cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.24948159.v1
title: Structure and elasticity of CaC2O5 suggests carbonate contribution to the seismic anomalies of Earth’s mantle

description: The original dataset calculated in article.
Including density, elastic constant, elastic modulus, semic wave velocity, band gap, band structure, density of states and phonon data. (In one excel and 5 sheet)
DOI: 10.6084/m9.figshare.24948159
title: Structure and elasticity of CaC2O5 suggests carbonate contribution to the seismic anomalies of Earth’s mantle

description: The original dataset calculated in article.
Including density, elastic constant, elastic modulus, semic wave velocity, band gap, band structure, density of states and phonon data. (In one excel and 5 sheet)
DOI: 10.5281/zenodo.10556567
title: Anadon et al. Ecosphere - Jamaica Bay datasets

description: Dataset for:

Anadón JD, O Piñeiro, A Ruhi, J Hornstein, JR Waldman "Decoupled shifts of dominant and rarer fish species as a response to warming and extreme events in a large estuary" Ecosphere, in press. 

Uploaded 23/01/2024

Contains five numbered files:

0: Readme file

1: Raw dataset from the seine sampling in Jamaica Bay, as obtained from the annual seine survey of young striped bass (Morone saxatilis) by the New York State Department of Environmental Conservation (NYSDEC).

2. Standardized-by-sampling-effort dataset, and obtained from the raw dataset (1). See main text and supplementary materials for sampling effort and seines per month and year.

3. Species abundance x year matrix for analyses. This is the matrix used for NMDS (untransformed) and all posterior analyses, and obtained from the standardized dataset (2).

4. Environmental data in Jamaica Bay used in this work (i.e. annual values) as obtained from the NYC Water Quality Survey database, collected by the NYC Department of Environmental Protection. See main text for selection of sampling stations and averaging.

5. Species traits dataset used for analyses, with data obtained from www.Fishbase.org and authors´ knowledge (i.e. migrant/resident).  

All original data employed in this work (i.e. files 1, 4, 5) comes from publicly available datasets. See further information on the main text of the publication and its references.
DOI: 10.5281/zenodo.10142777
title: Longitudinal plasma proteomics reveals biomarkers of alveolar-capillary barrier disruption in critically ill COVID-19 patients

description: This data deposition includes the aptamer assay quality statement and R script for reproducing the results associated with the study.
DOI: 10.5281/zenodo.10142776
title: Longitudinal plasma proteomics reveals biomarkers of alveolar-capillary barrier disruption in critically ill COVID-19 patients

description: This data deposition includes the aptamer assay quality statement and R script for reproducing the results associated with the study: Duijvelaar, E., Gisby, J., Peters, J.E. et al. Longitudinal plasma proteomics reveals biomarkers of alveolar-capillary barrier disruption in critically ill COVID-19 patients. Nat Commun 15, 744 (2024). 

The source data comprises clinical and proteomics data from 318 hospitalised patients with COVID-19 using 6385 unique plasma proteins (Somascan assay) and can be found here: https://doi.org/10.1038/s41467-024-44986-w

 

Qualified researchers can request access to additional pseudonymised data and related study documents by contacting Erik Duijvelaar at e.duijvelaar@amsterdamumc.nl, affiliated with Amsterdam University Medical Centers, Department of Pulmonary Medicine, Amsterdam Cardiovascular Sciences, Amsterdam, Netherlands. Requests will be subject to review, and data will only be shared in accordance with applicable privacy regulations and ethical considerations. Identifying information will be carefully removed to safeguard the confidentiality of study participants. Please allow up to five working days to process and respond to your data access request.
DOI: 10.5281/zenodo.10469692
title: Longitudinal plasma proteomics reveals biomarkers of alveolar-capillary barrier disruption in critically ill COVID-19 patients

description: This data deposition includes the aptamer assay quality statement and R script for reproducing the results associated with the study: Duijvelaar, E., Gisby, J., Peters, J.E. et al. Longitudinal plasma proteomics reveals biomarkers of alveolar-capillary barrier disruption in critically ill COVID-19 patients. Nat Commun 15, 744 (2024). 

The source data comprises clinical and proteomics data from 318 hospitalised patients with COVID-19 using 6385 unique plasma proteins (Somascan assay) and can be found here: https://doi.org/10.1038/s41467-024-44986-w

 

Qualified researchers can request access to additional pseudonymised data and related study documents by contacting Erik Duijvelaar at e.duijvelaar@amsterdamumc.nl, affiliated with Amsterdam University Medical Centers, Department of Pulmonary Medicine, Amsterdam Cardiovascular Sciences, Amsterdam, Netherlands. Requests will be subject to review, and data will only be shared in accordance with applicable privacy regulations and ethical considerations. Identifying information will be carefully removed to safeguard the confidentiality of study participants. Please allow up to five working days to process and respond to your data access request.
DOI: 10.34740/kaggle/dsv/7484425
title: Egypt Gold Prices | Daily Updated
DOI: 10.6084/m9.figshare.25060196
title: 164taxa.fas

description: The whole matrices for plastid, SNPs and SCNs in Corydalis.
DOI: 10.6084/m9.figshare.25060196.v1
title: 164taxa.fas

description: The whole matrices for plastid, SNPs and SCNs in Corydalis.
DOI: 10.5281/zenodo.10259269
title: Regeneration in drained peatland forests literature review

description: The dataset was collected using the methods of systematic literature review. It contains data about the regeneration of peatland forests: which regeneration methods, tree species and soil preparation methods have been studied and how different methods have managed to produce a forest with target density and species composition. This dataset consists of four related sub-datasets:

1) Publication dataset. Contains all the scientific articles (peer-reviewed and "grey literature", including non peer-revieved working reports and thesis) that were found in literature search and fullfilled the pre-defined inclusion criteria. The dataset was used for literature mapping.

2) Experiment dataset. Containt more detailed breakdown of the regeneration methods, tree species, soil preparation methods and site types studied. The dataset was used to asssess knowledge gaps.

3) Regeneration dataset. Regeneration success related to different regeneration and soil preparation methods. The dataset was used to assess which regeneration methods managed to produce seedling stands, which meet the minimum requirements for regeneration defined in the Finnish Forest Act (2014). 

4) Planting survival%. Regeneration success of planting (in % survival of planted seedlings) related to different soil preparation methods. A subset of the regeneration dataset.
DOI: 10.5281/zenodo.10259270
title: Regeneration in drained peatland forests literature review

description: The dataset was collected using the methods of systematic literature review. It contains data about the regeneration of peatland forests: which regeneration methods, tree species and soil preparation methods have been studied and how different methods have managed to produce a forest with target density and species composition. This dataset consists of four related sub-datasets:

1) Publication dataset. Contains all the scientific articles (peer-reviewed and "grey literature", including non peer-revieved working reports and thesis) that were found in literature search and fullfilled the pre-defined inclusion criteria. The dataset was used for literature mapping.

2) Experiment dataset. Containt more detailed breakdown of the regeneration methods, tree species, soil preparation methods and site types studied. The dataset was used to asssess knowledge gaps.

3) Regeneration dataset. Regeneration success related to different regeneration and soil preparation methods. The dataset was used to assess which regeneration methods managed to produce seedling stands, which meet the minimum requirements for regeneration defined in the Finnish Forest Act (2014). 

4) Planting survival%. Regeneration success of planting (in % survival of planted seedlings) related to different soil preparation methods. A subset of the regeneration dataset.
DOI: 10.25345/c5tt4g448
title: MassIVE MSV000093926 - A metabolomics perspective on clorobiocin biosynthesis: discovery of bromobiocin and novel derivatives through LC-MSE-based molecular networking
title: Streptomyces roseochromogenes DS 12.976 was cultivated in DSMZ 65 medium. Clorobiocin and structural analogs were extracted from the supernatant and analyzed via LC-MSE. RAW Files were used to generate Figures 2 and 7.
DOI: 10.5281/zenodo.10570844
title: Recordings of SSR analysis of selected grapevine genotypes as generated by GeneScan software

description: Recordings of SSR analysis of selected grapevine genotypes as generated by GeneScan software. It is original set of data that were used as a base for evaluation of each genotype from point of view of harbored loci of resistance against powdery and downy mildew.
DOI: 10.5281/zenodo.10570845
title: Recordings of SSR analysis of selected grapevine genotypes as generated by GeneScan software

description: Recordings of SSR analysis of selected grapevine genotypes as generated by GeneScan software. It is original set of data that were used as a base for evaluation of each genotype from point of view of harbored loci of resistance against powdery and downy mildew.
DOI: 10.34740/kaggle/dsv/7484442
title: 📒 Meta Kaggle ported to MS SQL SERVER 2022 DB
DOI: 10.5281/zenodo.10297762
title: mzhangrocks/KarakoramFault: Data files for hydrothermal degassing from the Karakoram fault

description: Tables S1–S2 and Data Sets S1–S2 for geochemical study on the hydrothermal degassing from the Karakoram fault
DOI: 10.5281/zenodo.8394768
title: mzhangrocks/KarakoramFault: Data files for hydrothermal degassing from the Karakoram fault

description: Tables S1–S2 and Data Sets S1–S2 for geochemical study on hydrothermal degassing from the Karakoram fault in western Tibetan Plateau
DOI: 10.5281/zenodo.8394769
title: mzhangrocks/KarakoramFault: Data files for hydrothermal degassing from the Karakoram fault

description: Table S1 and Data Set S1 for geochemical study on the hydrothermal degassing from the Karakoram fault
DOI: 10.5281/zenodo.10302438
title: SpectroFood dataset Mushroom

description: This dataset contains hyperspectral data in the visible / shortwave near-infrared spectral domain (400.00 - 998.04 nm) for mushroom. The data set contains cubes of 250 samples with 50 samples in one mat file, wavelength vector and sample labels in Matlab's mat format. The data set is coupled with dry matter content references that are provided here: https://zenodo.org/records/8362947
description: This project has received funding from the European Union's Horizon 2020 research and innovation programme under grand agreement no 862665 ICT AGRI FOOD, through regional funding provided by GSRI (Greece), BMEL (Germany), DAFM (Ireland) and VLAIO (Belgium).
DOI: 10.5281/zenodo.10302437
title: SpectroFood dataset Mushroom

description: This dataset contains hyperspectral data in the visible / shortwave near-infrared spectral domain (400.00 - 998.04 nm) for mushroom. The data set contains cubes of 250 samples with 50 samples in one mat file, wavelength vector and sample labels in Matlab's mat format. The data set is coupled with dry matter content references that are provided here: https://zenodo.org/records/8362947
description: This project has received funding from the European Union's Horizon 2020 research and innovation programme under grand agreement no 862665 ICT AGRI FOOD, through regional funding provided by GSRI (Greece), BMEL (Germany), DAFM (Ireland) and VLAIO (Belgium).
DOI: 10.5281/zenodo.10302425
title: SpectroFood dataset Leek

description: This dataset contains hyperspectral data in the visible / near-infrared spectral domain for leek. The samples were measured with two sensors FX10 and FX17 capturing the ranges 397.66 - 1003.81 nm and 935.61 - 1720.23 nm, respectively. The mat files 1-6 contain data measured with FX10, while files 7 - 12 contain the FX17 data.

The data set contains cubes of 288 samples, wavelength array and sample labels in Matlab's mat format. Each file captures 48 samples.

This data set exceeds the mean spectra presented in the data paper publication in the journal Data-in-Brief. The mean spectra captured 198 spectral measuring points of FX10, while the present data set also captures the last wavelengths of FX10, resulting in 224 measuring points. The mean spectra captured 223 spectral measuring points of FX17, while the present data set also captures the last wavelength of FX17, resulting in 224 measuring points.

The data set is coupled with dry matter content references that are provided here: https://zenodo.org/records/8362947
description: This project has received funding from the European Union's Horizon 2020 research and innovation programme under grand agreement no 862665 ICT AGRI FOOD, through regional funding provided by GSRI (Greece), BMEL (Germany), DAFM (Ireland) and VLAIO (Belgium).
DOI: 10.5281/zenodo.10302426
title: SpectroFood dataset Leek

description: This dataset contains hyperspectral data in the visible / near-infrared spectral domain for leek. The samples were measured with two sensors FX10 and FX17 capturing the ranges 397.66 - 1003.81 nm and 935.61 - 1720.23 nm, respectively. The mat files 1-6 contain data measured with FX10, while files 7 - 12 contain the FX17 data.

The data set contains cubes of 288 samples, wavelength array and sample labels in Matlab's mat format. Each file captures 48 samples.

This data set exceeds the mean spectra presented in the data paper publication in the journal Data-in-Brief. The mean spectra captured 198 spectral measuring points of FX10, while the present data set also captures the last wavelengths of FX10, resulting in 224 measuring points. The mean spectra captured 223 spectral measuring points of FX17, while the present data set also captures the last wavelength of FX17, resulting in 224 measuring points.

The data set is coupled with dry matter content references that are provided here: https://zenodo.org/records/8362947
description: This project has received funding from the European Union's Horizon 2020 research and innovation programme under grand agreement no 862665 ICT AGRI FOOD, through regional funding provided by GSRI (Greece), BMEL (Germany), DAFM (Ireland) and VLAIO (Belgium).
DOI: 10.5281/zenodo.10570888
title: Dataset related to article "Diagnostic performance of microUltrasound at MRI-guided confirmatory biopsy in patients under active surveillance for low-risk prostate cancer "

description: This record contains raw data related to article "Diagnostic performance of microUltrasound at MRI-guided confirmatory biopsy in patients under active surveillance for low-risk prostate cancer"

Abstract



 Background:  Active surveillance (AS) represents a standard of care of low-risk prostate cancer (PCa). However, the identification and monitoring of AS candidates remains challenging. Microultrasound (microUS) is a novel high-resolution imaging modality for transrectal ultrasonography (TRUS). We explored the impact of microUS TRUS and targeted biopsies in mpMRI-guided confirmatory biopsies.

 Methods:  Between October 2017 and September 2021, we prospectively enrolled 100 patients scheduled for MRI-guided confirmatory biopsy at 1 year from diagnosis of ISUP 1 PCa. TRUS was performed using the ExactVu microUS system; PRI-MUS protocol was applied to identify suspicious lesions (i.e., PRIMUS score ≥ 3). All patients received targeted biopsies of any identified microUS and mpMRI lesions and complementary systematic biopsies. The proportion of patients upgraded to clinically significant PCa (defined as ISUP ≥ 2 cancer; csPCa) at confirmatory biopsies was determined, and the diagnostic performance of microUS and mpMRI were compared.

 Results:  Ninety-two patients had a suspicious MRI lesion classified PI-RADS 3, 4, and 5 in respectively 28, 16, and 18 patients. MicroUS identified 82 patients with suspicious lesions, classified as PRI-MUS 3, 4, and 5 in respectively 20, 50, and 12 patients, while 18 individuals had no lesions. Thirty-four patients were upgraded to ISUP ≥ 2 cancer and excluded from AS. MicroUS and mpMRI showed a sensitivity of 94.1% and 100%, and an NPV of 88.9% and 100%, respectively, in detecting ISUP ≥ 2 patients. A microUS-mandated protocol would have avoided confirmatory biopsies in 18 patients with no PRI-MUS ≥ 3 lesions at the cost of missing four upgraded patients.

 Conclusions:  MicroUS and mpMRI represent valuable imaging modalities showing high sensitivity and NPV in detecting csPCa, thus allowing their use for event-triggered confirmatory biopsies in AS patients. MicroUS offers an alternative imaging modality to mpMRI for the identification and real-time targeting of suspicious lesions in AS patients.
DOI: 10.5281/zenodo.10570889
title: Dataset related to article "Diagnostic performance of microUltrasound at MRI-guided confirmatory biopsy in patients under active surveillance for low-risk prostate cancer "

description: This record contains raw data related to article "Diagnostic performance of microUltrasound at MRI-guided confirmatory biopsy in patients under active surveillance for low-risk prostate cancer"

Abstract



 Background:  Active surveillance (AS) represents a standard of care of low-risk prostate cancer (PCa). However, the identification and monitoring of AS candidates remains challenging. Microultrasound (microUS) is a novel high-resolution imaging modality for transrectal ultrasonography (TRUS). We explored the impact of microUS TRUS and targeted biopsies in mpMRI-guided confirmatory biopsies.

 Methods:  Between October 2017 and September 2021, we prospectively enrolled 100 patients scheduled for MRI-guided confirmatory biopsy at 1 year from diagnosis of ISUP 1 PCa. TRUS was performed using the ExactVu microUS system; PRI-MUS protocol was applied to identify suspicious lesions (i.e., PRIMUS score ≥ 3). All patients received targeted biopsies of any identified microUS and mpMRI lesions and complementary systematic biopsies. The proportion of patients upgraded to clinically significant PCa (defined as ISUP ≥ 2 cancer; csPCa) at confirmatory biopsies was determined, and the diagnostic performance of microUS and mpMRI were compared.

 Results:  Ninety-two patients had a suspicious MRI lesion classified PI-RADS 3, 4, and 5 in respectively 28, 16, and 18 patients. MicroUS identified 82 patients with suspicious lesions, classified as PRI-MUS 3, 4, and 5 in respectively 20, 50, and 12 patients, while 18 individuals had no lesions. Thirty-four patients were upgraded to ISUP ≥ 2 cancer and excluded from AS. MicroUS and mpMRI showed a sensitivity of 94.1% and 100%, and an NPV of 88.9% and 100%, respectively, in detecting ISUP ≥ 2 patients. A microUS-mandated protocol would have avoided confirmatory biopsies in 18 patients with no PRI-MUS ≥ 3 lesions at the cost of missing four upgraded patients.

 Conclusions:  MicroUS and mpMRI represent valuable imaging modalities showing high sensitivity and NPV in detecting csPCa, thus allowing their use for event-triggered confirmatory biopsies in AS patients. MicroUS offers an alternative imaging modality to mpMRI for the identification and real-time targeting of suspicious lesions in AS patients.
DOI: 10.5281/zenodo.10302385
title: SpectroFood dataset Broccoli

description: This dataset contains hyperspectral data in the visible / shortwave near-infrared spectral (470 - 900 nm) domain for broccoli. The cubes were downsized to 80 % in OpenCV using bilinear interpolation (https://docs.opencv.org/4.8.0/da/d6e/tutorial_py_geometric_transformations.html). 

The data set contains cubes of 250 samples, wavelength vector and sample labels in Matlab's mat format. In each mat file 10 sample readings are collected, however, labels in the files provide the sample number.

The data set is coupled with dry matter content references that are provided here: https://zenodo.org/records/8362947
description: This project has received funding from the European Union's Horizon 2020 research and innovation programme under grand agreement no 862665 ICT AGRI FOOD, through regional funding provided by GSRI (Greece), BMEL (Germany), DAFM (Ireland) and VLAIO (Belgium).
DOI: 10.5281/zenodo.10302386
title: SpectroFood dataset Broccoli

description: This dataset contains hyperspectral data in the visible / shortwave near-infrared spectral (470 - 900 nm) domain for broccoli. The cubes were downsized to 80 % in OpenCV using bilinear interpolation (https://docs.opencv.org/4.8.0/da/d6e/tutorial_py_geometric_transformations.html). 

The data set contains cubes of 250 samples, wavelength vector and sample labels in Matlab's mat format. In each mat file 10 sample readings are collected, however, labels in the files provide the sample number.

The data set is coupled with dry matter content references that are provided here: https://zenodo.org/records/8362947
description: This project has received funding from the European Union's Horizon 2020 research and innovation programme under grand agreement no 862665 ICT AGRI FOOD, through regional funding provided by GSRI (Greece), BMEL (Germany), DAFM (Ireland) and VLAIO (Belgium).
DOI: 10.5281/zenodo.10301752
title: SpectroFood dataset Apple

description: This dataset contains hyperspectral data in the visible / shortwave near-infrared spectral domain (430 - 990 nm) for apple. The data set contains cubes of 240 samples, wavelength array and sample labels in Matlab's mat format.

The data set is coupled with dry matter content references that are provided here: https://zenodo.org/records/8362947

 

 
description: This project has received funding from the European Union's Horizon 2020 research and innovation programme under grand agreement no 862665 ICT AGRI FOOD, through regional funding provided by GSRI (Greece), BMEL (Germany), DAFM (Ireland) and VLAIO (Belgium).
DOI: 10.5281/zenodo.10301753
title: SpectroFood dataset Apple

description: This dataset contains hyperspectral data in the visible / shortwave near-infrared spectral domain (430 - 990 nm) for apple. The data set contains cubes of 240 samples, wavelength array and sample labels in Matlab's mat format.

The data set is coupled with dry matter content references that are provided here: https://zenodo.org/records/8362947

 

 
description: This project has received funding from the European Union's Horizon 2020 research and innovation programme under grand agreement no 862665 ICT AGRI FOOD, through regional funding provided by GSRI (Greece), BMEL (Germany), DAFM (Ireland) and VLAIO (Belgium).
DOI: 10.5517/ccdc.csd.cc2g02bx
title: CCDC 2264188: Experimental Crystal Structure Determination

description: Related Article: Chong Deng, Xiao-Cheng Xu, Rong Sun, Yi Wang, Bing-Wu Wang, Han-Shi Hu, Wenliang Huang|2024|Organometallics|43|174|doi:10.1021/acs.organomet.3c00481
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.