dataesr/scientific-paragraphs-categorization huggingface dataset:
For the first interim analysis, an independent data monitoring committee conducted an unblinded review of efficacy and safety data. The review included 106 randomized patients who received at least one dose, who had baseline and at least one post-baseline value of weekly attack frequency, and who completed the week 4 visit for sample size re-estimation and futility evaluation. The review also included 110 randomized patients with at least one dose for safety evaluation. Based on pre-specified criteria, the committee recommended a sample size increase to 222. No further study modifications were recommended. The second interim analysis was performed on the final set of all randomized patients through the end of the double-blind period. The results from this second interim analysis are reported here.
Acknowledgements Most importantly, the authors thank the patients who participated in the study, their families, and the following investigators and study personnel:  Jean Schoenen ,  Centre Hospitalier Regional de la Citadelle ;  Koen Paemeleire ,  Universitair Ziekenhuis Gent ;  Marek Gawel ,  Stroyan Research ;  Suzanne Christie ,  Ottawa Headache Centre Research Inc. ;  Guy Boudreau ,  Centre de Traitement Neurologique ;  Rigmor Højland Glostrup Hospital ;  Markus Fa¨rkkila¨ ,  Helsingin Pa¨a¨nsa¨rkykeskus ;  Markku Nissila ,  Terveystalo Pulssi ;  Matti Ilmavirta ,  Suomen Terveystalo ;  Caroline Roos ,  Hopital Lariboisiere;  Michel Lanteri-Minet ,  Hoˆpital de Cimiez ;  Christian Lucas ,  CHRU de Lille Hoˆpital Roger Salengro ;  Anne Donnet ,  APHM Hoˆpital de la Timone ;  Christelle Creach ,  CHU St Etienne Hopital Nord ;  Dagny Holle-Lee ,  Universitaetsklinikum Essen ;  Arne May ,  Universita¨tsklinikum Hamburg -Eppendorf; Andreas Straube, Klinikum der Universita¨t Mu ¨nchen; Charly Gaul, Migra¨ne-und Kopfschmerzklinik GmbH & Co.
2017; 2018a, b; Thober et al. 2018; Visser-Quinn et al. 2019). For example, assuming a non-stationary climate under climate change: • What is the likely magnitude of a future flood event (return period) in a particular location, and how may that differ from flood events at present  (Collet et al. 2018a )? • How will this affect the future flood footprint of a given event in the future? • Will this uncertainty be greater than the inherent uncertainty associated with flood frequency estimation at present (e. g. Winter et al. 2018; Collet et al. 2017 ), or will parameter uncertainty in the model become more important? To date, no study has attempted to answer these questions. Previous work by the authors  (Collet et al. 2017 (Collet et al. , 2018a, b) , b)  used the Future Flows Hydrology (FFH) database  (Prudhomme et al.
Flow projections Following  Collet et al. (2017) , this study utilized daily flow projections from the FFH database, an 11-member perturbed parameter ensemble. It is through this perturbing of parameters that climate model parameter uncertainty may be explored. Flow projections were extracted for the Don River at Parkhill gauging station. As is standard in climate impact assessment  (Allen et al. 2018 ), this study focuses on two 30-year climate normals, a 1961-1990 baseline and the 2080s (2069-2098). To ensure consistency in the analysis, only flow projections are utilized. The focus is on the change in extreme events between the time periods, i. e. the changes in peak flow and uncertainty due to climate change.
Limitations of the study There are some limitations which are worth noting for this study and which warrant further consideration in future research. This study utilized data from the FFH database for a single emissions scenario, SRES A1B. This data is derived from the UKCP09 projections, a perturbed physical ensemble based on a single climate model (HADCM3). Projections from a hydroclimatological modelling chain that utilizes a multi-model ensemble may yield different results (e. g. the  EDgE projections, Thober et al. 2018). Other important considerations for future work include: • Modelling with the most recent CMIP5 projections; • Comparison across multiple emissions scenarios (e. g. RCP2. 6 and RCP8. 5); • Modelling across a range of topographical diverse catchments or longer river reaches, which explores the dynamic interaction of floodplain inundation, flood defence failures and flood management within river reaches-adding hydraulic complexity into the analysis.
The study was approved by our institutional review board, the research and ethics committee of the Catholic Institute of Lille Hospital Group and reported to the National Commission of Informatics and Freedoms. Both parents and children received written information and agreed to the use of their data. Socio-demographic, clinical and biological data at baseline and after 6 months of OIT were collected. OIT-related side effects after 6 months of OIT were gathered at the time of inclusion using a standard homemade survey (Supplemental text E1).
Oral food challenge A DBPCFC was performed at the time of diagnosis and an OFC was performed after 6 months of OIT. Except for placebo administration, the protocol was the same for both challenges, with hazelnut or placebo given in boiled apple as a matrix. During the DBPCFC, patients received ground hazelnut or placebo on two different days in randomized order. The hazelnut dose escalation protocol is detailed in a supplemental data appendix (Table  E1 ). In summary, the dose started at 0. 7 mg of hazelnut protein. Then, increasing doses (twice the cumulative dose) were administered every 20 minutes to a maximum cumulative dose of 1635 mg or until the occurrence of a hypersensitivity reaction. In the event of an allergic reaction, the DBPCFC was stopped and if necessary, appropriate treatment was administered.
As in our study, long-term buildup protocol for OIT appears to be safe  19. Although the literature has reported contrasting data on the frequency and severity of food OIT-related side effects, protocols using slow dose escalation and personalized regimens (doses adjusted based on the patient's reactive threshold) are usually associated with benign side effects  27- 29. Furthermore, patients were carefully selected for their ability to follow the OIT protocol (3 patients were excluded because of their inability to demonstrate compliance) and were systematically enrolled in education programs. Some studies have highlighted the occurrence of chronic gastrointestinal symptoms or EoE during OIT 30. In our study, there were no patients who developed EoE. Educating patients undergoing OIT protocol to avoid and recognize cofactors for reactions to foods, such as stress, certain medications (nonsteroidal anti-inflammatory drugs, codeine), alcohol, rigorous exercise, and fever can enhance the safety and tolerability of OIT  31, 32.
Interpretation of these findings is limited by our single-center study population. In addition, the population included in the study corresponds to 58% of the hazelnut allergic patients followed in our center. These results therefore may not be generalizable. The main strength of our study is that it provides the first descriptive data on 6-month hazelnut OIT in a large population of children and identifies cashew sensitization as a potential predictor of unsuccessful hazelnut desensitization. In conclusion, our results suggest that hazelnut OIT may be effective and safe in children with IgE-mediated FA to hazelnut. There is a need for randomized trials to confirm the efficacy, safety, feasibility, and ideal protocol of hazelnut OIT and prospective long-term tolerance monitoring studies.
We analyzed variations between consecutive shots by recording 100 single-shot diffraction patterns of an isolated object with an overall size of ~5 µm. Correlating the shots to a far-field simulation of the object revealing possible beam jitter. Here, a limit of correlation of 0. 75 was set to separate stable diffraction patterns from unstable ones. ~40 % of the recorded pattern can be considered as stable and, therefore, ~40% of shots can be considered as jitter free. For this reason, the measurement of the main dataset was repeated several times to ensure stable results for every scanning position.
Acknowledgements: The research leading to these results has received funding from the  European Community 's  Horizon 2020 research and innovation program  under grant agreement n°  654148  (LASERLAB EUROPE). M. Z. acknowledges support by the  Max Planck Society  ( Max Planck Research Group ) and the  Federal Ministry of Education and Research (BMBF)  under " Make our Planet Great Again -German Research Initiative " (Grant No.
57427209 "QUESTforENERGY") implemented by DAAD. F. T. acknowledges support by the  Federal State of Thuringia  and the  European Social Fund (ESF)  Project  2018 FGR 0080. P. M. G. and E. O. acknowledge support from the  European Community 's  Horizon 2020 research and innovation program  under grant agreement  665207 , project  VOXEL  and the  Universidad Politécnica de Madrid , project  DERKETA. This work is supported by  "Investissements d'Avenir" Labex PALM  ( ANR-10-LABX-0039-PALM ).
Acknowledgements We thank the  Ministerio de Educación y Ciencia  and the  Estación Biológica de Doñana (ICTS-RBD, Spain)  for the fi nancial and logistical support of the fi eldwork in Doñana National Park. Collecting trips to the Algarve were fi nanced by the  EU   FP7 ASSEMBLE  grant agreement no. 227799. We would like to thank the  Centro de Ciências do Mar (Centre of Marine Sciences) of the University of the Algarve, Portugal , for providing excellent working and sampling facilities, in particular  Dr Ana Amaral  for the kind and effi cient logistic support and  Dr Jorge Gonçalves  for collecting the samples at the islands near Sagres. Special thanks also go to the captain of the Zodiac for his help with sampling in the Ria Formosa. The research of S. G. was supported by a PhD-grant of  BOF-UHasselt.
M. M. is funded by a PhD fellowship from the  Research Foundation -Flanders (FWO-Vlaanderen). We would like to thank  Ria Vanderspikken  and  Natascha Steffanie  for their valuable assistance in the lab. Dr Bart Tessens  and  Dr Niels Van Steenkiste  are thanked for their involvement in collecting specimens from the Algarve, Portugal and  Doñana National Park, Spain. Dave Bosmans  is cordially thanked for his help with processing the images included in this work European Journal of Taxonomy 595:  1-17 (2020 ).
Modelling risk of importation For this study, Europe is defined according to the Wikipedia contemporary geographical definition but with exclusion of transcontinental countries (Azerbaijan, Georgia, Kazakhstan, Russia and Turkey)  [10]. The risk of importation to Europe is estimated as the probability that at least one case is imported from China to Europe. It is based on estimates from the platform EpiRisk  [11]  and accounts for origin-destination air travel flows of January 2019 from the Official Airline Guide (OAG) database of the GLEAM Project  [11] [12] [13]. Details of the computation are provided in the Supplementary Material. To estimate the risk in Europe prior to the travel ban in the Hubei province, we consider Wuhan as the only seed of the international spread  [3, [5] [6] [7].
Acknowledgements We thank the  GLEAM Project  for the use of EpiRisk,  Simon Cauchemez  and REACTing (https://reacting. inserm. fr/)for useful discussions. Funding statement: This study was partially supported by the  ANR  project  DATAREDUX  ( ANR-19-CE46-0008-03 ) to VC; the  H2020   MOOD  project to VC, CP, PYB.
A new subtype with a poor prognosis and characterized by a double mutation in the TSG NF2 and LATS2, both of which are involved in the Hippo signaling pathway, was identified by coupling genetic and transcriptomic analysis  (37). Other studies have proposed classifications into four subtypes that are also related to prognosis and partially to genetic alterations  (14, 18, 38). Interestingly, a meta-analysis that compared the subtypes obtained by clustering from several transcriptomic data sets showed that only the most extreme subtypes, which represent the "pure" epithelioid and sarcomatoid phenotypes, are found in all datasets. These findings suggest that intermediate subtypes might only reflect divisions of a continuum  (38, 39). Based on these results, histomolecular gradients obtained by a signal deconvolution method on transcriptomic data were proposed to consider MPM intertumor heterogeneity as well as intra-tumor heterogeneity.
In vitro Models MM cell lines have been widely used to study MM pathogenesis and evaluate the activity of numerous anti-cancer agents. The first MM cell lines were established in 1982 from the abdominal fluid of a patient  (60). In 1987, a MM cell line was established from a surgical sample of malignant pleura, namely H-Meso-1  (61). Since that study, numerous cell lines have been established from samples of patients by different groups to constitute local biocollection. Some of these collections have been extensively characterized  (19, 36, 37, (62) (63) (64) (65) (66) , as well as 21 cell lines in the Genomics of Drug Sensitivity in Cancer (GDSC) database (https://www. cancerrxgene. org/ celllines). MPM cell lines present common characteristics with regard to tumors and might lead to the identification of new biomarkers  (62, 67, 68).
FUNDING This work was supported by  Inserm ,  CNRS ,  Hadassah France , the  National Research Agency  under the  Programme d'Investissements d'Avenir  ( ANR-16-IDEX-0007 ), the  Pays de la Loire Region research program  by a financial support from the  Institut de Recherche en Santé Respiratoire des Pays de la Loire , the  Chancellerie des Universités de Paris (Legs POIX) , the  Ligue Contre le Cancer (Ile de France committee) , and  ARSMeso44. The authors thank the cluster LUNG innOvatiOn ( LUNG O2 ) for logistic support.
Background: Muscular strength should be one of the main parameters to assess the interest or not of surgery after proximal hamstring rupture. Yet, this parameter is difficult to compare between the different studies because of the heterogeneous assessment methods. Methods: We realized a critical review of strength assessment methods used to evaluate treatments performed after proximal hamstring rupture. The studies were selected from several medical databases with the keywords: « proximal hamstring rupture » OR « proximal hamstring avulsion » AND « strength » OR « isokinetic ». Findings: 24 articles evaluated muscular strength after proximal hamstring rupture. 7 have been excluded because the method was not described. 6 types of dynamometric evaluation were used: 2 with an isometric method, 3 with a pneumatic isotonic method and 13 with an isokinetic method.
Search Strategy This systematic review was performed with medical databases: Medline via PubMed, CINAHL and SPORTdiscus via EBSCOhost, Cochrane Library, EMBASE via OvidSP, and Web of Science. Article research extended from 1990 to 2018. Multiple searches were carried out using the following keywords: « Proximal Hamstring Rupture » OR « Proximal Hamstring Avulsion » AND « Strength » OR « Isokinetic ». Only studies in English language were selected. The search was performed independently by 2 assessors (A. F-C, M. D) to assess titles and abstracts of potentially relevant articles, and then the full-text articles were retrieved. In case of doubt, a third assessor's advice was asked (P. M). After identification of key articles, their reference and citation lists were perused for further information sources.
Statistical analysis We initially reported raw data from the studies. These results have been expressed in percentage of strength deficit with the standard deviation and/or with minimal and maximal values. Then, the strength deficits were weighted according to the number of evaluated patients in order to compare the studies. Weight means, standard deviation or minimal and maximal values were obtained by pooling the sums of each respective sample size and dividing them by the total sample size  (Bodendorfer et al. , 2017). The results were separated according to the different methods of muscular strength evaluation (isometric with hand held, isotonic with pneumatic system and isokinetic). Since the inter-machine reliability of the Cybex ® (Cybex, division of Lumex Inc. , Ronkonkoma, NY, USA) and Biodex ® (Biodex Medical Systems, Shirley, NY, USA) isokinetic dynamometers are acceptable (ICC : 0.
88-0. 92 ; SEM : 3,7-11,2 Nm ; CV : 8,5-10,7%), the studies which used these dynamometers were pooled (de Araujo Ribeiro  Alvares et al. , 2015). Conversely, studies using other dynamometers such as Isobex ® (Cursor AG, Bern, Switzerland) or Isomed ® 2000 (D. & R. Ferstl GmbH, Hemau, Germany) were excluded of this pooling, because the reproducibility of the measures was unknown even after research in the medical databases previously cited or on the websites of the manufacturers. The results obtained with pneumatic method, initially described by  Cross et al. (Cross et al. , 1998) , were analyzed separately; the reproducibility of these measures was not known. The results obtained with the isometric method using a handheld ® dynamometer were also analyzed separately because the method was very different from the pneumatic isotonic method or the isokinetic method  (Scudder, 1980).
Quality of the muscular strength assessment The quality of the muscular strength assessment of the studies was evaluated independently by 2 authors (M. D and A. F-C) using the Physiotherapy Evidence Database (PEDro) scale  (de Morton, 2009; Elkins et al. , 2010). If no consensus was found, the opinion of a 3rd reviewer was required (P. M). The PEDro scale has 11 items whose answers are "present" or "absent", the first item is not taken into account for the calculation of the final score  (van der Made et al. , 2015). According to PEDro scale, a study has a low-quality if its score is ≤ 5.
Studies' raw data (Table 3) The delay of the hamstring strength assessment was inconstant from one study to another, varying from 4 months to 100 months. The studies included 512 patients and 446 were evaluated, that is to say 87. 1%. Before surgery, the hamstring strength deficit was 46% in case of incomplete rupture and 76% in case of complete rupture  (Barnett et al. , 2015). If no surgery was performed, the mean strength deficit between 4 months and 100 months was decreasing from 40% +/-25 to 25% +/-16. At 2 years of follow-up, extreme values ranged from a complete recovery to a persistent strength deficit of 70%  (Fouasson-Chailloux et al. , 2019; Hofmann et al. , 2014). On an eccentric mode, a deficit of 40% +/-17 [17 -70%] persisted 24 months after the injury whereas the deficit of strength was reduced to 25% +/-16 on a concentric mode  (Fouasson-Chailloux et al.
MATERIALS AND METHODS Fieldwork for this project was conducted aboard RV Thomas G Thompson cruise TN303 at the culmination of the US GEOTRACES East Pacific Zonal Transect  (Moffett and German, 2018). Multibeam mapping of the summit of Teahitia Seamount was conducted using the EM302 multibeam sonar mounted aboard the RV Thompson. Survey lines were occupied in a NW/SE orientation to accommodate prevailing wind directions and the entire seamount was mapped in a series of overlapping ∼9 km surveys, offset from one another by 2 km and surveyed at 7. 5 kts. Seismic data for the study area are collected continuously by the Polynesian Seismic Network/Réseau Sismique, Polynésie (RSP). Data are monitored continuously at the Laboratoire de Géophysique in Papeete, Tahiti, where the seismic energy of each event is calculated using the standard methods described by  Gutenberg and Richter (1954).
Earthquake magnitude (M L ) coefficients are assigned according to the approach established by J. Talandier and colleagues, as described in  Talandier and Kuster (1976) ,  Okal et al. (1980)  and  Talandier and Okal (1984). Water column studies at Teahitia were conducted using a CTD-rosette system furnished by the Scripps Institution of Oceanography's Ocean Data Facility. The system comprised a Sea-Bird SBE9 + conductivity temperature depth (CTD) instrument mounted on a rosette frame equipped with a 12position carousel holding 30L General Oceanics Niskin sampling bottles. In addition to conventional in situ sensors (dissolved oxygen, fluorometer, transmissometer), two additional sensors were employed, specifically, for the hydrothermal plume studies conducted on this cruise: a Seapoint STM11 turbidity meter and a NOAA-PMEL Oxidation-Reduction Potential (ORP) sensor.
Oceanographic Evidence for Hydrothermal Perturbations at Teahitia Seamount In the preceding section, we presented geophysical evidence that document temporal variability in the volcano-tectonic cycle at Teahitia, and beyond, that could be consistent with a re-activation of that seamount specifically, and/or across the Society Islands hotspot in general. But a question that we can address using our CTD plume data from directly above Teahitia is: do the heat-flux values that can be derived from our water column investigations require any departure from what was observed at the seafloor previously? To address this question, a first calculation that we can pursue is to determine the heat flux implicit in our observed plume data. The optical and redox sensor data from our CTD cast provide clear evidence for a neutrally buoyant hydrothermal plume at ∼1400 m (Figure  5 ), i.
To obtain a more sophisticated/less idealized estimate of the source heat flux at Teahitia, therefore, we have also conducted a 3-D numerical simulation using the plume model described in  Lavelle et al. (2013). The model is a 3-D non-hydrostatic, time-dependent, turbulent convection construct for a domain that is open to flow on all four sides. Injection of heat flux over a 20 by 20 m area through the bottom boundary drives the buoyant rise of a plume into a calm, stratified, rotating (f-plane) water column. The spatial resolution of the model simulation run for Teahitia was 1. 5 m in all three dimensions. The background temperature and salinity used in the model were imported from the same WOCE Station P16-220 data set used to calculate the buoyancy frequency, previously (see above). An example of our model output is shown in Figure  7 : calculated temperature anomalies for a hydrothermal plume driven by a 10 MW heat flux, 4 h after initiation of the simulation.
ACKNOWLEDGMENTS We thank the  Captain  and crew of the RV Thomas G. Thompson cruise TN303 and, especially,  Rob Palomares  ( SIO ) for his support of our CTD operations and  Patrick A'Hearn  and  Steve Jalickee (UW)  for their support in conducting the EM302 multibeam survey. GX thanks  J. W. Lavelle  for support in conducting the 3D numerical simulations of the Teahitia plume. We also thank the  Schmidt Ocean Institute  for bringing this team of collaborators together and, in particular,  Captain Bernd Buchner  and the crew of the RV Falkor for their hospitality aboard ship in Papeete, where the first draft of this manuscript was generated. Finally, we thank  Guest Editor DA  and two reviewers for their contributions in improving the original version of this manuscript.
Results In ref. [6] , the model predictions have been initially compared to test data obtained on mortar specimens that have been loaded in uniaxial compression, up to several damage states (viewed as a degradation of the material's Young's modulus). Here we are going to compare the results obtained with this model with data related to other materials that are available in the literature. Among these we have: • three different concretes reported by Chen et al. [30]  and Kallel  [31]  respectively. The first one uses CEM I Portland cement, the second one uses CEM V, highly concentrated in fly ashes and blast-furnace slag. The third one is the concrete used in the MACENA project. The PSD of CEM I and MACENA concretes are shown in Fig. 3;  • Two different rocks: a sandstone tested by Osselin et al.