cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc24m1nh
title: CCDC 1984516: Experimental Crystal Structure Determination

description: Related Article: Valmik P. Jejurkar, Gauravi Yashwantrao, Pawan Kumar, Suditi Neekhra, Parimal J. Maliekal, Purav Badani, Rohit Srivastava, Satyajit Saha|2021|Chem.-Eur.J.|27|5470|doi:10.1002/chem.202004942
DOI: 10.5517/ccdc.csd.cc24m1jc
title: CCDC 1984512: Experimental Crystal Structure Determination

description: Related Article: Valmik P. Jejurkar, Gauravi Yashwantrao, Pawan Kumar, Suditi Neekhra, Parimal J. Maliekal, Purav Badani, Rohit Srivastava, Satyajit Saha|2021|Chem.-Eur.J.|27|5470|doi:10.1002/chem.202004942
DOI: 10.5517/ccdc.csd.cc25bdnl
title: CCDC 2005999: Experimental Crystal Structure Determination

description: Related Article: Ziqi Zhang|2020|CSD Communication|||
description: Related Article: Zi-Qi Zhang, Yi-Hao Xu, Jing-Cheng Dai, Yan Li, Jie Sheng, Xi-Sheng Wang|2021|Org.Lett.|23|2194|doi:10.1021/acs.orglett.1c00344
DOI: 10.5517/ccdc.csd.cc25nbpw
title: CCDC 2015548: Experimental Crystal Structure Determination

description: Related Article: Li-Bo Huang, Arthur Hardiagon, Istvan Kocsis, Cristina-Alexandra Jegu, Mihai Deleanu, Arnaud Gilles, Arie van der Lee, Fabio Sterpone, Marc Baaden, Mihail Barboiu|2021|J.Am.Chem.Soc.|143|4224|doi:10.1021/jacs.0c11952
DOI: 10.5517/ccdc.csd.cc25nbqx
title: CCDC 2015549: Experimental Crystal Structure Determination

description: Related Article: Li-Bo Huang, Arthur Hardiagon, Istvan Kocsis, Cristina-Alexandra Jegu, Mihai Deleanu, Arnaud Gilles, Arie van der Lee, Fabio Sterpone, Marc Baaden, Mihail Barboiu|2021|J.Am.Chem.Soc.|143|4224|doi:10.1021/jacs.0c11952
DOI: 10.5517/ccdc.csd.cc25nbry
title: CCDC 2015550: Experimental Crystal Structure Determination

description: Related Article: Li-Bo Huang, Arthur Hardiagon, Istvan Kocsis, Cristina-Alexandra Jegu, Mihai Deleanu, Arnaud Gilles, Arie van der Lee, Fabio Sterpone, Marc Baaden, Mihail Barboiu|2021|J.Am.Chem.Soc.|143|4224|doi:10.1021/jacs.0c11952
DOI: 10.5517/ccdc.csd.cc25nbsz
title: CCDC 2015551: Experimental Crystal Structure Determination

description: Related Article: Li-Bo Huang, Arthur Hardiagon, Istvan Kocsis, Cristina-Alexandra Jegu, Mihai Deleanu, Arnaud Gilles, Arie van der Lee, Fabio Sterpone, Marc Baaden, Mihail Barboiu|2021|J.Am.Chem.Soc.|143|4224|doi:10.1021/jacs.0c11952
DOI: 10.5517/ccdc.csd.cc26pznk
title: CCDC 2046919: Experimental Crystal Structure Determination

description: Related Article: Yannick Linne, Elisa Bonandi, Christopher Tabet, Jan Geldsetzer, Markus Kalesse|2021|Angew.Chem.,Int.Ed.|60|6938|doi:10.1002/anie.202016072
DOI: 10.5519/qd.j3udb19x
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (29057 records)
DOI: 10.25919/tykm-4c87
title: Parkes pulsar observations with undefined project IDs for 2020OCTS_02

description: Parkes pulsar observations with undefined project IDs for 2020OCTS. This collection contains data from the ToO project PX068.
DOI: 10.5281/zenodo.4643031
title: Actual SRFs of FY3D MWTS-2's SSPCs

description: The xlsx file uploaded by the author are the actual spectral response functions of three selected single passband channels(channel 5, 6 and 7).
DOI: 10.5281/zenodo.4643030
title: Actual SRFs of FY3D MWTS-2's SSPCs

description: The xlsx file uploaded by the author are the actual spectral response functions of three selected single passband channels(channel 5, 6 and 7).
DOI: 10.6084/m9.figshare.14331584
title: Raw file for labeled network

description: The raw file of the complete network in .cys format
DOI: 10.5281/zenodo.4642759
title: CReSCENT: CanceR Single Cell ExpressioN Toolkit (CReSCENT) v2.0 PBMC example infiles and commands

description: CReSCENT: CanceR Single Cell ExpressioN Toolkit (CReSCENT) v2.0<br> Example PBMC infiles and parameters (c) Pugh Lab. Under GNU General Public License v3.0 <br> ##############<br> ## CONTENTS<br> ############## A) File crescent_v2.0_pbmc_example_infiles_and_commands.tar.bz2,<br> folder INPUT_MTX<br> Contains four scRNA-seq PBMC datasets obtained from 10X<br> https://www.10xgenomics.com/resources/datasets/<br> Two of them originally had ~8,000 and ~10,000 cells, and were downsampled to 1,000 B) File crescent_v2.0_pbmc_example_infiles_and_commands.tar.bz2,<br> folder LISTS_AND_COMMANDS<br> Contains the tables with input parameters for the integration of the four<br> datasets above, using the four CReSCENT scRNA-seq one-line-command R scripts:<br> 1) Runs_Seurat_v3_MultiDatasets_QC_Normalization.R<br> 2) Runs_Seurat_v3_MultiDatasets_Integration.R<br> 3) Runs_Seurat_v3_MultiDatasets_PCA_Clustering_DimReduction.R<br> 4) Runs_Seurat_v3_MultiDatasets_DGE.R<br> Which can be obtained from:<br> https://github.com/pughlab/crescent/tree/master/bin/in_use For help on how to run these scripts, in a Console/Terminal type:<br> `Rscript Runs_Seurat_v3_MultiDatasets_QC_Normalization.R -h`<br> Each script code has a section 'Required libraries'<br> For Bug Reports and Feature Requests, please fill out a GitHub ticket:<br> https://github.com/pughlab/crescent/issues C) File crescent_v2.0_pbmc_example_infiles_and_commands.tar.bz2,<br> folder METADATA<br> Contains two tables with cell-level metadata to colour UMAP/TSNE plots<br> and to compara class_1 vs. class_2 for Differential Gene Expression detection D) File crescent_v2.0_pbmc_example_outfiles.tar.bz2,<br> folder SEURAT<br> Contains the results obtained by running the scripts using CReSCENT scripts<br> GitHub version 5a78fe9.<br> See sub-folder 'SEURAT/LOG_FILES' for R library versions and commands used for each script
DOI: 10.5517/ccdc.csd.cc27066p
title: CCDC 2055771: Experimental Crystal Structure Determination

description: Related Article: Alastair J. McMillan, Martyna Sieńkowska, Piero Di Lorenzo, Gemma K. Gransbury, Nicholas F. Chilton, Michela Salamone, Alessandro Ruffoni, Massimo Bietti, Daniele Leonori|2021|Angew.Chem.,Int.Ed.|60|7132|doi:10.1002/anie.202100030
DOI: 10.5517/ccdc.csd.cc2741hy
title: CCDC 2059469: Experimental Crystal Structure Determination

description: Related Article: Paul R. Carlson, Alexander S. Burns, Emily A. Shimizu, Shilin Wang, Scott D. Rychnovsky|2021|Org.Lett.|23|2183|doi:10.1021/acs.orglett.1c00340
DOI: 10.6084/m9.figshare.11272298
title: Microbe seedbanks

description: These datasets describe a study linking microbial communities to the community structure of bacterial and fungal communities. The meta-data are included as sheets within the excel files
DOI: 10.6084/m9.figshare.14331675.v1
title: Additional file 2 of An engineered membrane-bound guanylyl cyclase with light-switchable activity

description: Additional file 2. Raw data values.
DOI: 10.6084/m9.figshare.14331675
title: Additional file 2 of An engineered membrane-bound guanylyl cyclase with light-switchable activity

description: Additional file 2. Raw data values.
DOI: 10.6084/m9.figshare.14331687
title: Additional file 1 of Correlation analysis of stem hardness traits with fiber and yield-related traits in core collections of Gossypium hirsutum

description: Additional file 1 : Table S1. Descriptive statistics of 20 traits in 2017 and 2018. Table S2. Stem hardness variation among Gossypium hirsutum genotypes.
DOI: 10.6084/m9.figshare.14331687.v1
title: Additional file 1 of Correlation analysis of stem hardness traits with fiber and yield-related traits in core collections of Gossypium hirsutum

description: Additional file 1 : Table S1. Descriptive statistics of 20 traits in 2017 and 2018. Table S2. Stem hardness variation among Gossypium hirsutum genotypes.
DOI: 10.6084/m9.figshare.14331700.v1
title: Additional file 1 of Identification, characterization, and expression profiles of the GASA genes in cotton

description: Additional file 1: Table S1. The primers designed for qRT-PCR.
DOI: 10.6084/m9.figshare.14331703
title: Additional file 2 of Identification, characterization, and expression profiles of the GASA genes in cotton

description: Additional file 2: Table S2. Information on the GASA genes in G. arboretum, G. barbadense, G. herbaceum, G. raimondii, and A. thaliana.
DOI: 10.6084/m9.figshare.14331703.v1
title: Additional file 2 of Identification, characterization, and expression profiles of the GASA genes in cotton

description: Additional file 2: Table S2. Information on the GASA genes in G. arboretum, G. barbadense, G. herbaceum, G. raimondii, and A. thaliana.
DOI: 10.6084/m9.figshare.14331700
title: Additional file 1 of Identification, characterization, and expression profiles of the GASA genes in cotton

description: Additional file 1: Table S1. The primers designed for qRT-PCR.
DOI: 10.6084/m9.figshare.14331638
title: Data tables and supporting information for the paper entitled "Preliminary ESR dating results for fault barite: Insights into the history of fault activity recorded on basalt bedrock planes"

description: Data tables and supporting information for the paper entitled "Preliminary ESR dating results for fault barite: Insights into the history of fault activity recorded on basalt bedrock planes"
DOI: 10.6084/m9.figshare.14331638.v1
title: Data tables and supporting information for the paper entitled "Preliminary ESR dating results for fault barite: Insights into the history of fault activity recorded on basalt bedrock planes"

description: Data tables and supporting information for the paper entitled "Preliminary ESR dating results for fault barite: Insights into the history of fault activity recorded on basalt bedrock planes"
DOI: 10.5281/zenodo.4628346
title: [Table and Maps] Site of Memory: Sanctuaries dedicated to Yao 堯, Shun 舜, Yu 禹 and Tangshu Yu 唐叔虞 in Shanxi, China from the Han period (80 AD) to the Late Qing (1892)

description: *Table: Sanctuaries of Yao, Shun, Yu and Tangshu Yu in Shanxi from the Han to the Late Qing *Figure 1: The distributions of the sanctuaries of Yao, Shun, Yu and Tangshu Yu in Shanxi from the Han to the Late Qing *Figure 2: The Transitional distributions of the sanctuaries of Yao, Shun, Yu and Tangshu Yu in Shanxi listed in the following geography texts: (a) "Dilizhi" of <em>Hanshu</em> 漢書 地理志 (80 AD) (b) <em>Yuanhe junxianzhi</em> 元和郡縣志 (813) (c) <em>Taiping Huanyuji</em> 太平寰宇記 (976-983) (d) (Wanli)<em>Shanxi tongzhi</em> (萬曆)山西通志 (1629) (e) (Yongzheng)<em>Shanxi tongzhi</em> (雍正)山西通志 (1734) (f) (Guangxu)<em>Shanxi tongzhi</em> (光绪)山西通志 (1892)
description: Part of the article titled "Places Commemorating Yao, Shun and Yu in the Shanxi tongzhi" (in Korean)
DOI: 10.18112/openneuro.ds003580.v1.0.0
title: FSL open science dev dataset
DOI: 10.18112/openneuro.ds003581.v1.0.0
title: FSL open science dev dataset
DOI: 10.18112/openneuro.ds003582.v1.0.0
title: FSL open science dev dataset
DOI: 10.6084/m9.figshare.14331785.v1
title: Fujian.zip

description: Multiclass tidal wetland map for East Asia in 2020 by using our MTWM-TP classification framework on time series of Sentine-2 imagery.
DOI: 10.6084/m9.figshare.14331872
title: PCFS Validation into Mexican Spanish

description: This data is for the application of diagnostic and clinimetric validity tests to the PFCS Scale: self-reported questionnaire and structured interview.
DOI: 10.6084/m9.figshare.14331872.v1
title: PCFS Validation into Mexican Spanish

description: This data is for the application of diagnostic and clinimetric validity tests to the PFCS Scale: self-reported questionnaire and structured interview.
DOI: 10.5281/zenodo.4643074
title: Data files to support "Timescales of spontaneous fMRI fluctuations relate to structural connectivity in the brain"

description: Data files to support "Timescales of spontaneous fMRI fluctuations relate to structural connectivity in the brain". Some data files are processed rsfMRI time series of 100 subjects from the Human Connectome Project. Code is here: https://github.com/NeuralSystemsAndSignals/humanStructureFunction Preprint is here: https://doi.org/10.1101/655050
description: Updated connectome.zip. Mean streamline distances are now fixed.
DOI: 10.5281/zenodo.3909007
title: Data files to support "Timescales of spontaneous fMRI fluctuations relate to structural connectivity in the brain"

description: Data files to support "Timescales of spontaneous fMRI fluctuations relate to structural connectivity in the brain". Some data files are processed rsfMRI time series of 100 subjects from the Human Connectome Project. Code is here: https://github.com/NeuralSystemsAndSignals/humanStructureFunction Preprint is here: https://doi.org/10.1101/655050
description: Updated connectome.zip. Mean streamline distances are now fixed.
DOI: 10.25919/2abq-g015
title: Parkes pulsar observations with undefined project IDs for 2020OCTS_04

description: Parkes pulsar observations with undefined project IDs for 2020OCTS. This collection contains data from the ToO projects PX069 and PX070.
DOI: 10.6084/m9.figshare.13466570
title: Collapse of a Coastal Revetment Due to the Combined Effect of Anthropogenic and Natural Disturbances_Data & Figures

description: Observation data used for creating figures in the paper 'Collapse of a Coastal Revetment Due to the Combined Effect of Anthropogenic and Natural Disturbances' and Figures(12)
DOI: 10.6084/m9.figshare.13466570.v3
title: Data & Figures(Paper title : Collapse of a coastal revetment by the combined effect of anthropogenic and natural disturbances)

description: Observation data used for creating figures in the paper 'Collapse of a coastal revetment by the combined effect of anthropogenic and natural disturbances' and Figures(10)
DOI: 10.21227/k4n4-0r69
title: Driver Behavior Analysis Based on Smartphone Sensor Data

description: Driving behavior plays a vital role in maintaining safe and sustainable transport, and specifically, in the area of traffic management and control, driving behavior is of great importance since specific driving behaviors are significantly related with traffic congestion levels. Beyond that, it affects fuel consumption, air pollution, public health as well as personal mental health and psychology. Use of Smartphone sensors for data acquisition has emerged as a means to understand and model driving behavior. Our aim is to analyze driving behavior using on Smartphone sensors’ data streams. We present Smartphone sensor (Accelerometer, Gyroscope, Proximity, etc.) data recorded in live traffic while driver was executing the driving events.
DOI: 10.6084/m9.figshare.14332340
title: Supplementary Material for: Effects of Sex and Physical Activity Level on Serum Biomarker-Based Physiological Dysregulation: The Impact to Predict Frailty and Mortality in the Quebec NuAge Cohort

description: <b><i>Background:</i></b> Age-related changes in biological processes such as physiological dysregulation (the progressive loss of homeostatic capacity) vary considerably among older adults and may influence health profiles in late life. These differences could be related, at least in part, to the impact of intrinsic and extrinsic factors such as sex and physical activity level (PAL). <b><i>Objectives:</i></b> The objectives of this study were (1) to assess the magnitude and rate of changes in physiologi­cal dysregulation in men and women according to PAL and (2) to determine whether/how sex and PAL mediate the apparent influence of physiological dysregulation on health outcomes (frailty and mortality). <b><i>Methods:</i></b> We used data on 1,754 community-dwelling older adults (age = 74.4 ± 4.2 years; women = 52.4%) of the Quebec NuAge cohort study. Physiological dysregulation was calculated based on Mahalanobis distance of 31 biomarkers regrouped into 5 systems: oxygen transport, liver/kidney function, leukopoiesis, micronutrients, and lipids. <b><i>Results:</i></b> As expected, mean physiological dysregulation significantly increased with age while PAL decreased. For the same age and PAL, men showed higher levels of physiological dysregulation globally in 3 systems: oxygen transport, liver/kidney function, and leukopoiesis. Men also showed faster global physiological dysregulation in the liver/kidney and leukopoiesis systems. Overall, high PAL was associated with lower level and slower rate of change of physiological dysregulation. Finally, while mortality and frailty risk significantly increased with physiological dysregulation, there was no evidence for differences in these effects between sexes and PAL. <b><i>Conclusion:</i></b> Our results showed that both sex and PAL have a significant effect on physiological dysregulation levels and rates of change. Also, although a higher PAL was associated with lower level and slower rate of change of physiological dysregulation, there was no evidence that PAL attenuates the effect of physiological dysregulation on subsequent declines in health at the end of life. Substantial work remains to understand how modifiable behaviors impact the relationship between physiological dysregulation, frailty, and mortality in men and women.
DOI: 10.6084/m9.figshare.14332340.v1
title: Supplementary Material for: Effects of Sex and Physical Activity Level on Serum Biomarker-Based Physiological Dysregulation: The Impact to Predict Frailty and Mortality in the Quebec NuAge Cohort

description: <b><i>Background:</i></b> Age-related changes in biological processes such as physiological dysregulation (the progressive loss of homeostatic capacity) vary considerably among older adults and may influence health profiles in late life. These differences could be related, at least in part, to the impact of intrinsic and extrinsic factors such as sex and physical activity level (PAL). <b><i>Objectives:</i></b> The objectives of this study were (1) to assess the magnitude and rate of changes in physiologi­cal dysregulation in men and women according to PAL and (2) to determine whether/how sex and PAL mediate the apparent influence of physiological dysregulation on health outcomes (frailty and mortality). <b><i>Methods:</i></b> We used data on 1,754 community-dwelling older adults (age = 74.4 ± 4.2 years; women = 52.4%) of the Quebec NuAge cohort study. Physiological dysregulation was calculated based on Mahalanobis distance of 31 biomarkers regrouped into 5 systems: oxygen transport, liver/kidney function, leukopoiesis, micronutrients, and lipids. <b><i>Results:</i></b> As expected, mean physiological dysregulation significantly increased with age while PAL decreased. For the same age and PAL, men showed higher levels of physiological dysregulation globally in 3 systems: oxygen transport, liver/kidney function, and leukopoiesis. Men also showed faster global physiological dysregulation in the liver/kidney and leukopoiesis systems. Overall, high PAL was associated with lower level and slower rate of change of physiological dysregulation. Finally, while mortality and frailty risk significantly increased with physiological dysregulation, there was no evidence for differences in these effects between sexes and PAL. <b><i>Conclusion:</i></b> Our results showed that both sex and PAL have a significant effect on physiological dysregulation levels and rates of change. Also, although a higher PAL was associated with lower level and slower rate of change of physiological dysregulation, there was no evidence that PAL attenuates the effect of physiological dysregulation on subsequent declines in health at the end of life. Substantial work remains to understand how modifiable behaviors impact the relationship between physiological dysregulation, frailty, and mortality in men and women.
DOI: 10.6084/m9.figshare.14332577
title: Supplementary Material for: Analysis of Key Distinct Biological Characteristics of Human Placenta-Derived Mesenchymal Stromal Cells and Individual Heterogeneity Attributing to Donors

description: For potential clinical applications in the future, we investigated the distinct biological features of mesenchymal stromal cells (MSCs) derived from different origin areas of human placenta and individual heterogeneity among different donors. Chorionic plate MSCs (CP-MSCs), amniotic membrane MSCs (AM-MSCs), and decidual plate MSCs (DP-MSCs) were isolated from 5 human placentae and were analyzed in terms of main features of MSCs including surface marker profile, growth, differentiation potential, immune regulation capability, and tubulin acetylation (Ac-tubulin). The expression profile of surface markers in the 3 types of MSCs derived from the 5 donors was relatively stable. Heterogeneity was found in growth, differentiation potential, and immune regulation among MSCs according to the different areas of isolation and different donors. CP-MSCs and AM-MSCs derived from the placentae of donors 1–3 had a higher osteogenic differentiation potential than the corresponding DP-MSCs, but those derived from the placentae of donors 4 and 5 had a markedly lower osteogenic differentiation potential than DP-MSCs. All CP-MSCs derived from donors 1–3 had the highest adipogenic differentiation potential, but CP-MSCs derived from donors 4 and 5 did not show strong capability of adipogenic differentiation. CP-MSCs markedly inhibited the proliferation of peripheral blood mononuclear cells (PBMCs) induced by phytohemagglutinin, whereas AM- and DP-MSCs did not. All MSCs decreased the proportion of CD3+/CD8–/IFN-γ+ Th1 and CD3+/CD8–/IL17+ Th17 cells, but increased the proportion of Treg cells in PBMCs, with individual differences among the 5 donors. DP-MSCs from donors 1 and 2 had higher levels of Ac-tubulin compared with CP- and AM-MSCs. However, the levels of Ac-tubulin in AM-MSCs from donors 3 and 5 were higher than those of the other 2 types of MSCs. Our results revealed that there was tissue-specific heterogeneity among the 3 types of MSCs from different origin tissues of placenta and individual heterogeneity among donors. In future, the pre-selected placenta-derived MSCs with specific biological advantages may improve the curative effect of cell therapy in different situations.
DOI: 10.6084/m9.figshare.14332577.v1
title: Supplementary Material for: Analysis of Key Distinct Biological Characteristics of Human Placenta-Derived Mesenchymal Stromal Cells and Individual Heterogeneity Attributing to Donors

description: For potential clinical applications in the future, we investigated the distinct biological features of mesenchymal stromal cells (MSCs) derived from different origin areas of human placenta and individual heterogeneity among different donors. Chorionic plate MSCs (CP-MSCs), amniotic membrane MSCs (AM-MSCs), and decidual plate MSCs (DP-MSCs) were isolated from 5 human placentae and were analyzed in terms of main features of MSCs including surface marker profile, growth, differentiation potential, immune regulation capability, and tubulin acetylation (Ac-tubulin). The expression profile of surface markers in the 3 types of MSCs derived from the 5 donors was relatively stable. Heterogeneity was found in growth, differentiation potential, and immune regulation among MSCs according to the different areas of isolation and different donors. CP-MSCs and AM-MSCs derived from the placentae of donors 1–3 had a higher osteogenic differentiation potential than the corresponding DP-MSCs, but those derived from the placentae of donors 4 and 5 had a markedly lower osteogenic differentiation potential than DP-MSCs. All CP-MSCs derived from donors 1–3 had the highest adipogenic differentiation potential, but CP-MSCs derived from donors 4 and 5 did not show strong capability of adipogenic differentiation. CP-MSCs markedly inhibited the proliferation of peripheral blood mononuclear cells (PBMCs) induced by phytohemagglutinin, whereas AM- and DP-MSCs did not. All MSCs decreased the proportion of CD3+/CD8–/IFN-γ+ Th1 and CD3+/CD8–/IL17+ Th17 cells, but increased the proportion of Treg cells in PBMCs, with individual differences among the 5 donors. DP-MSCs from donors 1 and 2 had higher levels of Ac-tubulin compared with CP- and AM-MSCs. However, the levels of Ac-tubulin in AM-MSCs from donors 3 and 5 were higher than those of the other 2 types of MSCs. Our results revealed that there was tissue-specific heterogeneity among the 3 types of MSCs from different origin tissues of placenta and individual heterogeneity among donors. In future, the pre-selected placenta-derived MSCs with specific biological advantages may improve the curative effect of cell therapy in different situations.