cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.23708925.v4
title: Comparative Analysis of Pathological Characteristics and Prognostic Outcomes in Malignant Thyroid Tumors with Single and Co-existing <i>RAS</i> Mutations

description: Background: The implications of RAS mutations in malignant thyroid tumors are under scrutiny, focusing on prevalence, clinicopathological features, and prognosis. Methods: Centers include patients with malignant thyroid tumors from the TCGA, ICGC, MSKCC, and a multi-center thyroid cancer cohort in China. Pubmed/MEDLINE and Embase libraries were included in the systematic review. The differences in demography, clinical pathology, and prognosis of four distinct mutation groups ("non-mutation, single RAS mutation, driver mutation, and RAS co-mutation") were analyzed. Results: 21,370 patients with thyroid tumors who underwent RAS mutation testing were included. The overall frequency of RAS mutations was 19.34% (NRAS:12.94%&gt;HRAS:6.61%&gt;KRAS:5.00%). RAS co-mutations were more prevalent in tumors with lower differentiation levels. Importantly, RAS co-mutation, but not single RAS mutation increased the risk of Distant Metastasis (OR=12.28; 95%CI,3.19-47.25; P&lt;0.001), Advanced AJCC Stage (OR=4.60; 95%CI,1.91-11.08; P=0.001), Overall Survival (OS) (HR=2.90; 95%CI,1.63-5.13; P&lt;0.001), and Progression-free Survival (PFS) (HR=6.77; 95%CI,6.77-18.87; P&lt;0.001) compared with the non-mutation group. We also found the driver mutation group exhibited a higher risk of Extrathyroidal Extension, Advanced Tumor Stage, Lymph Node Metastasis, Distant Metastasis, Advanced AJCC Stage, OS, and PFS. Conclusions: RAS co-mutations might be the main contributor to malignant clinicopathological characteristics or prognosis, single RAS mutation not.
DOI: 10.6084/m9.figshare.23708925.v3
title: Comparative Analysis of Pathological Characteristics and Prognostic Outcomes in Malignant Thyroid Tumors with Single and Co-existing <i>RAS</i> Mutations

description: Background: The implications of RAS mutations in malignant thyroid tumors are under scrutiny, focusing on prevalence, clinicopathological features, and prognosis. Methods: Centers include patients with malignant thyroid tumors from the TCGA, ICGC, MSKCC, and a multi-center thyroid cancer cohort in China. Pubmed/MEDLINE and Embase libraries were included in the systematic review. The differences in demography, clinical pathology, and prognosis of four distinct mutation groups ("non-mutation, single RAS mutation, driver mutation, and RAS co-mutation") were analyzed. Results: 21,370 patients with thyroid tumors who underwent RAS mutation testing were included. The overall frequency of RAS mutations was 19.34% (NRAS:12.94%&gt;HRAS:6.61%&gt;KRAS:5.00%). RAS co-mutations were more prevalent in tumors with lower differentiation levels. Importantly, RAS co-mutation, but not single RAS mutation increased the risk of Distant Metastasis (OR=12.28; 95%CI,3.19-47.25; P&lt;0.001), Advanced AJCC Stage (OR=4.60; 95%CI,1.91-11.08; P=0.001), Overall Survival (OS) (HR=2.90; 95%CI,1.63-5.13; P&lt;0.001), and Progression-free Survival (PFS) (HR=6.77; 95%CI,6.77-18.87; P&lt;0.001) compared with the non-mutation group. We also found the driver mutation group exhibited a higher risk of Extrathyroidal Extension, Advanced Tumor Stage, Lymph Node Metastasis, Distant Metastasis, Advanced AJCC Stage, OS, and PFS. Conclusions: RAS co-mutations might be the main contributor to malignant clinicopathological characteristics or prognosis, single RAS mutation not.
DOI: 10.6084/m9.figshare.24563254
title: Commits Analysis for Author Expertise

description: Empirical Analysis on CI/CD Pipeline Evolution in Machine Learning Projects
DOI: 10.6084/m9.figshare.24563254.v1
title: Commits Analysis for Author Expertise

description: Empirical Analysis on CI/CD Pipeline Evolution in Machine Learning Projects
DOI: 10.6084/m9.figshare.24563257
title: Side Effects and Efficacy of CoronaVac® Covid-19 Vaccination

description: Side Effects and Efficacy of CoronaVac® Covid-19 Vaccination: Investigation in North Jakarta District Public Health Center Communities in Indonesia
DOI: 10.6084/m9.figshare.24563257.v1
title: Side Effects and Efficacy of CoronaVac® Covid-19 Vaccination

description: Side Effects and Efficacy of CoronaVac® Covid-19 Vaccination: Investigation in North Jakarta District Public Health Center Communities in Indonesia
DOI: 10.6084/m9.figshare.24563236
title: Industrial water use spatial dataset

description: The spatially distributed industrial water use dataset is created using a Random forest regression model at 0.5<sup>0</sup> resolution. The file contains the input and output datasets, explained in the 'README.txt' file in each folder. It also contains the Python codes created while preparing the datasets.
DOI: 10.6084/m9.figshare.24563236.v1
title: Industrial water use spatial dataset

description: The spatially distributed industrial water use dataset is created using a Random forest regression model at 0.5<sup>0</sup> resolution. The file contains the input and output datasets, explained in the 'README.txt' file in each folder. It also contains the Python codes created while preparing the datasets.
DOI: 10.6084/m9.figshare.24563274
title: Annex 6 from Drivers of microbial food-web structure along productivity gradients

description: (D, data that were available in terms of data rights)
DOI: 10.6084/m9.figshare.24563274.v1
title: Annex 6 from Drivers of microbial food-web structure along productivity gradients

description: (D, data that were available in terms of data rights)
DOI: 10.6084/m9.figshare.24288667
title: Burian_annex_2 from Drivers of microbial food-web structure along productivity gradients

description: R code of SEM
DOI: 10.6084/m9.figshare.24563277
title: Annex 11 from Drivers of microbial food-web structure along productivity gradients

description: (A; size spectra of most common eukaryotic plankton species)
DOI: 10.6084/m9.figshare.24563277.v1
title: Annex 11 from Drivers of microbial food-web structure along productivity gradients

description: (A; size spectra of most common eukaryotic plankton species)
DOI: 10.6084/m9.figshare.24563283
title: Annex 8 from Drivers of microbial food-web structure along productivity gradients

description: (A, weather data from L. Nakuru and L. Bogoria, respectively)
DOI: 10.6084/m9.figshare.24563283.v1
title: Annex 8 from Drivers of microbial food-web structure along productivity gradients

description: (A, weather data from L. Nakuru and L. Bogoria, respectively)
DOI: 10.6084/m9.figshare.24563286
title: Annex 4 from Drivers of microbial food-web structure along productivity gradients

description: (A; master-data file of the Arthrospira project)
DOI: 10.6084/m9.figshare.24563286.v1
title: Annex 4 from Drivers of microbial food-web structure along productivity gradients

description: (A; master-data file of the Arthrospira project)
DOI: 10.6084/m9.figshare.24563289
title: Annex 7 from Drivers of microbial food-web structure along productivity gradients

description: (A, weather data from L. Nakuru and L. Bogoria, respectively)
DOI: 10.6084/m9.figshare.24563289.v1
title: Annex 7 from Drivers of microbial food-web structure along productivity gradients

description: (A, weather data from L. Nakuru and L. Bogoria, respectively)
DOI: 10.6084/m9.figshare.24288673
title: Burian_annex_3 from Drivers of microbial food-web structure along productivity gradients

description: Data for SEM from two African soda-lakes
DOI: 10.6084/m9.figshare.24288673.v1
title: Burian_annex_3 from Drivers of microbial food-web structure along productivity gradients

description: Data for SEM from two African soda-lakes
DOI: 10.6084/m9.figshare.24288676
title: Burian_annex_1 from Drivers of microbial food-web structure along productivity gradients

description: Data used for the meta-analyses on bacteria-virus and chlorophyll-bacteria relationships
DOI: 10.6084/m9.figshare.24563280
title: Annex 10 from Drivers of microbial food-web structure along productivity gradients

description: (A, insitu light and T data from 2cm and 20cm under the water surface measured in L. Nakuru and L. Bogoria, respectively)
DOI: 10.6084/m9.figshare.24288676.v1
title: Burian_annex_1 from Drivers of microbial food-web structure along productivity gradients

description: Data used for the meta-analyses on bacteria-virus and chlorophyll-bacteria relationships
DOI: 10.6084/m9.figshare.24563280.v1
title: Annex 9 from Drivers of microbial food-web structure along productivity gradients

description: (A, insitu light and T data from 2cm and 20cm under the water surface measured in L. Nakuru and L. Bogoria, respectively)
DOI: 10.6084/m9.figshare.24563280.v3
title: Annex 10 from Drivers of microbial food-web structure along productivity gradients

description: (A, insitu light and T data from 2cm and 20cm under the water surface measured in L. Nakuru and L. Bogoria, respectively)
DOI: 10.6084/m9.figshare.24563280.v2
title: readme.txt from Drivers of microbial food-web structure along productivity gradients

description: Ratios between viruses, heterotrophic prokaryotes and chlorophyll <i>a</i> are key indicators of microbial food structure and both virus-prokaryote and prokaryote-chlorophyll ratios have been proposed to decrease with system productivity. However, the mechanisms underlying these responses are still insufficiently resolved and their consistency across aquatic ecosystem types requires critical evaluation. We assessed microbial community ratios in highly productive African soda-lakes and used our data from naturally hypereutrophic systems which are largely underrepresented in literature, to complement earlier across-system meta-analyses. In contrast to marine and freshwater systems, prokaryote-chlorophyll ratios in African soda-lakes did not decrease along productivity gradients. High-resolution time series from two soda-lakes indicated that this lack of response could be driven by a weakened top–down control of heterotrophic prokaryotes. Our analysis of virus–prokaryote relationships, revealed a reduction of virus–prokaryote ratios by high suspended particle concentrations in soda-lakes. This effect, likely driven by the adsorption of free-living viruses, was also found in three out of four additionally analysed marine datasets. However, the decrease of virus–prokaryote ratios previously reported in highly productive marine systems, was neither detectable in soda-lakes nor freshwaters. Hence, our study demonstrates that system-specific analyses can reveal the diversity of mechanisms that structure microbial food-webs and shape their response to productivity increases.
DOI: 10.6084/m9.figshare.24563292.v1
title: Annex 5 from Drivers of microbial food-web structure along productivity gradients

description: (B, data file used for the analysis)
DOI: 10.6084/m9.figshare.24563292
title: Annex 5 from Drivers of microbial food-web structure along productivity gradients

description: (B, data file used for the analysis)
DOI: 10.18141/1471973
title: Geocube

description: NOTICE: Geocube has been replaced by EDX Spatial, a modern geospatial platform to map, visualize, query and explore spatial data. Online web mapping tool for visualization and simple analysis of Earth-energy data files from public and DOE related sources. Geocube allows users to upload and visualize their own datasets but also comes preloaded with individual spatial datasets as well as spatial data collections that align to topical themes.
DOI: 10.21947/1958708
title: TTU-X Dual Doppler Synthesis

description: Dual-Doppler data fields from the TTU-X1 and TTU-X2 radars were interpolated to a Cartesian grid.
DOI: 10.21947/1959723
title: Lidar - Hawaii - Leosphere Windcube 866 (120), Oahu / Processed Data

description: The purpose of this dataset is to provide preliminary filtered, averaged lidar data and to standardize the data format of various datastreams from the buoy into NetCDF.
DOI: 10.6084/m9.figshare.24563314
title: Genome Data of Adenosma buchneroides Bonatie

description: Adenosma buchneroides Genome Sequencing and Assembly
DOI: 10.6084/m9.figshare.24563314.v1
title: Genome Data of Adenosma buchneroides Bonatie

description: Adenosma buchneroides Genome Sequencing and Assembly
DOI: 10.57931/2205512
title: Data for Hadjimichael et al. - Multi-actor, multi-impact scenario discovery

description: Naming convention for each file is S[scenario_id]_[realization_id].parquet All realizations are generated as per the accompanying paper: Hadjimichael, A., Reed, P.M., Quinn, J.D, Vernon, C.R., Thurber, T., Multi-actor, multi-impact scenario discovery of consequential narrative storylines for human-natural systems planning. Earth's Future (In Review) Each .parquet file contains the following columns: 'structure_id' : StateMod structure ID data corresponds to 'year': simulation year 'month': simulation month 'demand': water demand in acre-feet 'shortage': water shortage in acre-feet 'river_outflow': streamflow in diversion location in acre-feet 'control_location': other structure or reason for shortage
DOI: 10.7799/2205626
title: NREL 25-cm2 High-Pressure Low-Temperature Electrolysis Cell Hardware (Open Source)

description: This data resource describes an open-source cell hardware that enables low temperature electrolysis (LTE) testing at elevated pressures. Existing commercial options have several downsides when it comes to R&D testing. They are often not designed for repeated reassembly, may not be able to accommodate porous transport layers with different thicknesses, and do not give state-of-the-art performance. Therefore, this hardware was developed specifically with LTE R&D in mind and its design is being made available to the global LTE community. This work was planned and funded by the U.S. Department of Energy's H2NEW consortium (https://h2new.energy.gov/). The hardware design package (.zip file) details the drawings, auxiliary materials, and procedures required to fabricate, assemble, and operate the National Renewable Energy Laboratory's (NREL's) high-pressure low-temperature electrolysis cells. While the hardware itself—end plates, current collectors, flow fields, bolts and washers, tube fittings—is always the same, the assembly and operating procedures may change depending on the active materials being tested, especially for the membrane. Material-specific assembly and operating procedures will be posted to the H2NEW website as they are developed and validated. Disclaimer: The documents and drawings included in this download package describe a design for a low temperature electrolysis hardware that is intended to comply with leak testing according to ASME B31.1. Safe operation at ambient and elevated pressures is the sole responsibility of the end user, which should be evaluated on a case-by-case basis for each individual cell. Factors affecting the sealing capability may depend on, for example, machining quality, cell assembly components, operating conditions, and operating history. Operation at pressure should only be performed on qualified test stands by qualified operators. NREL/ALLIANCE FOR SUSTAINABLE ENERGY, LLC/DOE DISCLAIM ALL WARRANTIES, EXPRESS OR IMPLIED, INCLUDING THE WARRANTIES OF MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE, AND MAKES NO WARRANTY AS TO THE ACCURACY, COMPLETENESS, OR USEFULNESS OF ANY INFORMATION PROVIDED HEREIN. USE OF THIS PACKAGE IS AT THE USER’S OWN RISK.
DOI: 10.15473/2205673
title: CODAS Data from Oliktok Point, Beaufort Sea, Alaska

description: Cryosphere/Ocean Distributed Acoustic Sensing (CODAS) data collected from the Beaufort Sea, Alaska, using ~37.4 km of dark telecommunications fiber located at Oliktok Point, Alaska. Data were collected with a Silixa iDAS, using 10 m gauge length, 2 m spatial resolution, and 1000 Hz sample rate. Provided here are the DAS-recorded time series for the rapid refreeze event described in Baker & Abbott (2022) (see link below). This covers a date range of 2021-11-10 15:00 UTC to 2021-11-11 17:00 UTC. Data have been decimated to 100 Hz and 20 m (i.e., every 10th channel for 1831 channels, total), as used in Baker & Abbott (2022). Data have been extracted from raw format into 1-hour long .sac* files and organized into directories by channel number, spanning channels 100 to 18400. Time series units are nano-strainrate (nm/m/s). For distribution, data have been compressed into .zip files containing all time series files for 100 channels. *For information on the Seismic Analysis Code (SAC) file format: https://seiscode.iris.washington.edu/projects/sac
DOI: 10.6084/m9.figshare.24563368
title: <b>A phase II prospective study of the usefulness of the Franseen needle in endobronchial ultrasound-guided transbronchial needle aspiration</b>

description: Data sharing
DOI: 10.6084/m9.figshare.24563368.v1
title: <b>A phase II prospective study of the usefulness of the Franseen needle in endobronchial ultrasound-guided transbronchial needle aspiration</b>

description: Data sharing
DOI: 10.6084/m9.figshare.24563590
title: Energy transition index for 282 Chinese cities

description: The global target of limiting the increase in temperature to 1.5°C requires a shift from fossil fuels to renewable sources of energy, particularly in urban areas that house over half of the world's population and are major consumers of energy and emitters of carbon. However, cities vary in their energy systems and socioeconomic capacities to transition to renewable energy. To address this heterogeneity, this study proposes an Energy Transition Index (ETI) specifically designed for cities, and applies it to track the progress of energy transition in Chinese cities. The city-level ETI framework is based on the national ETI developed by the World Economic Forum (WEF) and comprises two sub-indexes: the Energy System Performance sub-index, which evaluates the current status of cities' energy systems in terms of energy transition, and the Transition Readiness sub-index, which assesses their socioeconomic capacity for future energy transition. The Energy System Performance sub-index includes two dimensions and seven components, while the Transition Readiness sub-index has four dimensions and eleven components. Each component consists of one or more indicators. The initial version of the dataset includes ETI and its sub-indexes for 282 Chinese cities from 2003 to 2019, with annual updates planned. The spatiotemporal data provided by the dataset facilitates research into the energy transition roadmap for different cities, which can help China achieve its energy transition goals.
DOI: 10.25345/c5x921v7r
title: MassIVE MSV000093400 - Chemogenetic restoration of astrocyte morphology is beneficial in obsessive-compulsive disorder
title: In vivo chemogenetic activation of astrocytes in the striatum via an engineered Gi-protein-coupled receptor was conducted in wild-type and SAPAP3 KO OCD mice. The resultant striatal tissue was extracted, homogenized in a detergent-free buffer, digested, and analyzed with LC/MS-MS.
DOI: 10.5281/zenodo.10128097
title: data4QJsubmission
DOI: 10.5281/zenodo.10128098
title: data4QJsubmission
DOI: 10.5281/zenodo.10129176
title: Data and Code for PM2.5 assimilation and health assessment in "Ultra-high-resolution mapping of ambient fine particulate matter to estimate human exposure in Beijing"
DOI: 10.5281/zenodo.10129177
title: Data and Code for PM2.5 assimilation and health assessment in "Ultra-high-resolution mapping of ambient fine particulate matter to estimate human exposure in Beijing"
DOI: 10.5281/zenodo.10129411
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Bonita J. Neiland, http://www.wikidata.org/entity/Q123199078. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q123199078
DOI: 10.5281/zenodo.10129412
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Bonita J. Neiland, http://www.wikidata.org/entity/Q123199078. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q123199078
DOI: 10.23728/b2share.98f873f4c37c4457817a9e183ff67d2d
title: Gesäuse-Johnsbachtal, Austria - Age profile, education attainment, residential pro

description: Age Profile, Education Attainment, Residential Profile
DOI: 10.5281/zenodo.10129420
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Charles Albert Bridges III, http://www.wikidata.org/entity/Q21393019. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q21393019
DOI: 10.5517/ccdc.csd.cc2g7stb
title: CCDC 2271612: Experimental Crystal Structure Determination

description: Related Article: Yongbo Tan, Huawen Huang|2023|Chem.Commun.|59|13462|doi:10.1039/D3CC04542K
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.cc2g801t
title: CCDC 2271805: Experimental Crystal Structure Determination

description: Related Article: Xiaojie Ren, Xiao-Yong Duan, Yanting Li, Jiahan Li, Jing Qi|2023|Org.Lett.|25|7917|doi:10.1021/acs.orglett.3c03171
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.10129425
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Jack Rodney Laundon, http://www.wikidata.org/entity/Q13426189. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q13426189
DOI: 10.5281/zenodo.10129426
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Jack Rodney Laundon, http://www.wikidata.org/entity/Q13426189. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q13426189
DOI: 10.5281/zenodo.10129429
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Henri Jacques-Félix, http://www.wikidata.org/entity/Q5894429. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q5894429
DOI: 10.5281/zenodo.10129430
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Henri Jacques-Félix, http://www.wikidata.org/entity/Q5894429. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q5894429
DOI: 10.5281/zenodo.10129170
title: Ethereum Transaction Data used for End-user Comprehension of Transfer Risks in Smart Contracts