dataesr/scientific-paragraphs-categorization huggingface dataset:
ACKNOWLEDGEMENTS We thank all our colleagues of the UMR 7156 GMGM for helpful discussions. We thank  L. Richert  and  Y. Mély  ( Faculty of Pharmacology of Strasbourg University ) and  J. Mutterer  ( IBMC-CNRS, Strasbourg ) for the help with microscopic techniques. This work was supported by the  Centre National de la Recherche Scientifique (CNRS) , the  University of Strasbourg  and the  LabEx MitoCross  ( National Program PIA, Programme Ivestissement d'Avenir ).
Study subjects Patients with PH presenting with oesophagogastric varices and hypersplenism who were treated in our department from January 2002 to February 2017 were screened for this single-centre retrospective cohort study. Two SPD types are used in our department: SSPD and STPD. The surgical details are described in a previous publication  [5, 6]. The inclusion criteria were:  (1)   All procedures were conducted in accordance with the Declaration of Helsinki from the World Medical Association and with the ethical standards of the committees responsible for human experimentation (institutional and national). The requirement for written informed patient consent was waived due to the retrospective and anonymous nature of this study; all data were used only for statistical analysis.
Data collection Survival and postoperative bleeding conditions of the patients were monitored and recorded. The following primary data were collected: age, gender, aetiology, Charlson score, blood type, history of variceal ligation, history of abdominal surgery, smoking, drinking, history of variceal bleeding, body mass index (BMI), Child-Pugh score at admission, model for end-stage liver disease (MELD) score at admission, albumin-bilirubin (ALBI) score at admission, and Comprehensive Complication Index (CCI) score. The following laboratory data were collected at admission and during the perioperative period: White blood cell (WBC) count, haemoglobin (Hb) level, platelet count, prothrombin time (PT), international normalised ratio (INR), total bilirubin (TBIL) level, direct bilirubin (DBIL) level, alanine transaminase (ALT) level, aspartate transaminase (AST) level, albumin (ALB) level, globulin (GLB) level, serum creatinine (Scr) level, cystatin C (Cys C) level, duration of the preoperative hospital stay, duration of the postoperative hospital stay, total hospital stay, operative time, intraoperative blood loss, time to first flatus, and type of surgery.
Statistical analysis Statistical analyses were performed using IBM SPSS statistics 22 software (SPSS Inc. , Chicago, IL, United States) and R version 3. 2. 2 software (Institute for Statistics and Mathematics, Vienna, Austria; http://www. r-project. org/). Continuous variables are presented as means ± SD, and categorical variables are presented as frequencies and percentages. Survival curves were generated using the Kaplan-Meier method, and the significance of difference in survival among selected variables was verified using the log-rank test. A univariate Cox regression analysis with an Enter method was used to estimate the relative risk (RR). A multivariate Cox regression analysis with a Forward Condition method rate was 81. 3% and the 10-year OS rate was 59. 7%. The 5-year DSS rate was 87.
Discussion IAV transmission dynamics is characterized by a high amount of different possible subtypes circulating in wild birds  1, 2. The species barrier constituted by the difference in linkage conformation of the SA IAV receptor between humans and birds is well known  3, 8, 9. Yet, reported human cases of LPAIV and HPAIV infections have repeatedly shown the possibility of direct IAV transmission between avian and human hosts  21, 22  , and therefore, it is of importance to investigate the zoonotic potential of AIVs. The current study presents data comparing the attachment pattern to human and pig tissues, of a panel of avian viruses together with an evaluation of the distribution of different SA linkage conformations in the target tissues. In addition, the glycan receptor tropism of the analysed viruses was evaluated.
Acknowledgements The authors want to thank  Drs Debby van Riel  and  Thijs Kuiken  for virus labelling and  Victor Lorente Leal  for part of the virus histochemistry stainings. The authors would also like to thank the Dept. of Pathology at the  Uppsala University Hospital  for providing the human tissue specimens and the pig abattoir for donation of pig tissues. Additionally, the authors would like to thank  Professor Nicolai Bovin  and  Carlo Unverzagt  for generous support of glycans. Funding for this study was obtained by the  Swedish Research Council  ( 2015-03877  and  2016-02596 ) and the  Knut and Alice Wallenberg Foundation. Dr. Munster  is supported by the  Intramural Research Program  of the  National Institute of Allergy and Infectious Diseases (NIAID) ,  National Institutes of Health (NIH).
This technique has been used successfully on more than 100 dugongs since the 1980s  [33, 39]. Procedures for capturing, handling and attaching the tracking units followed Sheppard et al. [18]  in Moreton Bay and New Caledonia or Fuentes, Cleguer  [40]  in Torres Strait. Details of individual dugongs are provided in S1 Table. The GPS satellite transmitters were programmed to communicate with satellites every hour (25 animals) or 30 min (three animals deployed in Moreton Bay) (S1 Fig). The TDRs recorded depths every 1-2 s (Mk9) or 75 s (MiniPAT). Each MiniPAT was programmed to transmit the data to the satellites upon detachment after 60 days or upon earlier detachment. The Mk9 units were recovered for data retrieval. The GPS location data were retrieved from the Argos web site and decoded using the Telonics Data Converter; the Wildlife Computers portal was used to obtain the MiniPAT data.
We used only high-quality location data: GPS fixes (± 2 to <10 m) and resolved Quick Fix Pseudoranging (QFP) fixes (± <75 m) for further analysis. The dive records from the Mk9 units were decoded by HexDecode. The sources of error in the depth records included: 1) drift in zero-reading; 2) wave action; 3) the depth resolution of the depth sensors; 4) the location of the depth sensors attached to the animals; and 5) the angle of animals' body. Thus the depth records were zero-offset at each 10-min interval using custom software  [41]. We assumed that the depth records collected by the Mk9 TDRs and MiniPATs were equivalent because: 1) both devices were made by the same manufacturer and had 0. 5 m depth sensor resolution, 2) the accuracy of the depth records were tank-tested at a local 15m deep aquarium, and 3) the reliability of the depth profile provided by the maximum memory capacity of the MiniPATs (60 days) was confirmed by sub-sampling the depth records collected by the Mk9 TDRs assuming that the depth records were collected at the same frequency as the MiniPATSs (75sec) using the 1 sec Mk9 TDR sampling frequency as the standard.
Acknowledgments Funding was provided by  James Cook University , the  Australian Marine Mammal Centre , the  National Environmental Science Program Tropical Water Quality Hub  and the  Torres Strait Regional Authority, ZoNeCo, AAMP (Agence des Aires Marines Protegees) , the  New Caledonian Dugong Technical Committee  under the 2012-2015  Dugong Action Plan  and an anonymous donor. Thanks to the  Torres Strait Regional Authority  and the  Mura Badulgal Representative Native Title Body Corporate  for their permission to conduct the tagging project in their sea country,  Lionel Gardes  and  Damien Grima  from the  Agence des Aires Marines Protegees ,  Mark Hamann  and  Shane Preston  from  JCU  and all the members of aerial survey and dugong tagging teams. Lachlan Marsh  developed the  Python program  to estimate the standard errors for abundance estimates.
Results Crystallization of the intact HAP2 ectodomain. The crystals used to determine the previously reported HAP2 X-ray structure grew only after limited proteolysis of the HAP2 ectodomain  (Fedry et al. , 2017). Here we screened for crystallization conditions of the unproteolysed HAP2 ectodomain in complex with HAP2-specific monoclonal antibodies (Mabs) obtained previously  (Fedry et al. , 2017). The complex with the single chain variable fragment (scFv) of one of these antibodies resulted in crystals in the hexagonal space group P6 3 22 diffracting to 2. 6Å resolution (Figure  S1 ). Structure determination by molecular replacement using the atomic model of HAP2, PDB code 5MF1, resulted in an electron density map of HAP2 displaying 1 protomer per asymmetric unit (i. e. , with the trimer axis coincident with a crystallographic 3-fold axis) and 80% of the volume occupied by solvent (Table  1 ).
Crystallization and Structure Determination Crystals were grown using the sitting drop method at 293K by mixing HAP2-scFv A20 protein solution in a ratio 1:1 with reservoir solution containing 0. 2M LiSO 4 , 0. 1M Tris-HCl pH 8. 5 and 25% w/v PEG 5000 MME. Small hexagonal plates obtained after 5 days were cryoprotected with reservoir solution containing 15% glycerol and plunged in liquid nitrogen. Data collection was carried out at the SOLEIL synchrotron (St Aubin, France). Data were processed, scaled and reduced with XDS  (Kabsch, 1988)  and AIMLESS  (Evans and Murshudov, 2013). Diffraction anisotropy was corrected with DEBYE and STARANISO programs using the STARANISO server (http://staraniso. globalphasing. org/). These programs perform an anisotropic cut-off of merged intensity data, a Bayesian estimation of structure amplitudes and apply an anisotropic correction to the data.
The HAP2 structure was determined by molecular replacement using PHASER and the coordinates of the previous crHAP2e ectodomain (PDB accession code 5MF1) as search model. The model was corrected and completed using COOT  (Emsley et al. , 2010)  and the corrected anisotropic amplitudes were used for model refinement in BUSTER  (Bricogne et al. , 2010). The stereochemical properties of the model were validated with MolProbity  (Chen et al. , 2010).
Acknowledgements Funding for this project was provided by the  ERC Advanced grant CelCelFus  (number  340371 ) to FAR, as well as recurrent funding from  Institut Pasteur  and the  CNRS. JF had a PhD fellowhsip from  Ecole Polytechnique AMX. We thank  I. Fernandez  for technical help and discussion;  W. J. Snell  for helpful discussions and for testing the effect antibodies against HAP2 on C. reinhardtii gamete fusion in vivo; Ahmed Haouz  and staff of the  Pasteur crystallogenesis  facility as well as the staff of Proxima-1 and -2 at the SOLEIL synchrotron for help during crystallization screening and diffraction data collection.
cell cytotoxicity Measurement Cell cytotoxicity was measured through the quantification of lactate dehydrogenase (LDH) ratio in cell supernatants versus cell lysates (PBS/Triton X-100 (0. 8%)). This was performed in 96-well plates (Costar) and absorbance was measured at 490 nm (kit CytoTox96 ® Non Radioactive Cytotoxicity Assay kit (Promega) in a Multiskan Ascent (Thermo Scientific) plate reader). Data were treated using the Ascent Software (Version 2. 6), with % cytotoxicity = {OD of supernatant/(OD of supernatant + OD lysate)} × 100.
5. 1). The mass tolerance was set to 7 ppm for precursor ions and 0. 02 Da for fragments. The maximum number of missed cleavages was limited to two for the trypsin protease. The following variable modifications were allowed: oxidation (Met), phosphorylation (Ser, Thr), acetylation (Protein N-term). The NCBInr database (2016) with the Mus musculus and the P. a taxonomies were used for the MS/MS identification step. Peptide identifications were validated using a 1% False Discovery Rate (FDR) threshold calculated with the Percolator algorithm. Protein abundance variations were measured according to the Hi-3 label-free quantification method and validated if their calculated ANOVA p-values were under 0. 05. Fold increase expression (cut-off ≥ 2, p ≤ 0. 05) between individual conditions were reported in Excel sheets (see Supplementary Material).
Mice experiments Six-to ten-week-old C57BL/6JRj WT mice were obtained from Janvier (Le Genest-Saint-Isle, France). Tlr4-/-and Tlr5-/on C57BL/6JRj background were bred in house, in a specific pathogen-free facility (#A59-350009, Institut Pasteur de Lille) and experiments complied with national regulations and ethical guidelines. statistics Statistical analysis of the differences observed between groups (in vivo) and experimental conditions (ex vivo and in vitro) was performed using either a non parametric test of variance (Kruskal-Wallis and Dunn's posttest) or using a parametric test (one-way ANOVA followed by the appropriate "multicomparison" posttests). Data were analyzed using the Prism ® (Graphpad Prism Version 6. 03) software. In addition, survival curves were analyzed with the Log-rank (Chi 2 ) test.
FigUre6| Venn Diagrams of total hits recovered in the supernatant of MPI cells, either non-infected (Control) or infected with WTp0-or ΔLasBp0-PAO1. MPI cells were either left un-infected (MPI Control, n = 2) or infected (moi 1) with WTp0-(n = 3) or ΔLasBp0-PAO1 (n = 3) in serum-free medium. After 4 h, supernatants were recovered, concentrated and analyzed by mass spectrometry (see Materials and Methods in Supplementary Material). For the identification step, all MS and MS/MS data were processed with the Proteome Discoverer software (Thermo Scientific, version 2. 1) coupled to the Mascot search engine (Matrix Science, version 2. 5. 1). The NCBInr database (2016) with the Mus musculus and the Pseudomonas aeruginosa taxonomies were used for the MS/MS identification step. Peptide identifications were validated using a 1% False Discovery Rate threshold calculated with the Percolator algorithm.
Data collection After informed consent and enrolment, baseline data will be collected. This will include demographics, morbidity, anthropometry (weight, height, MUAC, skinfolds), biochemical samples (blood, stool), dietary data (breastfeeding, food frequency and dietary diversity), and developmental milestone achievement. Participants may still be excluded if they are malnourished (MUAC< 115 mm, WHZ score < -3) or severely anaemic. Participants in the intervention groups will then be provided with a one-month supply of the food to which their site has been allocated. Thereafter, participants will be provided with food on a monthly basis, and they will continue to consume the food over a six-month period. Data will be collected monthly (anthropometry, morbidity, developmental milestones), and/or at endline (biochemical).
Anthropometric data Anthropometric measurements will include weight to the nearest 0. 1 kg, recumbent length to the nearest 0. 1 cm, skinfolds to the nearest 1 mm, and MUAC to the nearest 1 mm. Weight will be measured with a SECA scale, length will be measured on wooden UNICEF height boards, MUAC will be measured with a flexible UNICEF insertion tape and skinfolds will be measured with a standard caliper (Holtain, United Kingdom). Anthropometry will be measured monthly. Children with MUAC < 115 mm and WHZ < -3 at enrolment or at any time during the study will be excluded from the study and referred to the health centre for treatment.
Statistical analysis All data will be double-entered in Excel. Data will be analysed in the statistical software required by the PhD candidates' respective universities. Thus, anthropometric data will be analysed by one PhD candidate in the statistical software STATA version 13. 1, and biochemical and cognitive/developmental data will be analysed by another PhD candidate in SPSS and R. Since most of the measures being taken are repeated on a monthly basis, the assumption of independence is not satisfied. Therefore, a mixed effect model, which is appropriate for repeated measurements, will be used. Predictor variables will be checked for normality and linearity, and manipulated and recoded as necessary. Outcome variables will be manipulated and recoded if necessary to deal with non-normality and/or for easier interpretation.
Ethics and consent Ethics approval was received from the University of Queensland Medical Research Ethics Committee and the National Ethics Committee for Health Research (NECHR) in Cambodia. Written informed consent will be obtained from all the caregivers or parents of the participating children before recruitment into the study. Based on the experience of similar trials  [20, 22, 28, 45] , and given the inclusion and exclusion criteria, no harm is expected from trial participation. However, morbidity data will be collected every month, and this will record any harm (nausea, etc. ) that could come from participation in the trial.
Long Non-Coding RNA Microarray Analysis Total RNA extracted from 12 PTC samples and four normal thyroid tissues was hybridized to the Human LncRNA Microarray Version 3. 0 of the Arraystar company (Rockville, MD, USA). This system is based on probes able to recognize specific exons or splice junction of each lncRNA. The expression analysis was performed by comparing the average of the expression levels observed in 12 PTC samples with the average of the expression levels observed in four normal thyroid tissues. Bioinformatic analyses were performed by the Arraystar company based on the following databases: Refseq, UCSC, GENCODE, RNAdb, NRED, UCR, lincRNA catalogs  [35, 36]  (https://www. arraystar. com/humanlncrna-expression-microarray-v4-0/) (Table  S2 ).
Flow Cytometry Analysis For cell cycle analyses, cells were processed as previously described  [39]. Briefly, cells were trypsinized and, after washing in PBS, fixed in 70% ethanol. After a centrifugation at 1200 rpm for 10 min at 4 • C, cells were treated with 50 µg/mL propidium iodide and 25 µg/mL ribonuclease A in PBS for 20 min at RT safe of light. For each measurement 10,000 events were analysed using a FACScanto II flow cytometer (Becton Dickinson, San Jose, CA, USA) and then cell cycle data were analysed with the ModFit LT 2. 0 software (Verity Software House, Topsham, ME, USA) in a semiautomatic analysis procedure. The ModFit algorithm was finally used to analyse the files obtained, calculating the percentage of cells in each cell cycle phase.
Statistical Analysis GraphPad Prism software was used for statistical analyses. t-test and Anova tests were used to evaluate the statistical significance of the obtained data, while gene expression correlation was evaluated through non-parametric Spearman's Rank correlation coefficient. When Anova test was significant (p < 0. 05), we determined the differences between groups using Bonferroni post-test. In all the experiments, the significance was assessed for p < 0. 05. Data are reported as mean values ± standard error of mean (SEM).
Supplementary Materials: The following are available online at http://www. mdpi. com/2072-6694/10/5/146/s1, Figure  S1 : LncRNA expression analysis in additional PTC samples. qRT-PCR analysis to evaluate the expression of RP11-230G5. 2, DLEU2 and SLC26A4-AS1 in additional PTC samples. Results are reported as relative expression ± SEM compared to the mean of three normal thyroid samples set equal to 1; Figure  S2 : Expression analysis of RP5-1024C24. 1 and MPPED2 in thyroid carcinoma cell lines. qRT-PCR performed on papillary (TPC-1, B-CPAP), follicular (WRO), anaplastic (FB-1 and FRO) thyroid carcinoma cell lines and three normal thyroid tissue samples (NT1, NT2, NT3). Data are reported as 2 -∆Ct values ± SD; Figure  S3 : Analysis of RP5-1024C24. 1 and MPPED2 expression in TPC-1-and FRO-transfected cells.
qRT-PCR analysis performed on TPC-1 and FRO cell lines stably expressing RP5-1024C24. 1 (A), MPPED2 (B) or carrying the corresponding empty vector (EV), and three normal thyroid tissue samples (NT1, NT2, NT3). Data are reported as 2 -∆Ct values ± SEM; Table  S1 : PTC samples used for lncRNA microarray; Table  S2 : Whole list of lncRNAs deregulated in PTC vs. NT; Table  S3 : List of primer sequences used for qRT-PCR analyses. Author Contributions: R. S. contributed to the scientific planning and experimental execution, the interpretation and analyses of the data and the manuscript drafting; S. P. contributed to the experimental procedure and analyses of the data; P. S. and M. D. -P. contributed to samples collection and IHC analyses; D. D. , A. F. and R. C. C. P. contributed to cloning procedure and migration experiments; M.
Acknowledgments: This work was supported by grants provided by: " Progetto di Interesse Strategico Invecchiamento (PNR-CNR Aging Program )  PNR-CNR 2012-2014 " and " CNR Flagship Projects (Epigenomics-EPIGEN) ". Romina Sepe  was granted with a fellowship provided by " Fondazione Adriano-Buzzati Traverso ", 2016. We thank  Giuseppina Ippolito  and  Giulia Speranza  ( IEOS-CNR ) for administrative support and  Salvatore Sequino  ( DMMBM, University of Naples "Federico II" ) for technical support.
Differences in the average level of quality of life in groups of people due to their physical activity levels were assessed with ANOVA (means, Kruskal-Wallis test, Dunn's post hoc multiple comparison test) and multinomial logistic regression analysis. The level of statistical significance was set at α < 0. 05. The impact of physical activity levels on respondents' quality of life was estimated using Eta-squared (η 2 ). The effect sizes were categorized into small η 2 = 0. 01, medium η 2 = 0. 06, and large η 2 = 0. 14. All statistical calculations were made with the use of IBM SPSS Statistics 20 (Armonk, NY, USA).
Notes A related application of percolation theory has been proposed to describe innovation dynamics in a technology space rather than a social network (Silverberg & Verspagen ) The simulation model, called "PercolationPrice", is implemented in NetLogo. The code can be downloaded from the OpenABM database following the link: https://www. openabm. org/model/5955/version/1/view. The results presented here are obtained from batch simulations experiments, by running the model a number of times for di erent values of the product price. The batch simulation experiment in NetLogo is set with the BehaviorSpace function. The exact di usion size depends on the number of seeds, but the critical transition threshold does not. Simulations with seeds yield the same patterns. Simulations with less than seeds are less informative, since the variability of results is too large, with a standard deviation near 100%.
Theoretical predictions There are five theoretical calculations used in this study: three MC event generator predictions, and two predictions using analytic resummation merged with fixed order MC simulations. The three MC event generators used in this study are PYTHIA8, HERWIG++, and POWHEG. Version 8. 212 of PYTHIA8  [20]  is used with underlying event tune CUETP8M1  [21]  and NNPDF 3. 0 parton distribution functions (PDFs) NNPDF30 lo as 0130  [22]. The PDF4LHC15 NLO 100 meta-PDF set is used for uncertainty estimation, along with the PYTHIA8 generator. We use the LHAPDF  [23]  software package for this purpose, following the recommendations of Ref. [24]. The HERWIG++ version 2. 7. 0 generator  [25]  is used with tune CUETHS1  [21]. The HERWIG++ simulation sample is used for systematic uncertainty estimation and for generator-level comparisons, as it has a physics model that is different from PYTHIA8 in various aspects like parton showering, hadronisation, multiple-parton interactions, and the set of model parameters tuned to data.
The second level, known as the high-level trigger (HLT), consists of a farm of processors running a version of the full event reconstruction software optimized for fast processing, and reduces the event rate to around 1 kHz before data storage. The event reconstruction is based on the CMS particle-flow (PF) algorithm  [35] , which includes information from all subdetectors, including charged-particle tracks from the tracking system, energy deposits in the ECAL and HCAL, and tracks reconstructed in the muon chambers. Particles in an event are reconstructed and identified as electrons, muons, photons, charged hadrons, or neutral hadrons. Charged hadrons associated with pileup vertices are removed from consideration. This method is referred to as "charged-hadron subtraction" (CHS)  [36]. In our dataset, the average number of pileup interactions per beam crossing is 14.