dataesr/scientific-paragraphs-categorization huggingface dataset:
Metabolomic profiling. Raw data files were converted to mzXML files using MSConvert (Version 2. 1, ProteoWizard)  42. The data obtained from positive and negative ionization mode were analysed separately using MZmine (Version 2. 29)  43. Isolated chromatograms were built for each mass with a noise threshold of 10 5. A local minimum search algorithm was used to select the validated peaks. Peaks were then aligned by RANSAC (random sample consensus) algorithm with a tolerance of 10 ppm in m/z and 1 min in retention time. Missing values were filled in using the same m/z and RT range as observed in detected samples, where possible. We kept only those peaks that had no missing values after gap-filling. Peaks were then identified using the Human metabolome database  44  (HMDB, version 3. 0) with 15 ppm of mass tolerance.
Multivariate analysis. For multivariate analysis, metabolomic data were introduced into the SIMCA software (Version 14. 1, Sartorius Stedim Biotech, Germany). Raw data were mean-centred and scaled with the square root of the standard deviation (Pareto scaling)  45. At first, principal component analysis (PCA) was carried out using scaled data to visualize the overview of the dataset  46. Outliers were eliminated if observed. Orthogonal projections to latent structures discriminant analysis (OPLS-DA), a supervised model, was then established to relate the X data to the Y response  29, 30. In our case, the X is the metabolomic dataset and the Y is the histological classes allowing for the discrimination of different RCC subtypes. The OPLS-DA model was evaluated using R 2 X (cum) : the variation of X explained by the model; R 2 : the goodness-of-fit that is represented by the percentage of the variation of Y explained by the model; Q 2 : the goodness-of-prediction.
Q 2 of the model was evaluated using a cross-validation test. 1/7 of the data were withheld during model development. The withheld portion was then predicted by the model that had been established using the remaining 6/7 of the data. The predictions for the excluded parts were compared with the actual values and these steps were repeated until all data had been withheld once. Q 2 is the percentage of the variation of the dataset predicted by the model according to the cross-validation test. The significance of the cross-validation test was calculated by ANOVA using the predictive residuals. A significant model should have a CV-ANOVA p-value of less than 0. 05. Additionally, response permutation tests were performed for the model validation. To this end, the Y (classes) are permutated to appear in a different order while the X-dataset remains intact.
A new model is fitted to the permutated data. The R 2 and Q 2 of the permutated model are compared to the real model. A validated model should have all permutated Q 2 values lower than the original Q 2 and the Q 2 -intercept below zero. The influence of each metabolite on the classification was calculated by the variable influence on projection (VIP)  30. Metabolites with VIP >1 have an above average influence. In our case, only metabolites with VIP values >3 were selected for further pathway analysis using free web-based software, MetaboAnalyst (Version 3. 0)  32. Additionally, annotation of metabolites with VIP >3 was verified manually using a reference MS/MS spectrum of the Metlin database. About 15% of identifiers were invalidated, mainly due to the confusion between isomers and the presence of contaminants from the mass spectrometer.
Statistical analyses. Univariate analyses were carried out using GraphPad Prism (Version 5. 03, GraphPad Software Inc. , USA). Differences between unpaired groups were compared using the two-tailed Mann-Whitney test. For paired data, the two-tailed Wilcoxon matched-pairs signed rank test was applied. Data were shown as the mean ± SEM. The level of significance was indicated by *for p < 0. 05, **for p < 0. 01 and ***for p < 0. 001. Hierarchical cluster analyses (HCA) were performed by SIMCA software using Ward's method  47. The receiver operating characteristic (ROC)  48  curves were calculated using GraphPad Prism. The prognostic performance of the metabolomic-based OPLS-DA model was evaluated using an independent sample cohort by computing the area under the ROC curve (AUROC) using the predicted Y values for each RCC subtype.
Acknowledgements L. J. was funded by a grant from the " Commissariat Général à l'Investissement" ("Recherche en matière de Sûreté Nucléaire et Radioprotection" program  operated by the  "Agence Nationale de la Recherche" (ANR), France). The authors wish to thank  Sabine Lindenthal  and  Abby Cuttriss  for critical reading of the manuscript. We also thank  Sandrine Destrée  and  Arnaud Borderie  for excellent technical assistance.
Scoring Before the decision conference, a hierarchical search strategy obtained treatment effect data for the DMDs by identifying relevant studies in the following order: (1) European Union regulatory approval documents, (2) US regulatory approval documents, (3) reports from postmarketing surveillance, and (4) peer-reviewed publications (pivotal trials; secondary publications). Details of data and sources used in this model, including assumptions, are given in Supplemental Section 2. For both favorable and unfavorable effects, if the relevant data were not found in the first data source, then the second data source was searched and so on down the hierarchy until relevant data were identified and the search was stopped. Only 1 set of data was reported for each effect for each DMD. Only trials in which the DMD was given as monotherapy were chosen, and the highest values for favorable effects attained in any trials were included in the model (ie, the highest efficacy result).
For alemtuzumab, in which the clinical program did not include placebo as a comparator, arbitrary high values were assigned by the neurology experts on MRI and clinical efficacy measures. Data on unfavorable effects selected for inclusion in the model were based on the important identified and potential risks associated with the DMDs to be assessed. Generally, data were captured at the MedDRA System Organ Class level because the terminology across the different sources varied. For the most part data were taken from 2-year studies. Further refinement of the data continued throughout the 2 decision conferences, with data from a few new sources added after the meetings. Definitions of the criteria and all input data were summarized in an effects table  (Table 1 ). Most of the metrics in the effects table  (Table 1 ) were expressed as percentage reductions for the favorable effects and incidence, expressed as percentages, for the unfavorable effects.
In the first step the neurologists established a preference scale for each criterion, with low and high values, including all the input data in the effects table  (Table 1 ), assigned preference values of 0 and 100, respectively. In the second step, the performance metrics for all drugs on each scale were converted linearly to preference scores by using Hiview3 software, y which preserved y Hiview3 software, originally developed at the London School of Economics and Political Science and now at Catalyze Ltd, www. catalyze. co. uk, performed the conversion after the ranges were established. their relative positions on the input metrics. The linear approach was taken as an appropriate approximation for the criteria under consideration where an effect is measured by proportions of patients, to ensure all patients are treated equally.
Generating Results for the Model With scoring and weighting completed and all data and weights entered into the computer model, the Hiview3 software calculated the weighted average of the preference scores on the 18 criteria and summed the scores to give a single overall weighted preference value for each drug. In addition, the benefiterisk balance of each DMD was compared with that for cladribine. That process followed established priorities for assessing the DMDs and reflected the contributions that individual effects make to the overall weighted preference value for each.
Cladribine 3. 5 mgk/kg Annualized relapse rate (ARR) was the primary endpoint in the Phase III CLARITY trial. For the analysis, data for the cladribine 3. 5 mg/kg dose group from the CLARITY trial has been used. 2 In the CLARITY trial, the primary endpoint, ARR, was met, with cladribine 3. 5 mg/kg reducing ARR to 0. 14 compared to an ARR of 0. 33 in placebo patients, showing a relative risk reduction of 58%. 2  Standard measures of disability progression are time to sustained disability progression, measured by a 3month or 6-month confirmed change in expanded disability status scale (EDSS) score. Both timepoints for assessment of change in EDSS are widely accepted as demonstrative of disability progression; and time to 3-month sustained disability progression was chosen as a study endpoint in the cladribine studies.
In the CLARITY trial cladribine 3. 5 mg/kg led to a lower risk of 3-month confirmed EDSS progression (hazard ratio [HR] of 0. 67, 95% confidence interval [CI] of 0. 48e0. 93), a relative risk reduction of 33%. 2  An analysis of 6-month confirmed EDSS progression in patients from CLARITY was included in the combined summary of efficacy. In this analysis, cladribine 3. 5 mg/kg led to a relative risk reduction of 6-month confirmed EDSS progression (HR of 0. 53, 95% CI of 0. 36e0. 79), of 47% (data on file). In the CLARITY study, there was strong suppression of T1 Gd+ lesions (lease squares [LS] mean number of lesions 0. 12 for cladribine 3. 5 mg/kg, and 0. 91 for placebo; a relative risk reduction of 86%) and active T2 lesions (LS mean number of lesions 0. 38 for cladribine 3. 5 mg/kg, and 1.
Identification of data for each of the unfavourable effects Data on unfavourable effects selected for inclusion in the model were based upon the important identified and potential risks associated with cladribine and the comparator products. Generally data were captured at the MedDRA System Organ Class (SOC) level as the terminology across the different sources varied. For the most part the comparators data were taken from 2-year studies. The data sources for the unfavourable effects are described in the following sections.
Cladribine 3. 5 mg/kg In the integrated analysis of AEs in the placebocontrolled double-blind cohort, 1458 patients were exposed to cladribine (all doses) and 745 patients were exposed to placebo. The placebo controlled, double-blind cohort without the ONWARD study was used for the cladribine data (January 2016). This was compared to the CLARITY clinical study report (CSR) for validation. In the Infections and infestations system organ class (SOC), in the cladribine group AEs were reported for 755/1458, (51. 8%) patients (data on file). This value was entered in the effects table. For comparison, the incidence rate in the placebo group was 348/745 (46. 7%). Serious adverse events (SAEs) in the Infections and infestations SOC were reported for 37/1458, (2. 5%) patients in the cladribine group and 12/745 (1.
6%) in the placebo group (data on file). The value of 2. 5% was entered in the effects table for cladribine. Herpetic infection AEs were reported for 115/1458, (7. 9%) patients in the cladribine group and 24/745 (3. 2%) in the placebo group (data on file). The value of 7. 9% has been entered in the effects table for cladribine. In the Gastrointestinal disorders SOC, AEs were reported for 460/1458 (31. 6%) patients in the cladribine group and 233/745 (31. 3%) patients in the placebo group (data on file). The value of 31. 6% was entered in the effects table for gastrointestinal (GI) effects. In the Hepatobiliary disorders SOC, AEs were reported for 22 Bradycardia was reported for 3/1458 (0. 2%) patients in the cladribine group and was not recorded for any patients in the placebo group (data on file).
There were no events of atrioventricular block in either treatment group (data on file). There were no cases of progressive multifocal leukoencephalopathy (PML) reported in the studies (data on file). For the analysis of malignancy, the "All exposed" cohort was used, comprising all Phase II/III studies with any formulation of cladribine. It contained the maximum safety data available and was used to assess cladribine safety profile over time and in comparison to placebo. This cohort includes patients from the ONWARD study who were on background IFN-b therapy. The All exposed cohort comprised 1976 patients in the cladribine group (all doses) and 802 patients in the placebo group, with 8650 and 2361 patient years at risk, respectively. In this cohort, 32 patients in the cladribine group and 4 patients in the placebo group had at least one malignant tumor, giving an incidence per 100 PY of 0.
Fingolimod 0. 5mg In multiple sclerosis clinical studies the overall rate of infections (65. 1%) at the 0. 5 mg dose was similar to placebo. 31  (40%) in the placebo group. 32 The 43% value was entered in the effects table. In clinical trials, elevations 3-fold the upper limit of normal (ULN) or greater in alanine aminotransferase (ALT) occurred in 8. 0% of patients treated with fingolimod 0. 5 mg compared to 1. 9% of placebo patients. Elevations 5-fold the ULN occurred in 1. 8% of patients on fingolimod and 0. 9% of patients on placebo. 31 In the EPAR, the data from three completed, double-blind, controlled MS studies and interim data from two long-term extension studies in MS patients were pooled into five datasets using appropriate cut-offs to accommodate differences between studies in duration of treatment, doses, and comparators.
In one of these datasets (24-month treatment; N ¼ 1272), 43/425 (10. 1%) patients in the fingolimod 0. 5 mg group had an AE of ALT increased compared with 16/418 (3. 8%) patients in the placebo group and 50/429 (11. 7%) in the fingolimod 1. 25 mg group. 7 The 10. 1% value was entered in the effects table. In the same dataset (24-month treatment; N ¼ 1272), 7/425 (1. 6%) patients in the fingolimod 0. 5 mg group had a serious adverse event (SAE) in the system organ class (SOC) Infections and infestations compared with 8/418 (1. 9%) patients in the placebo group and 11/429 (2. 6%) in the fingolimod 1. 25 mg group. 7 The 1. 6% value was entered in the effects table for serious infections. In placebo-controlled trials, the rate of herpetic infections was 9% in patients receiving fingolimod 0. 5 mg and 7% in patients receiving placebo.
260. e8 Volume 41 Number 2 In light of the potentially serious autoimmune and other side effects that can occur many months to years after treatment with alemtuzumab, a strict monitoring program is in place requiring monthly complete blood count with differential, urine, and serum creatinine and quarterly thyroid function testing; moreover, according to the US and European labels, patients must be monitored for 48 months following their last infusion. The AE profile in the dataset including all Phase II/ III active-controlled studies, is presented in Table  35  of the Lemtrada EPAR. 11 Overall the incidence of infections reported as an AE was 652/919 (70. 9%) for alemtuzumab 12 mg and 264/496 (53. 2%) for IFN-b-1a. The incidence of serious infections was 25/ 919 (2. 7%) patients for alemtuzumab 12 mg and 5/ 496 (1.
The AE profile in the dataset including all placebocontrolled studies, is presented in Section 2. 6. 2 of the Tecfidera EPAR. 16 Overall the incidence of infections reported as an AE was 60% for dimethyl fumarate 240 mg bid (463 patients) and 56% for placebo (469 patients). The incidence of serious infections was similar (2% vs 2%) in patients treated with dimethyl fumarate 240 mg bid or placebo, respectively (Section 5. 3 of the Tecfidera US PI). 14  AEs in the gastrointestinal disorders SOC were reported at an increased incidence with dimethyl fumarate 120 mg bid compared with placebo in both placebo-controlled studies, Study 109MS301 (DEFINE): 44% vs 36% on placebo and Study 109MS302 (CONFIRM): 36% vs 26% on placebo. 16 he higher value (44%) has been entered into the effects table. Elevations of liver transaminases were reported as AEs at a slightly higher incidence with dimethyl fumarate 120 mg bid compared to placebo: AEs of increased alanine transaminase (ALT) were reported for 6% of patients in the dimethyl fumarate 120 mg bid group compared with 5% in the placebo group.
Teriflunomide 14 mg In the clinical studies the most common adverse reactions were headache, an increase in ALT, diarrhea, alopecia, and nausea. There were no deaths or serious opportunistic infections in the Phase III trials, and no data have confirmed an increased risk of malignancy or infections. 18 eriflunomide's US label carries a black-box warning of hepatotoxicity based on preclinical studies, and according to teriflunomide's prescribing information, initial liver function and hematological monitoring is required. Transaminase and bilirubin levels must be obtained prior to initiation and ALT levels must be monitored at least monthly for six months; recent blood count and a tuberculin skin test should be obtained before initiation and patients should be monitored for signs of infection.
260. e10 Volume 41 Number 2 described in the prescribing information) may be required. 18 he AE profile in the dataset including all placebocontrolled studies, is presented in Table  33  of the Aubagio EPAR. 21 Overall the incidence of infections reported as an AE was 256/415 (61. 7%) for teriflunomide 14 mg and 242/421 (57. 5%) for placebo. SAEs in the Infections and infestations SOC were reported by 2. 2% of patients in the teriflunomide 14 mg group and 2. 1% of patients in the placebo group. 21 Es in the gastrointestinal disorders SOC were reported by 45. 3% of patients in the teriflunomide 14 mg group and 34. 4% of patients in the placebo group. 21 Es of increased alanine transaminase (ALT) were reported for 150/1002 (15. 0%) patients in the teriflunomide 14 mg group compared with 89/997 (8.
ACKNOWLEDGMENTS This decision conferencing and subsequent analysis was sponsored by  EMD Serono, Inc , a business of  Merck KGaA, Darmstadt, Germany  (in the United States) and  Merck Serono SA e Geneva , an affiliate of  Merck KGaA Darmstadt, Germany (ROW). Merck KGaA  staff searched for and provided data used in construction of the  Multi-Criteria Decision Analysis (MCDA)  model. The neurologist decision makers who participated in the structured MCDA benefiterisk assessment also served as authors on this manuscript ( P. Vermersch ,  V. Martinelli ,  C. Pfleger ,  P. Rieckmann , and  L. Alonso-Magdalena ). L. Phillips was engaged as an independent specialist in MCDA and group processes to facilitate the decision conference. P. Vermersch , V.
Samples were diluted to a concentration of~50 mg/mL. Subsequently 2 mL of 6x loading dye (New England Biolabs) was added to 10 mL of sample and directly loaded onto the gel. For the determination of residual E. coli host RNA/DNA, the sample was diluted to 50 ng/mL. Of the resulting solution, 10 mL was mixed with 2 ml of 6x loading dye and this was subsequently loaded onto the gel. To semi-quantitative determine the ratio of the two pFAR plasmids in the final formulation, a standard curve of both plasmids was made with a range of 30 to 90 ng per slot. The final plasmid formulation was loaded on the same gel undiluted or diluted 1/20 v/v. Using the Gene-Genius software, the areas under the curve for each plasmid was determined and the relative concentration of both plasmids in the mixture was calculated to determine the final ratio.
Identity and Purity of MCB Identity of the MCB is determine by PCR of extracted DNA. The resulted sequence is machted with a validated database to find a match with a known micro organism. Purity of the MCB was determined with a monosepsis assay according ICH guidelines Q5D. In this test, the MCB is grown on plates and inspected for aberrant colonies (at least a 1000 colonies are inspected Both tests were performed by Sinesis Life Science, Leiden, The Netherlands under GMP regulations.
Statistical analysis Data were expressed as the mean ± standard deviation (SD). All experiments were performed at least 3 times. Statistical comparisons were performed with the program Excel using 2-tailed Student`s t test and with Graphpad Prism for ANOVA (Figure  S5F , Figure  S7A, B , Figure  S8F ,G), respectively. Differences with p ≤ 0. 05 were considered significant and marked as *, p ≤ 0. 01 was marked as **.
Acknowledgments The authors thank  Professor Noboru Mizushima  ( Department of Biochemistry and Molecular Biology, University of Tokyo ) for sharing the transgenic  Gfp-Lc3  and  Atg5  flox mouse strains. This study was funded by the  Deutsche Forschungsgemeinschaft (DFG, German Research Foundation ) collaborative research centers ( CRC/SFB )  1140  (project number  246781735  to T. B. H. ),  CRC   1192  (to T. B. H. ) and  CRC 992  (to T. B. H. ),  Heisenberg program  (T. B. H. ),  HU 1016/5-1  and  HU 1016/8-2  (to T. B. H. ); by the  European Research Council  ( ERC grant  to T. B. H. ), and by the  H2020-IMI2  consortium  Biomarker Enterprise  to  Attack Diabetic Kidney Disease (BEAt-DKD ) and this Joint Undertaking receives support from the  European Union 's  Horizon 2020 research and innovation programme and EFPIA  with  JDRF  ( 115974 ; to TBH); by the  Bundesministerium für Bildung und Forschung, STOP Fokale Segmentale Glomerulosklerose (BMBF-STOP-FSGS)  (T.
Funding This work was supported by the  German Research Foundation  [ CRC1140 ,  CRC1192 ];  European Foundation for the Study of Diabetes (EFSD) ;  German Research Foundation Heisenberg Program  [ HU1016/ 5-1 ];  German Research Foundation Heisenberg Program  [ HU1016/8-2 ];  EC | European Research Council (ERC) ;  H2020-IMI2 BEAt-DKD [115974]; BMBF-STOP-FSGS [01GM1518C ];  Excellence Initiative of the German Federal and State Governments BIOSS, FRIAS Freiburg Institute of Advanced Studies; Alexander von Humboldt Foundation ;  German Research Foundation  [CRC992];  National Natural Science Foundation of China (NSFC)  [81470912];  Berta Ottenstein Program ;  Else Kroener Fresenius Foundation NAKSYS;BMBF GlioPATH  [ 01ZX1402B ];  BMBF MAPTor-NET  [ 031A426B ];  German Research Foundation  [ TH 1358/3-1 ]; MESI-STRAT [754688];  Uehara Memorial Foundation ;  German TS Foundation, Stichting TSC Fonds  (calls 2015 and 2017);  PoLiMeR Innovative Training Network  ( Marie Sklodowska-Curie  grant agreement No.
After washing three times with PBS-/-, a secondary rabbit-specific polyclonal Ab conjugated with 488-Alexa Fluor Dyes (Invitrogen, Villebon sur Yvette, France) was added to cells and incubated in the dark for 1 h at 37°C. Specificity of primary Ab staining was determined with a control rabbit irrelevant Ab (Sigma-Aldrich, R9133, lot SLB7964V, Saint-Quentin Fallavier, France). DNA was stained using Hoechst 33342 (Molecular Probes, Villebon sur Yvette, France) and the cells were mounted in fluoromount-G TM medium (eBioscience SAS, Paris, France) for imaging with a Leica Microsystem DMi8 microscope (Nanterre, France). The image files were analysed with Image J 1. 49v software (National Institutes of Health, USA). In vitro NETs formation was quantified using a modified method reported previously  [20].
Pathological investigations Mice were euthanized on day 14 and their lung tissue was harvested immediately after death. The left lobes were fixed overnight in 10% buffered formalin (Sigma-Aldrich, Saint-Quentin Fallavier, France) and embedded in paraffin. The right lobes were frozen with optimal cutting temperature (OCT) compound (Sigma-Aldrich, Saint-Quentin Fallavier, France). Paraffinembedded sections were cut into 5 µm sections and stained with haematoxylin-eosin (H&E) (Sigma-Aldrich, Saint-Quentin Fallavier, France). The extent of pulmonary hemorrhage was assessed using quantification program CaloPix ® software (TRIBVN Healthcare, Chatillon, France), which is a digital slide and management software. Two blinded pathologists assessed the extent of DAH. Total, white (no tissue) and healthy areas were defined numerically at x20 magnification.