dataesr/scientific-paragraphs-categorization huggingface dataset:
Dt. We reported residuals 1 Dt À 1 Dt and their 10th and 90th percentiles. For all analyses, we used GRIND for MATLAB (accessed at http://www. sparcs-center. org/grind). We approximated a continuous landscape using the finite difference method where we discretized space in a lattice, while making sure that cells were sufficiently small to approximate continuous space for the parameters we used. This resulted in a 50 9 50 lattice. Importantly, a finer-meshed lattice did not alter the resulting dynamics for the parameters we used. Note that one should always be aware of situations of no recovery due to the discretization method used  (Keitt and others 2001; van de Leemput and others 2015). All differential equations were solved using an explicit Runge-Kutta (4, 5) solver with adaptive step size.
Developing and testing indicators based on spatiotemporal responses is an exciting and promising way forward. AC KNOWLEDGEMENT S IvdL, MS, and EvN are supported by the European Research Council (ERC) under ERC Grant Agreement 268732. VD acknowledges the support of a Marie Curie IEF grant and an Adaptation to a Changing Environment fellowship from ETH Zurich. OP E N A C C ES SThis article is distributed under the terms of the Creative Commons Attribution 4. 0 International License (http://creativecommons. org/licenses/by/ 4. 0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Acknowledgements The authors are very grateful to  Dr. M. Siddall  ( AMNH ) and  Dr. T. Chad Walter  ( USNM ) for the opportunity to work with type material. Special thanks are due to  Professor A. I. Azovsky  and  V. Aksenova  ( Dept. of Hydrobiology, Biology Faculty Lomonosov Moscow State University, Russia ),  Dr. P. Hutchings  ( Marine Invertebrates, Australian Museum, Sydney, Australia ) and  Dr. T. M. Worsfold  ( APEM Ltd. , UK ) for the useful advice, critical remarks and correcting our English. The anonymous reviewers' comments greatly improved the quality of the paper. This study was financially supported by a  State Research Program  granted to  Moscow State University  (project №  AAAA-A16-116021660062-9 ), by the  Russian Foundation for Basic Research  (grant №  15-04-02245a ), by the  Far Eastern Branch of the Russian Academy of Sciences  (grant №  15-I-6-059 ) and the  Russian Science Foundation  (grant №  14-50-00029 ).
ACKNOWLEDGMENTS AND DISCLOSURES This work was supported by the  René and Susanne Braginsky Foundation (KES) ,  University of Zurich (FHP, KES) ,  Deutsche Forschungsgemeinschaft  Grant No. TR-SFB 134  (KES), and  University of Zurich Clinical Research Priority Programs Multiple Sclerosis and Molecular Imaging Network Zurich (KES). The authors report no biomedical financial interests or potential conflicts of interest.
A reduction of HAM-A total score in anxious subjects in POSG or CTG and a significant reduction of positive subjects for HAM-A in POSG (p = 0 03) and in CDG (p = 0 01) were shown. Discussion. Three-week intake of selected POS represents a good approach to solve problems related to obesity and behavior disorders. However, new clinical trials need to be performed on a larger population and for a longer period of treatment before definitive conclusions can be made. This trial is registered with NCT01890070.
Categorical variables were compared among groups by Chi-square (χ 2 ) or Fisher's test. McNemar test was used for the comparison between groups at baseline (T0) and after treatment (T1). Statistical analyses were carried out using IBM SPSS 21. 0 for Windows (Armonk, NY: IBM Corp. USA). In all statistical tests performed, the null hypothesis was rejected at the 0. 05 level of probability.
Acknowledgments The authors are indebted to all the subjects who volunteered in the study. The authors thank the entire medical team from the  Section of Clinical Nutrition and Nutrigenomic, University of Rome Tor Vergata ,  Rome: Gemma Lou De Santis ,  Lorenzo Romano ,  Paola Gualtieri ,  Giorgia Cioccoloni ,  Magda Kavvadia , and  Benedetta Primiceri. The authors also thank  Mario Bigioni  for painting Figure 4. This study was supported by grants from the  Ministry of Agriculture, Food and Forestry  (D. M. :  2017188 03/24/2011 ).
Metabolomics We used HRMAS NMR spectroscopy to evaluate the impact of mitotane on the metabolome of tumoral cells. At visual inspection, all the spectra obtained from the 14 analyzed cellular samples were of good quality. The generated multivariate two-component PLS-DA allowed a clear separation of untreated from mitotanetreated H295R cells showing accurate representation of the data and a good cumulative confidence criterion of fit (R2Y = 0. 87) and prediction (Q2 = 0. 56). According to spectra visual evaluation and the results of PLS-DA model, both aspartate and glutamate were the most discriminant metabolites between cellular subgroups. As illustrated in Figure  1A , HRMAS spectra of untreated or mitotane-treated H295R cells demonstrated that aspartate content was drastically reduced upon mitotane exposure.
The number of loops was set to 328, thus giving the CPMG pulse train a total length of 93 ms. The parameters for the CPMG experiment were set as follows: sweep width, 14. 2 ppm; number of points, 32k; relaxation delay, 2 s; and acquisition time, 2. 3 s. A total of 1024 FIDs (free induction decay) were acquired resulting in an acquisition time of 75 min. Data were zero-filled to a 2k*1k matrix and weighted with a shifted square sine-bell function before Fourier transformation. HRMAS NMR spectra were bucketed into integral regions 0. 01 ppm wide (ppm range, 4. 8-1) using AMIX 3. 8 software (Bruker GmbH, Germany) and exported into SIMCA P (version 11. 0, Umetrics AB, Umeå, Sweden). Spectra were referenced by setting the lactate doublet chemical shift to 1. 33 ppm. To accommodate the influence of metabolites present at both high and low concentrations, without emphasizing spectral noise, unit variance scaling was employed for all analyses.
Metabolites were assigned using standard metabolite chemical shift tables available in the literature  [31]. To confirm resonance assignments, two-dimensional (2D) homonuclear and heteronuclear ( 1 H-13 C) experiments were also recorded immediately after the end of 1D spectra acquisition. Because the long duration of these experiments is potentially responsible of cellular degradation during NMR acquisition, only a few representative samples of both groups (e. g. : treated and untreated cells) were analyzed by 2D experiments. A combination of principal component analysis (PCA) and partial least square discriminant analysis (PLS-DA) was herein adopted  [32]. The PCA was performed to evaluate the quality of the data and to identify possible outliers. Then, the PLS-DA was employed to optimize the separation between cells subgroups.
Cross-validation was used to determine the number of components and to avoid data overfitting. Fourteen cellular samples (n = 7 untreated, n = 7 treated by 50 µM of mitotane during 48 h) were analyzed in an exploratory manner. Two measurements of model quality were reported for PLS-DA: R2Y and Q2 representing respectively, the goodness of fit (i. e. data variation) and the goodness of prediction, as estimated by cross-validation. Accordingly, the PLS-DA was performed on the whole set of variables to identify (and afterwards quantify) those metabolites with highest discriminating power. The procedure for metabolite quantification has been previously described  [32, 33]. Briefly, quantification was performed using an external reference standard of lactate, scanned under the same analytical conditions.
Generation of constructs The 5 0 UTR of the SOX9 gene (GenBank NM_000346. 3) from wild-type and mutant DNA was amplified by PCR, cloned into pcR2. 1 TOPO (Invitrogen, Karlsruhe, Germany) and subsequently transformed into competent Dh5a cells. Plasmids were isolated and forward (5 0 -ACT GCT GTG CTG TGA TTG GCG GGT GGC TCT AAG-3 0 ) and reverse (5 0 -CTA GGG CCC TTG GTT GCC CGG GGC CGG GGC AGG GGG CTG G-3 0 ) primers were used to create a 10 bp frameshift. All constructs, wild type, mutant and frameshift, were cloned in-frame 5 0 to the c-myc epitope tag using the HindIII and ApaI site in the pcDNA3. 1/myc-His/B expression vector (Invitrogen). A partial SOX9 Exon 1-containing vector (pcDNA3. 1/ Sox9/1-304) was digested with ApaI, and the resulting 711 bp fragment was introduced into the ApaI site next to the epitope of each construct.
The G>A transition is not found in 100 control chromosomes, dbSNP, or the ExAC consortium database  (Lek et al. 2016)  nor in 30 CD or CD-like cases without a SOX9 coding region mutation. Paternity was confirmed by microsatellite marker analysis. Interestingly, the flanking sequence of the upstream AUG translation start codon matches the Kozak consensus  (Kozak 1986 ) much better than the sequence preceding the wild-type AUG start codon (4/7 vs. 1/7) (Fig. 2B ).
1%) and thrombocytopenia (18. 8%) were the most common grade X3 toxicities across combinations and were DLTs with the oral rucaparib/carboplatin combination. Maximum tolerated dose for the combination was 240 mg per day oral rucaparib and carboplatin area under the curve 5 mg ml À 1 min À 1. Oral rucaparib demonstrated dose-proportional kinetics, a long half-life (E17 h), and good bioavailability (36%). Pharmacokinetics were unchanged by carboplatin coadministration. The rucaparib/carboplatin combination had radiologic antitumour activity, primarily in BRCA1-or BRCA2-mutated breast and ovarian/peritoneal cancers. Conclusions: Oral rucaparib can be safely combined with a clinically relevant dose of carboplatin in patients with advanced solid tumours (Trial registration ID: NCT01009190). The poly (ADP-ribose) polymerase (PARP) family includes enzymes that are involved in the repair of single-strand breaks, a common type of DNA damage, thus preventing the formation of DNA double-strand breaks  (Schreiber et al, 2006).
MATERIALS AND METHODS Study design. This study was an open-label, multicentre, doseescalating phase I study of rucaparib administered in combination with one of four different standard chemotherapeutic regimens (NCT01009190). Eligible patients X18 years of age had a histologically or cytologically confirmed advanced solid tumour, an Eastern Cooperative Oncology Group (ECOG) Performance Status of 0 or 1, life expectancy of X12 weeks, and adequate bone marrow, liver, and renal function. All BRCA testing was done locally and was not verified by the sponsor. The primary objective was to assess safety and tolerability and estimate the maximum tolerated dose (MTD) and/or select the recommended phase II dose of rucaparib in combination with chemotherapy. Secondary objectives were to characterise the pharmacokinetics (PK) and assess the antitumour activity of rucaparib when combined with chemotherapy.
Oral rucaparib in combination with carboplatin. Patients received lead-in doses of i. v. and oral rucaparib on days À 10 and À 5, respectively, followed by carboplatin (AUC3, 4, or 5) on day 1 and oral rucaparib on days 1-14 of every 21-day treatment cycle. The i. v. lead-in dose of rucaparib was discontinued once sufficient bioavailability data for oral rucaparib were available. The starting dose of 80 mg oral rucaparib was based on the safety established with up to 24 mg m À 2 i. v. rucaparib in combination with chemotherapy and an oral bioavailability of 36%. The protocol prespecified dose cohorts of 80, 120, and 180 mg oral rucaparib, after which rucaparib was to be escalated in 50% increments. Additional doses of 240 and 360 mg were subsequently evaluated. Similarly, carboplatin dosing began at AUC3, with a plan to escalate to AUC5 once the MTD of rucaparib was established; however, escalation was modified to evaluate AUC4 carboplatin before escalating to AUC5.
Patients discontinuing carboplatin could continue to receive oral rucaparib. Safety and efficacy assessments. Safety assessments included collection of adverse events (AEs) and serious AEs (defined by National Cancer Institute Common Terminology Criteria for Adverse Events version 3. 0;  Pedersen et al, 2013) , as well as vital signs, physical examination, 12-lead electrocardiogram, laboratory assessments, and verification of concurrent medications. Safety variables and demographic data were presented descriptively. The safety analysis set included all enrolled patients who started treatment. Dose-limiting toxicities (DLTs) were defined as any of the following occurring during cycle 1: grade 4 neutropenia lasting X7 days; febrile neutropenia; grade 3 thrombocytopenia lasting X7 days with bleeding or grade 4 thrombocytopenia lasting 43 days; grade X3 toxicity despite the use of adequate/maximal medical interventions and/or prophylaxis as dictated by local institutional clinical practices or the judgement of the investigator; grade 2 neurotoxicity that did not recover to grade p1 within 2 weeks of planned dose; toxicities that resulted in a delay of 414 days in initiation of cycle 2 dosing; or toxicities that resulted in failure to deliver X80% of the assigned oral rucaparib doses.
The PK parameter analysis population was defined as all treated patients who had at least one of the PK parameters of interest in at least one treatment period (cycle 1). Standard plasma PK parameters for rucaparib were estimated using noncompartmental methods and included: maximum plasma drug concentration (C max ); area under the plasma concentration time curve from time 0 to the last sampling time with measurable values (AUC 0-t ) and from time 0 to 24 h (AUC 0-24 ); and half-life (t 1/2 ). Plasma clearance or apparent plasma clearance and steady-state volume of distribution were calculated for rucaparib. The oral bioavailability of rucaparib was calculated as the ratio of dose-normalised AUC 0-t or AUC inf (data permitting) determined using oral rucaparib PK data collected on cycle 1 day À 5 to that determined using the i.
Rucaparib exhibited clinical activity in combination with chemotherapy in this study of heavily pretreated patients with advanced malignancies. More than two-thirds of all patients in the study had stable disease or better, and this is notable because patients were not preselected for HRD (only 10 of 85 patients were known to harbour a BRCA mutation). Of patients who received oral rucaparib and carboplatin, 63. 6% achieved disease control for X12 weeks, and PRs were reported in 3 patients with ovarian or breast cancer, 2 of whom had a known BRCA mutation. The benefits of inhibiting PARP in BRCA-mutated ovarian or breast cancer are well documented  (Fong et al, 2009; Audeh et al, 2010; Tutt et al, 2010; Kaye et al, 2012; Sandhu et al, 2013; Lee et al, 2014b). As a single agent, oral rucaparib has demonstrated activity against BRCA-mutated ovarian and breast cancer  (Shapira-Frommer et al, 2015; Drew et al, 2016; Swisher et al, 2017)  and is currently being evaluated in phase III studies as both maintenance and treatment therapy for patients with relapsed, high-grade ovarian cancer (ARIEL3 (NCT01968213) and ARIEL4 (NCT02855944)).
ACKNOWLEDGEMENTS We thank the staff of the  Belfast City Hospital ;  Beatson West of Scotland Cancer Centre, Glasgow; Churchill Hospital, Oxford ;  Royal Marsden Hospital, London; Guy's Hospital, London ;  Institut Curie, Paris ; and the  Northern Centre for Cancer Care, Newcastle. Above all, we particularly thank our patients, their families, and friends for their support and participation in this trial. This study was funded by  Clovis Oncology, Inc. , and  Cancer Research UK  and the  UK Department of Health funding for the UK Experimental Cancer Medicine Centre Network  (to RHW, TRJE, MRM, LRM, JS, and RP). Writing and editorial assistance funded by  Clovis Oncology , was provided by  Tim Lohret ,  Nathan Yardley , and  Shannon Davis  of  Ashfield Healthcare Communications (Middletown, CT, USA ).
2μm-pore filter (Thermo Fisher Scientific, Villebon sur Yvette, France). The donor gave signed informed consent and the study was validated by the ethics committee of the Institut Fédératif de Recherche IFR48 under number 09-022. The colonies appeared to be 0. 5 mm in size, homogeneous, translucent, smooth and non-haemolytic. Strain GD6 was a non-motile, Gram-negative and rod-shaped bacteria with a mean diameter of 250 nm and a length of 1 μm without spore-forming activity. Catalase and oxidase were negative. The complete 16S rRNA gene of the bacterium was sequenced as previously described  [4]  and shared 89. 5% of identity with Anaerotruncus massiliensis strain AT3 (GenBank Accession number LN866995)  [5]. The phylogenetically closest species standing in nomenclature was Hydrogenoanaerobacterium saccharovorans with 89.
MALDI-TOF-MS spectrum accession number. The MALDI-TOF-MS spectrum of 'Bittarella massiliensis' is available at http://mediterranee-infection. com/article. php? laref=256& titre=urms-database. (Last accessed 28 November 2016). Nucleotide sequence accession number. The 16S rRNA gene sequence was deposited in GenBank under Accession number LN881596. Deposit in a culture collection. Strain GD6 T was deposited in the collection de Souches de l'Unités des Rickettsies (CSUR, WDCM 875) under number P2149.
Studies and participants A total of 5,780 participants aged 9 months received at least one dose of CYD-TDV and 5,499 (95. 1%) received the third CYD-TDV dose. The numbers of participants in studies undertaken in Asia Pacific (including Australia) and Latin America were 3,233 (55. 9%) and 2,329 (40. 3%), respectively, and there were 218 (3. 8%) in the 2 US studies (CYD12 and CYD51). Participants included in the immunogenicity subset for CYD14, CYD15, CYD23 and CYD28 had similar baseline demographic data to the overall study population. The majority of participants were from endemic regions (4,400; 76. 1%) and most were children 6 to 11 y (1,833; 31. 7%) and adolescents 12 to 17 y (1,510; 26. 1%). Overall, there were 3,104 (53. 7%) participants aged 9-45 y (2,810 [48. 6%] aged 9 to 17 years) and 241 [4.
Antibody persistence Dengue neutralizing antibody persistence data post-dose 3 were available from the following studies: CYD14, CYD15, CYD22, CYD23 and CYD28. In this section, we focus on data from CYD14 and CYD15 as these were pivotal studies and included the most number of participants accessed for immunogenicity and have long-term follow-up up to 3 y post-dose 3 (follow-up is still ongoing through to 5 y post-dose 3). During the first 2 y of follow-up, GMTs for all serotypes decreased relative to postdose 3 in both studies, regardless of participant's age or dengue immune status at baseline (Fig. 4 ). The decrease in GMTs against all 4 serotypes from Year 1 to Year 2 of follow-up tended to be lower than between post-dose 3 and Year 1 of follow-up in all age groups. However, GMTs at Year 3 of followup remain stable or slightly increased relative to those at Year 2 for all serotypes in both studies.
Discussion Three doses of CYD-TDV 6 months apart consistently induces an increase in dengue neutralizing antibody GMTs, as measured by PRNT 50 , in all studied populations encompassing a wide age range and different regions with various dengue endemicity. In addition, several factors including age, previous exposure to dengue and region are known to impact on the level of CYD-TDV induced immune response. Therefore, to capture the fullness of the available immunogenicity profiles we did not pool the immunogenicity data across studies; all GMTs are reported by age, study, and region in this article. By presenting all the available data in this way, the reader should be able to identify general trends and any substantial outliers within each grouping. One of the strengths of our analysis is that we present laboratory data that were determined at centralized laboratories using the same validated PRNT 50 across all studies rather than compare results obtained from multiple different neutralization assays.
Immunogenicity In the current analysis, we focus on dengue neutralizing antibody titers obtained before the first CYD-TDV dose and 28 d after the third dose (in all participants except in CYD14, 3 CYD15, 2 CYD23 16 and CYD28  13  where subsets were assessed) as these were evaluated in all studies. Studies where CYD-TDV was co-administered with other childhood vaccines were also included in the current analysis as the co-administered products did not impact the humoral response to CYD-TDV; in these studies the immunogenicity data were combined across the groups that received 3 CYD-TDV doses. 11, 19, 21 In addition, we present persistence data where available. Pre-vaccination baseline blood samples were also assessed for antibodies against Japanese encephalitis (JE) for studies undertaken in Asia Pacific (except for CYD17 10 and CYD28  13  ) and for antibodies against Yellow Fever (YF) in those undertaken in the Americas (except for CYD12 8 and CYD33  19  ).
Acknowledgments This integrated analysis was performed by  Sanofi Pasteur. Editorial assistance with the preparation of the manuscript was provided by  Richard Glover , inScience Communications,  Springer Healthcare , Chester, UK. Funding for this assistance was also provided by  Sanofi Pasteur. The authors also thank  Jean-S ebastien Persico  for editorial assistance and manuscript coordination on behalf of  Sanofi Pasteur. We thank all the parents and participants who agreed to participate in these trials; the trial investigators and staff in the countries; and to the clinical research organization staff who contributed to the successful completion of the trials. The authors also wish to thank  Stephen W. Hildreth  ( Sanofi Pasteur ) for his contribution to the dossier writing, and the  Common Technical Document task force.
Scope of the study This study investigates the impact of conditioning methods on the performance of seasonal streamflow forecasts. It proposes an insight into how conditioning approaches impact forecast attributes such as reliability, sharpness and the detection of low-flow events. The aim is not to provide an overall better ensemble but to shed light on which forecast attributes can be expected to improve or deteriorate after conditioning. For that purpose, we used conditioning statistics based on precipitation indices derived from the System 4 seasonal precipitation forecasts issued by the European Centre for Medium-range Weather Forecasts (ECMWF) to select traces of past observed precipitation and streamflow. Eight streamflow forecast scenarios were built and analysed. Section 2 presents the data and the methodology used to build streamflow forecasts.
Observed and forecast hydrometeorological data Observed precipitation data come from the SAFRAN reanalysis of  Météo-France (Quintana-Seguí et al. , 2008; Vidal et al. , 2010). Daily values are available from August 1958 to July 2010 (i. e. 51 complete years) at an 8 km × 8 km grid resolution covering France. Data were aggregated at the catchment scale. Mean areal potential evapotranspiration was computed for each catchment using a temperature-based formula  (Oudin et al. , 2005)  and observed temperatures from the SAFRAN reanalysis. Daily streamflow data at the outlet of each catchment come from the French national archive (Banque Hydro, www. hydro. eaufrance. fr). Seasonal precipitation forecasts were collected from ECMWF GCM, System 4. Once a month, ECMWF provides a 51-member forecast ensemble for the next 7 months with TL255 (about 80 km spatial resolution;  Molteni et al.