dataesr/scientific-paragraphs-categorization huggingface dataset:
Conclusions This paper investigated the potential of using the statistical properties of wavelet coefficients of RCM images to characterize the skin lentigo. The proposed method computed the scale and shape parameters of a generalized Gaussian distribution associated with each band and each scale of images acquired at different depths. These parameters were then used to distinguish between healthy and lentigo tissues. A parametric T-test was performed to assess the statistical significance of the observed differences between healthy and lentigo images. The proposed hypothesis test was run on a database of 2250 real images associated with 45 patients. SVM classifiers were created and tested for the different parameters. The results of t-test and SVM classification were found in perfect agreement.
Statistical Analyses One-way ANOVA was performed using the GLM procedure of SAS (SAS Institute Inc. , Cary, NC, USA) for BW, feed intake, BW gain, FCR, breast meat yield, abdominal fat (both experiments) and ultimate pH, lightness and drip loss (experiment 2). For BW, BW gain, feed intake and FCR the statistical unit was the pen (n = 8/treatment). For breast meat yield, abdominal fat, ultimate pH, lightness and drip loss, the statistical unit was the animal (n = 32/treatment). Normality of data was assessed using the Shapiro-Wilk test and the hypothesis for a normal distribution of the data was not rejected. Differences between treatments were tested and significance was accepted at P < 0. 05. The relationships between N effi , N exc_BW, N vol , nitrogen and moisture (i. e. 100 -DM) contents in the manure content v.
CP content of the experimental diet were evaluated using linear regressions (R software v. 3. 2. 3; R Core Team, Vienna, Austria). In experiment 1, regression methods (i. e. linear, quadratic, linear plateau and curvilinear plateau models) were also used to model the effects of CP on animal Belloir, Méda, Lambert, Corrent, Juin, Lessire and Tesseraud performance and carcass characteristics using the REG procedures of SAS.
Acknowledgements The authors thank  Fréderic Mercerand  and  Nicolas Besne  ( INRA PEAT, Nouzilly, France ),  Philippe Rousseau  ( INRA EASM, Le Magneraud, France ),  Michel Couty ,  Jean-Marc Hallouis ,  Sabine Crochet ,  Thierry Bordeau  and  Estelle Cailleau-Audouin  ( INRA URA, Nouzilly, France ) and  Marcelle Eudaimon  ( Ajinomoto Eurolysine S. A. S. Customers Laboratory, Amiens, France ) for their collaboration in this study. They are also grateful to  Doreen Raine  ( Surrey, UK ) for editing the English language. This study received financial support from  INRA  and  Ajinomoto Eurolysine S. A. S.
Vandetanib distribution in beads Scanning electron microscopy showed the sectioned internal structure of DC Bead LUMI™ to be homogeneous and devoid of any visible pores (Fig. 3(a) ). SEM-EDX analysis was used to detect vandetanib distribution in sectioned sample loaded at maximum capacity of 135 mg/mL. Bromine was selected as the element of interest for the  drug distribution, being present in vandetanib molecules but not in DC Bead LUMI™. The sulfur and iodine distributions were also mapped to gain insight into the bead internal structure. Elemental mapping revealed that bromine was evenly distributed throughout the sectioned beads (Fig. 3(b) ), the bromine peak seen in the EDX spectrum (arrow, Fig. 3(e) ) being absent in the spectrum for control (unloaded) beads (data not shown). Sulfur and iodine distributions also appeared to be evenly distributed within the bead structure (Fig.
Patients and methods The study was conducted at 86 centres in 13 countries in Europe and South America and registered on clinicaltrials. gov (NCT01259713) and EudraCT  (2010-019562-91). The study was conducted in accordance with the Declaration of Helsinki. The protocol was approved by the institutional review board of each participating site. Written informed consent was obtained from each patient. An independent data safety monitoring board (DSMB) supervised the study and undertook a planned interim data review for futility when half the subjects had completed the study. An independent data review board (IDRB) performed a blinded review of data from all patients to assess the presence of IFD according to the revised consensus definitions. 4.
IFD monitoring and diagnostic-driven antifungal treatment Patients underwent prospective monitoring for the development of IFD according to defined study algorithms throughout the duration of the study and for the 30 days after stopping the study drug (Figures  S1-S3 , available as Supplementary data at JAC Online). Serum samples were drawn twice weekly and tested for galactomannan (GM) and 1,3-b-D-glucan (BDG) centrally in Belgium, Argentina or Brazil. The results were reported to the site within 48-72 h. A thoracic CT scan was recommended when the mycological criteria were met for a proven or probable IFD, and the study algorithm was followed according to the result (Figure  S2 ). 23 When no mycological criteria were met, 4 a work-up was undertaken when patients had unexplained fever (temperature 38 C for 72 h) despite antibiotic treatment, relapsing fever, new pulmonary infiltrates on chest X-ray or other potential signs and symptoms of IFD (Figure  S3 ).
10, 24, 25 A 0. 05 two-sided test was chosen because the interim boundaries were based around a two-sided test. We selected 2:1 randomization of L-AMB to placebo rather than 1:1 randomization due to ethical considerations and its potential to provide more comprehensive safety data for the L-AMB group. The primary efficacy analysis used the ITT population, i. e. all subjects who were randomly allocated to study treatment, who received at least one dose of study drug and met the major eligibility criteria (newly diagnosed with ALL and had not received systemically active antifungals within the previous 30 days). An ITT analysis excluding patients who were never neutropenic was done as was a post hoc per-protocol analysis set excluding patients receiving antifungals not permitted by the protocol.
Acknowledgements We extend our thanks to the participating patients, the investigators and their support staff. We also acknowledge the contribution of the Data Safety Monitoring Board (DSMB;  A. Pagliuca ,  A. J. Ullmann ,  C. Viscoli  and  D. Wang ), and the continuous reliable support of  S. Abella MD ,  R. Hargreaves ,  E. Harvey ,  S. Sanchez  and  C. Simcock. The Steering Committee members were  S. Agrawal ,  O. A. Cornely ,  J. P. Donnelly  and  N. Goekbuget  (Chair). The Independent Data Review Board members were  C. Cordonnier ,  C. P. Heussel  and  C. O. Morrissey. The results were presented in part at the 56th ASH Annual Meeting, 6-9 December 2014, San Francisco, CA,  USA  (Blood 2014; 24:  3646 ).
Methods Participants were drawn from the QUALITY (Quebec Adipose and Lifestyle Investigation in Youth) cohort, an ongoing longitudinal study of the natural history of obesity and cardiovascular risk factors in white youth. Children were recruited through elementary schools located within 3 major urban centers in Quebec, Canada. Eligibility criteria required participants to be white, aged 8 to 10 years at recruitment, with both biological parents available to participate in baseline data collection and at least 1 parent being obese (ie, body mass index ≥30 and/or waist circumference >102 cm in men and >88 cm in women). At baseline, 630 families participated in a clinic visit during which biological and physiological measurements were obtained, and questionnaires were completed between 2005 and 2008.
A similar assessment was conducted 2 years later, when participants were aged 10 to 12 years, between 2008 and 2011 (n=564). Written informed consent was obtained from parents, and children provided assent. The ethics review boards of the CHU Sainte Justine and the Quebec Heart and Lung Institute approved the study. A detailed description of the study design and data collection methods is available. 31 or the current analysis, we used a subsample of QUALITY participants (n=395) who were born at term (ie, 37 to <42 weeks of gestation), who had complete anthropometric data up to 2 years of age, and who completed a follow-up visit at age 10 to 12 years. Participants included in the analysis differed from those excluded in that they had slightly higher triglycerides (P=0. 049), higher diastolic BP (P=0.
However, given that puberty was not associated with birth weight or postnatal weight gain in our data and that its inclusion in models did not change the magnitude of b coefficients associated with early weight gain, models were not adjusted for pubertal development. Regression models were also adjusted for the suspected mediator (ie, childhood percentage of body fat mass) to estimate direct effects of birth weight for length and subsequent postnatal weight gain on cardiovascular risk factors. The linearity assumption for associations between independent variables and outcomes was tested using nonparametric smoothing splines and was found not to be violated. Indirect effects of birth weight for length and of postnatal weight gain on cardiovascular risk factors, via childhood adiposity, were estimated using path analysis (SAS proc calis; Figure ).
In sensitivity analyses, we tested the presence of interactions between sex and birth weight for length and between sex and postnatal weight gain using interaction terms included one at a time in covariate-adjusted models. Statistically significant interactions were found for triglycerides and for HDL cholesterol; sex-stratified analyses for these 2 outcomes are presented in Tables  S3-S4. Last, given that mechanisms linking early growth and later cardiovascular risk factors may be different for participants born with extreme birth weights, we repeated all analyses in a sample restricted to children born AGA (n=318), for which results are also presented in Tables S5-S7. All analyses were conducted with SAS version 9. 4.
Our study has limitations. First, weight and length data were obtained from health booklets and were not collected for research purposes, so variability in measurement precision is likely. Growth charts plotted for each participant were examined visually by 2 pediatricians, and a total of 209 (7%) measurements of weight or length were removed (eg, physiologically implausible measurements). Second, other than breastfeeding duration, we did not have nutritional data for the infancy period (eg, age at introduction of solid foods); confounding by early nutrition on associations of interest could not be investigated. Third, prepregnancy maternal weight status or weight gain during pregnancy were not available. In sensitivity analyses, however, estimated coefficients did not change following adjustment for maternal body mass index measured when participants were aged 8 to 10 years.
Acknowledgments The authors wish to thank  Katherine Gray-Donald PhD  and  Arnaud Chiolero MD, PhD  ( IUMSP, Lausanne University Hospital, Switzerland & Department of Epidemiology, McGill University, Montr eal ) for their contributions. Dr Marie Lambert  ( July 1952-February 2012 ), pediatric geneticist and researcher, initiated the QUALITY cohort. Her leadership and devotion to QUALITY will always be remembered and appreciated. The cohort integrates members of  TEAM PRODIGY , an inter-university research team including  Universit e de Montr eal, Concordia University ,  INRS-Institute-Armand Frappier, Universit e Laval , and  McGill University. The research team is grateful to all the children and their families who took part in this study, as well as the technicians, research assistants and coordinators involved in the QUALITY cohort project.
The clinicobiological data were retrieved from the local registry of each institution. Information regarding gender, age at the time of primary treatment, as well as immunogenetic features was available for all patients, while fluorescence in situ hybridization data were available for 1857 (53%) patients. Details regarding the molecular analyses are provided in the Online Supplementary Material. The study was approved by the local ethics review committee in each participating center. The evaluated patients received primary treatment between May 1980 and February 2014 and were stratified into two groups based on the date of this treatment; group A (n=2093) received primary treatment before 2006 and group B (n=1411) received primary treatment after January 1, 2006 (Table  1 ). The cut-off dates of January 2006 and February 2014 were chosen as they mark, respectively, the introduction of chemoimhaematologica 2018; 103:e158 Associations regarding categorical variables were assessed using the c 2 test.
Overall survival was measured from the date of diagnosis until the date of last follow-up or death, in order to minimize potential bias due to the longer follow up of the patients treated before 2006. Survival curves were constructed with the Kaplan-Meier method, and the log-rank test was used to determine statistically significant differences between survival proportions. All tests were two-sided and statistical significance was defined as a P-value <0. 05. Statistical analysis was performed using the Statistica Software v. 10•0 (StatSoftInc, Tulsa, OK, USA).
Funding: this work was supported in part by the  Swedish Cancer Society , the  Swedish Research Council , the  Lion's Cancer Research Foundation , the  Marcus Börgström Foundation and Selander's Foundation, Uppsala ;  H2020  " AEGLE, An analytics framework for integrated and personalized healthcare services in Europe " by the  EU ;  H2020  " MEDGENET, Medical Genomics and Epigenomics Network " (No. 692298 ) by the  EU ; GCH-CLL: funded by the  General Secretariat for Research and Technology (GSRT) of Greece  and the  Italian Ministry of Health (MoH) ;  IMI2  " HARMONY ", funded by the  EU ; project  CEITEC 2020  ( LQ1601 ) by  MEYS-CZ , project  AZV-MH-CZ 15-30015A-4/2015.
The analysis of the DOUBLON experiment has provided C/E's for several isotopic ratios in the first and second rows of the radial blanket after an irradiation in the PHENIX Sodium Fast Reactor. We have used this as a basis for the validation of the DARWIN-2. 3 (Tsilanizara et al. , 2000)  package for the depletion calculation in the radial blankets of SFR's  (Lebrat et al. , 2015). Unfortunately, no measurements have been performed in the upper and lower axial blankets of the fissile assemblies. Of course we expect our calculations to be reliable in these zones as well, as the initial compositions, nuclear reactions and neutron spectra are very similar. The representativity theory appeared to be the appropriate tool to correlate the available experimental information in the radial blanket to our calculations in the axial zones.
Introduction The analysis of the DOUBLON experiment has provided C/E's for several isotopic ratios in the first and second rows of the radial blanket after an irradiation in the PHENIX Sodium Fast Reactor. We have used this as a basis for the validation of the DARWIN-2. 3 (Tsilanizara et al. , 2000)  package for the depletion calculation in the radial blankets of SFR's  (Lebrat et al. , 2015). Unfortunately, no measurements have been performed in the upper and lower axial blankets of the fissile assemblies. Of course we expect our calculations to be reliable in these zones as well, as the initial compositions, nuclear reactions and neutron spectra are very similar. The representativity theory appeared to be the appropriate tool to correlate the available experimental information in the radial blanket to our calculations in the axial zones.
, 1997; Williams, 1978 Williams, , 1986) )  and can be written in our case: S r ¼ r N Â @N @r ð1Þ where S is a vector with N isotopes Â N reactions Â N groupes entries, to which we must add the decay constants of the radioactive isotopes involved. The sensitivity coefficients are computed for each isotope, each reaction and each of the 33 energy groups by the MECCYCO module of the ERANOS package  (Ruggieri et al. , 2006). This program performs adjoint multigroup evolution calculations, in order to obtain adjoint concentrations (i. e. importances). The relative sensitivities on the 239 Pu/ 238 U ratio are then obtained by a simple relationship: ⇑ Corresponding author. S r Pu239 U238 ðÞ ¼ r Pu239 U238 ÀÁ Â @ @r Pu239 U238 S r Pu239 U238 ðÞ ¼ r Pu239 U238 ÀÁ Â 1 U238 2 U238 Â @ @r ðPu239ÞÀPu239 Â @ @r ðU238Þ "# S r Pu239 U238 ðÞ ¼ r Pu239 Â @ @r ðPu239ÞÀ r U238 Â @ @r ðU238Þ S r Pu239 U238 ðÞ ¼ S r Pu239 À S r U238 ð2Þ where '' 239 Pu" and '' 238 U" are the final concentrations of each isotope.
Application to our study For our application, the above parameters are calculated in the positions of the PHENIX reactor that are represented on Fig. 1:  At the core midplane of the inner fuel assembly (FUEL) located in position 18/20, At mid-height of the lower (CAI) and upper (CAS) axial blankets of the same fuel assembly, In the first row of the radial blanket (FEF), at the core midplane of the assembly 24/13, In the second row of the radial blanket (FEG), at the core midplane of the assembly 24/12. The 42. 8 EFPD's of the cycle 10 of the PHENIX reactor are computed with the ERANOS package and its integrated depletion module MECCYCO, with the same calculation route that was used for the interpretation of the TRAPU and DOUBLON irradiations  (Lebrat et al. , 2015). The sensitivities are evaluated in ''fresh" fertile blankets composed of natural (for the CAI) or depleted (for the CAS, FEF and FEG) Uranium.
Fig. 2  shows the 33 energy group neutron spectrum obtained in the different zones of the reactor that we have studied; it is very similar in the various fertile zones and much ''harder" in the fuel. The same comment can be made on the sensitivity profiles shown on Figs. 3 4 5 6 ; to make the comparison easier on these figures, each sensitivity coefficients is normalized by its integral over energy. By definition, the normalized relative sensitivity coefficients are all positive. Once these sensitivities are calculated, we use MATLAB to perform the calculation of the representativity factors between two zones 1 and 2 as defined by Eq. (  4 ). The results are detailed in Table  2 , as well as the uncertainties due to nuclear data e that are defined by Eq. (3). Table  2  shows that the representativity factors between any two of the various fertile zones are very close to 1.
We conducted our study at the ONIAM between 2009 and 2011. We had access to anonymised data through a scientific partnership agreement between ONIAM and the French National Institute of Health and Medical Research (INSERM). Our corpus was made up of written documents from 61 cases filed by victims (i. e. people who believe they have been the victim of harm due to medical activity). When using the outof-court settlement mechanism, complainants must describe the extent and nature of the harm and identify the treatment and persons they consider to have caused it. To this end, they fill out a form, on which they answer the question: 'What harm and prejudices have been suffered?' They are also invited to attach a letter explaining the facts. These letters (not always provided) vary considerably in terms of length, content and style.
Acknowledgements This research was made possible through financial support from the  Agence Nationale de la Recherche (ANR) , the  Institut de la Recherche en Sant e Publique (IRESP)  and the  Haute Autorit e de Sant e (HAS). The study could not have taken place without a scientific agreement between the  Institut National de la Sant e et de la Recherche M edicale (INSERM)  and the  Office National d'Indemnisation des Accidents.
Lifetime drinking history (LDH) was used to calculate quantitative indices of alcohol consumption patterns, throughout the life span. 46 In particular, the duration (in years) of at-risk alcohol consumption was calculated from the reported age at onset of at-risk drinking to the end of at-risk alcohol consumption assessed at the first visit or during subsequent follow-up in subjects with still active alcohol intake at first visit. The amount of daily alcohol intake was extrapolated from the LDH and expressed as the average number of alcohol units per day. The possible presence of cirrhosis was also assessed and the time of cirrhosis diagnosis was reported using data from hospital discharge papers, medical records, physical examination, blood tests, imaging, and endoscopy. Specifically, cirrhosis diagnosis and its timing were based on liver biopsy or on the first occurrence of at least two of the following features: current or past cirrhosis complications (eg, ascites, variceal gastrointestinal bleeding, hepatic encephalopathy), the presence of hyperbilirubinemia, hypoalbuminemia, prolonged international normalized ratio, low platelet count, irregular liver surface at ultrasound/computed tomography, reduced portal vein flow at ultrasound, liver elastometry, gastroesophageal varices at endoscopy.
In the absence of a pathological diagnosis or overt cirrhosis, individuals with positivity of only one of the above-mentioned parameters were excluded from the current analyses. The dry weight to calculate body mass index (BMI) and the presence of diabetes at diagnosis of cirrhosis, or for those patients without a diagnosis of cirrhosis, at first visit were also reported. Patients were asked whether their body weight was stable (changes <5 kg) compared to that at age 25, at the first visit for noncirrhotic patients, and before the diagnosis of cirrhosis in cirrhotic patients. Blood samples were collected after an overnight fast and analyzed for biochemical parameters. DNA was collected from all the individuals. Individuals with other etiological factors (n=234) of liver disease (ie, hepatitis B and C infection, autoimmune hepatitis, primary biliary cholangitis, primary sclerosing cholangitis, Wilson's disease, hemochromatosis, Budd-Chiari syndrome), with incomplete LDH data (n=130), incomplete clinical/ biochemical data to achieve a diagnosis of alcoholic cirrhosis and/or a defined age at cirrhosis diagnosis (n=132), lack of body weight stability (n=41), or with poor DNA quality (n=35) were excluded from the analyses.
Acknowledgments The abstract of this paper was presented at the EASL Annual Meeting in 2017 as a poster with interim findings. The poster's abstract was published in "Poster Abstracts" in the Journal of Hepatology (2017, volume  66 , issue 1, supplement, page S348; doi. org/10. 1016/S0168-8278(17)31030-9 ). This research was supported by grants of  Sapienza, University of Rome  and by  "Wilhelm and Martina Lundgren Science" Fund.
Objective: To predict long-term disability outcomes in TEMSO core (NCT00134563) and extension (NCT00803049) studies in patients with relapsing forms of MS treated with teriflunomide. Methods: A post hoc analysis was conducted in a subgroup of patients who received teriflunomide in the core study, had MRI and clinical relapse assessments at months 12 (n 5 552) and 18, and entered the extension. Patients were allocated risk scores for disability worsening (DW) after 1 year of teriflunomide treatment: 0 5 low risk; 1 5 intermediate risk; and 2-3 5 high risk, based on the occurrence of relapses (0 to $2) and/or active (new and enlarging) T 2 -weighted (T 2 w) lesions (#3 or. 3) after the 1-year MRI. Patients in the intermediate-risk group were reclassified as responders or nonresponders (low or high risk) according to relapses and T 2 w lesions on the 18-month MRI.
Results: In patients with a score of 2-3, the risk of 12-week-confirmed DW over 7 years was significantly higher vs those with a score of 0 (hazard ratio [HR] 5 1. 96, p 5 0. 0044). Patients reclassified as high risk at month 18 (18. 6%) had a significantly higher risk of DW vs those in the low-risk group (81. 4%; HR 5 1. 92; p 5 0. 0004). Conclusions: Over 80% of patients receiving teriflunomide were classified as low risk (responders) and had a significantly lower risk of DW than those at increased risk (nonresponders) over 7 years of follow-up in TEMSO. Close monitoring of relapses and active T 2 w lesions after shortterm teriflunomide treatment predicts a differential rate of subsequent DW long term. ClinicalTrials.