cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25345/c5vt1gt2f
title: MassIVE Reanalysis RMSV000000423.3 - CCMS MassIVE Knowledge Base (MassIVE-KB) MS-GF+ reanalysis of MSV000078831 [1 out of 3] [launched by cfca6e4ba8934e65aa11617b56091339]
title: Center for Computational Mass Spectrometry (CCMS) systematic reanalysis of public proteomics mass spectrometry (MS) datasets provides a public, large-scale and comparable set of dataset reanalyses results including detailed provenance records. To further facilitate the broad reusability of public proteomics MS data, these reanalyses were also used to build the MassIVE Knowledge Base (MassIVE-KB) spectral library, a community-wide resource derived from hundreds of millions of identified spectra from tens of terabytes of mass spectrometry data.
DOI: 10.25345/c5r20s09w
title: MassIVE Reanalysis RMSV000000382.39 - CCMS MassIVE Knowledge Base (MassIVE-KB) MS-GF+ reanalysis of MSV000080596/PXD004242 [48 out of 51] [launched by cfca6e4ba8934e65aa11617b56091339]
title: Center for Computational Mass Spectrometry (CCMS) systematic reanalysis of public proteomics mass spectrometry (MS) datasets provides a public, large-scale and comparable set of dataset reanalyses results including detailed provenance records. To further facilitate the broad reusability of public proteomics MS data, these reanalyses were also used to build the MassIVE Knowledge Base (MassIVE-KB) spectral library, a community-wide resource derived from hundreds of millions of identified spectra from tens of terabytes of mass spectrometry data.
DOI: 10.25345/c5m90266m
title: MassIVE Reanalysis RMSV000000366.39 - CCMS MassIVE Knowledge Base (MassIVE-KB) MS-GF+ reanalysis of MSV000086387 A Quantitative Proteome Map of the Human Body, TMT10 MS3 [Mixture: 47] [launched by cfca6e4ba8934e65aa11617b56091339]
title: Center for Computational Mass Spectrometry (CCMS) systematic reanalysis of public proteomics mass spectrometry (MS) datasets provides a public, large-scale and comparable set of dataset reanalyses results including detailed provenance records. To further facilitate the broad reusability of public proteomics MS data, these reanalyses were also used to build the MassIVE Knowledge Base (MassIVE-KB) spectral library, a community-wide resource derived from hundreds of millions of identified spectra from tens of terabytes of mass spectrometry data.
DOI: 10.25345/c5gh9bd2x
title: MassIVE Reanalysis RMSV000000366.38 - CCMS MassIVE Knowledge Base (MassIVE-KB) MS-GF+ reanalysis of MSV000086387 A Quantitative Proteome Map of the Human Body, TMT10 MS3 [Mixture: 29] [launched by cfca6e4ba8934e65aa11617b56091339]
title: Center for Computational Mass Spectrometry (CCMS) systematic reanalysis of public proteomics mass spectrometry (MS) datasets provides a public, large-scale and comparable set of dataset reanalyses results including detailed provenance records. To further facilitate the broad reusability of public proteomics MS data, these reanalyses were also used to build the MassIVE Knowledge Base (MassIVE-KB) spectral library, a community-wide resource derived from hundreds of millions of identified spectra from tens of terabytes of mass spectrometry data.
DOI: 10.25345/c5br8mk66
title: MassIVE Reanalysis RMSV000000366.40 - CCMS MassIVE Knowledge Base (MassIVE-KB) MS-GF+ reanalysis of MSV000086387 A Quantitative Proteome Map of the Human Body, TMT10 MS3 [Mixture: 43] [launched by cfca6e4ba8934e65aa11617b56091339]
title: Center for Computational Mass Spectrometry (CCMS) systematic reanalysis of public proteomics mass spectrometry (MS) datasets provides a public, large-scale and comparable set of dataset reanalyses results including detailed provenance records. To further facilitate the broad reusability of public proteomics MS data, these reanalyses were also used to build the MassIVE Knowledge Base (MassIVE-KB) spectral library, a community-wide resource derived from hundreds of millions of identified spectra from tens of terabytes of mass spectrometry data.
DOI: 10.5281/zenodo.6373253
title: CT-derived Chest Muscle Metrics for Outcome Prediction in Patients with COVID-19.

description: Dataset from Schiaffino S, Albano D, Cozzi A, Messina C, Arioli R, Bnà C, Bruno A, Carbonaro LA, Carriero A, Carriero S, Danna PSC, D'Ascoli E, De Berardinis C, Della Pepa G, Falaschi Z, Gitto S, Malavazos AE, Mauri G, Monfardini L, Paschè A, Rizzati R, Secchi F, Vanzulli A, Tombini V, Vicentin I, Zagaria D, Sardanelli F, Sconfienza LM. CT-derived Chest Muscle Metrics for Outcome Prediction in Patients with COVID-19. Radiology. 2021 Aug;300(2):E328-E336. doi: 10.1148/radiol.2021204141. Epub 2021 Mar 16. PMID: 33724065; PMCID: PMC7971428. Abstract Background Lower muscle mass is a known predictor of unfavorable outcomes, but its prognostic impact on patients with COVID-19 is unknown. Purpose To investigate the contribution of CT-derived muscle status in predicting clinical outcomes in patients with COVID-19. Materials and Methods Clinical or laboratory data and outcomes (intensive care unit [ICU] admission and death) were retrospectively retrieved for patients with reverse transcriptase polymerase chain reaction-confirmed SARS-CoV-2 infection, who underwent chest CT on admission in four hospitals in Northern Italy from February 21 to April 30, 2020. The extent and type of pulmonary involvement, mediastinal lymphadenopathy, and pleural effusion were assessed. Cross-sectional areas and attenuation by paravertebral muscles were measured on axial CT images at the T5 and T12 vertebral level. Multivariable linear and binary logistic regression, including calculation of odds ratios (ORs) with 95% CIs, were used to build four models to predict ICU admission and death, which were tested and compared by using receiver operating characteristic curve analysis. Results A total of 552 patients (364 men and 188 women; median age, 65 years [interquartile range, 54-75 years]) were included. In a CT-based model, lower-than-median T5 paravertebral muscle areas showed the highest ORs for ICU admission (OR, 4.8; 95% CI: 2.7, 8.5; <em>P</em> &lt; .001) and death (OR, 2.3; 95% CI: 1.0, 2.9; <em>P</em> = .03). When clinical variables were included in the model, lower-than-median T5 paravertebral muscle areas still showed the highest ORs for both ICU admission (OR, 4.3; 95%: CI: 2.5, 7.7; <em>P</em> &lt; .001) and death (OR, 2.3; 95% CI: 1.3, 3.7; <em>P</em> = .001). At receiver operating characteristic analysis, the CT-based model and the model including clinical variables showed the same area under the receiver operating characteristic curve (AUC) for ICU admission prediction (AUC, 0.83; <em>P</em> = .38) and were not different in terms of predicting death (AUC, 0.86 vs AUC, 0.87, respectively; <em>P</em> = .28). Conclusion In hospitalized patients with COVID-19, lower muscle mass on CT images was independently associated with intensive care unit admission and in-hospital mortality. © RSNA, 2021 <em>Online supplemental material is available for this article.</em>
DOI: 10.5281/zenodo.6373252
title: CT-derived Chest Muscle Metrics for Outcome Prediction in Patients with COVID-19.

description: Dataset from Schiaffino S, Albano D, Cozzi A, Messina C, Arioli R, Bnà C, Bruno A, Carbonaro LA, Carriero A, Carriero S, Danna PSC, D'Ascoli E, De Berardinis C, Della Pepa G, Falaschi Z, Gitto S, Malavazos AE, Mauri G, Monfardini L, Paschè A, Rizzati R, Secchi F, Vanzulli A, Tombini V, Vicentin I, Zagaria D, Sardanelli F, Sconfienza LM. CT-derived Chest Muscle Metrics for Outcome Prediction in Patients with COVID-19. Radiology. 2021 Aug;300(2):E328-E336. doi: 10.1148/radiol.2021204141. Epub 2021 Mar 16. PMID: 33724065; PMCID: PMC7971428. Abstract Background Lower muscle mass is a known predictor of unfavorable outcomes, but its prognostic impact on patients with COVID-19 is unknown. Purpose To investigate the contribution of CT-derived muscle status in predicting clinical outcomes in patients with COVID-19. Materials and Methods Clinical or laboratory data and outcomes (intensive care unit [ICU] admission and death) were retrospectively retrieved for patients with reverse transcriptase polymerase chain reaction-confirmed SARS-CoV-2 infection, who underwent chest CT on admission in four hospitals in Northern Italy from February 21 to April 30, 2020. The extent and type of pulmonary involvement, mediastinal lymphadenopathy, and pleural effusion were assessed. Cross-sectional areas and attenuation by paravertebral muscles were measured on axial CT images at the T5 and T12 vertebral level. Multivariable linear and binary logistic regression, including calculation of odds ratios (ORs) with 95% CIs, were used to build four models to predict ICU admission and death, which were tested and compared by using receiver operating characteristic curve analysis. Results A total of 552 patients (364 men and 188 women; median age, 65 years [interquartile range, 54-75 years]) were included. In a CT-based model, lower-than-median T5 paravertebral muscle areas showed the highest ORs for ICU admission (OR, 4.8; 95% CI: 2.7, 8.5; <em>P</em> &lt; .001) and death (OR, 2.3; 95% CI: 1.0, 2.9; <em>P</em> = .03). When clinical variables were included in the model, lower-than-median T5 paravertebral muscle areas still showed the highest ORs for both ICU admission (OR, 4.3; 95%: CI: 2.5, 7.7; <em>P</em> &lt; .001) and death (OR, 2.3; 95% CI: 1.3, 3.7; <em>P</em> = .001). At receiver operating characteristic analysis, the CT-based model and the model including clinical variables showed the same area under the receiver operating characteristic curve (AUC) for ICU admission prediction (AUC, 0.83; <em>P</em> = .38) and were not different in terms of predicting death (AUC, 0.86 vs AUC, 0.87, respectively; <em>P</em> = .28). Conclusion In hospitalized patients with COVID-19, lower muscle mass on CT images was independently associated with intensive care unit admission and in-hospital mortality. © RSNA, 2021 <em>Online supplemental material is available for this article.</em>
DOI: 10.25345/c5707ws1w
title: MassIVE Reanalysis RMSV000000362.60 - CCMS MassIVE Knowledge Base (MassIVE-KB) MS-GF+ reanalysis of MSV000081607 Confetti, GluC-Chymotrypsin HCD [launched by cfca6e4ba8934e65aa11617b56091339]
title: Center for Computational Mass Spectrometry (CCMS) systematic reanalysis of public proteomics mass spectrometry (MS) datasets provides a public, large-scale and comparable set of dataset reanalyses results including detailed provenance records. To further facilitate the broad reusability of public proteomics MS data, these reanalyses were also used to build the MassIVE Knowledge Base (MassIVE-KB) spectral library, a community-wide resource derived from hundreds of millions of identified spectra from tens of terabytes of mass spectrometry data.
DOI: 10.25345/c53775z80
title: MassIVE Reanalysis RMSV000000362.61 - CCMS MassIVE Knowledge Base (MassIVE-KB) MS-GF+ reanalysis of MSV000081607 Confetti, LysC-Chymotrypsin-Trypsin HCD [launched by cfca6e4ba8934e65aa11617b56091339]
title: Center for Computational Mass Spectrometry (CCMS) systematic reanalysis of public proteomics mass spectrometry (MS) datasets provides a public, large-scale and comparable set of dataset reanalyses results including detailed provenance records. To further facilitate the broad reusability of public proteomics MS data, these reanalyses were also used to build the MassIVE Knowledge Base (MassIVE-KB) spectral library, a community-wide resource derived from hundreds of millions of identified spectra from tens of terabytes of mass spectrometry data.
DOI: 10.25345/c5zk55q6b
title: MassIVE Reanalysis RMSV000000416.7 - CCMS MassIVE Knowledge Base (MassIVE-KB) MS-GF+ reanalysis of MSV000080860/PXD003902 [3 out of 8] [launched by cfca6e4ba8934e65aa11617b56091339]
title: Center for Computational Mass Spectrometry (CCMS) systematic reanalysis of public proteomics mass spectrometry (MS) datasets provides a public, large-scale and comparable set of dataset reanalyses results including detailed provenance records. To further facilitate the broad reusability of public proteomics MS data, these reanalyses were also used to build the MassIVE Knowledge Base (MassIVE-KB) spectral library, a community-wide resource derived from hundreds of millions of identified spectra from tens of terabytes of mass spectrometry data.
DOI: 10.6084/m9.figshare.19391063.v2
title: Effects of Spartina invasions on blue carbon sequestration in China

description: 1. Coastal wetlands are large reservoirs of soil carbon (C) and have been invaded globally by the exotic species <i>Spartina alterniflora</i>. However, the effects of these invasions on blue C sequestration remain unclear. 2. Here, we conducted a meta-analysis of 2479 soil organic C (SOC) observations collected from 91 field studies in coastal China, the world’s largest introduced range for <i>S. alterniflora</i>. 3. Our results show that <i>S. alterniflora</i> invasions had no significant effect on SOC in vegetated native coastal wetlands in China. <i>S. alterniflora</i> increased the SOC in the top 30 cm of salt marshes after invading only one of the nine types of native marshes, the native marsh was dominated by a dwarf succulent species, <i>Suaeda salsa</i>, in the northern subtropics, and decreased the SOC in the top 60 cm of mangrove habitats after invasion in the southern subtropics. <i>S. alterniflora</i> invasions did not significantly affect the SOC in salt marshes or mangroves dominated by other native species. Therefore, the C sequestration capacity of <i>S. alterniflora</i> does not differ from those of most native dominant species. Moreover, the SOC in <i>S. alterniflora</i>-invaded ecosystems increased on only a decadal-scale and then decreased, rather than increasing monotonically as was previously thought. 4. <i>Synthesis and applications</i>. Our findings reveal that<i> S. alterniflora</i> invasions apparently increase the blue C sink in China only in native ecosystems dominated by specific species in specific regions and only over short time periods. Therefore, the expansion of <i>S. alterniflora</i> should not be considered as a natural climate solution to increase C sink in coastal China. Instead, future efforts are required to eradicate <i>S. alterniflora</i> preferentially in the coastal wetlands where<i> S. alterniflora</i> invasions do not increase C sinks, and to conserve and restore native coastal wetlands nationwide for increasing both ecological integrity and C sinks and mitigate climate change.
DOI: 10.25345/c5tt4fx3p
title: MassIVE Reanalysis RMSV000000393.6 - CCMS MassIVE Knowledge Base (MassIVE-KB) MS-GF+ reanalysis of MSV000080833/PXD001608 [4 out of 6] [launched by cfca6e4ba8934e65aa11617b56091339]
title: Center for Computational Mass Spectrometry (CCMS) systematic reanalysis of public proteomics mass spectrometry (MS) datasets provides a public, large-scale and comparable set of dataset reanalyses results including detailed provenance records. To further facilitate the broad reusability of public proteomics MS data, these reanalyses were also used to build the MassIVE Knowledge Base (MassIVE-KB) spectral library, a community-wide resource derived from hundreds of millions of identified spectra from tens of terabytes of mass spectrometry data.
DOI: 10.25345/c5q23r39n
title: MassIVE Reanalysis RMSV000000404.3 - CCMS MassIVE Knowledge Base (MassIVE-KB) MS-GF+ reanalysis of MSV000080772/PXD003514 [4 out of 8] [launched by cfca6e4ba8934e65aa11617b56091339]
title: Center for Computational Mass Spectrometry (CCMS) systematic reanalysis of public proteomics mass spectrometry (MS) datasets provides a public, large-scale and comparable set of dataset reanalyses results including detailed provenance records. To further facilitate the broad reusability of public proteomics MS data, these reanalyses were also used to build the MassIVE Knowledge Base (MassIVE-KB) spectral library, a community-wide resource derived from hundreds of millions of identified spectra from tens of terabytes of mass spectrometry data.
DOI: 10.25345/c5k93195w
title: MassIVE Reanalysis RMSV000000362.62 - CCMS MassIVE Knowledge Base (MassIVE-KB) MS-GF+ reanalysis of MSV000081607 Confetti, Elastase HCD [launched by cfca6e4ba8934e65aa11617b56091339]
title: Center for Computational Mass Spectrometry (CCMS) systematic reanalysis of public proteomics mass spectrometry (MS) datasets provides a public, large-scale and comparable set of dataset reanalyses results including detailed provenance records. To further facilitate the broad reusability of public proteomics MS data, these reanalyses were also used to build the MassIVE Knowledge Base (MassIVE-KB) spectral library, a community-wide resource derived from hundreds of millions of identified spectra from tens of terabytes of mass spectrometry data.
DOI: 10.25345/c5fj29h08
title: MassIVE Reanalysis RMSV000000586.31 - CCMS MassIVE Knowledge Base (MassIVE-KB) MS-GF+ reanalysis of MSV000079526/PXD000865 [8 out of 46], Stomach [launched by cfca6e4ba8934e65aa11617b56091339]
title: Center for Computational Mass Spectrometry (CCMS) systematic reanalysis of public proteomics mass spectrometry (MS) datasets provides a public, large-scale and comparable set of dataset reanalyses results including detailed provenance records. To further facilitate the broad reusability of public proteomics MS data, these reanalyses were also used to build the MassIVE Knowledge Base (MassIVE-KB) spectral library, a community-wide resource derived from hundreds of millions of identified spectra from tens of terabytes of mass spectrometry data.
DOI: 10.25345/c59s1kp51
title: MassIVE Reanalysis RMSV000000586.32 - CCMS MassIVE Knowledge Base (MassIVE-KB) MS-GF+ reanalysis of MSV000079526/PXD000865 [7 out of 46], Prostate [launched by cfca6e4ba8934e65aa11617b56091339]
title: Center for Computational Mass Spectrometry (CCMS) systematic reanalysis of public proteomics mass spectrometry (MS) datasets provides a public, large-scale and comparable set of dataset reanalyses results including detailed provenance records. To further facilitate the broad reusability of public proteomics MS data, these reanalyses were also used to build the MassIVE Knowledge Base (MassIVE-KB) spectral library, a community-wide resource derived from hundreds of millions of identified spectra from tens of terabytes of mass spectrometry data.
DOI: 10.23729/9976dbaf-3f24-4c7b-b4a4-ec77bdfea3f2
title: 3D Library Set 1

description: First set of structures for the GTK 3D structure library, intended to act as a database for geoinspired design projects. Samples are scanned only to add their structure to the library, with no other direct research interest. Preview dataset found at https://doi.org/10.23729/4e049d91-dcc8-4f1f-b06e-1267b29c8d21 . To obtain data, please contact fairdata-pas@gtk.fi .
DOI: 10.25345/c5610vw2p
title: MassIVE Reanalysis RMSV000000554.2 - CCMS MassIVE Knowledge Base (MassIVE-KB) MS-GF+ reanalysis of MSV000080740/PXD003324 [1 out of 2] [launched by cfca6e4ba8934e65aa11617b56091339]
title: Center for Computational Mass Spectrometry (CCMS) systematic reanalysis of public proteomics mass spectrometry (MS) datasets provides a public, large-scale and comparable set of dataset reanalyses results including detailed provenance records. To further facilitate the broad reusability of public proteomics MS data, these reanalyses were also used to build the MassIVE Knowledge Base (MassIVE-KB) spectral library, a community-wide resource derived from hundreds of millions of identified spectra from tens of terabytes of mass spectrometry data.
DOI: 10.5281/zenodo.5728078
title: Empresas de Design em Portugal (visão detalhada, 2018, SABI)

description: Base de dados criada a partir da SABI (Moody's company: base de dados privada com informação económico-financeiras sobre 800.000 empresas Portuguesas) e trabalhada na disciplina de Representação e Conhecimento, com estudantes do Mestrado de Design (Universidade de Aveiro, ano 2019-20). Extraíram-se informações sobre empresas com código 74.10 (atividade de Design) no ano 2018 obtendo uma amostra de 1.451 empresas com informações sobre Localização geográfica (concelho, distrito e área NUT II), Volume de Negócio, Exportações (%), Número de Empregados, Lucro (%) e contactos (email e website, quando existente). Os alunos apenas consideraram empresas que apresentavam Volume de Negócio positivo nesse ano (n=1.287) para criar as infografias. Para além dos dados existentes, adicionaram outros parâmetros, nomeadamente sobre a localização da empresa (área litoral, interior, sul ou ilhas), o seu tamanho seguindo as indicações europeias e classificação qualitativa de acordo com o seu investimento nos empregados face ao seu volume de negócios. Base de dados é desenvolvida no âmbito do projeto Design Obs. Para um Observatório de Design em Portugal: Modelos, Instrumentos, Representação e Estratégias (www.designobs.pt), cofinanciado pelo Programa Operacional Regional de Lisboa (LISBOA 2020) e o Programa Operacional Competitividade e Internacionalização (POCI-01-0145-FEDER-032445), através do Portugal 2020 e do Fundo Europeu de Desenvolvimento Regional (FEDER) e por fundos nacionais através da FCT – Fundação para a Ciência e a Tecnologia.
DOI: 10.5281/zenodo.5728077
title: Empresas de Design em Portugal (visão detalhada, 2018, SABI)

description: Base de dados criada a partir da SABI (Moody's company: base de dados privada com informação económico-financeiras sobre 800.000 empresas Portuguesas) e trabalhada na disciplina de Representação e Conhecimento, com estudantes do Mestrado de Design (Universidade de Aveiro, ano 2019-20). Extraíram-se informações sobre empresas com código 74.10 (atividade de Design) no ano 2018 obtendo uma amostra de 1.451 empresas com informações sobre Localização geográfica (concelho, distrito e área NUT II), Volume de Negócio, Exportações (%), Número de Empregados, Lucro (%) e contactos (email e website, quando existente). Os alunos apenas consideraram empresas que apresentavam Volume de Negócio positivo nesse ano (n=1.287) para criar as infografias. Para além dos dados existentes, adicionaram outros parâmetros, nomeadamente sobre a localização da empresa (área litoral, interior, sul ou ilhas), o seu tamanho seguindo as indicações europeias e classificação qualitativa de acordo com o seu investimento nos empregados face ao seu volume de negócios. Base de dados é desenvolvida no âmbito do projeto Design Obs. Para um Observatório de Design em Portugal: Modelos, Instrumentos, Representação e Estratégias (www.designobs.pt), cofinanciado pelo Programa Operacional Regional de Lisboa (LISBOA 2020) e o Programa Operacional Competitividade e Internacionalização (POCI-01-0145-FEDER-032445), através do Portugal 2020 e do Fundo Europeu de Desenvolvimento Regional (FEDER) e por fundos nacionais através da FCT – Fundação para a Ciência e a Tecnologia.
DOI: 10.25345/c52b8vg26
title: MassIVE Reanalysis RMSV000000479.2 - CCMS MassIVE Knowledge Base (MassIVE-KB) MS-GF+ reanalysis of MSV000080852/PXD004995 [1 out of 4] [launched by cfca6e4ba8934e65aa11617b56091339]
title: Center for Computational Mass Spectrometry (CCMS) systematic reanalysis of public proteomics mass spectrometry (MS) datasets provides a public, large-scale and comparable set of dataset reanalyses results including detailed provenance records. To further facilitate the broad reusability of public proteomics MS data, these reanalyses were also used to build the MassIVE Knowledge Base (MassIVE-KB) spectral library, a community-wide resource derived from hundreds of millions of identified spectra from tens of terabytes of mass spectrometry data.
DOI: 10.5517/ccdc.csd.cc29cp6l
title: CCDC 2126389: Experimental Crystal Structure Determination

description: Related Article: yebin wu, xiaojun ji, changyou ma|2021|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc29cvvd
title: CCDC 2126564: Experimental Crystal Structure Determination

description: Related Article: Wenbo Liu, Yushan, Zheng, Zhan Lu|2021|CSD Communication|||
description: Related Article: Wenbo Liu, Yushan Zheng, Yihui Mao, Jieping Chen, Xiang Ren, Zhaoyang Cheng, Zhan Lu|2022|Org.Lett.|24|1158|doi:10.1021/acs.orglett.1c04237
DOI: 10.5517/ccdc.csd.cc29d6kh
title: CCDC 2126896: Experimental Crystal Structure Determination

description: Related Article: Zixiao Qin|2021|CSD Communication|||