cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.4263905.v4
title: Code and Data: Critical transitions and the fragmenting of global forests

description: Source code for image processing and statistical analysis, and the patch size data files for the manuscript:<b><br></b><b>Critical transitions and the fragmenting of global forests</b>. (2016) Saravia L.A. Doyle S.R. Bond-Lamberty B. bioRxiv 091751; doi: http://dx.doi.org/10.1101/091751<br>Zip Files:<br>Patch Sizes distribution by region and year from 2000 to 2014: these are binary files consisting on a vector of doubles, the R command used to read it is readBin(connection_file, "double", n = 10^6)<br><b>africa_PatchSizes.zip</b><b>northamerica_PatchSizes.zip</b><b>southamerica_PatchSizes.zip</b><b>eurasia_PatchSizes.zip</b><b>oceania_PatchSizes.zip</b><b>southasia_PatchSizes.zip</b><br><b><br></b><b>ShaliziCodePowerlaw.zip</b> Code from C. R. Shalizi to fit power exponential distribution.<br><br><b>LargestPatchAnimations.zip</b> Animations of the two largest patches for all the regions defined in the paper. <br><b>PercolationAnimations.zip </b> Animation demonstrating percolation in a forest/non-forest model<br>Model fits plots of inverse cumulative distributions for patch size distribution by region and year: <b>africaAlphaEstimation.zip</b><b><br></b><b>eurasiaAlphaEstimation.zip</b><b><br></b><b>northamericaAlphaEstimation.zip</b><br><b>oceaniaAlphaEstimation.zip</b><br><b>southamericaAlphaEstimation.zip</b><br><b>southasiaAlphaEstimation.zip</b><br><b><br></b>R markdown files: <br><b>Fit_heavy_tails.Rmd</b> # Fitting heavy tails to modis VCF<b>Download_modis.Rmd</b> # Download modis files MOD44B version 051<b>Map_study_areas.Rmd</b> # Generate maps of study areas <b>Map_Max_patches.Rmd</b> # Generate GIF animations of maximum patch dynamics <br>R Files<b><br></b><b>map_fun.r </b># Map raster functions<b>power_fun.r </b># Function to fit continuos heavy tail distributions<br>MATLAB Files<br>Extract patch sizes from bin, and other analysis not used in the paper<br><b>data_input_script.m</b><b>GCF_spatial_analyses.m</b><br> DATA Tables: csv and tab separated text files with model fits for the patch size distribution models.<br><strong>Fitted_Patch_models.csv</strong><strong><strong>Fitted_Patch_models.txt</strong></strong><strong><strong><br></strong></strong><strong><strong><br></strong></strong><br>
DOI: 10.6084/m9.figshare.4263887.v1
title: Real-world data on nivolumab treatment of non-small cell lung cancer

description: <b>Background:</b> Checkpoint inhibitors have proven effectiveness in clinical trials for non-small cell lung cancer (NSCLC) patients, but if this is congruent with routine patient care is discussed. We present real-world experience with the PD1-inhibitor nivolumab in NSCLC. <b>Patients and methods:</b> Patients with NSCLC were considered eligible for nivolumab treatment after one or more lines of chemotherapy, and when in reasonable performance status (PS) [Eastern Cooperative Oncology Group (ECOG) <b>Results:</b> Fifty-eight patients (30 females) commenced therapy in the period June–August 2015. Median age was 64.6 years (range 32.3–88.2). Twenty-four patients had squamous cell carcinoma and 32 adenocarcinoma, 38 had received two or more prior lines of therapy. Fourteen cases (24%) were in ECOG PS 2. After a medium observation time of 14.3 months, 13 (22%) are still in treatment. Median time to treatment failure (TTF) was 4.0 months, 34% were off treatment during the first two months. Median overall survival (OS) is 11.7 months. There was no difference in TTF or OS among patients with squamous versus non-squamous histology or between 1 versus &gt;1 prior line of therapy. Four patients (7%) were off treatment due to toxicity, none were grade 4 or 5. <b>Conclusion:</b> Nivolumab treatment outside clinical trials seems to perform as expected.
DOI: 10.6084/m9.figshare.4263905.v5
title: Code and Data: Critical transitions and the fragmenting of global forests

description: Source code for image processing and statistical analysis, and the patch size data files for the manuscript:<b><br></b><b>Critical transitions and the fragmenting of global forests</b>. (2016) Saravia L.A. Doyle S.R. Bond-Lamberty B. bioRxiv 091751; doi: http://dx.doi.org/10.1101/091751<br>Zip Files:<br>Patch Sizes distribution by region, year and threshold from 2000 to 2015: these are binary files consisting on a vector of doubles, the R command used to read it is readBin(connection_file, "double", n = 10^8)<br><b>Africa_PatchSizes.zip</b><b>Northamerica_PatchSizes.zip</b><b>Southamerica_PatchSizes.zip</b><b>Eurasia_PatchSizes.zip</b><b>Oceania_PatchSizes.zip</b><b>Southasia_PatchSizes.zip</b><br><br><b>LargestPatchAnimations.zip</b> Animations of the two largest patches for all the regions defined in the paper. <br><b>PercolationAnimations.zip </b> Animation demonstrating percolation in a forest/non-forest model<br>R markdown files:<br><br><b>Threshold_sensitivity.Rmd</b> # Fitting heavy tails to modis VCF, Smax & RSmax patch analysis. <br><b>Download_modis.Rmd</b> # Download modis files MOD44B version 051<b><br></b><b>Map_study_areas.Rmd</b> # Generate maps of study areas <b><br></b><b>Map_Max_patches.Rmd</b> # Generate GIF animations of maximum patch dynamics <br>R Files<b><br></b><b>map_fun.r </b># Map raster functions<b>power_fun.r </b># Function to fit continuos heavy tail distributions<br>MATLAB Files<br>Extract patch sizes from bin, and other analysis not used in the paper<br><b>data_input_script.m</b><b>GCF_spatial_analyses.m</b><b><br></b>PYTHON Files<br><strong>powlawfit.py :</strong> Call the Python powerlawpackage from command line <br><br><br> DATA Tables: csv and tab separated text files with model fits for the patch size distribution models.<br><strong>Fitted_Patch_models.csv</strong><strong><strong>Fitted_Patch_models.txt</strong></strong><strong><strong><br></strong></strong><strong><strong><br></strong></strong><br>
DOI: 10.6084/m9.figshare.4263905.v6
title: Code and Data: Power laws and critical fragmentation in global forests

description: Source code for image processing and statistical analysis, and the patch size data files for the manuscript:<b><br></b><b>Power laws and critical fragmentation in global forests</b>. (2016) Saravia L.A. Doyle S.R. Bond-Lamberty B. bioRxiv 091751; doi: http://dx.doi.org/10.1101/091751<br>Zip Files:<br>Patch Sizes distribution by region, year and threshold from 2000 to 2015: these are binary files consisting on a vector of doubles, the R command used to read it is readBin(connection_file, "double", n = 10^8)<br><b>Africa_PatchSizes.zip</b><b>Northamerica_PatchSizes.zip</b><b>Southamerica_PatchSizes.zip</b><b>Eurasia_PatchSizes.zip</b><b>Oceania_PatchSizes.zip</b><b>Southasia_PatchSizes.zip</b><br><br><b>LargestPatchAnimations.zip</b> Animations of the two largest patches for all the regions defined in the paper. <br><b>PercolationAnimations.zip </b> Animation demonstrating percolation in a forest/non-forest model<br>R markdown files:<br><br><b>Threshold_sensitivity.Rmd</b> # Fitting heavy tails to modis VCF, Smax & RSmax patch analysis. <br><b>Download_modis.Rmd</b> # Download modis files MOD44B version 051<b><br></b><b>Map_study_areas.Rmd</b> # Generate maps of study areas <b><br></b><b>Map_Max_patches.Rmd</b> # Generate GIF animations of maximum patch dynamics <br>R Files<b><br></b><b>map_fun.r </b># Map raster functions<b>power_fun.r </b># Function to fit continuos heavy tail distributions<br>MATLAB Files<br>Extract patch sizes from bin, and other analysis not used in the paper<br><b>data_input_script.m</b><b>GCF_spatial_analyses.m</b><b><br></b>PYTHON Files<br><strong>powlawfit.py :</strong> Call the Python powerlawpackage from command line <br><br><br> DATA Tables: csv and tab separated text files with model fits for the patch size distribution models.<br><strong>Fitted_Patch_models.csv</strong><strong><strong>Fitted_Patch_models.txt</strong></strong><strong><strong><br></strong></strong><strong><strong><br></strong></strong><br>
DOI: 10.6084/m9.figshare.4263713
title: Catheter and Laryngeal Mask Endotracheal Surfactant Therapy: the CALMEST approach as a novel MIST technique

description: <i>Purpose</i>: Neonatal respiratory distress syndrome (RDS) is a major cause of mortality and morbidity among preterm infants. Although the INSURE (INtubation, SURfactant administration, Estubation) technique for surfactant replacement therapy is so far the gold standard method, over the last years new approaches have been studied, i.e. less invasive surfactant administration (LISA) or minimally invasive surfactant therapy (MIST). Here we propose an originally modified MIST, called CALMEST (Catheter And Laryngeal Mask Endotracheal Surfactant Therapy), using a particular laryngeal mask as a guide for a thin catheter to deliver surfactant directly in the trachea. <i>Materials and methods</i>: We performed a preliminary study on a mannequin and a subsequent <i>in vivo</i> pilot trial. <i>Results and conclusions</i>: This novel procedure is quick, effective and well tolerated and might represent an improvement in reducing neonatal stress. Ultimately, CALMEST offers an alternative approach that could be extremely useful for medical staff with low expertise in laryngoscopy and intubation.
DOI: 10.6084/m9.figshare.4263713.v1
title: Catheter and Laryngeal Mask Endotracheal Surfactant Therapy: the CALMEST approach as a novel MIST technique

description: <i>Purpose</i>: Neonatal respiratory distress syndrome (RDS) is a major cause of mortality and morbidity among preterm infants. Although the INSURE (INtubation, SURfactant administration, Estubation) technique for surfactant replacement therapy is so far the gold standard method, over the last years new approaches have been studied, i.e. less invasive surfactant administration (LISA) or minimally invasive surfactant therapy (MIST). Here we propose an originally modified MIST, called CALMEST (Catheter And Laryngeal Mask Endotracheal Surfactant Therapy), using a particular laryngeal mask as a guide for a thin catheter to deliver surfactant directly in the trachea. <i>Materials and methods</i>: We performed a preliminary study on a mannequin and a subsequent <i>in vivo</i> pilot trial. <i>Results and conclusions</i>: This novel procedure is quick, effective and well tolerated and might represent an improvement in reducing neonatal stress. Ultimately, CALMEST offers an alternative approach that could be extremely useful for medical staff with low expertise in laryngoscopy and intubation.
DOI: 10.6084/m9.figshare.4263629
title: PowerPoint Slides for: Vitamin K Metabolism in a Rat Model of Chronic Kidney Disease

description: <i>Background:</i> Patients with chronic kidney disease (CKD) have very high levels of uncarboxylated, inactive, extra-hepatic vitamin K-dependent proteins measured in circulation, putting them at risk for complications of vitamin K deficiency. The major form of vitamin K found in the liver is phylloquinone (K1). Menaquinone-4 (MK-4) is the form of vitamin K that is preferentially found in extra-hepatic tissues. <i>Methods:</i> In the present study, we assessed tissue concentrations of K1 and MK-4 and the expression of vitamin K-related genes in a rat model of adenine-induced CKD. <i>Results:</i> It was found that rats with both mild and severe CKD had significantly lower amounts of K1 measured in liver, spleen and heart and higher levels of MK-4 measured in kidney cortex and medulla. All animals treated with high dietary K1 had an increase in tissue levels of both K1 and MK-4; however, the relative increase in K1 differed suggesting that the conversion of K1 to MK-4 may be a regulated/limiting process in some tissues. There was a decrease in the thoracic aorta expression of vitamin K recycling (<i>Vkor</i>) and utilization (<i>Ggcx</i>) enzymes, and a decrease in the kidney level of vitamin K1 to MK-4 bioconversion enzyme <i>Ubiad1</i> in CKD. <i>Conclusion:</i> Taken together, these findings suggest that CKD impacts vitamin K metabolism, and this occurs early in the disease course. Our findings that vitamin K metabolism is altered in the presence of CKD provides further support that sub-clinical vitamin K deficiency may represent a modifiable risk factor for vascular and bone health in this population.
DOI: 10.6084/m9.figshare.4263647
title: PowerPoint Slides for: Disparities in Kidney Transplantation Access among Korean Patients Initiating Dialysis: A Population-Based Cohort Study Using National Health Insurance Data (2003-2013)

description: <i>Background:</i> The socioeconomic status of a person has an impact on his or her access to kidney transplantation as has been reported in western countries. This study examined the association between income level and kidney transplantation among chronic kidney disease patients undergoing dialysis in South Korea. <i>Methods:</i> We analyzed data from 1,792 chronic kidney disease patients undergoing dialysis and listed in the Korean National Health Insurance Claim Database (2003-2013). The likelihood of receiving the first kidney transplant over time was analyzed using competing risk proportional hazard models on time from initiating dialysis to receiving a transplant. <i>Results:</i> Of 1,792 patients on dialysis, only 184 patients (10.3%) received kidney transplants. Patients with medical aid had the lowest kidney transplantation rate (hazard ratio 0.29, 95% CI 0.16-0.51). A lower income level was significantly associated with a low kidney transplantation rate, after adjusting for covariates, compared to patients in the high-income level group. <i>Conclusions:</i> Our findings indicate that in South Korea, the total number of kidney transplants is remarkably low and there exists income disparity with regard to access to kidney transplantation. Thus, we suggest that plans be implemented to encourage organ donation and increase organ transplant accessibility for all patients irrespective of their socioeconomic status.
DOI: 10.6084/m9.figshare.4263629.v1
title: PowerPoint Slides for: Vitamin K Metabolism in a Rat Model of Chronic Kidney Disease

description: <i>Background:</i> Patients with chronic kidney disease (CKD) have very high levels of uncarboxylated, inactive, extra-hepatic vitamin K-dependent proteins measured in circulation, putting them at risk for complications of vitamin K deficiency. The major form of vitamin K found in the liver is phylloquinone (K1). Menaquinone-4 (MK-4) is the form of vitamin K that is preferentially found in extra-hepatic tissues. <i>Methods:</i> In the present study, we assessed tissue concentrations of K1 and MK-4 and the expression of vitamin K-related genes in a rat model of adenine-induced CKD. <i>Results:</i> It was found that rats with both mild and severe CKD had significantly lower amounts of K1 measured in liver, spleen and heart and higher levels of MK-4 measured in kidney cortex and medulla. All animals treated with high dietary K1 had an increase in tissue levels of both K1 and MK-4; however, the relative increase in K1 differed suggesting that the conversion of K1 to MK-4 may be a regulated/limiting process in some tissues. There was a decrease in the thoracic aorta expression of vitamin K recycling (<i>Vkor</i>) and utilization (<i>Ggcx</i>) enzymes, and a decrease in the kidney level of vitamin K1 to MK-4 bioconversion enzyme <i>Ubiad1</i> in CKD. <i>Conclusion:</i> Taken together, these findings suggest that CKD impacts vitamin K metabolism, and this occurs early in the disease course. Our findings that vitamin K metabolism is altered in the presence of CKD provides further support that sub-clinical vitamin K deficiency may represent a modifiable risk factor for vascular and bone health in this population.
DOI: 10.6084/m9.figshare.4263647.v1
title: PowerPoint Slides for: Disparities in Kidney Transplantation Access among Korean Patients Initiating Dialysis: A Population-Based Cohort Study Using National Health Insurance Data (2003-2013)

description: <i>Background:</i> The socioeconomic status of a person has an impact on his or her access to kidney transplantation as has been reported in western countries. This study examined the association between income level and kidney transplantation among chronic kidney disease patients undergoing dialysis in South Korea. <i>Methods:</i> We analyzed data from 1,792 chronic kidney disease patients undergoing dialysis and listed in the Korean National Health Insurance Claim Database (2003-2013). The likelihood of receiving the first kidney transplant over time was analyzed using competing risk proportional hazard models on time from initiating dialysis to receiving a transplant. <i>Results:</i> Of 1,792 patients on dialysis, only 184 patients (10.3%) received kidney transplants. Patients with medical aid had the lowest kidney transplantation rate (hazard ratio 0.29, 95% CI 0.16-0.51). A lower income level was significantly associated with a low kidney transplantation rate, after adjusting for covariates, compared to patients in the high-income level group. <i>Conclusions:</i> Our findings indicate that in South Korea, the total number of kidney transplants is remarkably low and there exists income disparity with regard to access to kidney transplantation. Thus, we suggest that plans be implemented to encourage organ donation and increase organ transplant accessibility for all patients irrespective of their socioeconomic status.
DOI: 10.6084/m9.figshare.4263602
title: Figure 9

description: 3D LES flow fields, and wind farm layout information. The accompanying "load.py" python file can be used to load the data.<br>data accompanying paper:"Wind-farm layout optimisation using a hybrid Jensen-LES approach" by Vahid S. Bokharaie, Pieter Bauweraerts and Johan Meyers
DOI: 10.6084/m9.figshare.4263599
title: Figure 8

description: 3D LES flow fields, and wind farm layout information. The accompanying "load.py" python file can be used to load the data.<br>data accompanying paper:"Wind-farm layout optimisation using a hybrid Jensen-LES approach" by Vahid S. Bokharaie, Pieter Bauweraerts and Johan Meyers
DOI: 10.6084/m9.figshare.4263602.v1
title: Figure 9

description: 3D LES flow fields, and wind farm layout information. The accompanying "load.py" python file can be used to load the data.<br>data accompanying paper:"Wind-farm layout optimisation using a hybrid Jensen-LES approach" by Vahid S. Bokharaie, Pieter Bauweraerts and Johan Meyers
DOI: 10.6084/m9.figshare.4263596
title: Figure 7

description: 3D LES flow fields, and wind farm layout information. The accompanying "load.py" python file can be used to load the data.<br>data accompanying paper:"Wind-farm layout optimisation using a hybrid Jensen-LES approach" by Vahid S. Bokharaie, Pieter Bauweraerts and Johan Meyers
DOI: 10.6084/m9.figshare.4263599.v1
title: Figure 8

description: 3D LES flow fields, and wind farm layout information. The accompanying "load.py" python file can be used to load the data.<br>data accompanying paper:"Wind-farm layout optimisation using a hybrid Jensen-LES approach" by Vahid S. Bokharaie, Pieter Bauweraerts and Johan Meyers
DOI: 10.6084/m9.figshare.4263593
title: Figure 6

description: 3D LES flow fields, and wind farm layout information. The accompanying "load.py" python file can be used to load the data.<br>data accompanying paper:"Wind-farm layout optimisation using a hybrid Jensen-LES approach" by Vahid S. Bokharaie, Pieter Bauweraerts and Johan Meyers
DOI: 10.6084/m9.figshare.4263596.v1
title: Figure 7

description: 3D LES flow fields, and wind farm layout information. The accompanying "load.py" python file can be used to load the data.<br>data accompanying paper:"Wind-farm layout optimisation using a hybrid Jensen-LES approach" by Vahid S. Bokharaie, Pieter Bauweraerts and Johan Meyers
DOI: 10.6084/m9.figshare.4263593.v1
title: Figure 6

description: 3D LES flow fields, and wind farm layout information. The accompanying "load.py" python file can be used to load the data.<br>data accompanying paper:"Wind-farm layout optimisation using a hybrid Jensen-LES approach" by Vahid S. Bokharaie, Pieter Bauweraerts and Johan Meyers
DOI: 10.6084/m9.figshare.4263578
title: Figure 4

description: 3D LES flow fields, Jensen flow fields and wind farm layout information. The accompanying "load.py" python file can be used to load the data.<br>data accompanying paper:"Wind-farm layout optimisation using a hybrid Jensen-LES approach" by Vahid S. Bokharaie, Pieter Bauweraerts and Johan Meyers
DOI: 10.6084/m9.figshare.4263584
title: Figure 5

description: 3D LES flow fields, and wind farm layout information. The accompanying "load.py" python file can be used to load the data.<br>data accompanying paper:"Wind-farm layout optimisation using a hybrid Jensen-LES approach" by Vahid S. Bokharaie, Pieter Bauweraerts and Johan Meyers
DOI: 10.6084/m9.figshare.4263578.v1
title: Figure 4

description: 3D LES flow fields, Jensen flow fields and wind farm layout information. The accompanying "load.py" python file can be used to load the data.<br>data accompanying paper:"Wind-farm layout optimisation using a hybrid Jensen-LES approach" by Vahid S. Bokharaie, Pieter Bauweraerts and Johan Meyers
DOI: 10.6084/m9.figshare.4263584.v1
title: Figure 5

description: 3D LES flow fields, and wind farm layout information. The accompanying "load.py" python file can be used to load the data.<br>data accompanying paper:"Wind-farm layout optimisation using a hybrid Jensen-LES approach" by Vahid S. Bokharaie, Pieter Bauweraerts and Johan Meyers
DOI: 10.6084/m9.figshare.4263572
title: Figure 3 TL

description: 3D LES flow fields, and wind farm layout information. The accompanying "load.py" python file can be used to load the data.<br>data accompanying paper:"Wind-farm layout optimisation using a hybrid Jensen-LES approach" by Vahid S. Bokharaie, Pieter Bauweraerts and Johan Meyers
DOI: 10.6084/m9.figshare.4263575
title: Figure 3 TR

description: 3D LES flow fields, and wind farm layout information. The accompanying "load.py" python file can be used to load the data.<br>data accompanying paper:"Wind-farm layout optimisation using a hybrid Jensen-LES approach" by Vahid S. Bokharaie, Pieter Bauweraerts and Johan Meyers
DOI: 10.6084/m9.figshare.4263572.v1
title: Figure 3 TL

description: 3D LES flow fields, and wind farm layout information. The accompanying "load.py" python file can be used to load the data.<br>data accompanying paper:"Wind-farm layout optimisation using a hybrid Jensen-LES approach" by Vahid S. Bokharaie, Pieter Bauweraerts and Johan Meyers
DOI: 10.6084/m9.figshare.4263575.v1
title: Figure 3 TR

description: 3D LES flow fields, and wind farm layout information. The accompanying "load.py" python file can be used to load the data.<br>data accompanying paper:"Wind-farm layout optimisation using a hybrid Jensen-LES approach" by Vahid S. Bokharaie, Pieter Bauweraerts and Johan Meyers
DOI: 10.6084/m9.figshare.4263569
title: Histology raw data

description: The table shows an overview of the histologic grading. The table provides Group number (1 = Control, 2 = CATH, 3 = SHAM), Mouse ID (Mouse), section number (Section), Observer ID (Observer) as well as parameter scores. Hearts were sampled for histopathological evaluation and serial transverse sections from base to apex with 300 µm distance were evaluated from each heart. Each section was graded with respect to six parameters: inflammation, perivascular inflammation, cardiomyocyte vacuolization, cardiomyocyte hyalinization, necrosis and fibrosis. The sections were scored blinded by two, independent pathologists, Observer 1 and 2, respectively. When multiple lesions of same type (parameter) were noted in one section, the most severe lesion (highest grade) was scored. Lesion place and inflammation type was concurrently noted (not shown in this table). CATH = mice were subjected to surgery with implantation of a catheter in their right common carotid artery. SHAM = mice were subjected to surgery with ligation but not catheterization of their right common carotid artery. CTRL = control mice, not subjected to surgery.<br>Paper available at Lab Anim<br>