cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc2f79nn
title: CCDC 2241351: Experimental Crystal Structure Determination

description: Related Article: CenJun Li, Chao fan, Chunchao Wang, Jianchao Chen, Chengjun Wu, TieMin Sun|2024|J.Mol.Struct.|1301|137331|doi:10.1016/j.molstruc.2023.137331
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.cc2fkr2v
title: CCDC 2251377: Experimental Crystal Structure Determination

description: Related Article: Kaishun Ye, Gang Li, Feiyang Li, Chao Shi, Zhen Jiang, Fuzheng Zhang, Qiuxia Li, Jie Su, Dandan Song, Aihua Yuan|2024|Phys.Chem.Chem.Phys.(PCCP)|26|2395|doi:10.1039/D3CP05304K
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.cc2fkr3w
title: CCDC 2251378: Experimental Crystal Structure Determination

description: Related Article: Kaishun Ye, Gang Li, Feiyang Li, Chao Shi, Zhen Jiang, Fuzheng Zhang, Qiuxia Li, Jie Su, Dandan Song, Aihua Yuan|2024|Phys.Chem.Chem.Phys.(PCCP)|26|2395|doi:10.1039/D3CP05304K
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.cc2fmq2w
title: CCDC 2253268: Experimental Crystal Structure Determination

description: Related Article: Stephanie García-Zavala, Ramón Guzmán-Mejía, J. Carlos Jiménez-Cruz, Rafael Herrera-Bucio, Hugo A. García-Gutiérrez, Pedro Navarro-Santos, Judit A. Aviña-Verduzco|2024|J.Mol.Struct.|1301|137358|doi:10.1016/j.molstruc.2023.137358
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.cc2fnkh5
title: CCDC 2254087: Experimental Crystal Structure Determination

description: Related Article: Xuan Wang, Ji-Jiang Wang, Long Tang, Er-Lin Yue, Chao Bai, Xiao Wang, Yuqi Zhang, Yi-Xia Ren, Xiao-Li Chen|2023|J.Mol.Struct.|1298|137056|doi:10.1016/j.molstruc.2023.137056
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: 10.6084/m9.figshare.25017886.v1
title: Additional file 2 of Wide-spread dispersal in a deep-sea brooding polychaete: the role of natural history collections in assessing the distribution in quill worms (Onuphidae, Annelida)

description: Additional file 2. List of specimens used in this study with voucher numbers, accession numbers, BOLD process IDs and locality data. Accession numbers for the sequences obtained in this study are marked in bold.
DOI: 10.6084/m9.figshare.25017883
title: Additional file 1 of Wide-spread dispersal in a deep-sea brooding polychaete: the role of natural history collections in assessing the distribution in quill worms (Onuphidae, Annelida)

description: Additional file 1. Uncorrected pairwise within- and between clade distances of the markers analyzed in this study (COI, 16S rRNA, 18S rRNA, ITS1, ITS2, and 28S rRNA).
DOI: 10.6084/m9.figshare.25017883.v1
title: Additional file 1 of Wide-spread dispersal in a deep-sea brooding polychaete: the role of natural history collections in assessing the distribution in quill worms (Onuphidae, Annelida)

description: Additional file 1. Uncorrected pairwise within- and between clade distances of the markers analyzed in this study (COI, 16S rRNA, 18S rRNA, ITS1, ITS2, and 28S rRNA).
DOI: 10.6084/m9.figshare.25017886
title: Additional file 2 of Wide-spread dispersal in a deep-sea brooding polychaete: the role of natural history collections in assessing the distribution in quill worms (Onuphidae, Annelida)

description: Additional file 2. List of specimens used in this study with voucher numbers, accession numbers, BOLD process IDs and locality data. Accession numbers for the sequences obtained in this study are marked in bold.
DOI: 10.6084/m9.figshare.25017889
title: Additional file 3 of Wide-spread dispersal in a deep-sea brooding polychaete: the role of natural history collections in assessing the distribution in quill worms (Onuphidae, Annelida)

description: Additional file 3. Primers and PCR settings for the markers analyzed in this study (COI, 16S rRNA, 18S rRNA, ITS1, ITS2, and 28S rRNA).
DOI: 10.6084/m9.figshare.25017889.v1
title: Additional file 3 of Wide-spread dispersal in a deep-sea brooding polychaete: the role of natural history collections in assessing the distribution in quill worms (Onuphidae, Annelida)

description: Additional file 3. Primers and PCR settings for the markers analyzed in this study (COI, 16S rRNA, 18S rRNA, ITS1, ITS2, and 28S rRNA).
DOI: 10.6084/m9.figshare.25017806
title: Additional file 1 of Sampling approaches and geographic coverage in Mayi Kuwayu: the national study of Aboriginal and Torres Strait Islander wellbeing

description: Additional file 1: Figure S1. Geographic distribution of the Mayi Kuwayu cohort by sex; Figure S2. Geographic distribution of the Mayi Kuwayu cohort by age group; Table S1. Comparison between coverage of Indigenous Regions
DOI: 10.6084/m9.figshare.25017806.v1
title: Additional file 1 of Sampling approaches and geographic coverage in Mayi Kuwayu: the national study of Aboriginal and Torres Strait Islander wellbeing

description: Additional file 1: Figure S1. Geographic distribution of the Mayi Kuwayu cohort by sex; Figure S2. Geographic distribution of the Mayi Kuwayu cohort by age group; Table S1. Comparison between coverage of Indigenous Regions
DOI: 10.6084/m9.figshare.25017845
title: Additional file 1 of Hepatocyte GPCR signaling regulates IRF3 to control hepatic stellate cell transdifferentiation

description: Additional file 1.
DOI: 10.6084/m9.figshare.25017845.v1
title: Additional file 1 of Hepatocyte GPCR signaling regulates IRF3 to control hepatic stellate cell transdifferentiation

description: Additional file 1.
DOI: 10.6084/m9.figshare.25017743
title: Data/Code for Guzy et al_2019_Influence of riparian buffers and habitat characteristics on salamander assemblages in headwater streams within managed forests

description: This repository includes data, code for the model, and code to make basic plots for the hierarchical salamander community occupancy model of [Guzy, J., Halloran, K., Homyack, J. and Willson, J.D., 2019. Influence of riparian buffers and habitat characteristics on salamander assemblages in headwater streams within managed forests. <i>Forest Ecology and Management</i>, <i>432</i>, pp.868-883. https://doi.org/10.1016/j.foreco.2018.10.006 ]We sampled salamanders with repeated, time, and area-constrained surveys within riparian streamside management zones (SMZs) during April–June 2014, 2015, and 2016. We used a multi-species, hierarchical Bayesian model developed by Zipkin et al. (2009) and modified by Hunt et al. (2013) to estimate species-specific occupancy responses to site-specific covariates (average SMZ width, stand age categories, SMZ composition, Site PC1, and Site PC2) and sampling covariates (PC1 and PC2). Data include Species occurrence files (n=10 species) are stored as a .csv for each species which includes presence-absence data for 102 sites during 4 surveys. Data are brought into Program R, and the model is run using the package R2Winbugs. The provided code ("Multi_species_occupancy_annotated_Guzy_et_al_2019.R") reads in each species and compiles one large encounter matrix ('X') which gets sent to the model. Site covariates are provided in file titled "Site Covariates". Sampling covariates are provided in the files titled "pc1" and "pc2". The annotated model is provided as well as code to generate some basic plots.
DOI: 10.6084/m9.figshare.25017743.v1
title: Data/Code for Guzy et al_2019_Influence of riparian buffers and habitat characteristics on salamander assemblages in headwater streams within managed forests

description: This repository includes data, code for the model, and code to make basic plots for the hierarchical salamander community occupancy model of [Guzy, J., Halloran, K., Homyack, J. and Willson, J.D., 2019. Influence of riparian buffers and habitat characteristics on salamander assemblages in headwater streams within managed forests. <i>Forest Ecology and Management</i>, <i>432</i>, pp.868-883. https://doi.org/10.1016/j.foreco.2018.10.006 ]We sampled salamanders with repeated, time, and area-constrained surveys within riparian streamside management zones (SMZs) during April–June 2014, 2015, and 2016. We used a multi-species, hierarchical Bayesian model developed by Zipkin et al. (2009) and modified by Hunt et al. (2013) to estimate species-specific occupancy responses to site-specific covariates (average SMZ width, stand age categories, SMZ composition, Site PC1, and Site PC2) and sampling covariates (PC1 and PC2). Data include Species occurrence files (n=10 species) are stored as a .csv for each species which includes presence-absence data for 102 sites during 4 surveys. Data are brought into Program R, and the model is run using the package R2Winbugs. The provided code ("Multi_species_occupancy_annotated_Guzy_et_al_2019.R") reads in each species and compiles one large encounter matrix ('X') which gets sent to the model. Site covariates are provided in file titled "Site Covariates". Sampling covariates are provided in the files titled "pc1" and "pc2". The annotated model is provided as well as code to generate some basic plots.
DOI: 10.6084/m9.figshare.25018007
title: Maza-Marquez-2024-supplemental-trees

description: These are supplemental trees in Newick format for the 2024 publication "Community ecology and functional potential of bacteria, archaea, eukarya, and viruses in Guerrero Negro microbial mat" by Maza-Marquez et al.
DOI: 10.6084/m9.figshare.25018007.v1
title: Maza-Marquez-2024-supplemental-trees

description: These are supplemental trees in Newick format for the 2024 publication "Community ecology and functional potential of bacteria, archaea, eukarya, and viruses in Guerrero Negro microbial mat" by Maza-Marquez et al.
DOI: 10.57770/p3tk72
title: Visium Spatial Gene Expression of embryonic mouse brain at embryonic day 15.5

description: Lissencephaly is a congenital neurodevelopmental disorder characterized by a complete loss of or simplified convolutions on the brain surface. It has been reported to result from genetic variants that lead to neuronal migration defects during cortical development. However, genetic causes inof nearly one-fifth of lissencephaly patients remain unidentified. Using trio whole exome sequencing (WES), we identified a de novo BAIAP2 variant p.Arg29Trp from a Taiwanese lissencephaly patient with a posterior more severe than anterior (P &gt; A) gradient, implicating BAIAP2 as a potential lissencephaly gene. Using spatial gene expression profiling, in situ hybridization, and immunofluorescence staining in the developing cortex, we found that Baiap2 was expressed in the cortical plate (CP) and intermediate zone (IZ) in an anterior low to posterior high gradient. To examine the potential roles of BAIAP2 in the pathogenesis of lissencephaly, we used in utero electroporation to explore the effects of the Baiap2 variant in the developing mouse cortex. We found that Baiap2 knockdown caused abnormalities in the migration, morphogenesis and differentiation of developing neurons. Expression of the p.Arg29Trp variant failed to rescue the migration defect, suggesting a loss-of-function effect of this variant. Mechanistically, we found that the variant interfered with the ability of BAIAP2 to localize to the cell membrane. These results suggest that BAIAP2 functions in the cytoskeleton, cell morphogenesis and migration, which are important for cortical development and the pathogenesis of human lissencephaly in humans.
DOI: 10.57770/iwasql
title: Single Cell RNA sequencing of embryonic mouse brain at embryonic day 13.5 and 15.5

description: The development of the cerebral cortex involves a series of dynamic events, including cell proliferation and migration, which rely on the motor protein dynein and its regulators NDE1 and NDEL1. While the NDE1 loss -of -function in NDE1 leads to microcephaly-related malformations of cortical development (MCDs), NDEL1 variants have not been founddetected in MCD patients. Here, we identified two patients with pachygyria, andwith or without subcortical band heterotopia (SBH), carrying the same a the first de novo lissencephaly-associatedsomatic mosaic NDEL1 variant, p.Arg105Pro (p.R105P), in two patients who presented with pachygyria and subcortical heterotopia. Through single-cell RNA sequencing and spatial transcriptomice analysis, we observed complementary expression of Nde1/NDE1 and Ndel1/NDEL1 in neural progenitors and postmitotic neurons, respectively. Ndel1 knockdown by in utero electroporation resulted in impaired neuronal migration, a phenotype that could not be rescued by p.R105P. Remarkably, p.R105P expression alone strongly disrupted neuronal migration, increased the length of the leading process, and impaired nucleus-centrosome coupling, suggesting a failure in nucleokinesis. Mechanistically, p.R105P disrupted NDEL1 binding to the dynein regulator LIS1. These cellular and molecular dysfunctions may underlie the pathogenesis of lissencephaly. This study identifies the first lissencephaly-associated NDEL1 variants andese results also sheds light on the distinct roles of NDE1 and NDEL1 in nucleokinesis and MCD pathogenesis.
DOI: 10.5281/zenodo.10526150
title: Wenatchee salmon management modeling objects

description: There are two .Rdata files inlcuded here. 

1) stan_run_non_centered_hatch_4_12.Rdata contains posterior samples of an integrated populatin model for spring Chinook salmon in the Wenatchee River Basin

2) list_of_sims_8_11_22.Rdata contains results of population-projection simulations under alternative habitat restoration and hatchery management strategies.
DOI: 10.5281/zenodo.10526151
title: Wenatchee salmon management modeling objects

description: There are two .Rdata files inlcuded here. 

1) stan_run_non_centered_hatch_4_12.Rdata contains posterior samples of an integrated populatin model for spring Chinook salmon in the Wenatchee River Basin

2) list_of_sims_8_11_22.Rdata contains results of population-projection simulations under alternative habitat restoration and hatchery management strategies.
DOI: 10.5281/zenodo.10526194
title: R2D Tool Example E12IstanbulRegionalSeismicRiskAnalysis

description: This dataset comes from the following work:
DOI: 10.5281/zenodo.7947036
title: R2D Tool Example E12IstanbulRegionalSeismicRiskAnalysis

description: This dataset comes from the following work:
DOI: 10.5281/zenodo.7947037
title: R2D Tool Example E12IstanbulRegionalSeismicRiskAnalysis

description: This dataset comes from the following work:
DOI: 10.5281/zenodo.10526240
title: Data of industrial heat source between 2012 and 2021 using long-term Active Fire/Hotspot data in China

description: Industrial heat sources serve as crucial indicators of energy consumption levels and air pollution. Energy-intensive industries are facing substantial challenges in transforming and upgrading in China. Therefore, accurately identifying industrial heat source locations and monitoring their temporal patterns are becoming utmost importance. In this study, a long-term industrial heat source datasets between 2012 and 2021 in China using long-term Active Fire/Hotspots (ACF) data has been constructed to monitor and analyze large-scale industrial heat sources. Firstly, density segmentation method based on an improved k-means algorithm using long-term ACF data and spatial topological correlation analysis was conducted to build industrial heat sources. Then, 4410 industrial heat sources were obtained between 2012 and 2021 in China, with an identification accuracy of 95.08% by manual verification using high-resolution remote sensing images and point of interest (POI) data. Finally, the trend in the spatio-temporal variation of industrial heat sources was analyzed using long-term series. The results from 2012 to 2021 showed that the spatial distribution of industrial heat sources in China exhibits local aggregation and a gradual shift from east to west.And,the number of industrial heat sources in China has followed a trend of an initial increase from 2012 to 2014, followed by a decrease since 2014, consistent with national energy reform-related policies.The result of this study indicated the temporal variation of industrial heat sources, enhanced the accuracy of fire points category identification, and demonstrated potential for advancing energy efficiency, emission reduction, and sustainable development in China.
DOI: 10.5281/zenodo.7824014
title: Data of industrial heat source between 2012 and 2021 using long-term Active Fire/Hotspot data in China

description: Industrial heat sources serve as crucial indicators of energy consumption levels and air pollution. Energy-intensive industries are facing substantial challenges in transforming and upgrading in China. Therefore, accurately identifying industrial heat source locations and monitoring their temporal patterns are becoming utmost importance. In this study, a long-term industrial heat source datasets between 2012 and 2021 in China using long-term Active Fire/Hotspots (ACF) data has been constructed to monitor and analyze large-scale industrial heat sources. Firstly, density segmentation method based on an improved k-means algorithm using long-term ACF data and spatial topological correlation analysis was conducted to build industrial heat sources. Then, 4410 industrial heat sources were obtained between 2012 and 2021 in China, with an identification accuracy of 95.08% by manual verification using high-resolution remote sensing images and point of interest (POI) data. Finally, the trend in the spatio-temporal variation of industrial heat sources was analyzed using long-term series. The results from 2012 to 2021 showed that the spatial distribution of industrial heat sources in China exhibits local aggregation and a gradual shift from east to west.And,the number of industrial heat sources in China has followed a trend of an initial increase from 2012 to 2014, followed by a decrease since 2014, consistent with national energy reform-related policies.The result of this study indicated the temporal variation of industrial heat sources, enhanced the accuracy of fire points category identification, and demonstrated potential for advancing energy efficiency, emission reduction, and sustainable development in China.
DOI: 10.5517/ccdc.csd.cc2fnx34
title: CCDC 2254416: Experimental Crystal Structure Determination

description: Related Article: Zhihu Ma, Yixia Ren, Xiaoming Song, Zhaoyu Li, Xiufang Hou|2024|J.Mol.Struct.|1301|137357|doi:10.1016/j.molstruc.2023.137357
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.cc2fpn71
title: CCDC 2255133: Experimental Crystal Structure Determination

description: Related Article: Lu-Lu Gan, Xun Li, Ming-Xia Du, Yuan-Ji Yan, Yang Zhang, Wen-Kui Dong, Yu-Jie Ding|2024|J.Mol.Struct.|1299|137199|doi:10.1016/j.molstruc.2023.137199
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.cc2fpn93
title: CCDC 2255135: Experimental Crystal Structure Determination

description: Related Article: Lu-Lu Gan, Xun Li, Ming-Xia Du, Yuan-Ji Yan, Yang Zhang, Wen-Kui Dong, Yu-Jie Ding|2024|J.Mol.Struct.|1299|137199|doi:10.1016/j.molstruc.2023.137199
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.cc2frhzp
title: CCDC 2256923: Experimental Crystal Structure Determination

description: Related Article: Meng Li, Weiwei Wang, Xiang Cheng, Yunxiao Wang, Yao Chen, Jiexiu Gong, Xihao Chang, Xianhai Lv|2023|J.Agric.Food Chem.|71|11365|doi:10.1021/acs.jafc.3c02671
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.cc2fsnlh
title: CCDC 2258027: Experimental Crystal Structure Determination

description: Related Article: Jingwen Shi, Yunan Zhang, Qi An, Yujiao Li, Lixin Liu|2024|J.Solid State Chem.|331|124545|doi:10.1016/j.jssc.2023.124545
description: Related Article: Jingwen Shi|2023|CSD Communication|||
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.cc2fv04g
title: CCDC 2259315: Experimental Crystal Structure Determination

description: Related Article: İsmail Yilmaz|2024|Polyhedron|250|116816|doi:10.1016/j.poly.2023.116816
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.cc2fv05h
title: CCDC 2259316: Experimental Crystal Structure Determination

description: Related Article: İsmail Yilmaz|2024|Polyhedron|250|116816|doi:10.1016/j.poly.2023.116816
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.