cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.24287749.v1
title: Supplementary Material for: Comprehensive analysis of the relationship between cuproptosis-related gene GCSH and prognosis, tumor microenvironment infiltration, and therapy response in endometrial cancer

description: Background: Cuproptosis, a novel form of cell death regulated by protein lipoylation and implicated in mitochondrial metabolism. However, the impact of the cuproptosis-related gene γ-glutamylcysteine synthetase (GCSH) on endometrial cancer (EC) prognosis, tumor immune microenvironment, and therapeutic response remains to be further researched. Methods: The differential expression of GCSH between endometrial cancer and normal tissues was analyzed using multiple public databases. Additionally, cancer and adjacent tissues were prospectively collected from 17 EC patients, and immunohistochemical analysis was performed to further investigate GCSH expression differences. The relationship between GCSH and the prognosis and clinicopathological characteristics of EC patients was evaluated, and a nomogram was constructed to predict patient survival based on GCSH expression. Then, Gene set variation analysis (GSVA) was utilized to explore the potential biological functions of GCSH in EC. The impact of GCSH on the tumor microenvironment (TME) was estimated. Finally, the effect of GCSH on the response to immunotherapy and chemotherapeutic drugs in EC was investigated. Results: The expression of GCSH was significantly upregulated in EC. High GCSH expression was associated with poor prognosis in EC patients. Enrichment analysis showed that high GCSH was associated with immune suppression. Furthermore, high GCSH was found to be associated with a non-inflamed TME, leading to decreased infiltration levels of immune cells. Finally, it was observed that patients with high GCSH were insensitive to both immunotherapy and chemotherapeutic drugs. Conclusion: This study revealed the role of GCSH in TME, response to therapy, and clinical prognosis in EC, which provided novel insights for the therapeutic application in EC.
DOI: 10.5281/zenodo.8429709
title: Ibai Rico JIRP 2023

description: Ibai Rico JIRP 2023
DOI: 10.5281/zenodo.8429707
title: Ibai Rico JIRP 2023

description: Ibai Rico JIRP 2023
DOI: 10.5281/zenodo.8429841
title: Evaluation of COVID-19 antigen rapid diagnostic tests for self-testing in Lesotho and Zambia - Lesotho data

description: Dataset with Lesotho data belonging to the publication: Evaluation of COVID-19 antigen rapid diagnostic tests for self-testing in Lesotho and Zambia
DOI: 10.5281/zenodo.8429840
title: Evaluation of COVID-19 antigen rapid diagnostic tests for self-testing in Lesotho and Zambia - Lesotho data

description: Dataset with Lesotho data belonging to the publication: Evaluation of COVID-19 antigen rapid diagnostic tests for self-testing in Lesotho and Zambia
DOI: 10.14272/ixzqvisqaobmip-uhfffaoysa-n/chmo0001146
title: 1H--13C heteronuclear single quantum coherence (1H-13C HSQC) ()
title: InChI=1S/C20H20O3/c1-12(2)16-9-8-13(3)17-11-15(20(22)23-19(16)17)10-14-6-4-5-7-18(14)21/h4-9,11-12,21H,10H2,1-3H3

description: dataset for 1H--13C heteronuclear single quantum coherence (1H-13C HSQC)
DOI: 10.14272/ixzqvisqaobmip-uhfffaoysa-n/chmo0000630
title: infrared absorption spectroscopy (IR) ()
title: InChI=1S/C20H20O3/c1-12(2)16-9-8-13(3)17-11-15(20(22)23-19(16)17)10-14-6-4-5-7-18(14)21/h4-9,11-12,21H,10H2,1-3H3

description: dataset for infrared absorption spectroscopy (IR) IR (ATR, ṽ) = 3360 (w), 3046 (w), 2962 (m), 2927 (w), 2867 (w), 1706 (m), 1677 (vs), 1633 (m), 1615 (w), 1598 (vs), 1584 (vs), 1487 (vs), 1458 (m), 1446 (m), 1381 (w), 1363 (w), 1350 (w), 1323 (m), 1306 (w), 1268 (m), 1262 (m), 1248 (m), 1211 (vs), 1166 (vs), 1149 (vs), 1095 (m), 1075 (vs), 1048 (vs), 1038 (vs), 997 (s), 970 (m), 946 (s), 898 (m), 880 (w), 866 (w), 846 (w), 833 (s), 782 (m), 771 (s), 752 (vs), 721 (m), 683 (m), 669 (s), 625 (m), 611 (s), 588 (s), 557 (m), 551 (m), 534 (m), 526 (m), 490 (s), 479 (s), 446 (s), 419 (m), 385 (m) cm–1.
DOI: 10.14272/ixzqvisqaobmip-uhfffaoysa-n/chmo0001148
title: 1H--13C heteronuclear multiple bond coherence (13C-1H HMBC) ()
title: InChI=1S/C20H20O3/c1-12(2)16-9-8-13(3)17-11-15(20(22)23-19(16)17)10-14-6-4-5-7-18(14)21/h4-9,11-12,21H,10H2,1-3H3

description: dataset for 1H--13C heteronuclear multiple bond coherence (13C-1H HMBC)
DOI: 10.14272/ixzqvisqaobmip-uhfffaoysa-n/chmo0001150
title: 1H--1H correlation spectroscopy (1H-1H COSY) ()
title: InChI=1S/C20H20O3/c1-12(2)16-9-8-13(3)17-11-15(20(22)23-19(16)17)10-14-6-4-5-7-18(14)21/h4-9,11-12,21H,10H2,1-3H3

description: dataset for 1H--1H correlation spectroscopy (1H-1H COSY)
DOI: 10.14272/ixzqvisqaobmip-uhfffaoysa-n/chmo0000596.1
title: distortionless enhancement with polarization transfer (DEPT) ()
title: InChI=1S/C20H20O3/c1-12(2)16-9-8-13(3)17-11-15(20(22)23-19(16)17)10-14-6-4-5-7-18(14)21/h4-9,11-12,21H,10H2,1-3H3

description: dataset for distortionless enhancement with polarization transfer (DEPT) 13C NMR (100 MHz, Chloroform-d [77.0 ppm], ppm) δ = 138.2, 130.5, 128.7, 128.3, 126.0, 120.9, 118.3, 32.5 (–), 26.4, 22.7, 18.2.
DOI: 10.14272/ixzqvisqaobmip-uhfffaoysa-n/chmo0001075
title: elemental analysis (EA) ()
title: InChI=1S/C20H20O3/c1-12(2)16-9-8-13(3)17-11-15(20(22)23-19(16)17)10-14-6-4-5-7-18(14)21/h4-9,11-12,21H,10H2,1-3H3

description: dataset for elemental analysis (EA)
DOI: 10.14272/ixzqvisqaobmip-uhfffaoysa-n/chmo0000593
title: 1H nuclear magnetic resonance spectroscopy (1H NMR) ()
title: InChI=1S/C20H20O3/c1-12(2)16-9-8-13(3)17-11-15(20(22)23-19(16)17)10-14-6-4-5-7-18(14)21/h4-9,11-12,21H,10H2,1-3H3

description: dataset for 1H nuclear magnetic resonance spectroscopy (1H NMR) 1H NMR (400 MHz, Chloroform-d [7.27 ppm], ppm) δ = 8.16 (s, 1H), 7.96 (s, 1H), 7.33 (d, J = 7.8 Hz, 1H), 7.23 (dd, J = 1.6 Hz, J = 7.5 Hz, 1H), 7.19–7.15 (m, 1H), 7.10 (d, J = 7.8 Hz, 1H), 6.98 (dd, J = 1.2 Hz, J = 8.1 Hz, 1H), 6.89 (dt, J = 1.2 Hz, J = 7.3 Hz, 1H), 3.90 (s, 2H), 3.56 (quint, J = 7.1 Hz, 1H), 2.53 (s, 3H), 1.26 (d, J = 6.8 Hz, 6H).
DOI: 10.14272/ixzqvisqaobmip-uhfffaoysa-n/chmo0000596
title: distortionless enhancement with polarization transfer (DEPT) ()
title: InChI=1S/C20H20O3/c1-12(2)16-9-8-13(3)17-11-15(20(22)23-19(16)17)10-14-6-4-5-7-18(14)21/h4-9,11-12,21H,10H2,1-3H3

description: dataset for distortionless enhancement with polarization transfer (DEPT) 13C NMR (100 MHz, Chloroform-d [77.0 ppm], ppm) δ = 138.2, 130.5, 128.7, 128.3, 126.0, 120.9, 118.3, 26.4.
DOI: 10.14272/ixzqvisqaobmip-uhfffaoysa-n/chmo0000595
title: 13C nuclear magnetic resonance spectroscopy (13C NMR) ()
title: InChI=1S/C20H20O3/c1-12(2)16-9-8-13(3)17-11-15(20(22)23-19(16)17)10-14-6-4-5-7-18(14)21/h4-9,11-12,21H,10H2,1-3H3

description: dataset for 13C nuclear magnetic resonance spectroscopy (13C NMR) 13C NMR (100 MHz, Chloroform-d [77.0 ppm], ppm) δ = 164.5 (C=O), 154.7 (COH), 150.7 (Cq), 138.1 (CH), 134.3 (Cq), 132.9 (Cq), 130.4 (CH), 128.7 (CH), 128.2 (CH), 127.1 (Cq), 126.0 (CH), 125.0 (Cq), 120.9 (CH), 118.3 (CH), 118.1 (Cq), 32.4 (CH2), 26.4 (CH(CH3)2), 22.6 (2C, CH(CH3)2), 18.2 (CH3).
DOI: 10.14272/ixzqvisqaobmip-uhfffaoysa-n.1
title: 3-(2-hydroxybenzyl)-8-isopropyl-5-methyl-2H-chromen-2-one
title: InChI=1S/C20H20O3/c1-12(2)16-9-8-13(3)17-11-15(20(22)23-19(16)17)10-14-6-4-5-7-18(14)21/h4-9,11-12,21H,10H2,1-3H3

description: This is a physical chemical entity[CHEBI_24431] associated with a molecule[CHEBI_25367]. The molecule[CHEBI_25367] can be described by the following structural desciptors[cheminf_000085]: InChI descriptor[cheminf_000113]: InChI=1S/C20H20O3/c1-12(2)16-9-8-13(3)17-11-15(20(22)23-19(16)17)10-14-6-4-5-7-18(14)21/h4-9,11-12,21H,10H2,1-3H3, and canonical SMILES descriptor[cheminf_000007]: Oc1ccccc1Cc1cc2c(C)ccc(c2oc1=O)C(C)C, and by the IUPAC name[cheminf_000107]: . The physical chemical entity[CHEBI_24431] has a component solvent[CHEBI_46787] which is described by the canonical SMILES descriptor[cheminf_000007]: The physical chemical entity[CHEBI_24431] has the following Sample ID as registered in the research data repository chemotion (www.chemotion-repository.net, https://doi.org/10.25504/FAIRsharing.iagXcR): CRS-21676 The physical chemical entity[CHEBI_24431] can be described by the physical descriptors [CHEMINF_000025]: Melting point descriptor[CHEMINF_000256]: 186.2 - 189.4 (°C) Boiling point descriptor[CHEMINF_000257]: Refractive index descriptor[CHEMINF_000253]: The physical chemical entity[CHEBI_24431] can be further described by the following assays[OBI:0000070][CHMO:0001133]: CHMO:0000593 | 1H nuclear magnetic resonance spectroscopy (1H NMR) CHMO:0000595 | 13C nuclear magnetic resonance spectroscopy (13C NMR) CHMO:0000596 | distortionless enhancement with polarization transfer (DEPT) CHMO:0000596 | distortionless enhancement with polarization transfer (DEPT) CHMO:0001150 | 1H--1H correlation spectroscopy (1H-1H COSY) CHMO:0001146 | 1H--13C heteronuclear single quantum coherence (1H-13C HSQC) CHMO:0001148 | 1H--13C heteronuclear multiple bond coherence (13C-1H HMBC) CHMO:0000630 | infrared absorption spectroscopy (IR) CHMO:0001075 | elemental analysis (EA) CHMO:0000480 | electron ionisation mass spectrometry (EI-MS) The physical chemical entity[CHEBI_24431] was deposited to the Molecule Archive of the Karlsruhe Insitute of Technology (KIT) with the following Sample ID: Used ontologies: CHEBI - Chemical Entities of Biological Interest CHEMINF - chemical information ontology (information entities about chemical entities) CHMO - Chemical Methods Ontology OBI - Ontology for Biomedical Investigations
DOI: 10.14272/ixzqvisqaobmip-uhfffaoysa-n/chmo0000480
title: electron ionisation mass spectrometry (EI-MS) ()
title: InChI=1S/C20H20O3/c1-12(2)16-9-8-13(3)17-11-15(20(22)23-19(16)17)10-14-6-4-5-7-18(14)21/h4-9,11-12,21H,10H2,1-3H3

description: dataset for electron ionisation mass spectrometry (EI-MS) MS (EI, 70 eV, 110 °C), m/z (%): 309 (23), 308 (100) [M]+, 293 (41), 280 (15), 199 (16), 187 (21), 159 (11), 107 (32). HRMS–EI (C20H20O3) (m/z): [M]+ calcd for 308.1407; found 308.1406.
DOI: 10.5285/ac452027-8bae-424c-94cc-3a6f5a88c842
title: Property Subsidence Assessment dataset 2023

description: The BGS Property Subsidence Assessment (PSA) dataset provides insurers and homeowners access to a better understanding of the shrink-swell hazard at both the individual property and/or postcode level for England and Wales. It builds upon the GeoSure shrink-swell data by mapping the hazard to the individual building polygon and considering the other susceptibility factors of building type, foundation depth, and drainage and tree proximity.
The user receives GIS building polygons with an overall susceptibility to subsidence score between 1-100. Scores are also classified from non-plastic to very high. Each building polygon is also scored from 1-10 for each subsidence factor (geology, foundation, drainage, building type, building storey and tree proximity).
Postcode data is also available as a table showing the ‘average’ PSA score for all buildings within the postcode.
The identification of shrink-swell related subsidence prone areas, alongside the inclusion of potential sources to exacerbate this phenomenon, can better inform insurers and homeowners and form the basis to make decisions concerning prevention and remediation. The product enhances geological information obtained from GIP and GeoSure via the inclusion of the crucial shrink-swell susceptibility factors (proximity to trees and foundation depth). This therefore allows the derivation of a risk element for the housing stock at Building level, which is then generalised to Postcode level.
DOI: 10.57841/casdc.0002751
title: 碳化硅改性核壳Al2O3钴基催化剂的费托反应性能
DOI: 10.6084/m9.figshare.24287857
title: Porosity and pore size distribution（汇总）.xlsx

description: main data for “<b>Effects of freeze‒thaw cycles and the prefreezing water content on the soil pore size distribution</b><b>”</b>
DOI: 10.57841/casdc.0002752
title: 简易制备的高导热钴基催化剂影响数据集
DOI: 10.57841/casdc.0002753
title: 钴锆界面对费托反应的影响
DOI: 10.57841/casdc.0002754
title: 费托反应中的传质行为
DOI: 10.57841/casdc.0002755
title: 费托反应中的工艺条件影响
DOI: 10.5281/zenodo.7068184
title: Raw diffraction images of [NiFe]-hydrogenase maturation factor HypD from Aquifex aeolicus (C360S mutant)

description: HypD is one of the maturation factors of [NiFe]-hydrogenase and can form a complex with other maturation factors (Muraki <em>et al.</em>, 2019). We used datasets to investigate the protocol of detecting polymorphs using Hierarchical clustering (Acta D., submitted). All diffraction datasets were collected at BL45XU, SPring-8, using an automated data collection system <em>ZOO</em>. From six crystals, datasets were collected from each one using a continuous helical scan scheme for 360º oscillation with the following experimental parameters; Beam size: 20 µm × 20 µm, Wavelength: 1.0000 Å, Total dose/crystal: 10 MGy, Detector: EIGER X 9M (DECTRIS Co. Ltd.). All crystals belonged to space group P212121 with unit cell parameters roughly corresponding to a=60.0, b=62.6, c=97.6 Å.
DOI: 10.5281/zenodo.7068185
title: Raw diffraction images of [NiFe]-hydrogenase maturation factor HypD from Aquifex aeolicus (C360S mutant)

description: HypD is one of the maturation factors of [NiFe]-hydrogenase and can form a complex with other maturation factors (Muraki <em>et al.</em>, 2019). We used datasets to investigate the protocol of detecting polymorphs using Hierarchical clustering (Acta D., submitted). All diffraction datasets were collected at BL45XU, SPring-8, using an automated data collection system <em>ZOO</em>. From six crystals, datasets were collected from each one using a continuous helical scan scheme for 360º oscillation with the following experimental parameters; Beam size: 20 µm × 20 µm, Wavelength: 1.0000 Å, Total dose/crystal: 10 MGy, Detector: EIGER X 9M (DECTRIS Co. Ltd.). All crystals belonged to space group P212121 with unit cell parameters roughly corresponding to a=60.0, b=62.6, c=97.6 Å.
DOI: 10.5281/zenodo.8413987
title: Quality correction factors as a function of radiation field size

description: This data set contains the quality correction factors as a function of radiation field size from Tables 1-5 of Cervantes et al. (2021). The quality correction factor is defined in Cervantes et al. (2021) as the ratio of calibration coefficients in presence and in absence of the magnetic field. Here the definition of the quality correction factor is the same as the magnetic field correction factor defined by others.
description: Grant number: EMPIR 19NRM01 MRgRT-DOS
description: {"references": ["https://doi.org/10.1088/1361-6560/ac3344"]}
DOI: 10.5281/zenodo.8413986
title: Quality correction factors as a function of radiation field size

description: This data set contains the quality correction factors as a function of radiation field size from Tables 1-5 of Cervantes et al. (2021). The quality correction factor is defined in Cervantes et al. (2021) as the ratio of calibration coefficients in presence and in absence of the magnetic field. Here the definition of the quality correction factor is the same as the magnetic field correction factor defined by others.
description: Grant number: EMPIR 19NRM01 MRgRT-DOS
description: {"references": ["https://doi.org/10.1088/1361-6560/ac3344"]}
DOI: 10.5281/zenodo.5551112
title: DeepBacs – Escherichia coli nucleoid denoising dataset and CARE model

description: Training and test images of H-NS-mScarlet-I expressing <em>E. coli </em>cells for image denoising, as well as a trained CARE model. Additional information can be found on our github wiki. The example images show confocal images of labelled <em>E. coli</em> nucleoids at low and high SNR. <strong>Training and test dataset</strong> <strong>Data type</strong>: Paired microscopy images (fluorescence) <strong>Microscopy data type</strong>: Confocal fluorescence images <strong>Microscope</strong>: Leica SP8 confocal microscope with a 1.40 NA 63x oil immersion objective <strong>Cell type</strong>: <em>E. coli</em> strain CS01 expressing H-NS-mScarlet-I fusion protein (H-NS-mScarlet-I) in NO34 parental strain (MreB-sfGFPsw, kindly provided by Zemer Gitai) <strong>File format</strong>: .tif (16-bit) <strong>Image size</strong>: 512 x 512 px<sup>2</sup> (Pixel size: 45 nm) <strong>CARE model</strong>: The CARE 2D model was generated using the ZeroCostDL4Mic platform (Chamier et al., 2021). It was trained from scratch for 100 epochs (600 steps/epoch) on 1400 paired image patches (image dimensions: (512 x 512 px²), patch size: (64 x 64 px²), 50 patches/image) with a batch size of 8 and a laplace loss function, using the CARE 2D ZeroCostDL4Mic notebook (v 1). Key python packages used include tensorflow (v 0.1.12), Keras (v2.3.1), csbdeep (v 0.6.2), numpy (v 1.19.5), cuda (v 11.0.221). The training was accelerated using a Tesla T4 GPU and data was augmented by a factor of 4 using rotation and flipping. The model weights can be used with the ZeroCostDL4Mic CARE 2D notebook and the CSBDeep Fiji plugin. <strong>Author(s)</strong>: Christoph Spahn<sup>1,2</sup>, Mike Heilemann<sup>1,3</sup> <strong>Contact email</strong>: christoph.spahn@mpi-marburg.mpg.de <strong>Affiliation(s)</strong>: 1) Institute of Physical and Theoretical Chemistry, Max-von-Laue Str. 7, Goethe-University Frankfurt, 60439 Frankfurt, Germany 2) ORCID: 0000-0001-9886-2263 3) ORCID: 0000-0002-9821-3578
DOI: 10.5281/zenodo.5551111
title: DeepBacs – Escherichia coli nucleoid denoising dataset and CARE model

description: Training and test images of H-NS-mScarlet-I expressing <em>E. coli </em>cells for image denoising, as well as a trained CARE model. Additional information can be found on our github wiki. The example images show confocal images of labelled <em>E. coli</em> nucleoids at low and high SNR. <strong>Training and test dataset</strong> <strong>Data type</strong>: Paired microscopy images (fluorescence) <strong>Microscopy data type</strong>: Confocal fluorescence images <strong>Microscope</strong>: Leica SP8 confocal microscope with a 1.40 NA 63x oil immersion objective <strong>Cell type</strong>: <em>E. coli</em> strain CS01 expressing H-NS-mScarlet-I fusion protein (H-NS-mScarlet-I) in NO34 parental strain (MreB-sfGFPsw, kindly provided by Zemer Gitai) <strong>File format</strong>: .tif (16-bit) <strong>Image size</strong>: 512 x 512 px<sup>2</sup> (Pixel size: 45 nm) <strong>CARE model</strong>: The CARE 2D model was generated using the ZeroCostDL4Mic platform (Chamier et al., 2021). It was trained from scratch for 100 epochs (600 steps/epoch) on 1400 paired image patches (image dimensions: (512 x 512 px²), patch size: (64 x 64 px²), 50 patches/image) with a batch size of 8 and a laplace loss function, using the CARE 2D ZeroCostDL4Mic notebook (v 1). Key python packages used include tensorflow (v 0.1.12), Keras (v2.3.1), csbdeep (v 0.6.2), numpy (v 1.19.5), cuda (v 11.0.221). The training was accelerated using a Tesla T4 GPU and data was augmented by a factor of 4 using rotation and flipping. The model weights can be used with the ZeroCostDL4Mic CARE 2D notebook and the CSBDeep Fiji plugin. <strong>Author(s)</strong>: Christoph Spahn<sup>1,2</sup>, Mike Heilemann<sup>1,3</sup> <strong>Contact email</strong>: christoph.spahn@mpi-marburg.mpg.de <strong>Affiliation(s)</strong>: 1) Institute of Physical and Theoretical Chemistry, Max-von-Laue Str. 7, Goethe-University Frankfurt, 60439 Frankfurt, Germany 2) ORCID: 0000-0001-9886-2263 3) ORCID: 0000-0002-9821-3578
DOI: 10.15151/esrf-es-1330512399
title: Neuron specific paralog of Microtubule Associated Protein 6 (MAP6) induces the formation of microtubule doublets indicating the role in neur

description: Microtubules play crucial roles in cellular processes. They alternate between phases of growth and shrinkage, described as dynamic instability essential to their activity. In neurons, dynamic and stable microtubules co-exist but the mechanisms underlying this stability still remain unclear. Recently, MAP6 was described as the first mammalian neuronal microtubule intraluminal protein that confers strong stability to microtubules. Based on sequence similarities, we identified the neuronal specific paralog of MAP6 which is MAP6d1. We found that MAP6d1 promotes rescues and reduces growth/shrinkage rates leading to the microtubules entering the pause phase. Surprisingly, MAP6d1 is also directly involved in the formation of microtubule doublets. As MAP6d1 is exclusively present in the neurons with motile cilia whose cytoskeletal arrangement includes microtubule doublets. Our objective is to solve the structure of MAP6d1 induced-microtubule doublets using cryo-electron tomography.
DOI: 10.5281/zenodo.8429940
title: U-Pb, Lu-Hf, and O in zircon from igneous and sedimentary rocks from the Ellsworth Mountains, West Antarctica

description: This dataset includes U-Pb, Lu-Hf, and O analyses of zircons from two igneous rocks: sample EHD0701A (79°57'47.43"S, 82°56'58.32"W) and sample EHD0305A (80°03'00.87"S, 82°59'07.91"W). EHD0701A is a foliated porphyritic hornblende micro-diorite, while EHD0305A is a basaltic andesite. Additionally, it contains Lu-Hf and O analyses of detrital zircon grains from ten meta-sedimentary samples: 13EG-01, 13EG-02, EHD2302A, EHD0801A, 13EG-05, EHD1705A, EA6, EAM1001B, 13EG-15, and 13EG-10. The coordinates for these samples and U-Pb data are published in Castillo et al. (2017). Zircon separation and analysis were conducted at the Australian National University in Canberra, Australia. Castillo, P., Fanning, C.M., Fernandez, R., Poblete, F., Hervé, F. 2017. Provenance and age constraints of Paleozoic siliciclastic rocks from the Ellsworth Mountains in West Antarctica, as determined by detrital zircon geochronology. GSA Bulletin 129, 1568-1584.
DOI: 10.5281/zenodo.8429939
title: U-Pb, Lu-Hf, and O in zircon from igneous and sedimentary rocks from the Ellsworth Mountains, West Antarctica

description: This dataset includes U-Pb, Lu-Hf, and O analyses of zircons from two igneous rocks: sample EHD0701A (79°57'47.43"S, 82°56'58.32"W) and sample EHD0305A (80°03'00.87"S, 82°59'07.91"W). EHD0701A is a foliated porphyritic hornblende micro-diorite, while EHD0305A is a basaltic andesite. Additionally, it contains Lu-Hf and O analyses of detrital zircon grains from ten meta-sedimentary samples: 13EG-01, 13EG-02, EHD2302A, EHD0801A, 13EG-05, EHD1705A, EA6, EAM1001B, 13EG-15, and 13EG-10. The coordinates for these samples and U-Pb data are published in Castillo et al. (2017). Zircon separation and analysis were conducted at the Australian National University in Canberra, Australia. Castillo, P., Fanning, C.M., Fernandez, R., Poblete, F., Hervé, F. 2017. Provenance and age constraints of Paleozoic siliciclastic rocks from the Ellsworth Mountains in West Antarctica, as determined by detrital zircon geochronology. GSA Bulletin 129, 1568-1584.