Assessing the efficacy and safety of mycophenolate mofetil versus azathioprine in patients with autoimmune hepatitis (CAMARO trial): study protocol for a randomised controlled trial

Background: Currently, the standard therapy for autoimmune hepatitis (AIH) consists of a combination of prednisolone and azathioprine. However, 15% of patients are intolerant to azathioprine which necessitates cessation of azathioprine or changes in therapy. In addition, not all patients achieve complete biochemical response (CR). Uncontrolled data indicate that mycophenolate mofetil (MMF) can induce CR in a majority of patients. Better understanding of first-line treatment and robust evidence from randomised clinical trials are needed. The aim of this study was to explore the potential benefits of MMF as compared to azathioprine, both combined with prednisolone, as induction therapy in a randomised controlled trial in patients with treatment-naive AIH. Method:s: CAMARO is a randomised (1:1), open-label, parallel-group, multicentre superiority trial. All patients with AIH are screened for eligibility. Seventy adult patients with AIH from fourteen centres in the Netherlands and Belgium will be randomised to receive MMF or azathioprine. Both treatment arms will start with prednisolone as induction therapy. The primary outcome is biochemical remission, defined as serum levels of alanine aminotransferase and immunoglobulin G below the upper limit of normal. Secondary outcomes include safety and tolerability of MMF and azathioprine, time to remission, changes in Model For End-Stage Liver Disease (MELD)-score, adverse events, and aspects of quality of life. The study period will last for 24 weeks. Discussion: The CAMARO trial investigates whether treatment with MMF and prednisolone increases the proportion of patients in remission compared with azathioprine and prednisolone as the current standard treatment strategy. In addition, we reflect on the challenges of conducting a randomized trial in rare diseases.Cellular mechanisms in basic and clinical gastroenterology and hepatolog

Data from: “The impact of linear infrastructure on terrestrial vertebrate populations: A trait-based approach”

This dataset was created for our study on the impacts of linear infrastructure on the population abundance of vertebrate species. We obtained mean abundances and standard deviations of vertebrate populations in sites disturbed by infrastructure and corresponding undisturbed sites by searching for published peer-reviewed and grey literature. We extracted 3,912 pairwise abundance comparisons between disturbed and non-disturbed areas from 110 primary sources, spanning 26 countries and 6 continents and 160, 443, 97 and 92 species of mammals, birds, reptiles and amphibians, respectively. We also extracted the sample size and sampling effort per sample for each observation to perform meta-analyses per species group. Additionally, we extracted the mean distance to infrastructure in the disturbed sites to determine how infrastructure affects vertebrate populations as a function of distance and derive the mean infrastructure-effect zone for each species group using meta-regression models. Further, we extracted the type of infrastructure and habitat for each observation as well as the mean body mass for all species and diet for mammals and birds to determine how infrastructure impacts are modulated by environmental characteristics and species traits using meta-regressions. The results of this research will be published as: de Jonge, M. M. J., Gallego-Zamorano, J., Huijbregts, M. A. J., Schipper, A. M., & Benítez‐López, A. (in press). The impact of linear infrastructure on terrestrial vertebrate populations: A trait-based approach. Global Change Biology This dataset, as well as the R scripts for the corresponding analysis and the full fitted models are available at: https://github.com/MelindadeJonge/Infrastructure_MetaAnalysis. The data is stored in 4 files ●2022_deJonge_Dataset_092022.csv: The full dataset including the sample size, mean abundance, standard deviation of the mean, habitat type, infrastructure type, source, location, species, and quality of each observation. For a description of how the data was extracted we refer the reader to: 2022_deJonge_Methodology_092022.pdf ●2022_deJonge_speciesList_092022.csv: a list of all species included in the database together with their identification code, body mass (g), diet (only for mammals and birds) and body length (mm, only for amphibians). ●2022_deJonge_CrossswalkInfrastructure.csv: Crosswalk to link the habitat types as reported in the database to a binary classification (open/closed). ●2022_deJonge_CrosswalkHabitat.csv: Crosswalk to link the infrastructure types as reported in the database to the classification scheme used in the analysis (paved roads, unpaved roads, powerlines, other non-traffic infrastructure). Additional information An overview of the definitions and units of the variables in each file is given in the codebook: “2022_deJonge_Codebook_092022.pdf” A description of the methodology used to obtain the data is given in ‘2022_deJonge_Methodology_092022.pdf” A list of all data sources is given in “2022_deJonge_dataSources.pdf

Data of 'Relating plant height to demographic rates and extinction vulnerability'

This dataset was developed for our study on plant allometry and extinction vulnerabilities. In this study we gathered plant demographic data from various sources and related this to maximum plant height. We derived allometric relationships with maximum plant height for the intrinsic population growth rate, variance in population growth rate due to environmental stochasticity and the maximum plant density. These relationships were used to relate maximum plant height to the Mean time to extinction and the Probability of extinction. The results of this research will soon be published as ‘Relating plant height to demographic rates and extinction vulnerability’ (forthcoming). In this repository we provide only the processed data from this study because the original data was gathered from existing open access and semi-open access databases. Original data for this project was gathered from the following databases: (1) TRY Plant Trait Database, (2) COMPADRE Plant Matrix Database Version 4.0.1, (3) Biomass allocation and growth data of seeded plants The processed data is stored in two files: - 2017_deJonge_MaximumPlantDensity.csv: This file contains 230 datapoints with maximum plant density (per square meter) and average individual plant mass (grams). A description of the methodology used to obtain the processed data is given in a PDF file called ‘2017_deJonge_Methodology.pdf’. Additionally, a description file called 'description.pdf' is added, which includes the information mentioned above

Data of "Conditional love? Co-occurrence patterns of drought-sensitive species in European grasslands are consistent with the stress gradient hypothesis"

This dataset was developed for our study on the spatial associations between plant species along a drought gradient in European grasslands. We obtained species occurrences for 161 species from the European Vegetation Archives for 20,722 georeferenced vegetation plots located in dry grasslands across Europe. We also extracted a set of environmental variables from various sources for each vegetation plot. This data was used in a context-dependent Joint Species Distribution Model (JSDMs) to determine how the residual spatial associations (i.e. spatial associations that can’t be explained from the included environmental predictors) shift along a drought gradient. We compared the observed shifts in spatial associations with expectations from the stress-gradient hypothesis while accounting for differences in species’ drought tolerance. The results of this research are published in: de Jonge, M. M., Benítez‐López, A., Hennekens, S., Santini, L., Huijbregts, M. A., & Schipper, A. M. (2021). Conditional love? Co‐occurrence patterns of drought‐sensitive species in European grasslands are consistent with the stress‐gradient hypothesis. Global Ecology and Biogeography, 30(8), 1609-1620. The data and associated code used in this study are publicly available in an archived GitHub repository: https://github.com/MelindadeJonge/ConditionalLove In this repository we provide only the processed data from this study because the original data was gathered from existing open access and semi-open access databases. Original data from this project was gathered from the following databases: ●European Vegetation Archives (project no. 44) ●CHELSA Climatologies dataset v.1.4 ●SoilGrids1km ●Species’ Ellenberg values for soil moisture Data files The processed data is stored in 4 files ●2021_deJonge_PlotInfo.csv: This file contains spatial and plot-level information for all 20,722 vegetation plots used in this study. Vegetation plots are identified by their unique plotID numbers. ●2021_deJonge_Occurrences.csv: This file contains the presences/absence matrix of all 161 species (columns) in the vegetation plots (rows) included in this analysis. The first column contains the plotID. ●2021_deJonge_Predictors.csv: This file contains the corresponding bioclimatic (minimum temperature of the coldest month, climatic water deficit, precipitation seasonality) and soil variables (organic carbon content, cation exchange capacity, pH) for each vegetation plot. ●2021_deJonge_SpeciesList.csv: This file contains the latin name, Ellenberg value for soil moisture and taxonomic information associated with all 161 species included in the study. Additional information An overview of the definitions and units of the variables in each file is given in the codebook: “2021_deJonge_Codebook.pdf” A description of the methodology used to obtain the processed data is given in ‘2021_deJonge_Methodology.pdf” A list of the original datasets obtained from the European Vegetation Archives together with their respective data custodians and the number of plots included in this analyses is given in “2021_deJonge_Custodians.pdf

Data of "Conditional love? Co-occurrence patterns of drought-sensitive species in European grasslands are consistent with the stress gradient hypothesis"

This dataset was developed for our study on the spatial associations between plant species along a drought gradient in European grasslands. We obtained species occurrences for 161 species from the European Vegetation Archives for 20,722 georeferenced vegetation plots located in dry grasslands across Europe. We also extracted a set of environmental variables from various sources for each vegetation plot. This data was used in a context-dependent Joint Species Distribution Model (JSDMs) to determine how the residual spatial associations (i.e. spatial associations that can’t be explained from the included environmental predictors) shift along a drought gradient. We compared the observed shifts in spatial associations with expectations from the stress-gradient hypothesis while accounting for differences in species’ drought tolerance. The results of this research are published in: de Jonge, M. M., Benítez‐López, A., Hennekens, S., Santini, L., Huijbregts, M. A., & Schipper, A. M. (2021). Conditional love? Co‐occurrence patterns of drought‐sensitive species in European grasslands are consistent with the stress‐gradient hypothesis. Global Ecology and Biogeography, 30(8), 1609-1620. The data and associated code used in this study are publicly available in an archived GitHub repository: https://github.com/MelindadeJonge/ConditionalLove In this repository we provide only the processed data from this study because the original data was gathered from existing open access and semi-open access databases. Original data from this project was gathered from the following databases: ●European Vegetation Archives (project no. 44) ●CHELSA Climatologies dataset v.1.4 ●SoilGrids1km ●Species’ Ellenberg values for soil moisture Data files The processed data is stored in 4 files ●2021_deJonge_PlotInfo.csv: This file contains spatial and plot-level information for all 20,722 vegetation plots used in this study. Vegetation plots are identified by their unique plotID numbers. ●2021_deJonge_Occurrences.csv: This file contains the presences/absence matrix of all 161 species (columns) in the vegetation plots (rows) included in this analysis. The first column contains the plotID. ●2021_deJonge_Predictors.csv: This file contains the corresponding bioclimatic (minimum temperature of the coldest month, climatic water deficit, precipitation seasonality) and soil variables (organic carbon content, cation exchange capacity, pH) for each vegetation plot. ●2021_deJonge_SpeciesList.csv: This file contains the latin name, Ellenberg value for soil moisture and taxonomic information associated with all 161 species included in the study. Additional information An overview of the definitions and units of the variables in each file is given in the codebook: “2021_deJonge_Codebook.pdf” A description of the methodology used to obtain the processed data is given in ‘2021_deJonge_Methodology.pdf” A list of the original datasets obtained from the European Vegetation Archives together with their respective data custodians and the number of plots included in this analyses is given in “2021_deJonge_Custodians.pdf

Data of "Conditional love? Co-occurrence patterns of drought-sensitive species in European grasslands are consistent with the stress gradient hypothesis"

This dataset was developed for our study on the spatial associations between plant species along a drought gradient in European grasslands. We obtained species occurrences for 161 species from the European Vegetation Archives for 20,722 georeferenced vegetation plots located in dry grasslands across Europe. We also extracted a set of environmental variables from various sources for each vegetation plot. This data was used in a context-dependent Joint Species Distribution Model (JSDMs) to determine how the residual spatial associations (i.e. spatial associations that can’t be explained from the included environmental predictors) shift along a drought gradient. We compared the observed shifts in spatial associations with expectations from the stress-gradient hypothesis while accounting for differences in species’ drought tolerance. The results of this research are published in: de Jonge, M. M., Benítez‐López, A., Hennekens, S., Santini, L., Huijbregts, M. A., & Schipper, A. M. (2021). Conditional love? Co‐occurrence patterns of drought‐sensitive species in European grasslands are consistent with the stress‐gradient hypothesis. Global Ecology and Biogeography, 30(8), 1609-1620. The data and associated code used in this study are publicly available in an archived GitHub repository: https://github.com/MelindadeJonge/ConditionalLove In this repository we provide only the processed data from this study because the original data was gathered from existing open access and semi-open access databases. Original data from this project was gathered from the following databases: ●European Vegetation Archives (project no. 44) ●CHELSA Climatologies dataset v.1.4 ●SoilGrids1km ●Species’ Ellenberg values for soil moisture Data files The processed data is stored in 4 files ●2021_deJonge_PlotInfo.csv: This file contains spatial and plot-level information for all 20,722 vegetation plots used in this study. Vegetation plots are identified by their unique plotID numbers. ●2021_deJonge_Occurrences.csv: This file contains the presences/absence matrix of all 161 species (columns) in the vegetation plots (rows) included in this analysis. The first column contains the plotID. ●2021_deJonge_Predictors.csv: This file contains the corresponding bioclimatic (minimum temperature of the coldest month, climatic water deficit, precipitation seasonality) and soil variables (organic carbon content, cation exchange capacity, pH) for each vegetation plot. ●2021_deJonge_SpeciesList.csv: This file contains the latin name, Ellenberg value for soil moisture and taxonomic information associated with all 161 species included in the study. Additional information An overview of the definitions and units of the variables in each file is given in the codebook: “2021_deJonge_Codebook.pdf” A description of the methodology used to obtain the processed data is given in ‘2021_deJonge_Methodology.pdf” A list of the original datasets obtained from the European Vegetation Archives together with their respective data custodians and the number of plots included in this analyses is given in “2021_deJonge_Custodians.pdf

Data from: “The impact of linear infrastructure on terrestrial vertebrate populations: A trait-based approach”

This dataset was created for our study on the impacts of linear infrastructure on the population abundance of vertebrate species. We obtained mean abundances and standard deviations of vertebrate populations in sites disturbed by infrastructure and corresponding undisturbed sites by searching for published peer-reviewed and grey literature. We extracted 3,912 pairwise abundance comparisons between disturbed and non-disturbed areas from 110 primary sources, spanning 26 countries and 6 continents and 160, 443, 97 and 92 species of mammals, birds, reptiles and amphibians, respectively. We also extracted the sample size and sampling effort per sample for each observation to perform meta-analyses per species group. Additionally, we extracted the mean distance to infrastructure in the disturbed sites to determine how infrastructure affects vertebrate populations as a function of distance and derive the mean infrastructure-effect zone for each species group using meta-regression models. Further, we extracted the type of infrastructure and habitat for each observation as well as the mean body mass for all species and diet for mammals and birds to determine how infrastructure impacts are modulated by environmental characteristics and species traits using meta-regressions. The results of this research will be published as: de Jonge, M. M. J., Gallego-Zamorano, J., Huijbregts, M. A. J., Schipper, A. M., & Benítez‐López, A. (in press). The impact of linear infrastructure on terrestrial vertebrate populations: A trait-based approach. Global Change Biology This dataset, as well as the R scripts for the corresponding analysis and the full fitted models are available at: https://github.com/MelindadeJonge/Infrastructure_MetaAnalysis. The data is stored in 4 files ●2022_deJonge_Dataset_092022.csv: The full dataset including the sample size, mean abundance, standard deviation of the mean, habitat type, infrastructure type, source, location, species, and quality of each observation. For a description of how the data was extracted we refer the reader to: 2022_deJonge_Methodology_092022.pdf ●2022_deJonge_speciesList_092022.csv: a list of all species included in the database together with their identification code, body mass (g), diet (only for mammals and birds) and body length (mm, only for amphibians). ●2022_deJonge_CrossswalkInfrastructure.csv: Crosswalk to link the habitat types as reported in the database to a binary classification (open/closed). ●2022_deJonge_CrosswalkHabitat.csv: Crosswalk to link the infrastructure types as reported in the database to the classification scheme used in the analysis (paved roads, unpaved roads, powerlines, other non-traffic infrastructure). Additional information An overview of the definitions and units of the variables in each file is given in the codebook: “2022_deJonge_Codebook_092022.pdf” A description of the methodology used to obtain the data is given in ‘2022_deJonge_Methodology_092022.pdf” A list of all data sources is given in “2022_deJonge_dataSources.pdf

Assessing the efficacy and safety of mycophenolate mofetil versus azathioprine in patients with autoimmune hepatitis (CAMARO trial): study protocol for a randomised controlled trial

Background: Currently, the standard therapy for autoimmune hepatitis (AIH) consists of a combination of prednisolone and azathioprine. However, 15% of patients are intolerant to azathioprine which necessitates cessation of azathioprine or changes in therapy. In addition, not all patients achieve complete biochemical response (CR). Uncontrolled data indicate that mycophenolate mofetil (MMF) can induce CR in a majority of patients. Better understanding of first-line treatment and robust evidence from randomised clinical trials are needed. The aim of this study was to explore the potential benefits of MMF as compared to azathioprine, both combined with prednisolone, as induction therapy in a randomised controlled trial in patients with treatment-naive AIH. Method:s: CAMARO is a randomised (1:1), open-label, parallel-group, multicentre superiority trial. All patients with AIH are screened for eligibility. Seventy adult patients with AIH from fourteen centres in the Netherlands and Belgium will be randomised to receive MMF or azathioprine. Both treatment arms will start with prednisolone as induction therapy. The primary outcome is biochemical remission, defined as serum levels of alanine aminotransferase and immunoglobulin G below the upper limit of normal. Secondary outcomes include safety and tolerability of MMF and azathioprine, time to remission, changes in Model For End-Stage Liver Disease (MELD)-score, adverse events, and aspects of quality of life. The study period will last for 24 weeks. Discussion: The CAMARO trial investigates whether treatment with MMF and prednisolone increases the proportion of patients in remission compared with azathioprine and prednisolone as the current standard treatment strategy. In addition, we reflect on the challenges of conducting a randomized trial in rare diseases

Data of 'Relating plant height to demographic rates and extinction vulnerability'

This dataset was developed for our study on plant allometry and extinction vulnerabilities. In this study we gathered plant demographic data from various sources and related this to maximum plant height. We derived allometric relationships with maximum plant height for the intrinsic population growth rate, variance in population growth rate due to environmental stochasticity and the maximum plant density. These relationships were used to relate maximum plant height to the Mean time to extinction and the Probability of extinction. The results of this research will soon be published as ‘Relating plant height to demographic rates and extinction vulnerability’ (forthcoming). In this repository we provide only the processed data from this study because the original data was gathered from existing open access and semi-open access databases. Original data for this project was gathered from the following databases: (1) TRY Plant Trait Database, (2) COMPADRE Plant Matrix Database Version 4.0.1, (3) Biomass allocation and growth data of seeded plants The processed data is stored in two files: - 2017_deJonge_MaximumPlantDensity.csv: This file contains 230 datapoints with maximum plant density (per square meter) and average individual plant mass (grams). A description of the methodology used to obtain the processed data is given in a PDF file called ‘2017_deJonge_Methodology.pdf’. Additionally, a description file called 'description.pdf' is added, which includes the information mentioned above