cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.21493593.v1
title: Supplementary Material for: Analysis of Patients with Asthma and Mixed Granulocytic Inflammatory Pattern in Sputum

description: <b><i>Background:</i></b> Patients with asthma usually present airway inflammation classified as eosinophilic, neutrophilic, mixed granulocytic, and paucigranulocytic pattern according to sputum inflammatory cells. <b><i>Objective:</i></b> The aim of the study was to analyze clinical and biological characteristics of patients with asthma and mixed granulocytic pattern in comparison with the other groups. <b><i>Methods:</i></b> Induced sputum was used to assess airway inflammation; lung function was evaluated as well as blood leukocytes and disease control. History of comorbidities was collected. <b><i>Results:</i></b> We retrospectively analyzed 231 subjects with asthma; patients with mixed granulocytic pattern were more frequently male compared with paucigranulocytic subjects, older than eosinophilic and paucigranulocytic patients with increased number and vitality of sputum cells compared to eosinophilic and paucigranulocytic patients and higher cumulative illness rating score, related to increased age. Smoking history, age of disease onset, and ICS treatment were not associated with higher mixed granulocytic pattern occurrence. Subjects with neutrophilic inflammation (mixed granulocytic and neutrophilic patterns considered altogether) were more frequently obese. In subjects under 67 years of age (median of the enrolled subjects), arterial hypertension was the only comorbidity more frequent in mixed granulocytic than in the other groups. 137/231 subjects were re-valuated during follow-up. Lung function of patients with mixed granulocytic, neutrophilic, and paucigranulocytic patterns improved less than that of eosinophilic patients. <b><i>Conclusion:</i></b> Aging and presence of comorbidities, in particular obesity and hypertension, are characteristics of patients with asthma and mixed granulocytic pattern. They could respond less well to treatment than eosinophilic patients.
DOI: 10.6084/m9.figshare.21493617.v1
title: Supplementary Material for: A Diagnostic Predictive Model of Bronchoscopy with Radial Endobronchial Ultrasound for Peripheral Pulmonary Lesions

description: <b><i>Background:</i></b> Several factors have been reported to affect the diagnostic yield of bronchoscopy with radial endobronchial ultrasound (R-EBUS) for peripheral pulmonary lesions (PPLs). However, it is difficult to accurately predict the diagnostic potential of bronchoscopy for each PPL in advance. <b><i>Objectives:</i></b> Our objective was to establish a predictive model to evaluate the diagnostic yield before the procedure. <b><i>Method:</i></b> We retrospectively analysed consecutive patients who underwent diagnostic bronchoscopy with R-EBUS between April 2012 and October 2015. We assessed the factors that were predictive of successful bronchoscopic diagnosis of PPLs with R-EBUS using a multivariable logistic regression model. The accuracy of the predictive model was evaluated using the receiver operator characteristic area under the curve (ROC AUC). Internal validation was analysed using 10-fold stratified cross-validation. <b><i>Results:</i></b> We analysed a total of 1,634 lesions; the median lesion size was 25.0 mm. Of these, 1,138 lesions (69.6%) were successfully diagnosed. In the predictive logistic model, significant factors affecting the diagnostic yield were lesion size, lesion structure, bronchus sign, and visible on chest X-ray. The predictive model consisted of seven factors: lesion size, lesion lobe, lesion location from the hilum, lesion structure, bronchus sign, visibility on chest X-ray, and background lung. The ROC AUC of the predictive model was 0.742 (95% confidence interval: 0.715–0.769). Internal validation using 10-fold stratified cross-validation revealed a mean ROC AUC of 0.734. <b><i>Conclusions:</i></b> The predictive model using the seven factors revealed a good performance in estimating the diagnostic yield.
DOI: 10.6084/m9.figshare.20626794
title: Supplementary Material for: Hepatic Events and Viral Kinetics in Hepatocellular Carcinoma Patients Treated With Atezolizumab Plus Bevacizumab

description: Introduction: In the Phase 3 IMbrave150 trial (NCT03434379), atezolizumab + bevacizumab demonstrated a clinically meaningful survival benefit over sorafenib in patients with unresectable hepatocellular carcinoma (HCC), including those with hepatitis B virus (HBV) or hepatitis C virus (HCV) infection. We used IMbrave150 data to investigate the safety and risk of viral reactivation or flare in infected patients treated with atezolizumab + bevacizumab or sorafenib. Methods: Patients with unresectable HCC not previously treated with systemic therapy were randomized 2:1 to atezolizumab + bevacizumab or sorafenib. In this exploratory analysis, safety was continually evaluated, including for hepatic adverse events. Patients were monitored for HBV and HCV reactivation and flare at screening, the beginning of Cycles 5 and 9, and at treatment discontinuation. Results: Of 501 enrolled patients, 485 were included in the safety population; 329 (68%) received atezolizumab + bevacizumab and 156 (32%) sorafenib. Overall, 150 (31%) and 58 (12%) patients had HBV and HCV infection, respectively. The safety profiles of atezolizumab + bevacizumab and sorafenib were consistent across patients regardless of viral infection. Overall, hepatic serious adverse events occurred in 11% of patients receiving atezolizumab + bevacizumab and 8% receiving sorafenib. HBV or HCV reactivation occurred in 2% or 16% of atezolizumab + bevacizumab–treated patients, respectively, vs 7% or 14% with sorafenib. There were no instances of hepatitis flare with atezolizumab + bevacizumab. Conclusions: Atezolizumab + bevacizumab had a similar hepatic safety profile in patients with and without HBV or HCV infection. Viral reactivation rates were similar between arms. Overall, these data support the use of atezolizumab + bevacizumab in patients with HCC and HBV or HCV infection without any special precaution.
DOI: 10.6084/m9.figshare.20626794.v1
title: Supplementary Material for: Hepatic Events and Viral Kinetics in Hepatocellular Carcinoma Patients Treated With Atezolizumab Plus Bevacizumab

description: Introduction: In the Phase 3 IMbrave150 trial (NCT03434379), atezolizumab + bevacizumab demonstrated a clinically meaningful survival benefit over sorafenib in patients with unresectable hepatocellular carcinoma (HCC), including those with hepatitis B virus (HBV) or hepatitis C virus (HCV) infection. We used IMbrave150 data to investigate the safety and risk of viral reactivation or flare in infected patients treated with atezolizumab + bevacizumab or sorafenib. Methods: Patients with unresectable HCC not previously treated with systemic therapy were randomized 2:1 to atezolizumab + bevacizumab or sorafenib. In this exploratory analysis, safety was continually evaluated, including for hepatic adverse events. Patients were monitored for HBV and HCV reactivation and flare at screening, the beginning of Cycles 5 and 9, and at treatment discontinuation. Results: Of 501 enrolled patients, 485 were included in the safety population; 329 (68%) received atezolizumab + bevacizumab and 156 (32%) sorafenib. Overall, 150 (31%) and 58 (12%) patients had HBV and HCV infection, respectively. The safety profiles of atezolizumab + bevacizumab and sorafenib were consistent across patients regardless of viral infection. Overall, hepatic serious adverse events occurred in 11% of patients receiving atezolizumab + bevacizumab and 8% receiving sorafenib. HBV or HCV reactivation occurred in 2% or 16% of atezolizumab + bevacizumab–treated patients, respectively, vs 7% or 14% with sorafenib. There were no instances of hepatitis flare with atezolizumab + bevacizumab. Conclusions: Atezolizumab + bevacizumab had a similar hepatic safety profile in patients with and without HBV or HCV infection. Viral reactivation rates were similar between arms. Overall, these data support the use of atezolizumab + bevacizumab in patients with HCC and HBV or HCV infection without any special precaution.
DOI: 10.48432/s0lbyh/sdidaw
title: agrobiodiversidade_amaro.tab

description: Conjunto de informações sobre a agrobiodiversidade conservada e usada na Comunidade Amaro em Brejo da Madre de Deus em Pernambuco.
DOI: 10.48432/s0lbyh/wybn7b
title: agrobiodiversidade_esperanca.tab

description: Conjunto de informações sobre a agrobiodiversidade conservada e usada na Comunidade Esperança em Brejo da Madre de Deus em Pernambuco.
DOI: 10.48432/s0lbyh/odcft4
title: agrobiodiversidade_estrago.tab

description: Conjunto de informações sobre a agrobiodiversidade conservada e usada na Comunidade Estrago em Brejo da Madre de Deus em Pernambuco.
DOI: 10.48432/s0lbyh/mud621
title: especies_cultivadas_amparo.tab

description: Conjunto de informações sobre as espécies conservadas e usadas na Comunidade Amparo em Brejo da Madre de Deus em Pernambuco.
DOI: 10.48432/s0lbyh/pp7alf
title: especies_cultivadas_esperanca.tab

description: Conjunto de informações sobre as espécies conservadas e usadas na Comunidade Esperança em Brejo da Madre de Deus em Pernambuco.
DOI: 10.48432/s0lbyh/wbu1g1
title: especies_cultivadas_estrago.tab

description: Conjunto de informações sobre as espécies conservadas e usadas na Comunidade Estrago em Brejo da Madre de Deus em Pernambuco.
DOI: 10.48432/s0lbyh/n9qs0k
title: legenda_agrobiodiversidade.tab

description: Legenda sobre a agrobiodiversidade conservada e usada.
DOI: 10.48432/s0lbyh/iggfan
title: legenda_espécies.tab

description: Legenda sobre as espécies conservadas e usadas.
DOI: 10.20351/29sg20221001
title: BLUEHARVESTING Cruise, RV Sarmiento de Gamboa

description: Oceanographic data acquired during the BLUEHARVESTING Cruise (29SG20221001)  on board the Research Vessel Sarmiento de Gamboa in 2022.
DOI: 10.5281/zenodo.6793488
title: Sea Level Datasets for HIDRA2 Training and Evaluation

description: HIDRA2 is a state-of-the-art deep neural model for sea-level prediction based on past sea level observations and future tidal and atmospheric forecasts. Training and evaluation was performed on the published sea level datasets.
DOI: 10.5281/zenodo.6793489
title: Sea Level Datasets for HIDRA2 Training and Evaluation

description: HIDRA2 is a state-of-the-art deep neural model for sea-level prediction based on past sea level observations and future tidal and atmospheric forecasts. Training and evaluation was performed on the published sea level datasets.
DOI: 10.5281/zenodo.7277108
title: Sea Level Datasets for HIDRA2 Training and Evaluation

description: HIDRA2 is a state-of-the-art deep neural model for sea-level prediction based on past sea level observations and future tidal and atmospheric forecasts. Training and evaluation was performed on the published sea level datasets.
DOI: 10.6084/m9.figshare.21493715
title: S2: Ecological and evolutionary responses of terrestrial arthropods to Middle–Late Pennsylvanian environmental change

description: Pterygote insect occurrence data from the Paleobiology Database primarily compiled by Clapham <i>et al</i>. 2016
DOI: 10.6084/m9.figshare.21493715.v1
title: S2: Ecological and evolutionary responses of terrestrial arthropods to Middle–Late Pennsylvanian environmental change

description: Pterygote insect occurrence data from the Paleobiology Database primarily compiled by Clapham <i>et al</i>. 2016
DOI: 10.6084/m9.figshare.21493718
title: S1: Ecological and evolutionary responses of terrestrial arthropods to Middle–Late Pennsylvanian environmental change

description: Documented occurrences of different forms of herbivory and detritivory throughout the Pennsylvanian and earliest Permian
DOI: 10.6084/m9.figshare.21493718.v1
title: S1: Ecological and evolutionary responses of terrestrial arthropods to Middle–Late Pennsylvanian environmental change

description: Documented occurrences of different forms of herbivory and detritivory throughout the Pennsylvanian and earliest Permian
DOI: 10.6084/m9.figshare.21493721.v1
title: S3: Ecological and evolutionary responses of terrestrial arthropods to Middle–Late Pennsylvanian environmental change

description: Pterygote insect family data from the Paleobiology Database primarily compiled by Clapham <i>et al</i>. 2016
DOI: 10.6084/m9.figshare.21493721
title: S3: Ecological and evolutionary responses of terrestrial arthropods to Middle–Late Pennsylvanian environmental change

description: Pterygote insect family data from the Paleobiology Database primarily compiled by Clapham <i>et al</i>. 2016
DOI: 10.5281/zenodo.7277182
title: Microssatelite CPD - Brazil

description: Compilação em DataFrame do número de pares de bases de diferentes animais (linhas) para 17 marcadores de microsatélite (coluna) de animais da raça Curraleiro Pé-Duro, uma raça de bovinos nativos do Brasil.
DOI: 10.5281/zenodo.7277181
title: Microssatelite CPD - Brazil

description: Compilação em DataFrame do número de pares de bases de diferentes animais (linhas) para 17 marcadores de microsatélite (coluna) de animais da raça Curraleiro Pé-Duro, uma raça de bovinos nativos do Brasil.
DOI: 10.6084/m9.figshare.21437223
title: Roberts and Longdon Sex and tissue diffs.zip

description: Dataset and R scripts associated with manuscript "Sex and tissue differences in virus susceptibility across species" <br> Sex_diff_script_25-10-22.R reads in datasets and carrys out MCMCglmm analysis to compare viral loads in males and females. <br> ddct_sex_day_data.csv is the sex difference qPCR data on viral load .tre file is the phylogeny of the fly species .Rdata files are the MCMCglmm models that are loaded into the above <br> Tissue_trop_script_25-10-22.R reads in datasets and carrys out analysis of differences in viral loads across tissue types and species. <br> ct_TT_no_fly.csv is the tissue tropism viral load data <br>
DOI: 10.6084/m9.figshare.21437223.v1
title: Roberts and Longdon Sex and tissue diffs.zip

description: Dataset and R scripts associated with manuscript "Sex and tissue differences in virus susceptibility across species" <br> Sex_diff_script_25-10-22.R reads in datasets and carrys out MCMCglmm analysis to compare viral loads in males and females. <br> ddct_sex_day_data.csv is the sex difference qPCR data on viral load .tre file is the phylogeny of the fly species .Rdata files are the MCMCglmm models that are loaded into the above <br> Tissue_trop_script_25-10-22.R reads in datasets and carrys out analysis of differences in viral loads across tissue types and species. <br> ct_TT_no_fly.csv is the tissue tropism viral load data <br>
DOI: 10.5281/zenodo.5977099
title: Data for the publication "Too frequent and too light Arctic snowfall with incorrect precipitation phase partitioning in the MIROC6 GCM"

description: These data are a set of 1yr simulations using the MIROC6-SPRINTARS global aerosol-climate model with different treatments of precipitation (i.e., diagnostic and prognostic). The outputs include diagnostics from the satellite simulator COSP2.<br> The data are used in the manuscript entitled "Too frequent and too light Arctic snowfall with incorrect precipitation phase partitioning in the MIROC6 GCM". All data used in this study are available from the corresponding author upon request.
DOI: 10.5281/zenodo.5977098
title: Data for the publication "Too frequent and too light Arctic snowfall with incorrect precipitation phase partitioning in the MIROC6 GCM"

description: These data are a set of 1yr simulations using the MIROC6-SPRINTARS global aerosol-climate model with different treatments of precipitation (i.e., diagnostic and prognostic). The outputs include diagnostics from the satellite simulator COSP2.<br> The data are used in the manuscript entitled "Too frequent and too light Arctic snowfall with incorrect precipitation phase partitioning in the MIROC6 GCM". All data used in this study are available from the corresponding author upon request.
DOI: 10.6084/m9.figshare.19144871
title: Cognitive biases in Lasius niger, datasets

description: Experiment 1: Developing a judgement bias task for L. niger<br>Experiment 2: Judgement biases in L. niger
DOI: 10.6084/m9.figshare.19144871.v1
title: Cognitive biases in Lasius niger, datasets

description: Experiment 1: Developing a judgement bias task for L. niger<br>Experiment 2: Judgement biases in L. niger
DOI: 10.5281/zenodo.5821533
title: LivWell: a sub-national database on the Living conditions of Women and their Well-being for 52 countries

description: LivWell is a global longitudinal database which provides a range of key indicators related to women’s socioeconomic status, health and well-being, access to basic services, and demographic outcomes. Data are available at the sub-national level for 52 countries and 447 regions. A total of 134 indicators are based on 199 Demographic and Health Surveys for the period 1990-2019, supplemented by extensive information on socioeconomic and climatic conditions in the respective regions for a total of 190 indicators. The resulting data offer various opportunities for policy-relevant research on gender inequality, inclusive development, and demographic trends at the sub-national level. For a full description, please refer to the article describing the database here: (link to come) The companion repository <em>livwelldata </em>allows to easily use the database in R. The R package can be downloaded following the instructions on the following git repository: https://gitlab.pik-potsdam.de/belmin/livwelldata. The version of the database in the package is the same as in this repository.
DOI: 10.5281/zenodo.6812400
title: LivWell: a sub-national database on the Living conditions of Women and their Well-being for 52 countries

description: LivWell is a global longitudinal database which provides a range of key indicators related to women’s socioeconomic status, health and well-being, access to basic services, and demographic outcomes. Data are available at the sub-national level for 52 countries and 447 regions. A total of 134 indicators are based on 199 Demographic and Health Surveys for the period 1990-2019, supplemented by extensive information on socioeconomic and climatic conditions in the respective regions for a total of 190 indicators. The resulting data offer various opportunities for policy-relevant research on gender inequality, inclusive development, and demographic trends at the sub-national level. For a full description, please refer to the article describing the database here: (link to come) The companion repository <em>livwelldata </em>allows to easily use the database in R. The R package can be downloaded following the instructions on the following git repository: https://gitlab.pik-potsdam.de/belmin/livwelldata. The version of the database in the package is the same as in this repository.
DOI: 10.5281/zenodo.7277104
title: LivWell: a sub-national database on the Living conditions of Women and their Well-being for 52 countries

description: LivWell is a global longitudinal database which provides a range of key indicators related to women’s socioeconomic status, health and well-being, access to basic services, and demographic outcomes. Data are available at the sub-national level for 52 countries and 447 regions. A total of 134 indicators are based on 199 Demographic and Health Surveys for the period 1990-2019, supplemented by extensive information on socioeconomic and climatic conditions in the respective regions for a total of 190 indicators. The resulting data offer various opportunities for policy-relevant research on gender inequality, inclusive development, and demographic trends at the sub-national level. For a full description, please refer to the article describing the database here: (link to come) The companion repository <em>livwelldata </em>allows to easily use the database in R. The R package can be downloaded following the instructions on the following git repository: https://gitlab.pik-potsdam.de/belmin/livwelldata. The version of the database in the package is the same as in this repository.
DOI: 10.5281/zenodo.7271498
title: A patient-centric modelling framework captures recovery from SARS-CoV-2 infection

description: The biology driving individual patient responses to SARS-CoV-2 infection remains ill understood. Here, we developed a patient-centric framework leveraging detailed longitudinal phenotyping data and covering a year post-disease onset, from 215 SARS-CoV-2 infected subjects with differing disease severities. Our analyses revealed distinct “systemic recovery” profiles, with specific progression and resolution of the inflammatory, immune cell, metabolic and clinical responses. In particular, we found a strong inter- and intra-patient temporal covariation of innate immune cell numbers, kynurenine metabolites and lipid metabolites, which highlighted candidate immunologic and metabolic pathways influencing the restoration of homeostasis, the risk of death and that of long COVID. Based on these data, we identified a composite signature predictive of systemic recovery at the patient level, using a joint model on cellular and molecular parameters measured soon after disease onset. New predictions can be generated using the online tool http://shiny.mrc-bsu.cam.ac.uk/apps/covid-19-systemic-recovery-prediction-app, designed to test our findings prospectively.
description: We thank NIHR BioResource volunteers for their participation, and gratefully acknowledge NIHR BioResource centres, NHS Trusts and staff for their contribution. We thank the National Institute for Health and Care Research, NHS Blood and Transplant, and Health Data Research UK as part of the Digital Innovation Hub Programme. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care. We are also grateful for the generous support of CVC Capital Partners, the Evelyn Trust (20/75), UKRI COVID Immunology Consortium, Addenbrooke's Charitable Trust (12/20A), the UKRI/NIHR through the UK Coronavirus Immunology Consortium (UK-CIC), the COVID-19 Rapid Response DCF (RG93172/HESS/40558) and the Botnar Research Centre for Child Health (BRCCH) for their financial support. H.R. would like to thank the Lopez–Loreta Foundation for their support. J.N., J.W. and E.H. would like to acknowledge the Australian Federal Government's Medical Research Future Fund (MRFF-ARAPC ARG76435), the Western Australian Department of Health, the Spinnaker Health Research Foundation and the McCusker Charitable Foundation for their support and contributions to this research program. K.G.C.S. acknowledges support from Wellcome Investigator and Collaborative Awards (200871/Z/16/ Z; 219506/Z/19/Z) and a Medical Research Council Programme Grant (MR/L019027). We would also like to thank the NIHR Cambridge Clinic Research Facility outreach team for enrollment of patients; and the NIHR Cambridge Biomedical Research Centre Cell Phenotyping Hub and the CRUK Cambridge Institute flow cytometry core facility for their support with flow and mass cytometry.