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

description: A dataset containing 37277 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Asplenium septentrionale (L.) Hoffm.",
 "HasCoordinate is TRUE",
 "HasGeospatialIssue is False",
 "DecimalLatitude is less than 90",
 "DecimalLongitude is less than 180",
 "DecimalLatitude is greater than -90",
 "DecimalLongitude is greater than -180"
 ]
}

 The dataset includes 37277 records from 352 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0428705-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25493/ssbt-a4u
title: Probabilistic cytoarchitectonic map of Area i30 (retrosplenial) (v11.0)

description: This dataset contains the distinct probabilistic cytoarchitectonic map of Area i30 (retrosplenial) in the individual, single subject template of the MNI Colin 27 reference space. As part of the Julich-Brain cytoarchitectonic atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. The results of the cytoarchitectonic analysis were then mapped to the reference space, where each voxel was assigned the probability to belong to Area i30 (retrosplenial). The probability map of Area i30 (retrosplenial) is provided in NifTi format for each hemisphere in the reference space. The Julich-Brain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and updated probability estimates for new brain structures may in some cases lead to measurable but negligible deviations of existing probability maps, as compared to earlier released datasets. 


The most probable delineation of Area i30 (retrosplenial) derived from the calculation of a maximum probability map of all currently released Julich-Brain brain structures can be found here:
Amunts et al. (2020) [Data set, v2.2] [DOI: 10.25493/TAKY-64D](https://doi.org/10.25493/TAKY-64D)
DOI: 10.25493/8sg7-zcg
title: Probabilistic cytoarchitectonic map of Area i29 (retrosplenial) (v11.0)

description: This dataset contains the distinct probabilistic cytoarchitectonic map of Area i29 (retrosplenial) in the individual, single subject template of the MNI Colin 27 reference space. As part of the Julich-Brain cytoarchitectonic atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. The results of the cytoarchitectonic analysis were then mapped to the reference space, where each voxel was assigned the probability to belong to Area i29 (retrosplenial). The probability map of Area i29 (retrosplenial) is provided in NifTi format for each hemisphere in the reference space. The Julich-Brain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and updated probability estimates for new brain structures may in some cases lead to measurable but negligible deviations of existing probability maps, as compared to earlier released datasets. 


The most probable delineation of Area i29 (retrosplenial) derived from the calculation of a maximum probability map of all currently released Julich-Brain brain structures can be found here:
Amunts et al. (2020) [Data set, v2.2] [DOI: 10.25493/TAKY-64D](https://doi.org/10.25493/TAKY-64D)
DOI: 10.25493/ycez-0h1
title: Probabilistic cytoarchitectonic map of Area a30 (retrosplenial) (v11.0)

description: This dataset contains the distinct probabilistic cytoarchitectonic map of Area a30 (retrosplenial) in the individual, single subject template of the MNI Colin 27 reference space. As part of the Julich-Brain cytoarchitectonic atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. The results of the cytoarchitectonic analysis were then mapped to the reference space, where each voxel was assigned the probability to belong to Area a30 (retrosplenial). The probability map of Area a30 (retrosplenial) is provided in NifTi format for each hemisphere in the reference space. The Julich-Brain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and updated probability estimates for new brain structures may in some cases lead to measurable but negligible deviations of existing probability maps, as compared to earlier released datasets. 


The most probable delineation of Area a30 (retrosplenial) derived from the calculation of a maximum probability map of all currently released Julich-Brain brain structures can be found here:
Amunts et al. (2020) [Data set, v2.2] [DOI: 10.25493/TAKY-64D](https://doi.org/10.25493/TAKY-64D)
DOI: 10.25493/e9fb-d2r
title: Probabilistic cytoarchitectonic map of Area a29 (retrosplenial) (v11.0)

description: This dataset contains the distinct probabilistic cytoarchitectonic map of Area a29 (retrosplenial) in the individual, single subject template of the MNI Colin 27 reference space. As part of the Julich-Brain cytoarchitectonic atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. The results of the cytoarchitectonic analysis were then mapped to the reference space, where each voxel was assigned the probability to belong to Area a29 (retrosplenial). The probability map of Area a29 (retrosplenial) is provided in NifTi format for each hemisphere in the reference space. The Julich-Brain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and updated probability estimates for new brain structures may in some cases lead to measurable but negligible deviations of existing probability maps, as compared to earlier released datasets. 


The most probable delineation of Area a29 (retrosplenial) derived from the calculation of a maximum probability map of all currently released Julich-Brain brain structures can be found here:
Amunts et al. (2020) [Data set, v2.2] [DOI: 10.25493/TAKY-64D](https://doi.org/10.25493/TAKY-64D)
DOI: 10.25493/xwg2-s8x
title: Virtual Epileptic Patient Cohort (v1.0)

description: The virtual epileptic patient cohort is derived from a dataset of 30 drug-resistant epilepsy patients from La Timone hospital in Marseille, France. These patients have undergone invasive SEEG electrode implantation to record seizure activity. This dataset contains simulated SEEG recordings of spontaneous seizures, stimulation-induced seizures and interictal activity with spikes. In addition, patient-specific information including whole-brain connectivity, reconstructed SEEG electrode implantation and epileptogenic zone hypothesis are provided. The patient’s epileptogenic zone (EZ) hypothesis is used to parametrize their whole-brain model used for simulating epileptic brain activity. The purpose of this virtual cohort containing ground truth epileptogenic zone information is for facilitating evaluation of diagnostic data analysis methods in clinical epilepsy research. 
We used The Virtual Brain platform to implement personalized brain models by integrating T1-MRI, diffusion-weighted MRI and CT-scans. For each brain model, the EZ was set using the clinical hypothesis in one scenario and the Virtual Epileptic Patient pipeline’s estimation of EZ in another scenario. We then ran simulations and validated the synthetic SEEG data against the empirical SEEG recordings by comparing for each electrode the seizure’s spatial and temporal propagation, the stimulation response and the interictal spike distribution. This dataset is BIDS-iEEG compatible, and the code used to generate it is available here: [https://github.com/BalanceKey/virtual_epilepsy_patient_cohort](https://github.com/BalanceKey/virtual_epilepsy_patient_cohort).
DOI: 10.15468/99y2vt
title: Angiospermas marinas (Alismatales, Tracheophyta) de Cuba

description: Lista de especies de angiospermas marinas (Orden Alismatales, División Tracheophyta) registradas en Cuba
DOI: 10.6084/m9.figshare.27187170
title: Supplementary data

description: Cellulose is a carbon source widespread in nature. However, it is a difficult task for any organism to get carbon atoms from the cellulose as it has a highly complex structure. Only a few taxonomic groups are known to decompose cellulose. They do it by producing cellulases, the various enzymes which break beta-glycosidic bonds in the cellulose.
DOI: 10.6084/m9.figshare.27187170.v2
title: Supplementary data

description: Cellulose is a carbon source widespread in nature. However, it is a difficult task for any organism to get carbon atoms from the cellulose as it has a highly complex structure. Only a few taxonomic groups are known to decompose cellulose. They do it by producing cellulases, the various enzymes which break beta-glycosidic bonds in the cellulose.
DOI: 10.6084/m9.figshare.27187170.v1
title: clusters_136

description: Cellulose is a carbon source widespread in nature. However, it is a difficult task for any organism to get carbon atoms from the cellulose as it has a highly complex structure. Only a few taxonomic groups are known to decompose cellulose. They do it by producing cellulases, the various enzymes which break beta-glycosidic bonds in the cellulose.
DOI: 10.6084/m9.figshare.27176145
title: Dataset Supporting the Bibliometric and Altimetric Review of Artificial Intelligence Use in Cariology

description: This dataset contains bibliometric and altimetric data from 175 articles on the use of Artificial Intelligence (AI) in cariology. It includes article titles, authors, study designs, diagnostic methods, citation counts, journal impact factors, publication years, and author affiliations. The data were collected on February 12, 2024, from the Web of Science Core Collection and Dimensions databases. Additionally, the dataset includes the flowchart following the BIBLIO methodology and the corresponding checklist, providing a detailed overview of the data collection and analysis process.
DOI: 10.6084/m9.figshare.27176145.v2
title: Dataset Supporting the Bibliometric and Altimetric Review of Artificial Intelligence Use in Cariology

description: This dataset contains bibliometric and altimetric data from 175 articles on the use of Artificial Intelligence (AI) in cariology. It includes article titles, authors, study designs, diagnostic methods, citation counts, journal impact factors, publication years, and author affiliations. The data were collected on February 12, 2024, from the Web of Science Core Collection and Dimensions databases.
DOI: 10.15468/dl.evf5qb
title: Occurrence Download

description: A dataset containing 1534329 species occurrences available in GBIF matching the query:
(Query is too complex. Can be viewed on the landing page)

 The dataset includes 1534329 records from 1598 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005379-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.y4xw8k
title: Occurrence Download

description: A dataset containing 39705956 species occurrences available in GBIF matching the query:
(Query is too complex. Can be viewed on the landing page)

 The dataset includes 39705956 records from 7694 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005378-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7ufb56
title: Occurrence Download

description: A dataset containing 213 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Wollemia nobilis W.G.Jones et al."
 ]
}

 The dataset includes 213 records from 40 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004619-200127171203522/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dgv6ph
title: Occurrence Download

description: A dataset containing 10 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((94.55456 22.72183,133.44544 22.72183,133.44544 38.27817,94.55456 38.27817,94.55456 22.72183))",
 "HasCoordinate is true",
 "TaxonKey is Schistodesmus lampreyanus (Baird & H.Adams, 1867)",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 10 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0064542-200221144449610/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.krsd6m
title: Occurrence Download

description: A dataset containing 24105 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Cypripedium calceolus L."
 ]
}

 The dataset includes 24105 records from 238 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0038496-191105090559680/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.q0cnld
title: Occurrence Download

description: A dataset containing 49098 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Lepus europaeus Pallas, 1778"
 ]
}

 The dataset includes 49098 records from 307 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0064544-160910150852091/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wp5kzu
title: Occurrence Download

description: A dataset containing 39 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is South America",
 "Country is Ecuador",
 "TaxonKey is Lachemilla jamesonii (L.M.Perry) Rothm."
 ]
}

 The dataset includes 39 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0048199-191105090559680/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9ywjxt
title: Occurrence Download

description: A dataset containing 980 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Geometry POLYGON((-12.87618 37.67851,-10.11881 34.60457,10.0633 37.86402,26.94555 33.63837,26.31312 40.05748,29.15447 41.18496,46.68074 45.40605,48.3398 56.78268,44.23852 66.94752,23.2975 73.36699,-11.31128 61.71139,-12.87618 37.67851))",
 "TaxonKey is Trisetum flavescens (L.) P.Beauv.",
 "Year 1941-2020"
 ]
}

 The dataset includes 980 records from 85 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0064555-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2vjcqj
title: Occurrence Download

description: A dataset containing 53 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Argentina",
 "Year 1950-2020",
 "TaxonKey is Pappophorum pappiferum (Lam.) Kuntze"
 ]
}

 The dataset includes 53 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0080906-200221144449610/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.lu8dhf
title: Occurrence Download

description: A dataset containing 71837 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Colombia",
 {
 "or" : [
 "Month is July",
 "Month is August",
 "Month is September"
 ]
 },
 "Year is 2018",
 "Geometry POLYGON((-78 3,-75 3,-75 5,-78 5,-78 3))",
 "HasCoordinate is true",
 "TaxonKey is Aves",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 71837 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001318-200221144449610/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.erqttm
title: Occurrence Download

description: A dataset containing 260 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "Year 1960-2020",
 "TaxonKey is Mimosa luisana Brandegee"
 ]
}

 The dataset includes 260 records from 21 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010493-200221144449610/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.axi4bh
title: Occurrence Download

description: A dataset containing 8 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Trichocereus chalaensis Rauh & Backeb."
 ]
}

 The dataset includes 8 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006290-180131172636756/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.feh8bt
title: Occurrence Download

description: A dataset listing the 3395262 species recorded in GBIF matching the query:
{
 "OccurrenceStatus" : [
 "is Present"
 ]
}

 The dataset's 3395262 records were derived from 39398 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069464-210914110416597/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.30100862.v1
title: Graded nomograms based on perioperative parameters for predicting New-Onset severe acute kidney injury following liver transplantation in patients with normal preoperative renal function: the SALT scale

description: This study aimed to develop a predictive model and construct a graded nomogram to estimate the risk of severe acute kidney injury (AKI) in patients without preexisting kidney dysfunction undergoing liver transplantation (LT). Patients undergoing LT between January 2022 and June 2023 were prospectively screened. Severe AKI was defined as Kidney Disease: Improving Global Outcomes stage 3. Using the least absolute shrinkage and selection operator (LASSO) analytics, we identified the preoperative, intraoperative, and postoperative factors associated with severe AKI. Machine learning were employed to develop predictive models, and the most suitable model was selected for further analysis. The Shapley Additive Explanation was utilized to construct graded nomograms, forming the Severe AKI post-LT (SALT) scale. Among the 405 patients, 44 had AKI stage 3 (severe AKI). The Model for End-Stage Liver Disease (MELD) score, estimated blood loss, alanine aminotransferase, D-dimer, and thromboelastography reaction time within 24 h post-LT were identified as risk factors. The logistic regression model achieved the highest area under the receiver operating characteristic curve (AUROC) of 0.885. The graded SALT scale, based on the logistic regression model, achieved AUROCs of 0.751, 0.826, and 0.894. The AUROCs for the testing cohort is 0.791. This preliminary study provides a SALT scale for assessing the occurrence of severe AKI after LT. Although additional data are needed to externally validate our model before applying it to patient care, our findings suggest that the SALT scale may be a feasible bedside tool for assessing the risk of AKI after LT.
DOI: 10.6084/m9.figshare.30100862
title: Graded nomograms based on perioperative parameters for predicting New-Onset severe acute kidney injury following liver transplantation in patients with normal preoperative renal function: the SALT scale

description: This study aimed to develop a predictive model and construct a graded nomogram to estimate the risk of severe acute kidney injury (AKI) in patients without preexisting kidney dysfunction undergoing liver transplantation (LT). Patients undergoing LT between January 2022 and June 2023 were prospectively screened. Severe AKI was defined as Kidney Disease: Improving Global Outcomes stage 3. Using the least absolute shrinkage and selection operator (LASSO) analytics, we identified the preoperative, intraoperative, and postoperative factors associated with severe AKI. Machine learning were employed to develop predictive models, and the most suitable model was selected for further analysis. The Shapley Additive Explanation was utilized to construct graded nomograms, forming the Severe AKI post-LT (SALT) scale. Among the 405 patients, 44 had AKI stage 3 (severe AKI). The Model for End-Stage Liver Disease (MELD) score, estimated blood loss, alanine aminotransferase, D-dimer, and thromboelastography reaction time within 24 h post-LT were identified as risk factors. The logistic regression model achieved the highest area under the receiver operating characteristic curve (AUROC) of 0.885. The graded SALT scale, based on the logistic regression model, achieved AUROCs of 0.751, 0.826, and 0.894. The AUROCs for the testing cohort is 0.791. This preliminary study provides a SALT scale for assessing the occurrence of severe AKI after LT. Although additional data are needed to externally validate our model before applying it to patient care, our findings suggest that the SALT scale may be a feasible bedside tool for assessing the risk of AKI after LT.
DOI: 10.15468/dl.zvu6d3
title: Occurrence Download

description: A dataset containing 102924 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Nymphaea alba"
 ]
}

 The dataset includes 102924 records from 900 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0051981-250827131500795/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.30100951
title: Additional file 2 of High-resolution time-series transcriptomic and metabolomic profiling reveals the regulatory mechanism underlying salt tolerance in maize

description: Additional file 2: Table S1. Phenotype divergence between HLZY and JI853 under salt. Table S2. Time-series expression profiles. Table S3. SSET genes identified by likelihood ratio test in HLZY and JI853. Table S4. DEAT genes identified by Wald-test in HLZY and JI853. Table S5. GO enrichment of DEAT genes at each time point in HLZY and JI853. Table S6. Ratio cluster of 5331 SSET genes. Table S7. Well-known stress responsive genes in Cluster 4. Table S8. Normalized intensities of 310 metabolites. Table S9. Gene-metabolite network constructed by LASSO-based decision algorithm. Table S10. RNA sequencing of gln2 mutants and WT plants under CK and salt conditions. Table S11. Metabolic change in gln2 mutant and WT plants under CK and salt conditions. Table S12. Primers in this study.