cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.cb40x9
title: Occurrence Download

description: A dataset containing 543 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON ((85.78125 19.973348786110602, 92.10937499999999 9.102096738726456, 114.60937499999999 10.487811882056695, 137.8125 25.16517336866393, 117.42187500000001 39.90973623453719, 78.046875 39.90973623453719, 68.203125 30.751277776257812, 70.3125 20.632784250388028, 85.78125 19.973348786110602))",
 "TaxonKey is Tsuga dumosa (D.Don) Eichler"
 ]
}

 The dataset includes 543 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004426-171002173027117/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/y878d3
title: Species of animals listed in Red Book of Ukraine from Medobory nature reserve

description: The database includes the findings of 64 species of animals listed in the third edition of the Red Book of Ukraine found in the Medobory nature reserve and adjacent areas.
DOI: 10.15468/dl.j2vqws
title: Occurrence Download

description: A dataset listing the 65075 species recorded in GBIF matching the query:
{
 "Country" : [
 "is Bolivia (Plurinational State of)"
 ]
}

 The dataset's 65075 records were derived from 1306 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017897-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.20295687
title: Additional file 4 of A de novo assembled high-quality chromosome-scale Trifolium pratense genome and fine-scale phylogenetic analysis

description: Additional file 4: Table S4. URLs and code of the software.
DOI: 10.6084/m9.figshare.20295687.v1
title: Additional file 4 of A de novo assembled high-quality chromosome-scale Trifolium pratense genome and fine-scale phylogenetic analysis

description: Additional file 4: Table S4. URLs and code of the software.
DOI: 10.6084/m9.figshare.8245019
title: Additional file 13: of Population structure, demographic history and local adaptation of the grass carp

description: Table S6. Enriched KEGG pathways and the gene counts under putative selection identified by outlier tests and Bayenv association tests. (XLSX 10 kb)
DOI: 10.6084/m9.figshare.19779333.v1
title: Immunomodulatory effects of icariin in a myocardial infarction mouse model

description: Myocardial infarction (MI) is a prevalent cardiovascular disease defined by myocardial ischemia and hypoxic damage caused by plaque rupture, thrombosis, lumen stenosis, or blockage in the coronary artery. However, the development of emergency percutaneous coronary interventional therapy has enabled the rapid restoration of blood perfusion to ischemic myocardium and the rescue of dying myocardium cells. Some dying myocardium cells have caused irreversible damage and impaired cardiac function recovery in recent years. Icariin has been utilized to treat various ailments as a natural chemical extract. In this study, we employed a variety of approaches to observe MI, including western blotting, quantitative RT–PCR, immunohistochemistry, and flow cytometric analysis using icariin. As demonstrated by the research findings, icariin may prevent MI-induced cell apoptosis. This is accomplished by inhibiting proinflammatory factors via the Nrf2/HO-1 signaling pathways. These data imply that icariin may be an effective treatment for MI.
DOI: 10.6084/m9.figshare.16633301.v1
title: Additional file 6 of Transcriptomic analysis of salt tolerance-associated genes and diversity analysis using indel markers in yardlong bean (Vigna unguiculata ssp. sesquipedialis)

description: Additional file 6: Supplementary Table S6. GO analysis of DEGs induced by salt stress in Suzi 41 and Sujiang 1419.
DOI: 10.6084/m9.figshare.16633304
title: Additional file 7 of Transcriptomic analysis of salt tolerance-associated genes and diversity analysis using indel markers in yardlong bean (Vigna unguiculata ssp. sesquipedialis)

description: Additional file 7: Supplementary Table S7. KEGG pathways enriched with DEGs under high salinity in Suzi 41 and Sujiang 1419.
DOI: 10.6084/m9.figshare.20295774
title: Additional file 5 of Association of serum 25-hydroxyvitamin D (25(OH)D) levels with the gut microbiota and metabolites in postmenopausal women in China

description: Additional file 5: Table S1. Characteristics and clinical and biochemical indexes between HVD group (n=44) and LVD group (n=44).
DOI: 10.25935/4fm1-xh69
title: Saturn electron model derived from "Raytracing analysis for the propagation of Saturn narrowband emission within the Saturnian magnetosphere"

description: This archive consists of the electron density model derived from paper: Raytracing analysis for the propagation of Saturn narrowband emission within the Saturnian magnetosphere.
DOI: 10.6084/m9.figshare.1434692
title: Administration of progranulin (PGRN) triggers ER stress and impairs insulin sensitivity via PERK-eIF2α-dependent manner

description: Progranulin (PGRN) has recently emerged as an important regulator for glucose metabolism and insulin sensitivity. However, the direct effects of PGRN <i>in vivo</i> and the underlying mechanisms between PGRN and impaired insulin sensitivity are not fully understood. In this study, mice treated with PGRN for 21 d exhibited the impaired glucose tolerance and insulin sensitivity, remarkable ER stress as well as attenuated insulin signaling in liver and adipose tissue but not in skeletal muscle. Furthermore, treatment of mice with phenyl butyric acid (PBA), a chemical chaperone alleviating ER stress, resulted in a significant restoration of systemic insulin sensitivity and recovery of insulin signaling induced by PGRN. Consistent with these findings <i>in vivo</i>, we also observed that PGRN treatment induced ER stress, impaired insulin signaling in cultured hepatocytes and adipocytes, with such effects being partially nullified by blockade of PERK. Whereas PGRN-deficient hepatocytes and adipocytes were more refractory to palmitate-induced insulin resistance, indicating the causative role of the PERK-eIF2α axis of the ER stress response in action of PGRN. Collectively, our findings supported the notion that PGRN is a key regulator of insulin resistance and that PGRN may mediate its effects, at least in part, by inducing ER stress via the PERK-eIF2α dependent pathway.
DOI: 10.6084/m9.figshare.10347839
title: All data files and processing script of "Anhydrite-assisted hydrothermal metal transport to the ocean floor – insights from thermo-hydro-chemical modeling"

description: Data files and processing script.<br><b>Data</b>This directory contains all the data of simulation results, which are stored in hdf5 (XDMF) format. One can visualize the results in ParaView.<br><b>Figures.ipynb</b>This is a Jupyter-notebook file which contains all the python scripts to generate figure 2 and figure 4-10.makemovie.pyThis is a python script to generate the SI Movie1.<br><b>scifig</b>There are some python script to generate figures in Figures.ipynb
DOI: 10.6084/m9.figshare.24503747
title: Alternative splicing of IRF3 plays an important role in the development of hepatocarcinoma

description: Alternative splicing is a process causing mRNA translation to produce different proteins, and it is crucial for the development of tumours. In this study, we constructed a prognostic model related to alternative splicing events in hepatocarcinoma using bioinformatics analysis, including the alternative splicing of CSAD, AFMID, ZDHHC16, and IRF3. The model is an independent prognostic factor and can accurately predict a patient’s prognosis. IRF3 is a transcription factor related to the immune response. Its alternative splicing can affect the expression of various genes related to prognosis and plays an essential role in the tumour microenvironment. We also verified the expression of IRF3 exon skipping isoform in hepatocarcinoma at the mRNA level. In conclusion, we discovered that the alternative splicing of IRF3 is essential for the development of hepatocarcinoma. This study provides new insight into the development of treatments for hepatocarcinoma.
DOI: 10.6084/m9.figshare.24503747.v1
title: Alternative splicing of IRF3 plays an important role in the development of hepatocarcinoma

description: Alternative splicing is a process causing mRNA translation to produce different proteins, and it is crucial for the development of tumours. In this study, we constructed a prognostic model related to alternative splicing events in hepatocarcinoma using bioinformatics analysis, including the alternative splicing of CSAD, AFMID, ZDHHC16, and IRF3. The model is an independent prognostic factor and can accurately predict a patient’s prognosis. IRF3 is a transcription factor related to the immune response. Its alternative splicing can affect the expression of various genes related to prognosis and plays an essential role in the tumour microenvironment. We also verified the expression of IRF3 exon skipping isoform in hepatocarcinoma at the mRNA level. In conclusion, we discovered that the alternative splicing of IRF3 is essential for the development of hepatocarcinoma. This study provides new insight into the development of treatments for hepatocarcinoma.
DOI: 10.6084/m9.figshare.11396556
title: Spatiotemporal Modeling and Real-Time Prediction of Origin-Destination Traffic Demand

description: Traffic demand prediction has been a crucial problem for the planning, scheduling, and optimization in transportation management. The prediction of traffic demand counts for origin-destination (OD) pairs has been considered challenging due to the high variability and complicated spatiotemporal correlations in the data. Though several articles have considered estimating traffic flows from counts observed at specific locations, existing traffic prediction models seldom dealt with spatiotemporal demand count data of certain OD pairs, or they failed to effectively consider domain knowledge of the traffic network to enhance the prediction accuracy of traffic demand. To tackle the aforementioned challenges, we formulate and propose a multivariate Poisson log-normal model with specific parameterization tailored to the traffic demand problem, which captures the spatiotemporal correlations of the traffic demand across different routes and epochs, and automatically clusters the routes based on the demand correlations. The model is further estimated using an expectation-maximization algorithm and applied for predicting future demand counts at the subsequent epochs. The estimation and prediction procedures incorporate Markov chain Monte Carlo sampling to overcome the computational challenges. Simulations as well as a real application on a New York yellow taxi data are performed to demonstrate the applicability and effectiveness of the proposed method. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.11396556.v2
title: Spatiotemporal Modeling and Real-Time Prediction of Origin-Destination Traffic Demand

description: Traffic demand prediction has been a crucial problem for the planning, scheduling, and optimization in transportation management. The prediction of traffic demand counts for origin-destination (OD) pairs has been considered challenging due to the high variability and complicated spatiotemporal correlations in the data. Though several articles have considered estimating traffic flows from counts observed at specific locations, existing traffic prediction models seldom dealt with spatiotemporal demand count data of certain OD pairs, or they failed to effectively consider domain knowledge of the traffic network to enhance the prediction accuracy of traffic demand. To tackle the aforementioned challenges, we formulate and propose a multivariate Poisson log-normal model with specific parameterization tailored to the traffic demand problem, which captures the spatiotemporal correlations of the traffic demand across different routes and epochs, and automatically clusters the routes based on the demand correlations. The model is further estimated using an expectation-maximization algorithm and applied for predicting future demand counts at the subsequent epochs. The estimation and prediction procedures incorporate Markov chain Monte Carlo sampling to overcome the computational challenges. Simulations as well as a real application on a New York yellow taxi data are performed to demonstrate the applicability and effectiveness of the proposed method. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.11396556.v1
title: Spatiotemporal modeling and real-time prediction of origin-destination traffic demand

description: Traffic demand prediction has been a crucial problem for the planning, scheduling, and optimization in transportation management. The prediction of traffic demand counts for origin-destination (OD) pairs has been considered challenging due to the high variability and complicated spatiotemporal correlations in the data. Though several papers have considered estimating traffic flows from counts observed at specific locations, existing traffic prediction models seldom dealt with spatiotemporal demand count data of certain OD pairs, or they failed to effectively consider domain knowledge of the traffic network to enhance the prediction accuracy of traffic demand. To tackle the aforementioned challenges, we formulate and propose a multivariate Poisson log-normal model with specific parametrization tailored to the traffic demand problem, which captures the spatiotemporal correlations of the traffic demand across different routes and epochs, and automatically clusters the routes based on the demand correlations. The model is further estimated using an Expectation-Maximization (EM) algorithm and applied for predicting future demand counts at the subsequent epochs. The estimation and prediction procedures incorporate Markov chain Monte Carlo (MCMC) sampling to overcome the computational challenges. Simulations as well as a real application on a New York yellow taxi data are performed to demonstrate the applicability and effectiveness of the proposed method. Supplementary materials for the article are available online.
DOI: 10.6084/m9.figshare.24503776
title: Summer sea-ice melting enhances phytoplankton and dimethyl sulfide (DMS) productions in the Weddell–Scotia Confluence

description: The relationships among sea ice melting, phytoplankton assemblages, and the production of climate-relevant trace gases in the Southern Ocean are gaining increasing attention from the scientific community. This is especially true for dimethyl sulfide (DMS), which plays an important role in atmospheric chemistry by influencing the formation of sulfated aerosols with radiative impacts and constituting cloud condensation nuclei. In the current study, DMS and its precursors, dimethylsulfoniopropionate (DMSP) and chlorophyll <i>a</i> (Chl <i>a</i>), were quantified in the Weddell–Scotia Confluence (WSC) during the 2018 record ice extent minimum period. Mixed layer changes were found to be generally associated with spatial variation in sea ice melt, with the depth being six times deeper in ice-free, well-mixed regions than in seasonal ice-melting zones. The surface Chl <i>a</i> concentration increased from ice-free to ice-melting regions with elevated sea ice meltwater percentages and drawdown surface nutrient concentrations. The concentrations of surface and depth-integrated Chl <i>a</i> in the upper 150 m reached maxima in the ice-melting region with the highest fraction of sea ice meltwater, illustrating that sea ice melting promoted the occurrence of phytoplankton blooms. The DMS and DMSP concentrations in the vicinity of the ice-melting zone were approximately three times higher than those in the ice-free waters. The observations of this study show that the regions of ice melting in the WSC were a zone of particularly high sea–air fluxes of DMS because sea ice melting processes enhanced the production of biogenic sulfur, which could significantly contribute to the atmospheric budget of DMS in the polar regions.
DOI: 10.6084/m9.figshare.24503992
title: <b>Exploring the causal effects and potential mechanisms affecting LDL-C: a </b><b>multiomics</b><b> Mendelian randomization study</b>

description: This dataset contains data about the causal effects and potential mechanisms affecting plasma LDL-C levels.
DOI: 10.6084/m9.figshare.8245007.v1
title: Additional file 11: of Population structure, demographic history and local adaptation of the grass carp

description: Table S4. List of annotated genes under putative selection identified by outlier tests and Bayenv association tests. (XLSX 20 kb)
DOI: 10.6084/m9.figshare.8245136
title: Additional file 10: of Genome-wide profiling of the alternative splicing provides insights into development in Plutella xylostella

description: Table S7. Genes showing isoforms produce functional variants (XLSX 18 kb)
DOI: 10.6084/m9.figshare.8245265
title: MOESM2 of Zika virus antagonizes interferon response in patients and disrupts RIG-Iâ MAVS interaction through its CARD-TM domains

description: Additional file 2: Table S2. Functional categories of the 69 pre-defined antiviral ISGs in vivo.
DOI: 10.6084/m9.figshare.5099983
title: A Multi-Year Data Set on Aerosol-Cloud-Precipitation-Meteorology Interactions for Marine Stratocumulus Clouds

description: Airborne data of meteorology, aerosol, and cloud properties that have been harmonized from nine field campaigns during May-September periods between 2005 and 2021 off the California coast. A consistent set of instruments were deployed on the Center for Interdisciplinary Remotely-Piloted Aircraft Studies Twin Otter for these flights. A unique aspect of the compiled data set is detailed measurements of aerosol microphysical properties (size distribution, composition, bioaerosol detection, hygroscopicity), cloud drop size distributions across a broad diameter range, different sampling inlets to distinguish between clear air aerosol and droplet residual particles in cloud, and cloud water composition. The data set is suitable for studies associated with
aerosol-cloud-precipitation-meteorology-radiation interactions, especially owing
to sharp aerosol perturbations from ship traffic and biomass burning. The
data set can be used for model initialization and synergistic application with meteorological
models and remote sensing data to improve understanding of the very
interactions that comprise the largest uncertainty in the effect of
anthropogenic emissions on radiative forcing.
DOI: 10.6084/m9.figshare.11391234
title: Insulin resistance is associated with Sfrp5 in obstructive sleep apnea,

description: Abstract Introduction: Obstructive sleep apnea, a common disease, is usually complicated by insulin resistance and type 2 diabetes mellitus. Adipokine is considered to play an important role in the development of insulin resistance and type 2 diabetes mellitus in obstructive sleep apnea. Objective: To assess whether secreted frizzled-related protein 5, a new adipokine, is involved in untreated obstructive sleep apnea patients. Methods: Seventy-six subjects with obstructive sleep apnea and thirty-three control subjects without obstructive sleep apnea were recruited and matched in terms of body mass index and age. The fasting secreted frizzled-related protein 5 plasma concentration was tested using ELISA. In addition, the correlation between secreted frizzled-related protein 5 and the homeostasis model assessment of insulin resistance was obtained. Multiple linear regression analysis models with stepwise selection were performed to determine the independent associations between various factors and secreted frizzled-related protein 5. Results: Plasma secreted frizzled-related protein 5 levels were significantly lower in the obstructive sleep apnea group than in the control group (obstructive sleep apnea group: 28.44 ± 13.25 ng/L; control group: 34.16 ± 13.51 ng/L; p = 0.023). In addition, secreted frizzled-related protein 5 was negatively correlated with homeostasis model assessment of insulin resistance but positively correlated with the mean and lowest oxygen saturation with or without adjusting for age, gender, body mass index, neck circumference, waist circumference and waist-to-hip ratio. The multiple linear regression analysis showed there was an independent negative association between secreted frizzled-related protein 5 and homeostasis model assessment of insulin resistance. Conclusion: Secreted frizzled-related protein 5 was involved in obstructive sleep apnea and the decrease in secreted frizzled-related protein 5 was directly proportional to the severity of obstructive sleep apnea. There was an independent negative correlation between homeostasis model assessment of insulin resistance and secreted frizzled-related protein 5 in the obstructive sleep apnea group. Secreted frizzled-related protein 5 might be a therapeutic target for insulin resistance in obstructive sleep apnea.
DOI: 10.6084/m9.figshare.8245196.v1
title: Additional file 7: of Genome-wide profiling of the alternative splicing provides insights into development in Plutella xylostella

description: Table S4. GO annotations for the 156 genes. Only the terms showing pâ &lt;â 0.05 were listed. (XLSX 18 kb)
DOI: 10.6084/m9.figshare.8245211
title: Additional file 9: of Genome-wide profiling of the alternative splicing provides insights into development in Plutella xylostella

description: Table S6. Gene showing AS event during developmental stages and sexes. (XLS 62 kb)
DOI: 10.6084/m9.figshare.11391234.v1
title: Insulin resistance is associated with Sfrp5 in obstructive sleep apnea,

description: Abstract Introduction: Obstructive sleep apnea, a common disease, is usually complicated by insulin resistance and type 2 diabetes mellitus. Adipokine is considered to play an important role in the development of insulin resistance and type 2 diabetes mellitus in obstructive sleep apnea. Objective: To assess whether secreted frizzled-related protein 5, a new adipokine, is involved in untreated obstructive sleep apnea patients. Methods: Seventy-six subjects with obstructive sleep apnea and thirty-three control subjects without obstructive sleep apnea were recruited and matched in terms of body mass index and age. The fasting secreted frizzled-related protein 5 plasma concentration was tested using ELISA. In addition, the correlation between secreted frizzled-related protein 5 and the homeostasis model assessment of insulin resistance was obtained. Multiple linear regression analysis models with stepwise selection were performed to determine the independent associations between various factors and secreted frizzled-related protein 5. Results: Plasma secreted frizzled-related protein 5 levels were significantly lower in the obstructive sleep apnea group than in the control group (obstructive sleep apnea group: 28.44 ± 13.25 ng/L; control group: 34.16 ± 13.51 ng/L; p = 0.023). In addition, secreted frizzled-related protein 5 was negatively correlated with homeostasis model assessment of insulin resistance but positively correlated with the mean and lowest oxygen saturation with or without adjusting for age, gender, body mass index, neck circumference, waist circumference and waist-to-hip ratio. The multiple linear regression analysis showed there was an independent negative association between secreted frizzled-related protein 5 and homeostasis model assessment of insulin resistance. Conclusion: Secreted frizzled-related protein 5 was involved in obstructive sleep apnea and the decrease in secreted frizzled-related protein 5 was directly proportional to the severity of obstructive sleep apnea. There was an independent negative correlation between homeostasis model assessment of insulin resistance and secreted frizzled-related protein 5 in the obstructive sleep apnea group. Secreted frizzled-related protein 5 might be a therapeutic target for insulin resistance in obstructive sleep apnea.