dataesr/scientific-paragraphs-categorization huggingface dataset:
PLASMA AND ACCELERATORS PHYSICS To understand the behavior of the plasmas in the next generation of tokomaks, like ITER, simulations are performed with the GYSELA code  (Grangirard & al. 2007 ), developed at CEA/IRFM Cadarache, with the goal to reduce the turbulences for improving performances in these machines. The GYSELA simulation performed in the framework of the Grands Défis CINES 2010 was the largest simulation ever realized on the ITER model. The simulation used 272 billion cells in the 5dimentional mesh and had run one month on 8192 processors of the Jade machine in CINES. The code used 27GB by node and generated more than 6TB of data. Fig. 9  represents in 3D the electrostatic potential fluctuations inside the torus. The EVEDA (Engineering Validation and.
IVAPP2015-InternationalConferenceonInformationVisualizationTheoryandApplications Engineering Design Activity) linear accelerator is being studied and constructed in Europe, to be installed in Japan. It accelerates Deuteron particles to the energy of 9 MeV. It is the full scale prototype of the first phase of the IFMIF (International Fusion Materials Irradiation Facility) project. IFMIF  (Thooris & al. 2014 ) is a Europe-Japan joint project aiming at constructing an accelerator-based neutron source, the world's most intense one, dedicated to study materials that must withstand the intense neutron flux coming from the fusion plasma of future tokamaks. Simulations were made with a million particles, which need some tens of hours computing, using TraceWin, a beam transport code developed at IRFU.
CONCLUSIONS If the development of the SDvision visualization code was basically motivated by the need of analyzing the results (and sometimes detecting computing bugs) from huge amounts of data with complex structures, the production, thanks to the interface, of images, videos and stereoscopic movies in the domain of astrophysics simulation have caused a lot of requests for communication with the general public. Several movies generated by SDvision have been screened in exhibitions, museums and in our 3D room for visitors at Saclay. A new dedicated room has been equipped in our laboratory for the projection of astrophysical stereoscopic movies generated. Due to the increasing production of data simulations and demand on analysis of bigger and bigger surveys catalogues, an effort is now in progress to speed up the code for images generation, especially with the use of OpenGL shaders.
Material and methods Animals and data recorded A total of 12 Holstein sires widely used were introduced in this study. Their EBV for fertility was well known (reliability ⩾ 0. 95). In France, the bull fertility EBV is a combination of the following three variables: heifer conception rate, cow conception rate and calving to first-service interval. The EBV for cow conception rate is estimated by calving ratethat is, presence of a calving after an insemination in a period corresponding to the gestation length of the breed  (Barbat et al. , 2010). All AIs of the daughters during the postpartum period are taken into account. In this study, the 2010 edition of the bull EBVs (INRA and Institut de l'Elevage) was used. This EBV is expressed in units of genetic standard deviation (σ g = 7 points of conception rate; Barbat et al.
, 2010) relative to 0 being the phenotypic value of a female reference population (cows registered in the national database and born between 2002 and 2004 for the 2010 EBV). Bulls' EBVs ranged from -0. 7 to 1. A clinical examination was carried out by technicians on the day of AI to exclude cows with metritis or pyometra (abnormal vaginal discharge before or after uterine palpation). The initial survey group of females consisted of 4239 daughters of the 12 bulls in their first or second lactation. After exclusion for clinical genital disease at AI, missing data or doubtful pregnancy status at 90 days after AI, a sub-sample of 3508 cows was included for the final analysis. These cows were maintained in 984 herds and the final number of completely phenotyped cows per progeny group ranged from 93 to 516 per sire (Table  1 ).
The percentage of eliminated cows did not differ between the progeny groups. Phenotypes were determined after first service in cows that calved from September 2006 to September 2010. For each cow, the following data were recorded: region and herd of origin, date of calving, lactation rank, date of first service, date of return to oestrous and/or date of second AI, milk yield, milk fat and protein contents recorded by the milk board once a month during the first 3 months of lactation. Milk samples were collected following oestrous detection or first AI and 18 to 25 days later. Transrectal ultrasonography was performed to identify the presence of a living embryo at days 45 and 90 after the first AI. Sire effect on embryonic death in Holstein cows Progesterone assay Milk samples were collected at the beginning of the morning milking session from the four mammary quarters into a plastic tube containing a Bronopol and Natamycin pellet (8 mg Bronopol and 0.
MP and MF contents were introduced in the multivariate models as quantitative variables, as well as the MF/MP ratio and the MF-MP difference. Relationships between variation factors and dependent variables were tested in a first step by univariate analysis using the χ 2 -test with SAS ® 9. 2 software (SAS Institute Inc. , Cary, NC, USA). All variables associated with the dependent variables at a threshold of 20% were subsequently introduced with their interactions in multivariate mixed logistic regression models using the GLIMMIX procedure of SAS. The random herd effect was introduced in all models (3. 6 ± 2. 1 cows followed per herd) and was applied on the  Ledoux, Ponsart, Grimard, Gatien, Deloche, Fritz, Lefebvre and Humblot intercept  (Witte et al. , 2000). The multivariate models were simplified step by step to retain only variables associated with dependant variables at the threshold of 10%.
Acknowledgements This study was supported by the  French National Agency for Research (ANR-GENANIMAL  and the  Apis Gene GIS. The authors address their special thanks to their correspondents in AI centers:  Didier Berthelot  (SORELIS),  Patrick Bonnand  and  Aurélien Michel  (AMELIS),  Jacky Martin  (ELIACOOP),  Alain Chevallier ,  Jean-Luc Viala  and  Christian Nicolas  (GENOE),  Jean-Michel Philippot (URCEO), Hervé de Préaumont (CIA l'Aigle), Pierrick Drevillon (CECNA) ,  Pierre Gigant  and  Lionel Simerman  (ELITEST),  Brahim Khireddine  (COOPELSO),  Philippe Gisbert  and  Gilles Mally  (GENESIA),  Olivier Sourbé  ( Groupe Altitude ),  Philippe George  ( CIA Meurthe et Moselle ), the trainees  Julie Goffin ,  Pierre Vergiat ,  Benoit Mouchard  and  Anthony Groualle. They also acknowledge the technicians and the farmers for their active and persistent co-operation and  Loic Desquilbet  for help in statistical analysis.
Other notable difference is the existence of two different quaternary states of SCO0520, a TTR family regulator from Streptomyces coelicolor (PDB: 2Q24) and the propensity of SCO0520 oligomerize in solution  [17]. Different DNA binding modes may also be influenced by different ligands which bind to the same ligand binding cavity of LBD. Recent crystal structures of DesT in complex with palmitoyl-CoA or oleoyl-CoA showed that tails of both FA bind deep within the hydrophobic ligand binding cavity of DesT  [18]. However, binding modes of palmitoyl-CoA and oleoyl-CoA are different and they exert opposite effects on the DNA binding properties of DesT. Upon binding, each FA induces a different set of conformational changes that dictate the structural and functional status of the protein either to be in "repressive" or "de-repressive" state.
Crystallization, structure determination and refinement Size-exclusion purified Fad35R-SeMet was used for crystallization. We screened for crystallization conditions using Nextel and ammonium sulphate screening suites (Nextal Classic suite-96, Qiagen Sciences, Maryland USA). Using the sitting drop method, 1μL of protein (30 mg/mL) stock was mixed with 1μL of reservoir solution and the mixture was equilibrated against 80 μL of precipitant solution. Diffraction quality Fad35R-SeMet crystals grew in two weeks and the optimum crystallization condition was found to be the following; 0. 2 M Tris-sodium citrate, 0. 1 M Tris-HCl, pH 8. 5, 30% (v/v) PEG400. We used single wavelength anomalous dispersion (SAD) phasing method for resolving the structure. Fad35R-SeMet crystals diffracted to 3. 4 Å and the SAD dataset was obtained at Se edge (λ = 0.
9775Å) on a MARCCD 225 detector at the BM14 beamline of the European Synchrotron facility (ESRF, France). The oscillation angle was kept as 1°, the exposure time was 40 sec per frame, and the detector distance was 385 mm. The peak dataset were then indexed, integrated, and scaled using the HKL2000 suite  [20]. Data collection statistics are shown in Table  1. Each monomer of Fad35R consists of three SeMet residues and the positions of the Se atoms were determined used SHELXD program (correlation coefficient, CC all/ weak: 53. 81/27. 55; Patterson figure of merit, PATFOM 15. 01)  [21]. The initial phases were computed and partial model was built with SHELXE as part of the HKL2MAP package  [22, 23]. The resulting phases were of poor quality and the electron density was not continuous to trace the entire molecule.
However, the model quality was improved by the iterative manual model building using COOT and followed by model refinement using the REFMAC  [24, 25]. The model was further improved by several rounds of SAD phasing using PHASER  [26] , phase combination using SIGMAA  [27]  density modification using PIRATE  [28]  and iterative model building with BUCCANEER  [29]. At this stage, the phases were improved and electron density map was continuous to trace the missing residues in the model except for the N-terminal residues, 1 to 23. The automatic model building was not successful in building the entire molecule due to the limitation of resolution. The remaining part of the structure, including side chains were modeled manually. The model was refined using the program REFMAC5 and iterative manual rebuilding of the model is performed in COOT.
Two glycerol molecules were identified and included in the refinement. The Translation, Libration and Screw-rotation (TLS) displacement parameters were determined for the one group for each molecule and TLS-restrained refinement was performed  [30]. For the final model, the R work is 20. 8% and R free is 25. 6%. The structure has good stereochemistry as indicated by program PROCHECK  [31]  and final refinement statistics are shown in Table  1. The refined model of Fad35R and structure factors were deposited in the Protein Data Bank under the accession code 4G12. Surface area was calculated with the PDBe PISA server  [32].
Dynamic light scattering studies Dynamic light scattering studies were performed using Beckman Coulter (delsa Nanose) instruments equipped with 512 channels. He-Ne laser used with 45 mwatt power and angle of scattering was 165°. Measurements were performed with 100 μm aperture using glass cuvette containing 1. 8 mL of sample in a cell holder equipped with a thermostat. The autocorrelation function of the scattering data was analyzed using the following equation to obtain the translation diffusion coefficient of the protein. GðtÞ ¼ B þ A expðÀ t t Þ ð eq1Þ Where τ is the auto correlation time and it is defined as t ¼ 1 2Dq 2 ðeq2Þ Where D is the diffusion coefficient and q is the scattering vector.
Sedimentation velocity Sedimentation velocity experiments were performed using an Optima XL-I analytical ultracentrifuge equipped with absorbance optics with an An50Ti rotor (Beckman Coulter). Gel filtration purified Fad35R was extensively dialyzed in the standard buffer (50 mM Tris-Cl, pH 8. 0, 300 mM NaCl, 10% glycerol, 0. 1 mM DTT) and protein filtered with 0. 22 μM was used. Sedimentation velocity studies were carried out at 45,000 rpm at 20°C using a two-channel charcoal-filled centerpiece with sapphire windows. Velocity data were collected by scanning samples at a wavelength of 280 nm with a spacing of 0. 003 cm and an average of 3 scans per step. The partial specific volume, solvent density and viscosity were calculated using SEDN-TERP  [33]. The molecular weight for Fad35R was obtained by fitting the sedimentation data with Sedfit, freely available analysis software  [34].
Structure determination and quality of the structure Fad35R consists of 215 amino acid residues (Genbank accession number CAB08924. 1). The BLAST search reveals that the protein has conserved domains of the TTRs but overall sequence identity is low (~18%). Therefore, we determined the crystal structure of Fad35R by the SAD method, and refined it to 3. 1 ). With the exception of the N-terminal residues 1-24, for which no electron density is observed, the polypeptide chain of each monomer can be unambiguously traced from the N-terminus to C-terminus (Fig 1A  and 1B ). The disordered first 24 residues of N-terminal which immediately precede the conserved DNA binding helix-turn-helix (HTH) motif may likely to be ordered upon DNA binding as observed in the structure of SimR  [15]. During refinement, unaccounted electron density was observed at the predicted ligand binding pocket.
Expression of CD46, CD150 and nectin-4 by MPM and healthy primary cells We measured the expression of known MV receptors (CD46, CD150 and nectin-4) on the surface of MPM and healthy primary cells. The majority of MPM cells expressed higher levels of CD46 than healthy primary cells (Figure  3A-3B ). However, no statistical difference was observed between MPM cells sensitive or not to MV infection (Figure  3B ). We did not detect any expression of CD150 or nectin-4 (Supplemental figure  2 ), which are receptors for the pathogenic as well as vaccine MV strains  [14, 15, 24]. Altogether these data show that a majority of tumor MPM cell lines overexpress CD46 as the only known MV receptor and that sensitivity of these cells to MV infection is not related to CD46 expression.
IFN-α and IFN-β inhibit MV replication in MPM cell lines sensitive to MV replication In the last set of experiments we tested the effect of type I IFN (IFN-α and IFN-β) on MV replication in sensitive tumor cell lines. We first measured the expression of IFNAR1 and IFNAR2 in all MPM cells lines. A low expression was found on the surface of all tumor cell lines (data not shown). We then exposed the fifteen MPM cell lines sensitive to MV to increasing amounts of IFN-α and IFN-β and measured MV replication using MV-ch (Figure  7 ). MV replication was reduced in a dose-dependent manner in all tumor cell lines. Interestingly, the inhibition was lower in three out of the four MPM cell lines that express IFN-α, IFN-β and Mx1 constitutively (Meso34, 36 and 37), whereas the inhibition was more profound in tumor cell lines that did not develop a type I IFN response in the presence of the virus, such as Meso31, 47, 76, 225 and 11.
DISCUSSION In this study, we measured the sensitivity of a large panel of human MPM tumor cell lines and of different types of healthy cells to the oncolytic activity of the Schwarz vaccine strain of MV. We found that fifteen out of twenty-two MPM tumor cell lines are sensitive to MV replication and cytopathic effect, whereas replication was limited or absent in the four types of healthy cells (fibroblasts, mesothelial, bronchial and endothelial cells) as well as in the seven remaining MPM tumor cell lines. Our data also show that the sensitivity of tumor cell lines is not correlated to overexpression of the MV cell receptor CD46, contrary to what has been described in the literature  [3, 7]. Nevertheless, the virus needs CD46 to enter the cells. In a search for factors that affect the sensitivity of MPM tumor cells to MV oncolytic activity, we studied the innate antiviral type I and III IFN immune response of these cells.
ACKNOWLEDGEMENTS We thank  Philippe Hulin  and the cellular and tissular core facility of  Nantes University (MicroPiCell ) for their expertise in video microscopy. We also thank  Juliette Desfrançois  and the core facility of flow cytometry (Cytocell). This work was supported by  "la Ligue Régionale Grand Ouest contre le Cancer  (CSIRGO :  CD16 ,  CD22 ,  CD44 ,  CD49 ,  CD72 ,  CD79  and  CD85 )", " La Ligue Nationale contre le Cancer ", "ARSMESO44 association", "la  Fondation du Souffle et le Fonds de Dotation Recherche en Santé Respiratoire", "la Fondation pour la Recherche Médicale (FRM) ", and "la Fondation ARC pour la recherche sur le cancer".
Clinical assessments Socio-demographic characteristics, age at onset, number of hospital admissions and personal history of suicide attempts were recorded on the basis of both medical notes and data extracted from the DIGS. Patients were also assessed for lifetime cannabis and other substance use, and were asked to state precisely when use had begun, its duration and the mode of consumption. Patients were assigned to the "pre-onset CUD" group if they met lifetime DSM-IV-R criteria for cannabis use disorders (cannabis abuse or dependence) before or at the time of schizophrenia onset. Otherwise, they were assigned to the "no pre-onset" CUD group. Patients with other substance use disorders were excluded with an exception for tobacco smoking. Age at onset of schizophrenia was defined as the age at which the patient first met DSM-IV-R criteria for schizophrenia, according to medical case notes and interviews.
Assessment of symptom dimensions and OCCPI ratings The Operational Criteria Checklist for Psychotic Illness (OCCPI)  [39]  consists of 90 items assessing clinical characteristics and symptoms used in a wide range of operational diagnostic systems. We chose to use the OCCPI because (1) the presence of symptoms is recorded categorically; (2) a wide range of psychotic symptoms are recorded; (3) it is designed to assess symptoms that have occurred at some point in the subject's life (lifetime perspective); (  4 ) it records affective symptom data and (  5 ) it can make use of data from different interviews. The OCCPI was completed, for the lifetime occurrence of symptoms by two raters using the DIGS and the information from interviews recorded in case notes. The inter-rater reliability (Kappa) of factorial scores was assessed for 30 test cases and was found to be very good [Kappa = 0.
Data analyses Principal component analysis (PCA) The aim of a principal component analysis is to reduce the number of variables used to describe a sample, by choosing linearly uncorrelated variables called principal components. All items defining a single symptom (n = 48) were chosen and coded dichotomously. We performed a principal component analysis on 28 symptoms of the OCCPI (20 symptoms were excluded due to a lack of variance or >10 % missing data). We extracted the initial factors and then performed an orthogonal rotation by the VARIMAX method. The number of meaningful factors was determined by the scree plot. For each of the symptom dimensions identified, OCCPI items with a loading greater than 0. 4 were used to construct a quantitative scale. Subjects were scored by calculating the proportion of items present for each symptom dimension.
The rationale for our decision was driven by retrospective design. Indeed, retrospective self-report of cannabis use (e. g. by reporting daily dose) might be highly impacted by recall and declaration biases. To improve data accuracy, we used a structured assessment tool that has a very good reliability to assess CUD  [64]. The second limitation is that we cannot rule out an effect of medication use on the clinical profiles of subjects. Thirdly, our dimensional approach did rely on a principal component analysis that did not distinguish separate negative and disorganized dimensions in our sample. We therefore cannot exclude the possibility of an association between pre-onset CUD and one of these dimensions. Finally, in our PCA, the extracted components explained 46 % of the variance in the symptom data being recorded.
This membrane-associated complex is composed of the TssL and TssM inner membrane proteins and of the TssJ outer membrane lipoprotein  [8] [9] [10] [11] [12] [13]. The TssM and TssL proteins interact and stabilize each other and share homologies with the Type IVb secretion system IcmF and DotU subunits respectively  [12, 14, 15]. In enteroaggregative Escherichia coli (EAEC), TssM (accession number: EC042_4539; gene ID: 387609960) is a 1129-amino-acid protein anchored to the inner membrane by three transmembrane helices and bearing a large ~750 amino-acid periplasmic domain (aminoacids 386-1129). The C-terminal extremity of the TssM periplasmic domain interacts with the L1-2 loop of the TssJ lipoprotein with a K D of 2-4 μM  [11]. By combining interactions with inner membrane and outer membrane-associated components, the TssM protein crosses the cell envelope and is therefore central to the T6SS membrane complex.
Nb25 disrupts the TssMp-TssJ interaction in vitro We hypothesized that if nb25 and TssJ share the same TssM binding site, nb25 should disrupt the TssM-TssJ complex. We therefore analyzed the effect of nb25 on the stability of the TssM-TssJ complex. Competition experiments were performed by incubating the purified TssMp-TssJ complex with an excess of nb25, prior to analysis by gel filtration. Three peaks were observed on the chromatogram (Fig. 4 ). Analysis of the peaks by SDS-PAGE (Fig. 4 , inset) showed that peak 1 (~90 kDa) contained TssMp and nb25 (theoretical weight of the TssMp-nb25 complex = 98 kDa), while peak 2 (~18 kDa) contained TssJ (theoretical      weight = 17 kDa) and peak 3 (~14 kDa), the excess of nb25 (theoretical weight = 14 kDa). These data confirm that nb25 binds to TssMp and chases TssJ from the pre-assembled TssMp-TssJ complex.
Nanobodies structure determination Crystallization screening experiments were performed with several commercial kits. The nanodrop crystallization experiments were performed in Greiner plates. The reservoirs of the Greiner plates were filled up using a TECAN pipetting robot, while the nano-L drops were dispensed by a Mosquito robot using nano-crystallization protocols  [37]. All crystallization experiments were performed at 293K. Nanobody nb02 crystallized at 15 mg/mL in 100 mM sodium cacodylate (pH 6. 5), 25% w/v PEG 8000, 200 mM (NH 4 ) 2 SO 4. Nanobody nb25 crystallized at 15 mg/mL in 100 mM CHES (pH 10), 1 M K/Na tartrate, 200 mM Li 2 SO 4. Crystals were mounted in loops and soaked in their crystallization solution supplemented by 4M TMAO before cryocooling. Data collection of nb02 and nb25 were performed at synchrotrons ESRF (Grenoble, France) beamline ID29 and Soleil PX1 (saint-Aubin, France), respectively (Table  1 ).
Data were integrated with XDSME and scaled with XSCALE. The nb02 crystals belong to space-group P2 1 , with cell dimensions a = 50. 0, b = 48. 6, c = 52. 9 Å 3 , β = 118. 8°. Two molecules in the symmetric unit yield a Vm value of 2. 0 Å 3 /Da and 38% solvent. The nb25 crystals belong to space-group C222 1 , with cell dimensions a = 52. 0, b = 70. 9, c = 145. 7 Å 3. Two molecules in the asymmetric unit yielded a Vm value of 2. 20 Å 3 /Da and 45% solvent. These crystals diffracted to 1. 70 Å and 1. 38 Å resolution, respectively (Table  1 ). Molecular replacement was performed using MOL-REP  [38]  and nanobody structures with high sequence similarity to nb25 (PDB: 4KRP) and nb02 (PDB: 4HEP) as starting models. Refinement was performed using autoBUSTER  [39]  alternated with rebuilding with COOT  [40].
Acknowledgments We thank the ERSF and Soleil Synchrotron radiation facilities for beamline allocation,  Nicolas Flaugnatti  and  Laure Journet  for the development of the Sci-1-dependent antibacterial competition assay, the members of the Cascales and Cambillau research groups for helpful discussions,  Olivier Uderso ,  Isabelle Bringer  and  Annick Brun  for technical assistance, and  Amar Dissoir  for encouragements.