mRNAs for circRNA-Tcf20. The lncRNA-Snhg12, <i>Edn1, Stat1,</i> miR-212-3p and miR-223-3p were upregulated in sepsis ARDS patients. CircRNA-Tcf20, <i>Col1a1, Col1a2 and Flt3</i> were significantly downregulated in sepsis ARDS patients. The biological function analysis indicated that these genes were enriched in the TNF signaling pathway, Necroptosis signaling pathway and the PI3K-Akt signaling pathway. <b>Conclusions:</b> Our findings suggest that circRNA-Tcf20, miR-212-3p, miR-223-3p, <i>Col1a1, Col1a2 and Flt3</i> may be new regulatory factors that participate in the pathogenesis of sepsis-related acute lung injury. CircRNA-Tcf20, lncRNA-Snhg12 and all the other RNAs may be potential biomarkers for septic ALI/ARDS.
DOI: 10.6084/m9.figshare.27906949.v1
title: Whole transcriptome sequencing identifies key lncRNAs, circRNAs and miRNAs in sepsis-associated acute lung injury

description: <b>Purpose:</b> In this study, we identified differentially expressed genes (DEGs) and signaling pathways to gain insight into the pathogenesis of acute lung injury (ALI). <b>Methods:</b> C57BL/6 mice were intravenously injected with lipopolysaccharide (LPS) to establish a sepsis-induced ALI model. Hematoxylin-eosin (H&E) and enzyme-linked immunosorbent assays (ELISAs) were used to evaluate the model. Whole transcriptome sequencing was performed to identify the expression changes in lncRNAs, circRNAs, miRNAs and mRNAs in lung tissues. The crucial RNAs and the biological function of the target genes were confirmed and annotated based on bioinformatics analysis. Real-time quantitative reverse transcription-polymerase chain reaction (qRT–PCR) was employed to verify the expression levels of key lncRNAs, circRNAs, miRNAs and mRNAs in the lung tissues and human bronchoalveolar lavage (BALF). <b>Results:</b> A total of 3304 (1632 upregulated and 1672 downregulated) differentially expressed mRNAs, 794 (397 up and 397 down) differentially expressed lncRNAs, 89 (58 up and 31 down) differentially expressed circRNAs, and 14 (11 up and 3 down) differentially expressed miRNAs were identified between the control and LPS lung tissues. The lncRNA ceRNA subnetwork and circRNA ceRNA subnetwork were constructed based on the observed interaction and co-expression among the differentially expressed RNAs. An analysis of the protein–protein interaction (PPI) network and hub genes revealed crucial mRNAs for circRNA-Tcf20. The lncRNA-Snhg12, <i>Edn1, Stat1,</i> miR-212-3p and miR-223-3p were upregulated in sepsis ARDS patients. CircRNA-Tcf20, <i>Col1a1, Col1a2 and Flt3</i> were significantly downregulated in sepsis ARDS patients. The biological function analysis indicated that these genes were enriched in the TNF signaling pathway, Necroptosis signaling pathway and the PI3K-Akt signaling pathway. <b>Conclusions:</b> Our findings suggest that circRNA-Tcf20, miR-212-3p, miR-223-3p, <i>Col1a1, Col1a2 and Flt3</i> may be new regulatory factors that participate in the pathogenesis of sepsis-related acute lung injury. CircRNA-Tcf20, lncRNA-Snhg12 and all the other RNAs may be potential biomarkers for septic ALI/ARDS.
DOI: 10.15468/dl.55kgsh
title: Occurrence Download

description: A dataset listing the 591919 species recorded in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "Geometry POLYGON ((91.0506 -15.74986, 168.1681 -15.74986, 168.1681 63.9154, 91.0506 63.9154, 91.0506 -15.74986))"
 ]
}

 The dataset's 591919 records were derived from 7239 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0047732-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.d7cr7e
title: Occurrence Download

description: A dataset containing 55 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Astragalus nummularius Lam."
 ]
}

 The dataset includes 55 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009570-210819072339941/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vnue4j
title: Occurrence Download

description: A dataset containing 50 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Astragalus pubiflorus DC."
 ]
}

 The dataset includes 50 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009549-210819072339941/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.skn6wy
title: Occurrence Download

description: A dataset containing 64 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Astragalus cavanillesii Podlech"
 ]
}

 The dataset includes 64 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009589-210819072339941/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.twgasc
title: Occurrence Download

description: A dataset containing 39 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Astragalus hellenicus Boiss."
 ]
}

 The dataset includes 39 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009586-210819072339941/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.88yzcp
title: Occurrence Download

description: A dataset containing 18 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Astragalus maurus (Humbert & Maire) Pau"
 ]
}

 The dataset includes 18 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0114739-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dz84xk
title: Occurrence Download

description: A dataset containing 18 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Astragalus maurus (Humbert & Maire) Pau"
 ]
}

 The dataset includes 18 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009611-210819072339941/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cmvu6u
title: Occurrence Download

description: A dataset containing 85 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "Country is Ukraine",
 "Country is Russian Federation"
 ]
 },
 "TaxonKey is Astragalus pubiflorus DC."
 ]
}

 The dataset includes 85 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0120800-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.787ghh
title: Occurrence Download

description: A dataset containing 116 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Astragalus pubiflorus DC."
 ]
}

 The dataset includes 116 records from 23 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0182515-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.89v68f
title: Occurrence Download

description: A dataset containing 20 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Astragalus hellenicus Boiss."
 ]
}

 The dataset includes 20 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0126937-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hqyv27
title: Occurrence Download

description: A dataset containing 1686 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "Country is Switzerland",
 "Country is Germany",
 "Country is Czechia",
 "Country is Hungary",
 "Country is Austria"
 ]
 },
 "TaxonKey is Astragalus exscapus L."
 ]
}

 The dataset includes 1686 records from 55 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0126926-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mqugd6
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-36.39648 -10.49194,-38.30404 -11.10077,-36.41048 -12.1561,-35.18045 -11.26646,-36.39648 -10.49194))",
 "TaxonKey is Hastula cinerea (Born, 1778)"
 ]
}

 The dataset includes 4 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005296-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2sut65
title: Occurrence Download

description: A dataset containing 785 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Astragalus dasyanthus Pall."
 ]
}

 The dataset includes 785 records from 60 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0183342-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.