dataesr/scientific-paragraphs-categorization huggingface dataset:
Tolerance of MTX and discontinuation Tolerance data on MTX are more consensual than those for efficacy. The most common side effects include gastrointestinal effects, abnormal liver function results, and respiratory symptoms. The most severe adverse effects associated with MTX are medullar aplasia and MTX pneumonitis; however, these adverse effects are rare. 21, 22 astrointestinal disorders associated with MTX are the main cause of MTX discontinuation. MTX withdrawal was estimated at 8-33%, occurring during the first 6 months of treatment. 23, 24 In the Cochrane MTX for PsA review, four studies reported serious adverse events and also reported associated withdrawals, but MTX discontinuation was comparable to that with placebo [risk ratio, 1. 32 (95% confidence interval (CI), 0. 51-3. 42)].
The effect of MTX on drug survival was most prominent in patients receiving infliximab. 32  In contrast, analysis of data in the Canadian Rhumadata clinical database and registry found that concomitant MTX did not demonstrate improved 5-year retention with adalimumab or etanercept (52% for combination therapy versus 67% for monotherapy; p = 0. 74). 44 retrospective analysis of 487 PsA patients with ustekinumab treatment in Hungary showed that concomitant MTX did not have a significant effect on ustekinumab survival. 45  No clear data are available for interleukin 17 inhibitors or JAKi at this time. 46  Other conditions one should be aware of As previously mentioned, bDMARDs and tsD-MARDs must now be positioned as first-line therapies in PsA patients with 'severe' disease or 'poor prognosis'.
Despite historical mischaracterization as a cosmetic condition, patients with the autoimmune disorder vitiligo experience substantial quality-of-life (QoL) burden. This systematic literature review of peer-reviewed observational and interventional studies describes comprehensive evidence for humanistic burden in patients with vitiligo. PubMed, EMBASE, Scopus and the Cochrane databases were searched through February 10, 2021, to qualitatively assess QoL in vitiligo. Two independent reviewers assessed articles for inclusion and extracted data for qualitative synthesis. A total of 130 included studies were published between 1996 and 2021. Geographical regions with the most studies were Europe (32. 3%) and the Middle East (26. 9%). Dermatology-specific instruments, including the Dermatology Life Quality Index (DLQI; 80 studies) and its variants for children (CDLQI; 10 studies) and families (FDLQI; 4 studies), as well as Skindex instruments (Skindex-29, 15 studies; Skindex-16, 4 studies), were most commonly used to measure humanistic burden.
Literature search PubMed, EMBASE, Scopus and the Cochrane database were searched for articles from the earliest entry in respective databases through February 10, 2021. The search string (Appendix S1), which was limited to articles published in English, included the keywords vitiligo, leucoderma, leukoderma, quality of life and patient-reported outcomes. No limitations were placed on interventions. Duplicate results from the separate databases were removed before assessment of article eligibility. Subsequent to the searches, additional articles were identified from other sources, including through appraisal of existing systematic reviews and meta-analyses. Peer-reviewed primary publications, including interventional and observational studies, were selected for inclusion. Two independent reviewers (WvdS and KW) performed title and abstract review as well as a full-text review and data extraction.
Studies excluded during these processes were reviews, editorials and commentaries, study protocols, articles with content irrelevant to general QoL in vitiligo, data sets that had <5 participants (e. g. patients with vitiligo or their caregivers), and retracted articles. The reviewers independently assessed the risk of bias in a qualitative manner and resolved disagreements by discussion. This systematic literature review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. 17 No institutional review board approval was required for the study because all data were collected from published articles. The study protocol was registered with PROSPERO (CRD42021260138).
Literature search Initial database searches yielded 620 results, of which 285 were duplicate records that were excluded from screening; 14 records were identified through other sources. Screening resulted in the exclusion of 179 articles during title and abstract review; an additional 40 articles were excluded upon full-text review due to irrelevant content (n = 30), inclusion of <5 patients with vitiligo or their caregivers (n = 6), editorials/commentaries (n = 2), reviews (n = 1) and retracted articles (n = 1). A total of 130 articles were retained for data extraction and inclusion in qualitative synthesis (Fig. 1 ).
MP has served as a consultant for  Incyte Corporation  and  Pfizer , a principal investigator for  Pfizer  and PPM, and received non-restricted research grants from  Pierre Fabre  and PPM. RHH has served as a principal investigator for  Incyte Corporation  and  Pfizer  and a subinvestigator for  Immune Tolerance Network. HJ was an employee and shareholder of  Incyte Corporation  when the study was conducted. RM and MO are employees and shareholders of  Incyte Corporation. JS has received grants and/or honoraria from  AbbVie ,  Calypso Biotech ,  Bristol Myers Squibb, Incyte Corporation, LEO Pharma ,  Eli Lilly ,  Novartis ,  Pfizer ,  Pierre-Fabre , The study was funded by  Incyte Corporation, Wilmington, DE, USA , which was involved in design of the literature search, analysis of the search results, manuscript preparation and publication decisions in collaboration with the authors.
Several holes were drilled during this expedition (Fig. 1 ). Logging while drilling (LWD) data were successfully recovered while drilling hole C0019B to the depth of 850 meters below seafloor (mbsf). The primary purpose for drilling hole C0019D up to 854. 8 mbsf was to install observatory instruments to monitor wellbore temperature. Furthermore, drilling cores were acquired from hole C0019E, which was drilled until 844. 5 mbsf, close to C0019B (about 10m south of this hole). It is now well established that fluids can greatly affect fault strength and consequently trigger an earthquake. Porosity is a fundamental property of rocks that can help to understand tectonic processes and fault zone behavior as it can serve as an indicator of Coseismic volumetric strain and fluid pressure anomaly around the fault zone  (Wang & Barbour, 2017).
This method, which is based on the analysis of an intensity histogram, having defined a value as a threshold, pixels with values less and higher than the threshold are considered different phases. Two approaches for image segmentation are employed in this work. First, the AVIZO® software is used, which provides an interactive thresholding panel with several tools for segmentation that can be combined to separate pores from solid. However, since the threshold is visually determined in this method, results can be highly biased by the user, leading to over/underestimation of porosity  (Chauhan et al. , 2016; Iassonov et al. , 2009; Kaestner et al. , 2008). Fig. 4  shows the threshold value and segmented (binary) image obtained for one of the cores. To reduce the bias in the manual thresholding method, a second approach based on the K-means clustering algorithm was adopted.
, 2019). This low resolution will increase the risk of underestimation (or overestimation) of porosity or other subsequent quantification on the binary images. For this reason, and also because the results of segmentation by visual inspection were unsatisfactory, the number of the clusters was further explored with another index known as the Davies-Bouldin index  (Davies & Bouldin, 1979). Generally, the idea behind the different clustering approaches is to identify different groups in a given dataset. The more separated are the clusters, the better is the clustering. Furthermore, the data points belonging to each cluster should be as close as possible in terms of intensity values  (Halkidi et al. , 2001). Davies-Bouldin (DB) index is a measure of similarity between each cluster   and the most similar one to it,   (,  = 1, … , ).
Introduction Immune checkpoint inhibitors (ICIs), targeting the pro-grammed-cell-death-1 protein (PD-1), its ligand (PD-L1) and the cytotoxic-T-lymphocyte-associated-antigen-4 (CTLA-4), have improved clinical outcomes of many cancer types. Despite dramatic benefits, ICIs may promote inflammation in any organ and are associated with immune-related adverse events that may concern the cardiovascular and pulmonary systems  [1] [2] [3]. As recent publications raised concerns about potential pulmonary arterial damage associated with ICIs  [4] [5] [6] , we faced a case of precapillary pulmonary hypertension (PH) occurring in a patient treated with nivolumab. We thus aimed at investigating the potential risk of PH associated with ICI cancer treatment through a descriptive analysis of the cases reported in VigiBase, the World Health Organization's pharmacovigilance database.
We selected data of all serious adverse drug reactions reported with ICIs (anti-PD-1 agents: nivolumab, pembrolizumab, cemiplimab; anti-PD-L1 agents: atezolizumab, avelumab, durvalumab; or anti-CTLA-4 agents: ipilimumab) from January 2015 (after FDA approval of nivolumab) to February 2021. PH cases were identified using a selection of MedDRA Preferred Terms (Medical Dictionary of Regulatory Activities): "pulmonary hypertension," "pulmonary arterial hypertension" and "pulmonary veno-occlusive disease. " From 73,032 ICI-associated serious adverse reactions reports recorded in VigiBase, we identified 42 PH cases including 11 PAH (26%). Among the 42 cases, 38 (90. 5%) occurred with ICI monotherapy, including 21 (50%) patients treated with nivolumab (Table  1 ). Within the 36 reports where indication was available, ICIs were mainly prescribed for lung cancer (50.
Acknowledgements The  Uppsala Monitoring Centre  has provided the data, but the study results and conclusions are those of the authors and not necessarily those of the  Uppsala Monitoring Centre, National Centers , or WHO. Author contribution P. P. , A. T. J. M. , P. G. and J. L. F. equally contributed to the design of the study, the interpretation of data, drafting, revising and approving the manuscript; P. P. , C. L. and J. L. F. acquired and analyzed the data from VigiBase; C. L. , X. Q. , D. M. , D. H. B. contributed to the conception of the work, revising and criticizing and approving the manuscript; all authors agree to be accountable for all the aspects of the work (notably accuracy/integrity of data).
Acknowledgements This research paper was funded and supported by  Directorate General for Scientific Research and Technological Development (DGRSDT) Algeria  and  French program  METMAR-MERMEX as part of the  PHC   TASSILI  project (Code PHC:  17MDU986 ; Title: Inputs, accumulations and trace metal contaminations in Algiers and  Marseille coastal areas). Gratefully acknowledged is  Dr. Matea Krmpotić  from  Ruđer Bošković Institute: Division of Experimental Physics  for comments and general discussion, which greatly improved the manuscript.
Study design and participants Between 2007 and 2010, UK Biobank recruited 502,493 participants (aged 37-73 years) from the general population. Participants attended one of 22 assessment centres across England, Scotland, and Wales where they completed a self-administered, touch-screen questionnaire and face-to-face interview, and trained staff took a series of measurements including: height, weight, and blood pressure. Ethnicity, education level, sleep duration, smoking status, and alcohol intake were self-reported. Townsend area deprivation index was derived from postcode of residence using aggregated data on unemployment, car and home ownership, and household overcrowding. (4) Blood pressure was measured by a trained nurse. Hours of physical activity were self-reported using the validated International Physical Activity Questionnaire.
Outcome ascertainment Clinical endpoints were ascertained through data linkage in the UK Biobank. Date and cause of death was obtained from death certificates held within the National Health Service Information Centre (England and Wales) and the National Health Service Central Register Scotland (Scotland). Date and cause of hospital admissions were obtained through record linkage to Health Episode Statistics (England and Wales) and Scottish Morbidity Records (Scotland). Detailed information about the linkage procedures can be found at http://content. digital. nhs. uk/services.
, 2017; Piao et al. , 2020). Here, we investigate trends of LAI and their drivers for the longest, continuous data series of 1982-2018 based on an assemble of remotely sensed data sets (AVHRR, GIMMS LAI3g, and GLASS) using a commonly used best-fit trend breaks approach including three statistical analysis models  (Chen et al. , 2014)  (a simple linear regression model, a breakpoint [BP] model and a turn-point [TP] model, see Section 2) to identify a reversal point (RP). We first analyze vegetation growing trends at both global and pixel scales using growing season integrated LAI. We use three statistical analysis models to detect the mechanism of vegetation dynamics from 1982 to 2018 and then apply the Akaike information criterion (AIC) method to choose the best fit model at each pixel across the globe  (Chen et al.
Extraction of Unchanged Plant Areas The GLASS-GLC product is used in this study to mask unchanged land cover (LC) to minimize the impact of LC change on LAI changing trends (https://doi. pangaea. de/10. 1594/PANGAEA. 913496). This product was generated by GLASS CDRs using the random forest classifier on the Google Earth Engine (GEE) platform with a spatial resolution of 5-km  (Liang et al. , 2013; Liu et al. , 2020). The overall accuracy with global forest, cropland, grassland, shrubland, tundra, barren land and snow/ice is about 82. 81%. Based on this data set, we selected pixels as unchanged land when the frequency of land cover change is lower than 3 years from 1982 to 2018 after eliminating snow/ice and water pixels. Due to the GLASS-GLC product lacking detailed sub-classification of forest, the synGLC product  (Xu et al.
, 2014)  with a spatial resolution of 8-km (https://synglc. xuguang. info/#Intro), integrated information from five land cover products such as MCD12Q1 and GLC2000, was employed to fit the five forest types, including evergreen broad-leaf forest (EBF), deciduous broadleaved forest (DBF), evergreen needle leaved forest (ENF), deciduous needle leaved forest (DNF) and mixed forest (MF), into corresponding unchanged pixels of the GLASS-GLC product. We then produced the unchanged plant area data set with nine classes. If pixels did not match forest types for the two products, we chose GLASS-GLC classes data. Only pixels classified as forest in GLASS-GLC and any types of forest in synGLC can be transformed and replaced.
Extraction of Growing Season Phenology The study focuses on the LAI in growing season and it was extracted following researches  (Zhu et al. , 2016). Considering the missing daily values of AVHRR LAI products, to reduce the uncertainty of plant growing season extraction, we first interpolated the 8-day GLASS LAI data linearly to daily intervals, then the Savitzky-Golay filter was utilized to do data smoothing. From the beginning of each year, the start date of growing season was determined when the value of LAI reaches the 15% of overall amplitude and exceeds 0. 1 m 2 m -2. The end time of growing season was determined when LAI fulfills the conditions of 15% of overall amplitude and exceeds 0. 1 m 2 m -2 , with this time should be after the date corresponding to the maximum (see Figure  S18  in Supporting Information S1 as an example).
Eventually, the growing season length for every year can be defined as the span between the start and end dates, while the 37-year average was regarded as overall growing season length. Because of the lag of the growing season in the southern hemisphere, the yearly calculation was based on 2-year LAI datasets and the range was restricted in 365 days, particularly the start and end dates for EBF were simply set as 1 and 365, respectively. Finally, the start and end dates of growing season during 1982-2018 were derived from the global gridded LAI data set (Figure  S19  in Supporting Information S1).
7% [45. 0%]) and GLASS LAI (Figure  1e ). All three LAI data sets also consistently show a gradually increasing LAI trend (best fit linear model, greening) over less than 9. 4% of global vegetated land (Figure  1e ). Overall, the BP model detected RPs predominantly across the globe, while the TP model detected RPs mainly in the northern Eurasia, central Africa and southern north America (Figures S2-S4 in Supporting Information S1). The global ensemble median trends in the growing season LAI before BP and TP were 0. 0942 (95% CI (confident interval): 0. 0936-0. 0947) and 0. 1007 (95% CI: 0. 1000-0. 10134) m 2 m -2 decadel -1 , while after the RPs of the BP and TP models were -0. 0053 (95% CI: -0. 0044 to -0. 0061) and -0. 0559 (95% CI: -0. 0576 to -0. 0542) m 2 m -2 decadel -1 , respectively (t-test, trends before and after BP are significant different, p < 0.
1, Figures  1f  and 1g , Figures  2a  and 2b , Figures  S5a  and S5b , and Figures  S6a  and S6b  In Supporting Information S1). We next calculated the time series of trends in the growing season LAI with 15-year moving windows during 1982-2018 (Figure  1h ). We found that the global mean trends significantly increased from 1982 to 2003 and then decreased to 2011 and then stalled to date based on the AVHRR and GLASS data sets; and the GIMMS LAI3g shows that the trends kept on decreasing from 1982 to 2010 at a rate of -0. 016 m 2 m -2 decadel -2 , and then stalling to 2018. As shown in Figure  2  and a Figures S5-S6 in Supporting Information S1, the three data sets consistently show positive and negative values over a large proportion of the global vegetated land during the periods before and after the RPs, respectively.
Before the RPs, the pronounced growth spread over most of six continents, especially over the mid-low latitudes such as south Asia and north Africa primarily controlled by the BP model. Whereas vegetation browning (i. e. , LAI decreasing) remarkably occupied western North America and Amazon regions. It was reported that the inferior data quality caused by cloudy over Amazon may cause a great deal of trend uncertainty and affect the fitting results between different LAI products  (Chen et al. , 2019; Forzieri et al. , 2017). The global ensemble median trends in the growing season LAI before the RPs estimated from the three data sets are 5. 91 ± 3. 34% decadel -1 (0. 090 ± 0. 241 m 2 m -2 decadel -1 ), with 6. 16 ± 3. 85% (0. 094 ± 0. 235) and 6. 58 ± 4. 18% (0. 100 ± 0. 275) of BP and TP, respectively.
05° and temporal resolutions of 8 days (http://www. glass. umd. edu/Download. html) was produced using MODIS and AVHRR land surface reflectance via Generalized Regression Neural Network (GRNNs) model, and the accuracy was evaluated by comparing with other LAI products such as MODIS and CYCLOPES, as well as field measurements. The GIMMS LAI data set, named LAI3g, was generated based on AVHRR GIMMS NDVI3g, MODIS LAI datasets using a Feed Forward Neural Network (FFNN) model with a composited temporal resolution of 15 days and a bi-cubic resampled spatial resolution of 1/12° (http://sites. bu. edu/cliveg/datacodes/). Evaluation of this product also utilized LAI products for other satellites and field measurements. Using the same way of processing AVHRR LAI, the two products can be composited to multi-year global LAI means(1982-2018 of GLASS, 1982-2016 of LAI3g).
Data Availability Statement There are three popular and state-of-arts LAI data sets used in this study, which are the AVHRR LAI data set, the GIMMS LAI3g LAI data set, and the GLASS LAI data set, and are respectively available at https://data. noaa. gov/ dataset/dataset/noaa-climate-data-record-cdr-of-avhrr-leaf-area-index-lai-and-fraction-of-absorbed-photosynthet, http://sites. bu. edu/cliveg/datacodes/, and http://www. glass. umd. edu/Download. html. The climate data set (maximum and mean daily air temperature, vapor pressure deficit, actual vapor pressure) were acquired from the Climatic Research Unit (CRU), which are available at https://crudata. uea. ac. uk/cru/data/hrg/. The monthly RSW data were obtained from Modern-Era Retrospective analysis for Research and Applications Version 2 (MERRA-2) with a spatial resolution of 0.
5° × 0. 625° from 1982 to 2018, which are available at https://climatedataguide. ucar. edu/variables/land/soil-moisture. The land cover data set of GLASS-GLC product was obtained from the GLASS Climate Data Records (CDRs), which are available at https://doi. pangaea. de/10. 1594/PANGAEA. 913496. All the data and results developed in this study can be requested from corresponding author (baozhang. chen@igsnrr. ac. cn). The primary code is available at https://github. com/EFPaper2022EF002788code/LAIcode. git.
2. 2. Climate and Soil Moisture Data Set 05° and temporal resolutions of 8 days (http://www. glass. umd. edu/Download. html) was produced using MODIS and AVHRR land surface reflectance via Generalized Regression Neural Network (GRNNs) model, and the accuracy was evaluated by comparing with other LAI products such as MODIS and CYCLOPES, as well as field measurements. The GIMMS LAI data set, named LAI3g, was generated based on AVHRR GIMMS NDVI3g, MODIS LAI datasets using a Feed Forward Neural Network (FFNN) model with a composited temporal resolution of 15 days and a bi-cubic resampled spatial resolution of 1/12° (http://sites. bu. edu/cliveg/datacodes/). Evaluation of this product also utilized LAI products for other satellites and field measurements. Using the same way of processing AVHRR LAI, the two products can be composited to multi-year global LAI means(1982-2018 of GLASS, 1982-2016 of LAI3g).
Due to the uncertainties in different LAI products, especially interannual trend fitting, the averaged value of the three products at a pixel level was calculated for overall analysis. The means for 2017 and 2018 were only produced by AVHRR and GLASS datasets because of the insufficient time series in LAI3g. In order to explore drivers of global LAI trend changes, the global gridded daily maximum air temperature ( 𝐴𝐴 𝐴𝐴 max air ), 𝐴𝐴 NOAA Climate Data Record (CDR) of AVHRR LAI and Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), Version 5 (https:// data. noaa. gov/dataset/dataset/noaa-climate-data-record-cdr-of-avhrr-leaf-area-index-lai-and-fraction-of-ab-VPD and root zone soil wetness (RSW) were selected in this study. Specifically, 𝐴𝐴 𝐴𝐴 max ( 𝐴𝐴 mean air ) and actual vapor pressure (VAP) at a spatial resolution of 0.
The study protocol was approved by the Institutional Review Board of the French learned Society for Respiratory Medicine -Société de Pneumologie de Langue Francaise) (CEPRO 2018-011). A standard form was used to retrospectively record from patients' files the details of patients and TO characteristics, including demographics, smoking status, occupational exposure, medical history, respiratory symptoms, pulmonary function tests (PFT) results, and radiological and histological findings. Bronchoscopic data included TO location, tracheal stenosis, and classification depending on nodules concentration in the mucosa: scattered, diffuse or confluent  [6]. When available, microbiologic results of bronchial aspiration conventional culture were recorded. Therapeutic management and outcomes were recorded.