dataesr/scientific-paragraphs-categorization huggingface dataset:
Statistical Analysis For statistical analysis, only data of one eye per patient was used. If applicable, the eye with the better image quality was chosen; otherwise, one eye was selected randomly. Values are shown as mean 6 SEM. All statistical analysis was done using Graph Pad Prism version 6 (GraphPad Software, Inc. , La Jolla, CA, USA). Data groups were compared using a two-tailed t-test for parametric data with a confidence interval of 95%. P < 0. 05 was considered statistically significant.
Acknowledgments The authors thank  Joerg Fischer, PhD ,  Yoshihiko Katayama, PhD , and  Kester Nahen, PhD  ( Heidelberg Engineering GmBH, Heidelberg, Germany ), for providing technical assistance for the FLIO device. Supported by  Swiss National Science Foundation  Grant  320030_156019  ( Bern, Switzerland ). The sponsor or funding organization had no role in the design or conduct of this research. Disclosure:  C. Dysli , Heidelberg Engineering (S);  R. Fink , None;  S. Wolf ,  Heidelberg Engineering (C, S) ,  Bayer (C) ,  Novartis, (C) ,  Alcon (C) ,  Allergan (C) ,  Roche (C) ;  M. S. Zinkernagel ,  Heidelberg Engineering (S) ,  Bayer (C) ,  Novartis (C, I).
Patients and methods study design This prospective blinded observational study was conducted in 20 centers across France. Centers were asked to prospectively include patients visiting their ER between November 2011 and November 2014 with a certain or probable diagnosis of COPD exacerbation. Patients were followed up until 30 days after inclusion. The protocol was approved by the Comité de Protection des Personnes Ile de France 1 (2012-A01237-36). Written informed consent was obtained from all patients. The study was registered on ClinicalTrials. gov: NCT01857947.
Data collection The following data were collected: age, sex, comorbid conditions, smoking history, known diagnosis of COPD, chronic bronchitis or emphysema, age at first respiratory symptoms, usual severity of dyspnea at steady state using the modified Medical Research Council scale, self-reported number of emergency visits and hospitalizations during the past 6 months and maintenance treatments. The history of the current exacerbation, dyspnea grade at entry and clinical signs of severity, as well as results of routine venous and arterial blood sampling and chest X-ray, were recorded. Diagnostic procedures and treatments in the hospital were collected. Upon discharge, the local coordinating respiratory physician was requested to provide his/her final conclusions regarding the diagnosis (confirmed ECOPD or alternative diagnosis) and the certain or probable etiology of the exacerbation.
The first step was the comparison of MR-proADM levels between patients who met and those who did not meet the primary end point. Second, receiver operating characteristic (ROC) curves were built using the ROCR package  15  to assess the global performance of MR-proADM to predict the occurrence of the primary end point and to define the optimal cutoff. A bootstrap method was used to calculate the 95% confidence interval (CI) of areas under the ROC curves, sensitivities and specificities. Third, the 2008 clinical risk score  8  was calculated and the patients were allocated to the risk categories. Finally, a multivariate logistic regression analysis assessed the predictive performance of the MR-proADM plasma levels after adjustment on the 2008 clinical score. The same strategy was followed for copeptin.
Acknowledgments The study was an investigator-initiated study primarily funded by  Thermo Scientific Biomarkers (formerly BRAHMS AG) ,  Hennigsdorf, Germany , which provided all reagents gratis and, through an unrestricted research grant, funded all shipment costs of blood samples to the central biomarker testing facility at  University Hospital Pitié-Salpêtrière. Drs Martin Dres ,  Nicolas Roche ,  Pierre Hausfater ,  Thomas Similowski ,  Jean-Marc Treluyer  and  Patrick Plasisance  are the members of the  UTAPE Scientific Committee. The list of the  UTilité de la pro-Adrénomédulline comme facteur Prédictif d'évolution des Exacerbations de BPCO (UTAPE)  study investigators is as follows:  Patrick Plaisance  ( Lariboisiere Hospital, Paris ),  Arnaud Martinage  ( CHU Nantes ),  Nicolas Fraimout  ( CHU Nice ),  Pierre-Géraud Claret  ( Hôpital Carrémeau, Nîmes ),  Karim Tazarourte  ( CH Marc Jacquet, Melun ),  Eric Roupie  ( CHU Caen ),  Patrick Ray  ( Tenon Hospital, Paris ),  Paul Gayol  ( Hôpitaux Universitaires de Strasbourg -Hôpital Civil ),  Philippe Sattonnet  ( Hôpital Bel-Air CHR Metz-Thionville ),  Fatima Rayeh  ( CHU Poitiers ),  Dominique Savary  ( CHR Annecy ),  Bertrand Renaud  ( CHU Cochin, Paris ),  Mehdi Khellaf  ( CHU Henri Mondor, Créteil ) and  Sébastien Beaune  ( CHU Ambroise Paré, Boulogne Billancourt ).
Identification of subjects susceptible to develop drug-induced long QT We first performed a clinical study (clinicaltrials. gov NCT01338441) where we prospectively evaluated cardiac repolarization of healthy subjects in response to a pharmacological challenge with a single 80 mg oral dose of sotalol. Sotalol is a non-selective competitive b-adrenergic receptor blocker with additional Class III antiarrhythmic properties by its inhibition of potassium channels  (Zanetti, 1993). Sotalol is widely recognized as a classical QT-prolonging drug  (Soyka et al. , 1990). A total of ninety-two subjects were enrolled in the study (Figure  1A ). All subjects gave their written informed consent to participate the study. Included subjects were aged from 18 to 40 years (30. 1 ± 6. 2 years), had a body mass index (BMI) between 19 and 29 kg/m 2 (23.
These data indicate that the contrasted responses to sotalol in iPSC-derived CMs are strongly related to the inter-individual differences in response to sotalol as recorded during clinical investigations. We also evaluated the effect of sotalol on action potential duration (APD) measured in a representative iPSC-CMs line from each group (P11009 as low-S and P11029 as high-S). Experimenter for APD measurement was however kept blinded of the observed drug sensitivity of selected iPS lines. Sotalol (100 and 300 mM) significantly prolonged the action potential, the duration of 90% repolarization (APD 90 ) of high-S (P11029) iPSC-CMs (289 ± 22 in drug-free vs. 492 ± 66 and 435 ± 92 after 100 and 300 mM sotalol, respectively n = 5) but not that of the low-S line (P11009) even at high dose (339 ± 63 vs.
e. divided by 96). Using this approach, a gene that is up-regulated in the high-S group because of gender specific expression, should be identified as significantly up-regulated in most of the female versus male groups sets of DEGs. The same accounts for down-regulated genes. As shown in Figure  5B  and C, this trend was not observed for most of the genes, arguing against gender differences being the reason for differential gene expression between the high-S and low-S group. Finally, to further investigate if the DEGs are the consequence of sex specific gene expression, we predicted regulatory transcription factors of the DEGs based on two transcription factor target databases and ranked them by significance (Figure  5 -figure supplement 1). The sex-hormone related transcription factors were ranked 16 (AR), 20 (ESR1) and 24 (ESR2) or 27 (PGR) and 180 (ESR1), and no sex hormone related transcription factor was among the top 10 candidates.
Network analysis and direct neighbors identification To search for differentially expressed direct neighbors of LQTS disease genes, we generate a human interactome by merging all protein-protein interaction databases of the Expression2 kinases suite  (Chen et al. , 2012) , except the 'Predicted PPI' database, and a recently published protein-protein interaction network  (Rolland et al. , 2014). Small letter symbols of the merged interactome were replaced by their human homologues, using the Mouse Genome Informatics mouse-human orthology database and the NCBI mouse-human homologene database. Finally, we removed all network nodes that were not official human gene symbols as reported in the NCBI geneInfo database. Differentially expressed genes in the direct neighborhood of LQTS disease genes ('AKAP9', 'ANK2', 'CACNA1C', 'CALM1', 'CALM2', 'CAV3', 'KCNE1', 'KCNE2', 'KCNH2', 'KCNJ2', 'KCNJ5', 'KCNQ1', 'SCN4B', 'SCN5A', 'SNTA1') were identified (path length = 1).
Each drug was tested in at least three different wells. Raw MEA data were acquired using QT-Screen Lite and MC-Rack softwares (Multi Channel Systems, Reutlingen, Germany). The data were then exported on QT-Analyzer Software to analyze the field potential duration and the inter-beat interval (Multi Channel Systems, Reutlingen, Germany). Parameters were averaged on the 2 min recordings. Inter-beat interval (in ms) was used to calculate the instantaneous beat rate. To account for the dependency between repolarization rate and the beating rate, FPD was firstly adjusted using the popular Bazett's formula (adjustedFPD = rawFPD / RR1/2). We however found that, as expected, this formula was associated with an important over-correction thus supporting the need for an alternative adjustment formula according to  Funck-Brentano et al.
(Funck-Brentano and Jaillon, 1993)  (Figure  2 -figure supplement 3, panel A). We thus plotted the FPD / inter-beat-interval pairs recorded at various beating rates under baseline conditions. The following equation with the same dimension as a Bazett's formula: adjustedFPD = rawFPD / RRa, where alpha is a regression parameter, was applied to raw data in order to have a new estimate of the correction factor and results in appropriate corrections of FPD (Figure  2 -figure supplement 3, panel B). Cells were considered as developing arrhythmias in response to sotalol as they presented ectopic beats or spontaneous beating rates became irregular.
Patch clamp recordings hiPSC-derived embryoid bodies were enzymatically dissociated into single cardiomyocytes and plated on matrigel-coated glass coverslips. The action potential of cardiomyocytes was assessed in the current-clamp mode using whole-cell patch-clamp technique with a HEKA EPC10 amplifier and Pulse/PulseFit software (HEKA, Germany). Pipette solution consisted of: 110 mM potassium aspartate, 20 mM KCl, 10 mM HEPES, 1 mM MgCl2, 0. 1 mM ATP (disodium salt), 5 mM ATP (magnesium salt), 5 mM phosphocreatine (disodium salt) and 1 mM EGTA (pH 7. 2). The external bath solution contained 140 mM NaCl, 5 mM KCl, 1 mM MgCl2, 10 mM D-glucose, 1 mM CaCl2 and 10 mM HEPES (pH 7. 4). hiPSC-CMs were perfused with either control or sotalol-containing Tyrode's solution for 5 min. The whole-cell condition was then reached.
05 (nQuery Advisor version 4. 0). Responses to drugs, as measured in vitro, were normalized to baseline values and expressed as changes to baseline to account for inter-line variability. All recorded data were analyzed. A two-way analysis of variance with repeated measures was performed to analyze response to sotalol. Sotalol concentrations define the first factor and the sensitivity group the second factor. Individual comparisons were performed when the overall analysis was significant. Dose response curves were built to estimate EC50 using the Hill equation.
A careful examination of the regions previously suspected to correspond to TMHs confirmed the positions of TMH 3 and permitted to refine the ends of the TMH 6. To finalize this analysis and to obtain the most accurate annotation of TMHs, we compared the results of various programs dedicated to membrane protein alignment (MAFFT, KALIGN, AlignMe) with local alignment of the predicted TMHs. Using Aliview, an editing software of multiple sequence alignment (MSA) based on Muscle  [45] , we finally obtained a refined alignment of human, mouse and rat sequences of ABCB10, ABCD1, ABCD2 and ABCD3 (Figure  2 ) and deduced the very likely positions of the TMHs (Table  1 ). Conserved residues located between the TMHs are known features of ABC transporters and emerged from this alignment reinforcing its validity.
Using Aliview, an editing software of multiple sequence alignment (MSA) based on Muscle  [45] , we finally obtained a refined alignment of human, mouse and rat sequences of ABCB10, ABCD1, ABCD2 and ABCD3 (Figure  2 ) and deduced the very likely positions of the TMHs (Table  1 ). Conserved residues located between the TMHs are known features of ABC transporters and emerged from this alignment reinforcing its validity. The analysis of the structural alignment computed by Espript server  [46]  also revealed conserved coupling helices extending the helical structure of TMHs in ABCD proteins in agreement with other ABC transporters.
A 2. 85 Å resolution crystal structure has been determined in the presence of a non-hydrolysable analog of ATP and demonstrated an open-inwards conformation. We used the rod form of this crystal structure (PDB ID 4AYX) as a template to obtain a structural model of human ABCD1 using the Swiss-Model server (Figure  3 ). The structural model was constructed from the ABCD1/ABCB10 pairwise alignment presented in Appendix A (Figure  A1 ). In order to improve the quality of the alignment, the N-terminal part of each sequence containing specific subcellular targeting signals was deleted. Gaps, mainly located in the loops linking helices, were inserted to fit with the results of the predictive secondary structures for each protein. If low confidence remains in the regions corresponding to these gaps, the overall model resulted in a reliable predictive structure, particularly in TMHs, NBDs and contact regions between ICLs and TMDs.
Alignment Aliview, an editing software of alignment based on Muscle algorithm  [45]  was used to perform MSA of peroxisomal ABC transporter sequences. Alignment of human ABCD1 with human ABCB10 was performed in three steps. First, the human, mouse and rat sequences of ABCB10, ABCD1, ABCD2 and ABCD3 were aligned. Then, the known positions of the TMHs of ABCB10 were used as anchors to perform local alignment with the putative TMHs of the ABCD proteins. Finally, rodent sequences were removed as well as ABCD2 and ABCD3 sequences in order to obtain an ACBD1/ABCB10 pairwise alignment suitable for homology modeling.
Homology Modeling Homology modeling was computed using the "target-template alignment" mode of the SWISS-MODEL  [65] [66] [67]. The optimized ABCD1/ABCB10 pairwise alignment (Figure  A1 ) computed was used as template to direct the homology modeling process against the 2. 85 Å resolution rod form structure of ABCB10 (PDB ID 4AYX). A sequence identity of 17. 7% for the alignment was sufficient to Swiss-Model server to successfully compute a homodimeric model for ABCB1 (pdb file in Supplementary Data).
Sensitivity A major strength of this study is the use of colposcopy-directed biopsy on all women. As a result, our findings may better reflect p16 sensitivity in combination with other cervical neoplasia screening methods. In addition, this study included detailed data on CD4 count and ART exposure. However, this study has several limitations. P16 staining was performed on archived samples, of which 24. 8% had indeterminate results. Sensitivity analysis showed that there was no difference between subjects with indeterminate and determinate p16 results by sociodemographic characteristics, clinical factors, or CIN2/3. The use of archived samples may have reduced quality due to long-term storage and the de-staining and re-staining procedures. Cell loss may have occurred during the removal of plastic coverslips, reducing p16 interpretability.
, 2007)  For genotyping of the STR polymorphism, the surrounding region in intron 2 was amplified using the FAM (fluorescein marker 6-carboxyfluorescein) labeled forward primer 5'-FAM-GCATTGCTGAATGTATCAGGGA-3', and the reverse primer 5'-CTTGAGAAATGTTTTCTAGGC-3'  (Folwaczny et al. , 2011). The PCR program consisted in an initial denaturation step at 95 ºC for 5 min, 35 cycles of 95 ºC for 30 s, 56 ºC for 30 s, and 72 ºC for 30 s, and a final extension step at 72 ºC for 10 min. The number of (GT)n repeats was identified by sizing the PCR products with the ABI 310 sequencer and the Genescan Analysis 2. 1 software (Applied Biosystems, Foster City, CA, USA). The following subdivision based on the number of repeats (n) was used: Allele S, n ≤ 16; Allele M, 17 ≤ n ≤ 22, and Allele L, n ≥23, which was further simplified as a binary variable S versus others (M or L)  (Yim et al.
Derivation of a hemolytic component The derivation of a hemolytic component followed the strategy described by  Nouraie and collaborators (2013). These authors derived a hemolytic component using principal component analysis (PCA) with 4 degrees of freedom from data on the reticulocyte count (%), and serum lactate dehydrogenase (U/L), aspartate aminotransferase (U/L) and total bilirubin concentrations (mg/dL). Levels of aspartate aminotransferase were not available in our patient database, but as this is a more distal marker of hemolysis and the other three are more direct markers, we worked with these remaining three degrees of freedom. For the PCA only steady state values were used. The association of this component with clinical phenotypes was assessed.
Genotype-to-phenotype association studies A stepwise approach in the statistical analysis of genotype-to-phenotype association was used (Fig. S1 ). In this manner the open-source whole genome association analysis toolset PLINK v1. 07 program  (Purcell et al. , 2007) , particularly adapted to cross-sectional association analysis of SNPs, was applied to the analysis of SNP rs4696480, c. -16934A>T, in exploratory preliminary association testing for the selection between various possible infectious disease subphenotypes. This preliminary analysis was followed by other crosssectional analytical methods, for association testing of the variants and haplotypes of the all the different TLR2 polymorphic loci under consideration (indel, SNP and STR). These informative tests included descriptive statistics for the comparison of rates or the chi-square test applied dichotomous traits.
Acknowledgements We are grateful to the patients and their families. We also thank  Dominique Labie  for having suggested this topic of research. We thank  INSA's "Unidade de Tecnologia e Inovacão " as well as  Andreia Coelho  and  Emanuel Ferreira  for technical support. We thank  Eric David Bosne  for insight in PCA. We also thank  Audrey V. Grant ,  Baltazar Nunes ,  Paula Faustino  and  Vera C. M. David  for their helpful suggestions in the elaboration of the study. This study was carried out with financial support from  FCT/MEC  through national funds and cofinanced by  FEDER , under the Partnership Agreement PT2020, in the project with reference  UIDMULTI/00211/2013 , and was partially funded by  FCT  grants  PIC/IC/83084/2007  and the  Centro de Investigação em Genética Molecular Humana (CIGMH).
Preclinical validation of the QDEM-based 3-plex immunoassay. Preclinical validation of the QDEM-based multiplexed immunoassay was performed, in which the standard curve with the recombinant protein was included, as well as 10 control and 42 lung cancer BAL samples. The fluorescence intensity data were statistically analyzed. Figure  2  shows the results of AMBP, PRDX2, and PARK7 analyses in the 3-plex immunoassay. Higher concentrations of AMBP and PRDX2 markers were found in the lung cancer group compared to the control group (with a fold change (FC) of 3. 4 and 2. 0, respectively), whereas PARK7 concentration was lower (FC = 0. 49). The  differences for the three markers were statistically significant. The AUC values were 0. 899, 0. 747, and 0. 192 for AMBP, PRDX2, and PARK7, respectively, which significantly differed from the threshold value of 0.
A minimum of 5,000 events per sample were recorded. The microparticle size distribution was estimated by measuring the side and forward light scatter (SSC-A and FSC-A dot plots). The green (515 nm, optical codes) fluorescence intensities of each microsphere population associated with QD fluorescence were analyzed in the FITC-A channel. The data were processed using the FACSDiva software (Becton Dickinson, Franklin Lakes, NJ, USA). Coupling of antibodies to QDEM. QDEM of different size types (4. 08, 6. 1, and 8. 24 μ m; 5. 10 7 of each) were washed and resuspended in PBS, pH 6. 2. Then, the QDEM were activated by adding 10 μ L of 50 mg/mL N-Hydroxysulfosuccinimide (Sulfo-NHS, Thermo Fisher Scientific, Villebon-sur-Yvette, France) and 10 μ L of 50 mg/mL 1-Ethyl-3-(3-dimethylaminopropyl)carbodiimide (EDC, Thermo Fisher Scientific, Villebon-sur-Yvette, France) aqueous solutions, gently mixed in a vortex mixer, and incubated for 20 min at room temperature with gentle mixing.
The median fluorescence intensity (MFI) values were obtained for each sample quantifying 200 QDEM. The LCM concentration was determined by interpolating the MFI values into the standard curve using the SigmaPlot 11 software (Systat Software Inc, San Jose, CA, USA). For the development of a 3-plex immunoassay, the same procedure was performed, except that the reagents for the quantification of the three biomarkers were added into a single well. For the quantification of the three proteins identified by Progenika Biopharma as differentially expressed in lung cancer, the BALF dilution, capture antibody, detection antibody, and SAPE concentration were optimized for each candidate biomarker (Table  4 ). The immunoassays were also validated. Standard curve fit estimated by backcalculation of standards (the difference between the actual and interpolated concentrations should be < 20% for at least six out of seven standards), intra-assay variation (coefficient of variation (CV) < 15%), inter-assay variation (CV < 15%), and the limit of quantification (LoQ) were determined.
Statistical analysis. In order to compare the data on the control and lung cancer groups, two statistical analyses were performed using the SPSS 15 software (SPSS Inc. , Chicago, IL, USA). First, univariate analysis was performed for each assay of the 3-plex immunoassay system. After using the Levene and Kolmogorov-Smirnov tests to assess the suitability of a parametric or a non-parametric analysis, the non-parametric Mann-Whitney U test was used to calculate the P values (the differences between the median values were taken to be significant at P < 0. 05). Second, multivariate logistic regression (the enter method) was used in order to assess how each of the three markers of the multiplexed immunoassay fitted the statistical model. The method included the receiver operating characteristic (ROC) curve and the area under the curve (AUC) values (threshold, 0.
Acknowledgements This work was supported by the  European Commission  through the  FP7 Cooperation Program  Grant  NMP-2009-4. 0-3-246479NAMDIATREAM  and by the  French Agence Nationale de Recherche  through the  ICENAP project of the M-ERA. NET EU Programme. This study was also supported by the  Federal Targeted Program for Research and Development of the Ministry of Education and Science of the Russian Federation  (grant no. 14. 578. 21. 0054 , contract no. RFMEFI57814 X 0054 ). We would like to specially thank  Dr. Rafael Zalacain  and  Dr. Guillermo López Vivanco  from the  Hospital Universitario de Cruces (Barakaldo, Spain)  for providing the BALF samples.
7 b ); in the case of BMDM, the number of colonies obtained with CRM0019 was slightly higher compared to the reference strain (Fig. 7 c ). CRM0019 showed a higher growth rate in A549 cells compared to the reference strain, mainly after 48 and 72 h (see Additional file 6), with a nearly 10-fold increase. For both macrophage lines, the results were similar to those observed in the first infection, except for RAW cells infected with CRM0019 at 72 h (see Additional file 3). Mycobacterial growth rate was also determined for M. smegmatis, which showed no colonies after reinfection of all cell types (data not shown).