cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc2bkjt8
title: CCDC 2161810: Experimental Crystal Structure Determination

description: Related Article: Mengshan Ye, Alexandra C. Brown, Daniel L. M. Suess|2022|J.Am.Chem.Soc.|144|13184|doi:10.1021/jacs.2c03195
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.
DOI: 10.5517/ccdc.csd.cc2bkjv9
title: CCDC 2161811: Experimental Crystal Structure Determination

description: Related Article: Mengshan Ye, Alexandra C. Brown, Daniel L. M. Suess|2022|J.Am.Chem.Soc.|144|13184|doi:10.1021/jacs.2c03195
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.
DOI: 10.5281/zenodo.6938982
title: NPL DigAC project data

description: Data from NPL for the DigAC project. This is the raw data used in the published paper for the project.
DOI: 10.5281/zenodo.6938981
title: NPL DigAC project data

description: Data from NPL for the DigAC project. This is the raw data used in the published paper for the project.
DOI: 10.6084/m9.figshare.20401944
title: Maloney and Careau

description: #DATE_TIME = date and time #CHAMBER = measurement chamber #TEST = repeated test sequence #ID = individual identity #MASS.start = body mass (g) at the start of measurement #MASS.end = body mass (g) at the end of measurement #HEMA = hematocrit #HEART = heart mass #LIVER = liver mass #KIDNEYS = kidneys mass #GAS = gastrocnemius mass #SKIN.MASS = skin mass #AREA = fur area #FUR.MASS = fur mass #Age1 = age of the mouse #TAIL.MASS = tail mass #BODY.LENGTH = body length #TAIL.LENGTH = tail length #TEMP = temperature #slp.22 = slope at 22 degrees #slp.10 = slope at 10 degrees #S = difference in slope between 22 and 10 -&gt; substitution (first method) #slp.10.2 = slope at 10 degrees calculated using second method #slp.22.2 = slope at 22 degrees calculated using second method #S.2 = difference in slope between 22 and 10 -&gt; substitution (second method) #MEAN.S.10 = mean locomotor speed at 10 degrees #MEAN.S.22 = mean locomotor speed at 22 degrees #DEE.10 = mean DEE at 10 degrees #DEE.22 = mean DEE at 22 degrees #N.22 = number of observations where the mouse is moving above 0.1 at 22 degrees #N.10 = number of observations where the mouse is moving above 0.1at 10 degrees #n.10 = total observations at 10 degrees #n.22 = total observations at 22 degrees #A10 = average active MR at 10 degrees #A22 = average active MR at 22 degrees #R10 = average resting MR at 10 degrees #R22 = average resting MR at 22 degrees #BOUT = torpor bouts expressed during the 48h period (0 = no, 1 = yes) #RMR.22 = resting metabolic rate at 22 degrees
DOI: 10.6084/m9.figshare.20401944.v1
title: Maloney and Careau

description: #DATE_TIME = date and time #CHAMBER = measurement chamber #TEST = repeated test sequence #ID = individual identity #MASS.start = body mass (g) at the start of measurement #MASS.end = body mass (g) at the end of measurement #HEMA = hematocrit #HEART = heart mass #LIVER = liver mass #KIDNEYS = kidneys mass #GAS = gastrocnemius mass #SKIN.MASS = skin mass #AREA = fur area #FUR.MASS = fur mass #Age1 = age of the mouse #TAIL.MASS = tail mass #BODY.LENGTH = body length #TAIL.LENGTH = tail length #TEMP = temperature #slp.22 = slope at 22 degrees #slp.10 = slope at 10 degrees #S = difference in slope between 22 and 10 -&gt; substitution (first method) #slp.10.2 = slope at 10 degrees calculated using second method #slp.22.2 = slope at 22 degrees calculated using second method #S.2 = difference in slope between 22 and 10 -&gt; substitution (second method) #MEAN.S.10 = mean locomotor speed at 10 degrees #MEAN.S.22 = mean locomotor speed at 22 degrees #DEE.10 = mean DEE at 10 degrees #DEE.22 = mean DEE at 22 degrees #N.22 = number of observations where the mouse is moving above 0.1 at 22 degrees #N.10 = number of observations where the mouse is moving above 0.1at 10 degrees #n.10 = total observations at 10 degrees #n.22 = total observations at 22 degrees #A10 = average active MR at 10 degrees #A22 = average active MR at 22 degrees #R10 = average resting MR at 10 degrees #R22 = average resting MR at 22 degrees #BOUT = torpor bouts expressed during the 48h period (0 = no, 1 = yes) #RMR.22 = resting metabolic rate at 22 degrees
DOI: 10.6084/m9.figshare.20401953
title: ML-training dataset.xlsx

description: Machine learning dataset
DOI: 10.5281/zenodo.6664593
title: Hexagonal Silicon-Germanium Nanowire Branches with Tunable Composition

description: Hexagonal SiGe-2H has been recently shown to have a direct bandgap, and holds the promise to be compatible with silicon technology. Hexagonal Si (Ge) has been grown on an epitaxial lattice matched template consisting of wurtzite GaP (GaAs). Here, we present the growth of hexagonal Si and SiGe nanowire branches grown from a wurtzite stem by the Vapor-Liquid-Solid (VLS) growth mode, which is substantiated by <em>in-situ</em> transmission electron microscopy. We show that the composition can be tuned through the whole range of stoichiometry from Si to Ge, and the possibility to realize Si and SiGe heterostructures in these branches.
DOI: 10.5281/zenodo.6664592
title: Hexagonal Silicon-Germanium Nanowire Branches with Tunable Composition

description: Hexagonal SiGe-2H has been recently shown to have a direct bandgap, and holds the promise to be compatible with silicon technology. Hexagonal Si (Ge) has been grown on an epitaxial lattice matched template consisting of wurtzite GaP (GaAs). Here, we present the growth of hexagonal Si and SiGe nanowire branches grown from a wurtzite stem by the Vapor-Liquid-Solid (VLS) growth mode, which is substantiated by <em>in-situ</em> transmission electron microscopy. We show that the composition can be tuned through the whole range of stoichiometry from Si to Ge, and the possibility to realize Si and SiGe heterostructures in these branches.
DOI: 10.5281/zenodo.4640084
title: Data of "Universal platform for scalable semiconductor-superconductor nanowire networks '

description: Data of "Universal platform for scalable semiconductor-superconductor nanowire networks '
DOI: 10.5281/zenodo.4640083
title: Data of "Universal platform for scalable semiconductor-superconductor nanowire networks '

description: Data of "Universal platform for scalable semiconductor-superconductor nanowire networks '
DOI: 10.26050/wdcc/gcos_ehi_1960-2020_cohc
title: GCOS EHI 1960-2020 Continental Heat Content

description: Project: GCOS Earth Heat Inventory - A study under the Global Climate Observing System (GCOS) concerted international effort to update the Earth heat inventory (EHI), and presents an updated international assessment of ocean warming estimates, and new and updated estimates of heat gain in the atmosphere, cryosphere and land over the period from 1960 to present. Summary: The file “GCOS_EHI_1960-2020_Continental_Heat_Content_data.nc” presents an updated estimate of the global continental heat storage for the period 1960-2020. For the first time, the continental heat storage is assessed as composed by: ground heat storage due to changes in subsurface temperatures, inland water heat storage due to the warming of inland water bodies, and permafrost heat storage due to thawing of ground ice in the Arctic. Furthermore, we argue that all three components of the continental heat storage should be monitored independently of their relative magnitude, as heat gain in the three components alters several important climate phenomena affecting society and ecosystems. This file contains the total continental heat storage relative to 1960. The ground heat storage has been estimated by inverting 1079 subsurface temperature profiles form the Xibalbá database (https://figshare.com/articles/dataset/Xibalb_Underground_Temperature_Database/13516487) and a bootstrap technique to aggregate the Singular Value Decomposition (SVD) inversions of each profile (Cuesta-Valero et al., 2022a). The data are used in Cuesta-Valero et al. (2022b) and von Schuckmann et al. (2022).
DOI: 10.34740/kaggle/dsv/4001685
title: Dutch News Articles
DOI: 10.6084/m9.figshare.20393778
title: Size data of paint microplastics in Location 5 -original file

description: Size data of paint microplastics in Location 5 -original file
DOI: 10.6084/m9.figshare.20393778.v1
title: Size data of paint microplastics in Location 5 -original file

description: Size data of paint microplastics in Location 5 -original file
DOI: 10.5281/zenodo.6913925
title: Supplementary dataset to publication

description: Supplementary data to the publication: Potratz M., Zaeck L.M., Weigel C., Klein A., Freuling C.M., Müller T., <strong>Finke S.</strong> <strong>2020. </strong>Neuroglia Infection by Rabies Virus after Anterograde Virus Spread in Peripheral Neurons. <strong>Acta Neuropathologica Communications. </strong>8:199. doi.org/10.1186/s40478-020-01074-6.
DOI: 10.6084/m9.figshare.20363190.v3
title: Construction of a cross-species cell landscape at single-cell level

description: We applied scRNA-seq to map organism-level cell landscapes at multiple life stages for mice, zebrafish, and Drosophila. By integrating the comprehensive dataset of more than 2.6 million single cells, we constructed a cross-species cell landscape and identified signatures and common pathways that changed throughout the lifespan. We identified structural inflammation and mitochondrial dysfunction as the most common hallmarks of organism ageing, and found that pharmacological activation of mitochondrial metabolism alleviated ageing phenotypes in mice. Meanwhile, the cross-species cell landscape with other published data sets were stored in an integrated online portal Cell Landscape (http://bis.zju.edu.cn/cellatlas/).
DOI: 10.5281/zenodo.5243907
title: RECOMS_ESR02

description: The uploaded data is Text & still images that go under the thematic focus of general health & wellbeing.<br> Key words: Agroecology, mothers, health
DOI: 10.5281/zenodo.5243906
title: RECOMS_ESR02

description: The uploaded data is Text & still images that go under the thematic focus of general health & wellbeing.<br> Key words: Agroecology, mothers, health
DOI: 10.6084/m9.figshare.20369295
title: New separation protocol reveals spray painting as a neglected source of microplastics in soil: using graffiti as example

description: Paint microplastic counting- original file Size data of paint microplastics in Location 5 -original file <br>
DOI: 10.6084/m9.figshare.20369295.v1
title: Paint microplastic counting- original file

description: Paint microplastic counting- original file
DOI: 10.5281/zenodo.6939839
title: PhD Thesis Data Nikolaos G Bliziotis

description: Data for each chapter of my thesis, titled "Untargeted Plasma Metabolomics of Endocrine Hypertension" can be found here, along with the associated metadata (word file).
DOI: 10.5281/zenodo.6614995
title: PhD Thesis Data Nikolaos G Bliziotis

description: Data for each chapter of my thesis, titled "Untargeted Plasma Metabolomics of Endocrine Hypertension" can be found here, along with the associated metadata (word file).
DOI: 10.6084/m9.figshare.20402019
title: Ecological compensation mechanism in a trans-provincial river basin: a hydrological/water-quality modeling-based analysis

description: Data used for SWAT model validation: <br> 1. Table.xlsx: the comparison of monthly streamflow between observations and simulations; comparison of site-level TN and TP concentration between record and simulations. <br> 2. SWATCUP1_***: the setting files for SWAT-CUP for model calibration. <br> 3. FullHRU: characteristics of HRU and Subbasin files generated by SWAT
DOI: 10.6084/m9.figshare.20402019.v2
title: Ecological compensation mechanism in a trans-provincial river basin: a hydrological/water-quality modeling-based analysis

description: Data used for SWAT model validation: <br> 1. Table.xlsx: the comparison of monthly streamflow between observations and simulations; comparison of site-level TN and TP concentration between record and simulations. <br> 2. SWATCUP1_***: the setting files for SWAT-CUP for model calibration. <br> 3. FullHRU: characteristics of HRU and Subbasin files generated by SWAT
DOI: 10.6084/m9.figshare.20402019.v1
title: Tangbai River Basin SWAT simulation

description: Data used for SWAT model validation: <br> 1. Table.xlsx: the comparison of monthly streamflow between observations and simulations; comparison of site-level TN and TP concentration between record and simulations. <br> 2. SWATCUP1_***: the setting files for SWAT-CUP for model calibration. <br> 3. FullHRU: characteristics of HRU and Subbasin files generated by SWAT
DOI: 10.34740/kaggle/dsv/4001812
title: YouTube Trending Video Dataset (updated daily)
DOI: 10.7284/148936
title: Expendable Probe data collected during research cruise LMG0512 using a Sippican MK21 instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/148937
title: Expendable Probe data collected during research cruise LMG0512 using a Sippican MK21 instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/148942
title: Fluorometer data collected during research cruise LMG0512 using a Turner 10-AU instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/148939
title: GNSS (Global Navigation Satellite System) data collected during research cruise LMG0512 using a Ashtech ADU2 instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/148940
title: GNSS (Global Navigation Satellite System) data collected during research cruise LMG0512 using a Garmin GPS-17HVS instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/148943
title: GNSS (Global Navigation Satellite System) data collected during research cruise LMG0512 using a Trimble Centurion P(Y) instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/148944
title: Gyrocompass data collected during research cruise LMG0512 using a SGB Meridian instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.20317962
title: Profiling the 3D interaction between germ cell tumors and microenvironmental cells at the transcriptome and secretome level

description: The tumor microenvironment (TM), consisting of the extracellular matrix (ECM), fibroblasts, endothelial cells and immune cells, might affect tumor invasiveness and the outcome of standard chemotherapy. This study investigated the cross-talk between germ cell tumors (GCT) and surrounding TM cells (macrophages, T-lymphocytes, endothelial cells, fibroblasts) at the transcriptome and secretome level. Using high-throughput approaches of three-dimensional (3D) co-cultured cellular aggregates, this study offers newly identified pathways to be studied with regard to sensitivity towards cisplatin-based chemotherapy or tumor invasiveness as a consequence of the cross-talk between tumor cells and TM components. Mass-spectrometry-based secretome analyses revealed that TM cells secreted factors involved in ECM organization, cell adhesion, angiogenesis and regulation of insulin-like growth factor (IGF) transport. To evaluate direct cell–cell contacts, green fluorescent protein (GFP)-expressing GCT cells and mCherry-expressing TM cells were co-cultured in 3D. Afterwards, cell populations were separated by flow cytometry and analyzed by RNA-sequencing. Correlating the secretome with transcriptome data indicated molecular processes such as cell adhesion and components of the ECM being enriched in most cell populations. Re-analyses of secretome data with regard tolysine- and proline-hydroxylated peptides revealed a gain in proteins, such as collagens and fibronectin.Cultivation of GCT cells on collagen I/IV- or fibronectin-coated plates significantly elevated adhesive and migratory capacity, while decreasing cisplatin sensitivity of GCT cells. Correspondingly, cisplatin sensitivity was significantly reduced in GCT cells under the influence of conditioned medium from fibroblasts and endothelial cells. This study sheds light on the cross-talk between GCT cells and their circumjacent TM, which results in deposition of the ECM and eventually promotes a pro-tumorigenic environment through enhanced migratory and adhesive capacity, as well as decreased cisplatin sensitivity. Hence, our observations indicate that targeting the ECM and its cellular components might be a novel therapeutic option in combination with cisplatin-based chemotherapy for GCT patients.
DOI: 10.6084/m9.figshare.20317962.v2
title: Profiling the 3D interaction between germ cell tumors and microenvironmental cells at the transcriptome and secretome level

description: The tumor microenvironment (TM), consisting of the extracellular matrix (ECM), fibroblasts, endothelial cells and immune cells, might affect tumor invasiveness and the outcome of standard chemotherapy. This study investigated the cross-talk between germ cell tumors (GCT) and surrounding TM cells (macrophages, T-lymphocytes, endothelial cells, fibroblasts) at the transcriptome and secretome level. Using high-throughput approaches of three-dimensional (3D) co-cultured cellular aggregates, this study offers newly identified pathways to be studied with regard to sensitivity towards cisplatin-based chemotherapy or tumor invasiveness as a consequence of the cross-talk between tumor cells and TM components. Mass-spectrometry-based secretome analyses revealed that TM cells secreted factors involved in ECM organization, cell adhesion, angiogenesis and regulation of insulin-like growth factor (IGF) transport. To evaluate direct cell–cell contacts, green fluorescent protein (GFP)-expressing GCT cells and mCherry-expressing TM cells were co-cultured in 3D. Afterwards, cell populations were separated by flow cytometry and analyzed by RNA-sequencing. Correlating the secretome with transcriptome data indicated molecular processes such as cell adhesion and components of the ECM being enriched in most cell populations. Re-analyses of secretome data with regard tolysine- and proline-hydroxylated peptides revealed a gain in proteins, such as collagens and fibronectin.Cultivation of GCT cells on collagen I/IV- or fibronectin-coated plates significantly elevated adhesive and migratory capacity, while decreasing cisplatin sensitivity of GCT cells. Correspondingly, cisplatin sensitivity was significantly reduced in GCT cells under the influence of conditioned medium from fibroblasts and endothelial cells. This study sheds light on the cross-talk between GCT cells and their circumjacent TM, which results in deposition of the ECM and eventually promotes a pro-tumorigenic environment through enhanced migratory and adhesive capacity, as well as decreased cisplatin sensitivity. Hence, our observations indicate that targeting the ECM and its cellular components might be a novel therapeutic option in combination with cisplatin-based chemotherapy for GCT patients.
DOI: 10.6084/m9.figshare.20317962.v1
title: Profiling the 3D interaction between germ cell tumors and microenvironmental cells at the transcriptome and secretome level

description: The tumor microenvironment (TM), consisting of the extracellular matrix (ECM), fibroblasts, endothelial cells and immune cells, might affect tumor invasiveness and the outcome of standard chemotherapy. This study investigated the cross-talk between germ cell tumors (GCT) and surrounding TM cells (macrophages, T-lymphocytes, endothelial cells, fibroblasts) at the transcriptome and secretome level. Using high-throughput approaches of three-dimensional (3D) co-cultured cellular aggregates, this study offers newly identified pathways to be studied with regard to sensitivity towards cisplatin-based chemotherapy or tumor invasiveness as a consequence of the cross-talk between tumor cells and TM components. Mass-spectrometry-based secretome analyses revealed that TM cells secreted factors involved in ECM organization, cell adhesion, angiogenesis and regulation of insulin-like growth factor (IGF) transport. To evaluate direct cell–cell contacts, green fluorescent protein (GFP)-expressing GCT cells and mCherry-expressing TM cells were co-cultured in 3D. Afterwards, cell populations were separated by flow cytometry and analyzed by RNA-sequencing. Correlating the secretome with transcriptome data indicated molecular processes such as cell adhesion and components of the ECM being enriched in most cell populations. Re-analyses of secretome data with regard tolysine- and proline-hydroxylated peptides revealed a gain in proteins, such as collagens and fibronectin.Cultivation of GCT cells on collagen I/IV- or fibronectin-coated plates significantly elevated adhesive and migratory capacity, while decreasing cisplatin sensitivity of GCT cells. Correspondingly, cisplatin sensitivity was significantly reduced in GCT cells under the influence of conditioned medium from fibroblasts and endothelial cells. This study sheds light on the cross-talk between GCT cells and their circumjacent TM, which results in deposition of the ECM and eventually promotes a pro-tumorigenic environment through enhanced migratory and adhesive capacity, as well as decreased cisplatin sensitivity. Hence, our observations indicate that targeting the ECM and its cellular components might be a novel therapeutic option in combination with cisplatin-based chemotherapy for GCT patients.
DOI: 10.7284/148953
title: Fluorometer data collected during research cruise LMG0511 using a Turner 10-AU instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/148950
title: GNSS (Global Navigation Satellite System) data collected during research cruise LMG0511 using a Ashtech ADU2 instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/148951
title: GNSS (Global Navigation Satellite System) data collected during research cruise LMG0511 using a Garmin GPS-17HVS instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/148954
title: GNSS (Global Navigation Satellite System) data collected during research cruise LMG0511 using a Trimble Centurion P(Y) instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/148955
title: Gyrocompass data collected during research cruise LMG0511 using a SGB Meridian instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/148964
title: Fluorometer data collected during research cruise LMG0509 using a Turner 10-AU instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/148961
title: GNSS (Global Navigation Satellite System) data collected during research cruise LMG0509 using a Ashtech ADU2 instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition