dataesr/scientific-paragraphs-categorization huggingface dataset:
5 mg/kg) or twice (0. 25 mg/kg) daily for 3-days compared to artemether-lumefantrine in children 12-17 years before age de-escalation to younger children (NCT01445938). Results In the first study 113 patients received SAR97276A: 30 adults single-dose IV, 34 adults single-dose IM, 30 adults 3-day dose IM and 19 children 3-day dose IM. SAR97276A given as a single-dose to adult patients showed insufficient efficacy by IM route (20 cured of 34; and IV route (23/30 cured). The 3-day treatment showed a sufficient level of efficacy when given IM to adults (27/30 cured) but not when given to children 7-17 years (13/19 cured). In the second study 20 patients were recruited and randomly assigned (2:2:1 ratio) to receive once-daily SAR97276A, twicedaily SAR97276A or artemether-lumefantrine. All patients receiving SAR97276A once-daily and 5/8 patients receiving SAR97276A twice-daily required rescue therapy.
Study design and participants We used data from a study described in detail elsewhere  [13, [16] [17] [18]. This was a French prospective multicenter cross-sectional study aimed at assessing the diagnostic accuracy of a RADT (StreptAtest, Dectrapharm, France; a rapid immunochromatographic strip assay) in 678 consenting children aged 3 to 15 years, with throat culture on a blood agar plate in a microbiology laboratory as the reference standard. Seventeen primary care office-based pediatricians participated. Between October 1, 2010, and May 31, 2011, double throat swabs were collected from consecutive children who had a diagnosis of pharyngitis and had not received antibiotics within the previous week. One swab was used for performing the RADT in the pediatrician's office following the manufacturer's instructions; the other swab was sent to the hospital laboratory for throat culture according to standard methods.
Statistical analysis Missing data. The number of missing values ranged from 0. 4% to 6. 2% per candidate predictor variable. Missing values were imputed 10 times using multiple imputations with chained equations as described previously  [13]. Statistical analyses were performed separately in each imputed dataset; estimated parameters and corresponding variances were pooled using Rubin's rule  [20]. All statistical analyses were performed in Stata/SE 13 (StataCorp, College Station, Texas). Model building. As recommended, first degree fractional polynomial transformations of the continuous variables age and maximum body temperature were used to explore deviations from linearity in univariable logistic models  [21]. All candidate predictor variables were included in the initial multivariable logistic regression model, regardless of their association with the outcome in univariable analysis.
Efficiency and diagnostic accuracy of the model-based strategy The calculated probabilities of GAS in our study group ranged from 0. 08 to 0. 97 across imputed datasets (Fig  3 ). The proportion of participants with low and high calculated probability of GAS were both <5%. With our model-based rule for selective testing, RADT could be avoided in 6. 6% of participants (95% CI, 4. 7% to 8. 5%). The sensitivity of the model-based selective testing strategy was 92% (95% CI, 89% to 95%) at a specificity of 88% (95% CI, 85% to 91%).
Discussion Clinical practice guidelines from the AHA, the IDSA, and the AAP recommend using signs and symptoms to select children with pharyngitis who should undergo RADT for GAS (Table  1 )  [3] [4] [5]. Applying multivariable logistic regression to data from a prospective multicenter cross-sectional study of 676 French children with pharyngitis, we developed and evaluated a model-based rule for selective testing. While the model showed fair discrimination and good calibration, its application would have resulted in a reduction of less than 7% in RADT use. We believe that such a reduction in RADT use is not clinically relevant, considering the additional burden of having to use a computerized model-based decision rule. Our study has several strengths. First, we included 676 participants, which is larger than most previous studies which aimed at developing prediction models for GAS pharyngitis in children.
fr/), and our results might not be widely generalizable. We chose the decision thresholds in our model-based rule a priori, based on clinical arguments previously reported and used in the literature  [2, 13 ]. Yet we acknowledge that we currently lack agreement on such cutoff values. Guidelines from the AHA and the IDSA only provide lists of signs and symptoms suggestive of GAS or viral etiology, but do not explain how such clinical criteria should be combined for decision making, which leaves primary care physicians with unclear guidance. Consensual decision cutoffs could be identified through a survey involving primary care physicians and infectious diseases specialists. We used logistic modeling procedures for developing and evaluating our clinical prediction model. We are aware that other modeling approaches exist, such as classification and regression trees, neural networks, and support vector machines  [25] , but relied on empirical evidence that such techniques may not outperform logistic regression modeling in clinical prediction  [28] , and that they may be reliable only in the case of very large datasets  [29].
Acknowledgments This article is dedicated to the memory of  Professor Edouard Bingen ,  Department of Microbiology ,  Robert Debre  ´Hospital and  Paris Diderot University. We thank  A. Liboz  ( Department of Microbiology, Robert DebreHospital ),  M. Boucherat, MD  (database design),  F. de La Rocque, MD  (study conception),  I. Ramay ,  D. Menguy ,  S. Tortorelli  and  M. Fernandes  (ACTIV), and all the physician investigators who participated in the RADT GAS study:  M. Benani , MD; F. Corrard, MD; P. Deberdt, MD;  M. Goldrey, MD ;  J. Gosselin , MD; M. Koskas, MD;  P. Martin, MD ;  A. S. Michot, MD ;  N. D'Ovidio, MD; D. Qutob, MD ;  C. Romain , MD;  O. Romain, MD ;  C. Schlemmer , MD; F. Thollot, MD;  A. Wollner, MD.
This work was supported by a research grant from the  French Ministry of Health  (PHRC Regional 2012, AOR 12089). The clinical study was internally funded by ACTIV and externally by Dectrapharm, manufacturer of the rapid test. JFC was supported by educational grants from  Agence Regionale de Santed'Ile-de-France ,  Laboratoires Guigoz -SocieteFrancaise de Pediatrie -Groupe de  to a RADT-for-all strategy. grant from  Assistance Publique.
X-ray Diffraction The structure of the membrane was studied using a multilayer CS 0. 8 -PEC-SEC 0. 8 /PAI-SO 2 film and compared with the model film CS 0. 8 -PEC-SEC 0. 8. Figure  3  shows the X-ray diffraction patterns obtained by the reflection from the membrane sample formed as a result of layer-wise deposition of the SEC 0. 8 solution onto the microporous support, followed by deposition of CS 0. 8 solution onto the SEC 0. 8 /PAI-SO 2 composite film. (The ratio of the number of positively charged -NH 3 + groups in CS and negatively charged -SO 3 -groups in SEC was 1:1). Analysis of these data showed that the formation of the PEC layer by the deposition of CS and SEC layers on the PAI-SO 2 support was characterized by crystallization of the CS, as previously found for the model CS 0. 8 -PEC-SEC 0.
Acknowledgments: This work was financially supported by the  Russian Science Foundation  (project # 16-19-10536 ). Author Contributions: S. V. K. , V. A. P. , V. V. K. and Y. A. S. conceived and designed the experiments; E. V. K. , V. A. P. , Y. G. B. , K. A. R. and A. S. O. performed the experiments; S. V. K. , V. V. K. , V. A. P. and Y. A. S. analyzed the data; S. V. K. and Y. A. S. wrote the paper. All authors discussed the contents of the manuscript and approved the submission.
Materials and methods study design This was a 2-year multicenter, prospective, noninterventional cohort study in outpatients aged 18-65 years with a current diagnosis of MDD (Diagnostic and Statistical Manual of Mental Disorders [DSM]-IV-TR) enrolled by either a primary care physician or a psychiatrist in France, UK, Spain, Germany, and Sweden. This study is registered with ClinicalTrials. gov (NCT01427439). Enrolled patients were either initiating antidepressant monotherapy or undergoing their first switch of antidepressant for a new episode of major depression, with the choice of antidepressant used based on the clinical judgment of the treating physician. Patients receiving antidepressant combination therapy at the time of the initial consultation and patients with schizophrenia or other psychotic disorders, bipolar disorder, substance dependence, mood disorders due to a general medical condition or substances, dementia, or other neurodegenerative diseases significantly impacting cognitive functioning were excluded from study entry.
study assessments and data collection Study assessments and data collection occurred during routine visits within the normal course of care at baseline, 2 months (±3 weeks), and 6 months (±1 month), after which data were collected approximately every 6 months up to 2 years. Patient characteristics recorded included demographic information, history of MDD, characteristics of the current episode of depression, MDD management and resource use, and the presence of any other mental disorder or functional syndrome. Clinical severity of depression was assessed at all visits by patients using the nine-item Patient Health Questionnaire (PHQ-9)  32  and by all participating investigators using the Clinical Global Impressions-severity of illness scale (CGI-S). 33 The Montgomery-Åsberg Depression Rating Scale (MADRS)  34  was also administered when patients were recruited by psychiatrists.
Alternative definitions included reducing the cutoff used to define remission, placing MADRS before PHQ-9 in the composite definition of remission, increasing the cutoff used to define relapse, and imposing a defined minimum change in PHQ-9 score. These later analyses were conducted using the final model identifying factors associated with relapse at month 6 for patients in remission at month 2 obtained by backward selection. All statistical analyses were performed using SAS version 9. 2 (SAS Institute, Cary, NC, US).
Variables were selected based on literature review and clinical evaluation. all variables were assessed at baseline, unless otherwise indicated. Abbreviations: aseX, arizona sexual experience scale; cgi-s, clinical global impressions-severity of illness; M2, month 2; Mcs, mental component summary; MMas-4, 4-item Morisky-Green Medication Adherence Scale; PCS, physical component summary; PDQ-5, 5-item Perceived Deficit Questionnaire; PHQ-9, 9-item Patient Health Questionnaire; Pre-M2, prior and up to M2 (any time before baseline, at baseline, or between baseline and M2); sF-12, 12-item short-Form health survey; WPai-shP, Work Productivity and Activity Impairment-specific health problem. postbaseline data (n=101, including 76 who met the inclusion criteria at baseline). The majority of patients were enrolled and followed up by primary care physicians (n=969; 83.
PHQ-9 total score was chosen as the first criterion for these composite definitions. The PHQ-9 is a brief, selfadministered questionnaire specifically developed for evaluation of the severity of depressive symptoms,  32  and is widely used in both research settings and clinical practice. PHQ-9 total score was assessed for all patients in the study, regardless of the setting (primary or specialized care). The second criterion used was MADRS total score. 34 The MADRS is widely used to assess depression severity in randomized clinical trials of antidepressant therapy. 80, 81 This scale requires training to ensure reliable scoring, and was thus administered only by psychiatrists in this study; however, the majority of patients (83. 6%) were enrolled and followed up by general practitioners. The investigator-administered CGI-S was the final criterion for the composite definitions of remission and relapse; however, CGI-S score was only used if data were unavailable for both of the previous scales, as this assessment scale is not specific for depression.
information on the contributions of different source sectors and/or source regions to ozone (O 3 ) or fine particulate matter  (PM 2. 5  ) concentrations. This information can be useful in designing air quality management strategies and in understanding the potential benefits of reducing emissions from a particular source category. The Comprehensive Air quality Model with Extensions (CAMx) offers unique source attribution tools, called the Ozone and Particulate Source Apportionment Technology (OSAT/PSAT), which track source contributions. We present results from a CAMx source attribution modeling study for a summer month and a winter month using a recently evaluated European CAMx modeling database developed for Phase 3 of the Air Quality Model Evaluation International Initiative (AQMEII). The contributions of several source sectors (including model boundary conditions of chemical species representing transport of emissions from outside the modeling domain as well as initial conditions of these species) to O 3 or PM 2.
More recently,  Tagaris et al. (2015)  used the zero-out approach with CMAQ to calculate the contributions of emissions from the 10 SNAP source sectors to air quality over Europe for a summer month  (July 2006). The study described in this paper differs from and complements the previous source attribution studies. We take advantage of the source apportionment tools (OSAT and PSAT) in CAMx to calculate the contributions of the 10 SNAP sectors, biogenic emissions, dust emissions, and sources outside the modeling domain (boundary conditions) to a large number of cities in Europe. The CAMx modeling database for 2010, developed as part of the Air Quality Model Evaluation International Initiative (AQMEII), is used for the analysis. AQMEII is a joint regional air quality model evaluation effort between the North American and European modeling communities to improve the understanding of uncertainties in model predictions of ozone and PM 2.
As part of Phase 3, a CAMx modeling database has been developed and evaluated for Europe  (Solazzo et al. , 2017) , and this database was used in the study described in this paper. (Yarwood et al. , 2005)  and the coarse-fine (CF) aerosol scheme. CAMx was applied for the whole year for a domain covering Europe and a portion of Africa. The domain (see Fig. 1 ) is defined in a Lambert conic conformal projection that includes 270 by 225 grid cells with a 23 km horizontal grid resolution. Input meteorological data were generated using WRF-Chem 3. 4. 1, the coupled chemistry version of the Weather Research and Forecasting (WRF) model  (Skamarock et al. , 2008) , driven by the European Centre for Medium-Range Weather Forecasts (ECMWF) analysis fields. WRF-Chem was used rather than WRF to obtain emission estimates for wind-blown dust.
(2013)  and  Giordano et al. (2015). Solazzo et al. (2017)  conducted a detailed model performance evaluation of CAMx for 2010 in the framework of the AQMEII Phase 3 project. Here we present a brief summary of model performance using a set of ground-based observations belonging to the AirBase network (http://www. eea. europa. eu/data-and-maps/data/ airbase-the-european-air-quality-database-8) and covering most of the computational domain. Only background stations are considered in the analysis. Furthermore, analysis was carried out for the whole set, including urban, suburban, and rural sites (all background, AB), as well as for rural background sites only (RB). Note that the rural background sites are the most appropriate for model performance evaluation because the coarse resolution (23 km) used in the simulation cannot reproduce local-scale processes that can take place, particularly within the urban areas, and that can also influence the observed values at background sites.
Data availability. CAMx, the model used in the study, can be downloaded from http://www. camx. com/. The Air-Base data used to evaluate model performance can be obtained from http://www. eea. europa. eu/data-and-maps/ data/airbase-the-european-air-quality-database-8. The AQMEII modeling inputs used in the study are available to the AQME project participants at the AQME website: website:http://aqmeii. jrc. ec. europa. eu/. The Supplement related to this article is available online at doi:10. 5194/acp-17-5643-2017-supplement.
96 TeV  [8] , and by the ATLAS Collaboration at the LHC using pp collisions at √ s = 7 TeV  [9]  and √ s = 8 TeV  [10]. These results are in agreement with the SM predictions within uncertainties  [11]. In this paper, the measurement of the tt+γ production cross section in pp collisions at √ s = 8 TeV is presented. The analysis is based on a data sample corresponding to an integrated luminosity of 19. 7 fb -1 , recorded with the CMS detector in 2012. The measurement of the tt+γ production cross section in the semileptonic decay channel is performed relative to the tt production cross section. The tt+γ cross section is measured in a fiducial kinematic region defined by the presence of exactly one charged lepton and corresponding neutrino, at least three jets, and a photon within the selection requirements.
Calculation of the cross section ratio The fiducial tt+γ cross section (σ fid. tt+γ ) and the inclusive tt+γ cross section (σ tt+γ ) can be calculated based on the equations: σ fid. tt+γ = N tt+γ tt+γ L , σ tt+γ = N tt+γ A tt+γ tt+γ L = σ fid. tt+γ A tt+γ , (2) where N tt+γ is the number of tt+γ events observed, A tt+γ is the acceptance of tt+γ events within the fiducial phase space, tt+γ is the efficiency of the tt+γ selection within events in the acceptance region, and L is the integrated luminosity of the data set. The acceptance is determined at generator level, by requiring generated events to fall within the fiducial phase space defined for the analysis. Events are required to have exactly one generated prompt lepton in the fiducial phase space. For electrons, this requires p T > 35 GeV and |η| < 2.
Summary The results of a measurement of the production of a top quark-antiquark (tt) pair produced in association with a photon have been presented. The measurement is performed using 19. 7 fb -1 of data collected by the CMS detector at a center-of-mass energy of 8 TeV. The analysis has been performed in the semileptonic e+jets and µ+jets decay channels. The ratio of the tt+γ to tt production cross sections has been measured to be R = σ tt+γ /σ tt = (5. 2 ± 1. 1) × 10 -4. By multiplying the measured ratio by the previously measured value of the tt cross section, the fiducial cross section for tt+γ production of 127 ± 27 fb has been found for events in the e+jets and µ+jets final states. The measured values are in agreement with the theoretical predictions.
Acknowledgments We congratulate our colleagues in the CERN accelerator departments for the excellent performance of the LHC and thank the technical and administrative staffs at  CERN  and at other  CMS institutes  for their contributions to the success of the CMS effort. In addition, we gratefully acknowledge the computing centres and personnel of the Worldwide LHC Computing Grid for delivering so effectively the computing infrastructure essential to our analyses. Finally, we acknowledge the enduring support for the construction and operation of the LHC and the CMS detector provided by the following funding agencies:  BMWFW  and  FWF (Austria) ;  FNRS  and  FWO (Belgium) ;  CNPq ,  CAPES ,  FAPERJ , and  FAPESP (Brazil) ;  MES (Bulgaria) ;  CERN ;  CAS, MoST , and  NSFC (China) ;  COLCIENCIAS (Colombia) ;  MSES  and  CSF (Croatia) ;  RPF (Cyprus) ;  SENESCYT (Ecuador) ;  MoER ,  ERC IUT , and  ERDF (Estonia) ;  Academy of Finland ,  MEC , and  HIP (Finland) ;  CEA  and  CNRS/IN2P3  (France);  BMBF ,  DFG , and  HGF (Germany) ;  GSRT (Greece) ;  OTKA  and  NIH (Hungary) ;  DAE  and  DST (India) ;  IPM (Iran) ;  SFI (Ireland) ;  INFN (Italy) ;  MSIP  and  NRF (Republic of Korea) ;  LAS (Lithuania) ;  MOE  and  UM (Malaysia) ;  BUAP ,  CINVESTAV ,  CONACYT ,  LNS ,  SEP , and  UASLP-FAI (Mexico) ;  MBIE (New Zealand );  PAEC (Pakistan) ;  MSHE  and  NSC (Poland) ;  FCT (Portugal) ;  JINR (Dubna) ;  MON, RosAtom ,  RAS ,  RFBR  and  RAEP (Russia) ;  MESTD (Serbia) ;  SEIDI, CPAN, PCTI  and  FEDER (Spain) ;  Swiss Funding Agencies (Switzerland) ;  MST (Taipei) ; ThEPCenter, IPST, STAR, and  NSTDA (Thailand) ;  TUBITAK  and  TAEK (Turkey) ;  NASU  and  SFFR (Ukraine) ;  STFC  ( United Kingdom );  DOE  and  NSF (USA).
We thought that a change of 25% would be significant. -Functional disability related to LBP was measured by the Quebec Back Pain Disability Scale at each evaluation time. The higher the score (/100), the higher the disability. We considered as determined by Ostelo et al. [21]  20 points of change of the Quebec score as clinically significant. -Quality of life was measured at each evaluation time on a horizontal visual analogue scale 100 mm long. The question asked was: "In your opinion, how was your quality of life over the last month?" (0 = no impact to 100 = major deterioration). We considered as clinically significant a change of 0. 2 standard deviation (small change), 0. 5 standard deviation (moderate change) and 0. 8 standard deviation (large change)  [22, 23]. -Inability to work was measured by a compendium of data indicating the number of sick leave days due to LBP in the 8 months preceding inclusion and during follow-up.
A variation of strength up to 20% or a reversal of the flexor/extensor ratio was considered as clinically significant. -MODIC classification of discopathy and Hadar classification of the rector spinae muscles were based on MRI performed in the previous year. The MODIC measures are divided in 3 classes:  [24] : there were type 1 (inflammatory phase), type 2 (fatty phase) and type 3 (marked sclerosis adjacent to the endplates). We collected the data in order to look for predictive factors for efficacy of BoNT-A. -Tolerance to BoNT-A injections was studied by actively asking at each visit for possible side effects (pain at injection points, sensation of general weakness, falling, nausea, diplopia, dry mouth).
Blood was collected from an antecubital vein on D1 (pre-exercise, immediately post-exercise, and 1 h post-exercise) and from D2 to D5 only one sample daily, using a vacutainer system. One tube of EDTA-treated blood was centrifuged (10 min, 3500g) to separate out the plasma. Another tube of blood was clotted and centrifuged (10 min, 5000g) to separate out the serum. Serum myoglobin concentration and plasmatic both, creatinine concentration and total creatine kinase (CK) activity were determined using assay kits obtained from Abcam, Cambridge, UK. Statistical analysis. Data sets were analyzed using Statview software version 4. 51. 1 (Abacus Concepts, Berkeley, CA). The data are expressed as mean ± standard deviation (SD). Normality was evaluated by the Shapiro-Wilk test. During the length of the studied exercise inducing DOMS, changes within and between both groups were analyzed using paired and unpaired Student's t-test.
Conflict of Interest Fytexia is involved in the research and development and marketing and sales of polyphenol extracts from various fruit and vegetables regularly consumed within the Mediterranean diet for food and nutraceutical industries. Therefore, Fytexia has a commercial interest in this publication. UCAM and UMR 204 Nutripass were paid by Fytexia to perform and report the scientific work that formed the basis of this publication. Fytexia, UCAM, UMR 204 Nutripass, and all authors declare that the data in this report represent a true and faithful representation of the work that has been performed. The financial assistance of Fytexia is gratefully acknowledged.