cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.19180613
title: Supplementary Material for: Comparison of Mortality Prediction Scores in Intermediate-Care Patients with Liver Cirrhosis at a German university transplant Center; a prospective study

description: Background & Aims: Mortality prediction models help to extract and relate patient data upon admission to intensive or intermediate care units (ImCU). Considering technical and economic healthcare developments, re-evaluations of score performances are required to warrant their validity. This study validates and compares established scoring systems in cirrhotic ImCU-patients. Methods: APACHE II, SAPS 2 and 3, SOFA, MPMo II and III, MELD, CLIF-C ACLF, CLIF-C AD and ImCUSS were calculated in patients with cirrhosis (n=98) at ImCU-admission. Discrimination performances were evaluated by area-under-the-receiver-operating-characteristic-curves (AUROCs), calibration performances with calibration belt plots and their corresponding p-values. Results: Overall, SAPS 3 and CLIF-C ACLF have shown the best 90-day-mortality prediction outcomes with AUROCs of 0.825 and 0.783 along with calibration belt p-values of 0.128 and 0.061, respectively. In a subgroup analysis of patients with acute-on-chronic liver failure (ACLF), expanded SAPS 2, SOFA and SAPS 3 reached the best AUROCs, i.e., 0.760, 0.750 and 0.714, but none of the tested scores reached an acceptable calibration. Conclusion: 90-day-mortality risk prediction of the SAPS 3 and CLIF-C ACLF was accurrate in our cohort of patients with liver cirrhosis admitted to ImCU. A particular challenge remains the mortality prediction in patients with ACLF requiring ImCU-level care; here, further developments are needed to generate scores with acceptable predictive performances.
DOI: 10.5281/zenodo.5104289
title: Data for "Paris Agreement requires substantial, broad, and sustained policy efforts beyond COVID-19 recovery packages"

description: This dataset contains the underlying data for the following publication: Tanaka, K., C. Azar, O. Boucher, P. Ciais, Y. Gaucher, D. J. A. Johansson (2021) Paris Agreement requires substantial, broad, and sustained policy efforts beyond COVID-19 recovery packages. https://arxiv.org/abs/2104.08342 (accepted for publication in Climatic Change)
description: K.T. benefited from State assistance managed by the National Research Agency in France under the Programme d'Investissements d'Avenir under the reference ANR-19-MPGA-0008.
DOI: 10.5281/zenodo.6475446
title: River network and hydro-geomorphological parameters at 1/12° resolution for global hydrological and climate studies

description: Global scale river routing models (RRMs) are commonly used in a variety of studies, including studies on the impact of climate change on extreme flows (floods and droughts), water resources monitoring or large scale flood forecasting. Over the last two decades, the increasing number of observational datasets, mainly from satellite missions, and the increasing computing capacities, have allowed better performances of RRMs, namely by increasing their spatial resolution. The spatial resolution of a RRM corresponds to the spatial resolution of its river network, which provides flow direction of all grid cells. River networks may be derived at various spatial resolution by upscaling high resolution hydrography data.<br> This paper presents a new global scale river network at 1/12° derived from the MERIT-Hydro dataset. The river network is generated automatically using an adaptation of the Hierarchical Dominant River Tracing (DRT) algorithm, and its quality is assessed over the 70 largest basins of the world. Although this new river network may be used for a variety of hydrology-related studies, it is here provided with a set of hydro-geomorphological parameters at the same spatial resolution. These parameters are derived during the generation of the river network and are based on the same high resolution dataset, so that the consistency between the river network and the parameters is ensured. The set of parameters includes a description of river stretches (length, slope, width, roughness, bankfull depth), floodplains (roughness, sub-grid topography) and aquifers (transmissivity, porosity, sub-grid topography).<br> The new river network and parameters are assessed by comparing the performances of two global scale simulations with the CTRIP model, one with the current spatial resolution (1/2°) and the other with the new spatial resolution (1/12°). It is shown that CTRIP at 1/12° overall outperforms CTRIP at 1/2°, demonstrating the added value of the spatial resolution increase.<br> The new river network and the consistent hydro-geomorphology parameters may be useful for the scientific community, especially for hydrology and hydro-geology modelling, water resources monitoring or climate studies.
description: V1.1.2 includes the last version of the code used to derive the upscaled river network and all the hydrogeomorphological parameters. In this version, the river dataset is slightly different because of two modifications: 1. the land threshold used to define land cells is now 0.25 (0.5 in the previous version) 2. the minimum river width is now 10 m (30 m in the previous version), and the subsequent minimum river depth is also smaller.
DOI: 10.6084/m9.figshare.19419269
title: Supplementary Material for: Requirement of Na+/H+ exchanger NHE1 for vasopressin-induced osteogenic signaling and calcification in human aortic smooth muscle cells

description: Background/Aims: Vasopressin is a powerful stimulator of vascular calcification, augmenting osteogenic signaling in vascular smooth muscle cells (VSMCs) including up-regulation of the transcription factors core-binding factor α-1 (CBFA1), msh homeobox 2 (MSX2), and SRY-Box 9 (SOX9), as well as of tissue-nonspecific alkaline phosphatase (ALPL). Vasopressin-induced osteogenic signaling and calcification require the serum- & glucocorticoid-inducible kinase 1 (SGK1). Known effects of SGK1 include up-regulation of Na+/H+ exchanger 1 (NHE1). NHE1 further participates in the regulation of reactive oxygen species (ROS). NHE1 has been shown to participate in the orchestration of bone mineralization. The present study, thus, explored whether vasopressin modifies NHE1 expression and ROS generation, as well as whether pharmacological inhibition of NHE1 disrupts vasopressin-induced osteogenic signaling and calcification in VSMCs. Methods: Human aortic smooth muscle cells (HAoSMCs) were treated with vasopressin in the absence or presence of SGK1 siRNA, SGK1 inhibitor GSK-650394, and NHE1 blocker cariporide. Transcript levels were determined by using qRT-PCR, protein abundance by western blotting, ROS generation with 2’,7’-dichlorofluorescein diacetate (DCFDA) fluorescence, as well as ALP activity and calcium content by using colorimetric assays. Results: Vasopressin significantly enhanced the NHE1 transcript and protein levels in HAoSMCs, effects significantly blunted by SGK1 inhibition with GSK-650394 or SGK1 siRNA. Vasopressin increased ROS accumulation, an effect significantly blocked by NHE1 inhibitor cariporide. Vasopressin further significantly increased osteogenic markers CBFA1, MSX2, SOX9, and ALPL transcript levels, as well as ALP activity and calcium content in HAoSMCs, all effects significantly blunted by SGK1 silencing or in the presence of GSK-650394 and cariporide. Conclusion: Vasopressin stimulates NHE1 expression and ROS generation, an effect dependent on SGK1 and required for vasopressin-induced stimulation of osteogenic signaling and calcification of VSMCs.
DOI: 10.5281/zenodo.6477052
title: 2c6be7d3-ff0a-4398-ad4b-673be45152d1

description: These data sets are one of the workflows of ddbj/workflow-registry.
DOI: 10.5281/zenodo.6477051
title: 2c6be7d3-ff0a-4398-ad4b-673be45152d1

description: These data sets are one of the workflows of ddbj/workflow-registry.
DOI: 10.21227/qgbp-w789
title: Dynamic decentralization domains for the Internet of Things - Simulation Repository

description: The Internet of Things and edge computing are fostering a future of ecosystemshosting complex decentralized computations, deeply integrated with our very dynamicenvironments. Digitalized buildings, communities of people, and cities will be thenext-generation “hardware and platform”, counting myriads of interconnected devices, on top ofwhich intrinsically-distributed computational processes will run and self-organize. They willspontaneously spawn, diffuse to pertinent logical/physical regions, cooperate and compete,opportunistically summon required resources, collect and analyze data, compute results, triggerdistributed actions, and eventually decade.How would a programming model for such ecosystems look like? Based on research findings onself-adaptive/self-organizing systems, this paper proposes design abstractions based on“dynamic decentralization domains”: regions of space opportunistically formed to supportsituated recognition and action. We embody the approach into a Scala API to enact distributedexecution on a network of devices and show its applicability in a case study of environmentalmonitoring.
DOI: 10.13016/de6m-ixyc
title: CULTURAL LANDSCAPES AND HISTORIC ARCHAEOLOGY OF THE RILEY TRACT, ROCK CREEK PARK, WASHINGTON DC

description: Rock Creek Park is an urban forest within the District of Columbia and is administered by the National Park Service. Before it was established in 1890, much of the area was farmed by a diverse group of landowners and tenants, including William Riley owned 100 acres in what is now the northern section of the park. Today this area is used regularly by hikers, runners, dog-walkers, and horseback riders and is informally referred to as the "wilderness" area of the park. Many believe it is a natural forest, unaware of the land's history. Left relatively undisturbed for years, this heavily wooded parkland contains intact historical archaeology resources and cultural landscapes. Survey of the Riley tract located several cultural landscape features including a stone wall, a dam, two terraced.fields, and a vineyard. Two previously recorded 19th-century sites were also revisited and further characterized. The research located the site of an earlier tenancy, likely late 18th-century, as well as evidence of three 19th -century structures. Many of the newly discovered structures and landscapes features are associated with the late 19th-century Riley farmstead. The research demonstrates that the Riley tract contains extensive evidence of 18th and 19th-century workplaces, and parkland should be interpreted not just as a natural area but recognized for the extensive human component evident in its intact cultural landscapes and archaeological sites.
DOI: 10.6084/m9.figshare.19634788
title: Additional file 2 of Comparative transcriptomic analyses of citrus cold-resistant vs. sensitive rootstocks might suggest a relevant role of ABA signaling in triggering cold scion adaption

description: Additional file 2:Additional Table 1. Most represented KEGG pathways. KEGG is developed by Kanehisa Laboratories from https://www.kegg.jp/kegg/ .
DOI: 10.6084/m9.figshare.19634788.v1
title: Additional file 2 of Comparative transcriptomic analyses of citrus cold-resistant vs. sensitive rootstocks might suggest a relevant role of ABA signaling in triggering cold scion adaption

description: Additional file 2:Additional Table 1. Most represented KEGG pathways. KEGG is developed by Kanehisa Laboratories from https://www.kegg.jp/kegg/ .
DOI: 10.6084/m9.figshare.19634809
title: Additional file 1 of Exploration of mRNAs and miRNA classifiers for various ATLL cancer subtypes using machine learning

description: Additional file 1: Supplementary data file 1. List of DEGs for each ATLL subtype.
DOI: 10.6084/m9.figshare.19634809.v1
title: Additional file 1 of Exploration of mRNAs and miRNA classifiers for various ATLL cancer subtypes using machine learning

description: Additional file 1: Supplementary data file 1. List of DEGs for each ATLL subtype.
DOI: 10.6084/m9.figshare.19634812.v1
title: Additional file 2 of Exploration of mRNAs and miRNA classifiers for various ATLL cancer subtypes using machine learning

description: Additional file 2: Supplementary data file 2. List of unique DEGs for each ATLL subtype.
DOI: 10.6084/m9.figshare.19634812
title: Additional file 2 of Exploration of mRNAs and miRNA classifiers for various ATLL cancer subtypes using machine learning

description: Additional file 2: Supplementary data file 2. List of unique DEGs for each ATLL subtype.
DOI: 10.6084/m9.figshare.19634815
title: Additional file 3 of Exploration of mRNAs and miRNA classifiers for various ATLL cancer subtypes using machine learning

description: Additional file 3: Supplementary data file 3. The involvement of each gene in each pathway and the previously reported function of genes in the ATLL progression.
DOI: 10.6084/m9.figshare.19634815.v1
title: Additional file 3 of Exploration of mRNAs and miRNA classifiers for various ATLL cancer subtypes using machine learning

description: Additional file 3: Supplementary data file 3. The involvement of each gene in each pathway and the previously reported function of genes in the ATLL progression.
DOI: 10.6084/m9.figshare.19634818
title: Additional file 4 of Exploration of mRNAs and miRNA classifiers for various ATLL cancer subtypes using machine learning

description: Additional file 4: Supplementary data file 4. The target genes of miR-21.
DOI: 10.6084/m9.figshare.19634818.v1
title: Additional file 4 of Exploration of mRNAs and miRNA classifiers for various ATLL cancer subtypes using machine learning

description: Additional file 4: Supplementary data file 4. The target genes of miR-21.
DOI: 10.6084/m9.figshare.19634840.v1
title: Additional file 2 of Simple topographic parameter reveals the along-trench distribution of frictional properties on shallow plate boundary fault

description: Additional file 2. Result_ols_A.csv; raw data for WOA plot (Fig. 4A).
DOI: 10.6084/m9.figshare.19634840
title: Additional file 2 of Simple topographic parameter reveals the along-trench distribution of frictional properties on shallow plate boundary fault

description: Additional file 2. Result_ols_A.csv; raw data for WOA plot (Fig. 4A).
DOI: 10.6084/m9.figshare.19634843
title: Additional file 3 of Simple topographic parameter reveals the along-trench distribution of frictional properties on shallow plate boundary fault

description: Additional file 3. Result_ct_A.csv; raw results for critical taper parameters (Fig. 4A).
DOI: 10.6084/m9.figshare.19634843.v1
title: Additional file 3 of Simple topographic parameter reveals the along-trench distribution of frictional properties on shallow plate boundary fault

description: Additional file 3. Result_ct_A.csv; raw results for critical taper parameters (Fig. 4A).
DOI: 10.6084/m9.figshare.19634846
title: Additional file 4 of Simple topographic parameter reveals the along-trench distribution of frictional properties on shallow plate boundary fault

description: Additional file 4. Result_ols_B.csv; raw data for WOA plot (Fig. 4B).
DOI: 10.6084/m9.figshare.19634846.v1
title: Additional file 4 of Simple topographic parameter reveals the along-trench distribution of frictional properties on shallow plate boundary fault

description: Additional file 4. Result_ols_B.csv; raw data for WOA plot (Fig. 4B).
DOI: 10.6084/m9.figshare.19634849
title: Additional file 5 of Simple topographic parameter reveals the along-trench distribution of frictional properties on shallow plate boundary fault

description: Additional file 5. Result_ct_B.csv; raw results for critical taper parameters (Fig. 4B).
DOI: 10.6084/m9.figshare.19634849.v1
title: Additional file 5 of Simple topographic parameter reveals the along-trench distribution of frictional properties on shallow plate boundary fault

description: Additional file 5. Result_ct_B.csv; raw results for critical taper parameters (Fig. 4B).
DOI: 10.6084/m9.figshare.19634870
title: Additional file 1 of Oxford Nanopore and Bionano Genomics technologies evaluation for plant structural variation detection

description: Additional file 1.
DOI: 10.6084/m9.figshare.19634870.v1
title: Additional file 1 of Oxford Nanopore and Bionano Genomics technologies evaluation for plant structural variation detection

description: Additional file 1.
DOI: 10.6084/m9.figshare.19634637
title: Supplementary Material for: Resistance to Erythropoiesis-Stimulating Agents among Patients on Hemodialysis Is Typically Transient

description: <b><i>Introduction:</i></b> This study examines factors associated with erythropoiesis-stimulating agent (ESA) hyporesponsiveness, the duration of ESA hyporesponsiveness, the frequency of new episodes, and variation across countries. <b><i>Methods:</i></b> We used international Dialysis Outcomes and Practice Patterns Study data from 2015 to 2018 (<i>N</i> = 26,656) to investigate changes in ESA Resistance Index (ERI), calculated as epoetin dose divided by [hemoglobin × body weight] in patients on hemodialysis. We illustrated the proportion of patients who moved to other ERI quintiles over 12 months, and we studied the incidence and duration of ESA resistance. We examined case-mix factors associated with quintiles of ERI. <b><i>Results:</i></b> Most patients migrated out of their original ERI quintile within 4 months. Only 22% of patients in the top quintile of ERI at baseline (4.4% of all patients) remained in the top quintile during all 12 months of follow-up. A total of 42% of patients manifested an upper-quintile ERI during at least 1 month. Median duration of a new episode of ESA resistance was 2 months. Catheter hemoaccess, elevated C-reactive protein, lower transferrin saturation, lower serum albumin concentration, and recent hospitalization occurred more frequently among patients in the highest ERI quintile at baseline. ERI values were highest in the USA, Italy, and Mideastern nations and lowest in Russia and Japan. <b><i>Discussion/Conclusion:</i></b> It is a misconception to envision a sizable, fixed segment of the population with permanent resistance to ESA – resistance fluctuates frequently. The implications of these findings for prescription of ESAs and of hypoxia-inducible factor-prolyl hydroxylase inhibitors are discussed.
DOI: 10.6084/m9.figshare.19634914
title: Additional file 2 of Lack of an association between dietary patterns and adiposity among primary school children in Kilimanjaro Tanzania

description: Additional file 2.
DOI: 10.6084/m9.figshare.19634914.v1
title: Additional file 2 of Lack of an association between dietary patterns and adiposity among primary school children in Kilimanjaro Tanzania

description: Additional file 2.
DOI: 10.6084/m9.figshare.19634920.v1
title: Additional file 2 of Lung tissue shows divergent gene expression between chronic obstructive pulmonary disease and idiopathic pulmonary fibrosis

description: Additional file 2. Supplementary tables. Table S1. IPF vs. control differential expression results. Table S2. COPD vs. control differential expression results. Table S3. Overlap genes from COPD and IPF vs. control differential expression. Table S4. COPD GWAS loci genes within ± 200 kb in overlapping differential expression genes. Table S5. IPF GWAS loci genes within ± 200 kb in overlapping differential expression genes. Table S6. Hallmark pathway enrichment. Table S7. COPDGene phase 2 RNASeq subject characteristics. Table S8. IPF study (Molyneaux et al.) subject characteristics. Table S9. GSVA score associations with outcomes in COPDGene.
DOI: 10.6084/m9.figshare.19634920
title: Additional file 2 of Lung tissue shows divergent gene expression between chronic obstructive pulmonary disease and idiopathic pulmonary fibrosis

description: Additional file 2. Supplementary tables. Table S1. IPF vs. control differential expression results. Table S2. COPD vs. control differential expression results. Table S3. Overlap genes from COPD and IPF vs. control differential expression. Table S4. COPD GWAS loci genes within ± 200 kb in overlapping differential expression genes. Table S5. IPF GWAS loci genes within ± 200 kb in overlapping differential expression genes. Table S6. Hallmark pathway enrichment. Table S7. COPDGene phase 2 RNASeq subject characteristics. Table S8. IPF study (Molyneaux et al.) subject characteristics. Table S9. GSVA score associations with outcomes in COPDGene.
DOI: 10.6084/m9.figshare.19634960
title: Additional file 2 of Is energy excess the initial trigger of carbon overflow metabolism? Transcriptional network response of carbon-limited Escherichia coli to transient carbon excess

description: Additional file 2. Transcriptome analysis. (Sheet 1) All time-dependent transcript data (4209 different transcripts in total, including regulation through single or multiple TF/SF combinations from those combinations identified later on as relevant). (Sheet 2) Time-dependent color-coded transcript data (heat maps) of genes responding differentially to the glucose pulse (1739 DEGs in total) sorted into respective clusters (14 clusters in total). (Sheet 3) Assignment to GO category “biological process” as well as the results of the functional enrichment analysis for determination of over-represented GO categories “biological process” (log10 nominal p-values of Fisher’s exact test). These data were used for the visualization of results presented in Fig. 2. (Sheet 4) 1739 DEG sorted into the 14 clusters together with their known control through all known TFs and SFs and the results of the functional enrichment analysis for determination of the most relevant TF/SF combinations (log10 nominal p-values of Fisher’s exact test). These data were used for the visualization of the results presented in Fig. 3. (Sheet 5) Selection of the most relevant TF/SF combinations. Time-dependent control of gene expression through single or multiple TF/SF combinations from those combinations identified as relevant. (Sheet 6) Fisher’s exact test (Sheet 7), corrected T-test and (Sheet 8) log10 T-test.
DOI: 10.6084/m9.figshare.19634960.v1
title: Additional file 2 of Is energy excess the initial trigger of carbon overflow metabolism? Transcriptional network response of carbon-limited Escherichia coli to transient carbon excess

description: Additional file 2. Transcriptome analysis. (Sheet 1) All time-dependent transcript data (4209 different transcripts in total, including regulation through single or multiple TF/SF combinations from those combinations identified later on as relevant). (Sheet 2) Time-dependent color-coded transcript data (heat maps) of genes responding differentially to the glucose pulse (1739 DEGs in total) sorted into respective clusters (14 clusters in total). (Sheet 3) Assignment to GO category “biological process” as well as the results of the functional enrichment analysis for determination of over-represented GO categories “biological process” (log10 nominal p-values of Fisher’s exact test). These data were used for the visualization of results presented in Fig. 2. (Sheet 4) 1739 DEG sorted into the 14 clusters together with their known control through all known TFs and SFs and the results of the functional enrichment analysis for determination of the most relevant TF/SF combinations (log10 nominal p-values of Fisher’s exact test). These data were used for the visualization of the results presented in Fig. 3. (Sheet 5) Selection of the most relevant TF/SF combinations. Time-dependent control of gene expression through single or multiple TF/SF combinations from those combinations identified as relevant. (Sheet 6) Fisher’s exact test (Sheet 7), corrected T-test and (Sheet 8) log10 T-test.