dataesr/scientific-paragraphs-categorization huggingface dataset:
D. 2. 3. Rabbits Rabbits are usually fed a pelleted diet (in the form of complete feedingstuffs) consisting of dried forages, cereals and vegetable proteins supplemented with minerals, vitamins and trace elements. Lebas and Renouf (2009)  reviewed diet formulations used in experimental studies: in 58 diets, cereals and cereal by-products (mostly wheat bran) cereals, cereal by-products (mostly wheat bran) and oilseed meals (mostly soybean meal and sunflower meal) were 18-20%, 18-20% and 16%, respectively. Dried lucerne is a particularly important ingredient in some diets, and has been included at levels of up to 65%  (Lebas and Renof, 2009). No data on levels of zearalenone in lucerne meal were available to EFSA, and therefore, this feed has not been included in the example diet used to estimate exposure.
IL-4 and IL-13 have been implicated as central mediators in atopic dermatitis. Clear clinical benefit has been found following the administration of the IL-4Rα blocking antibody dupilumab  [13]  in trials of patients with atopic dermatitis. Trials evaluating the role of IL-13-neutralisation alone in atopic dermatitis are on-going (NCT02347176, NCT02340234). Tralokinumab (CAT-354) is a fully human, IL-13-neutralising IgG4 monoclonal antibody with a very high affinity  [14]  for IL-13. Alanine scanning mutation analysis demonstrated that tralokinumab bound to IL-13 in helix D (PCT/GB2004/003059). Tralokinumab functionally neutralises IL-13 in a range of cell-based assays (IL-13Rα1:IL-4Rα interactions  [15] ) and has shown efficacy in moderatesevere asthma  [10, 11]. It is currently in pivotal phase 3 trials for moderate-severe asthma (STRATOS 1 and 2 [NCT02161757, NCT02194699]) as well as a phase 2 trial for atopic dermatitis (NCT02347176).
The structure of IL-13 in this complex is very similar to IL-13 in crystal structures from the Protein Data Bank (PDB) 3G6D  [16] , 4I77  [17]  and 4PS4  [18]. Superimposing these PDB IL-13 structures with that of the IL-13-tralokinumab complex reported here demonstrates high structural similarity with root mean square deviation (RMSD) values of 0. 5, 0. 45 and 0. 53, respectively. There is a small (20°) but n o t a b l e m o v e m e n t o f h e l i x D i n t h e tralokinumab-bound IL-13 structure, as compared with other structures such as the IL-13 NMR structure  [19]. The overall structure of the IL-13 four-helix bundle in the IL-13-tralokinumab complex is consistent with the previously solved crystal structures of IL-13. The structure of the tralokinumab  Fab fragment bound to IL-13 forms a classical immunoglobulin fold characterised by an antiparallel beta-sheet structure.
By minimising IgG capture levels and performing antigen titrations at higher flow rate, mass transport effects were minimised. The resulting improvements in data quality allowed us to fit the whole dataset to the simplest 1:1 model. There is a specific genetic variant of IL-13 that contributes to the risk of asthma, namely 2044A/G (amino acid R130 where the arginine residue is substituted with glutamine [Q130R])  [23] [24] [25]. In the structure described in this paper, we have investigated the location of this change in IL-13 with respect to the tralokinumab-binding site. The amino acid R130 is located at the C terminus of helix D (Fig. 7 ). As described earlier, helix D is part of the binding interface. However, the mutation at position R130 is located at the opposite side of helix D with respect to the side that engages antibody binding.
Cloning of tralokinumab mutants The QuikChange Lightning Multi Site-Directed Mutagenesis Kit (Agilent cat #210514) was used to introduce the following mutations into the tralokinumab for diffraction studies were obtained by introducing a seed stock derived from crystal clusters grown at 3. 5-4 M formate concentrations into pre-equilibrated drops over a reservoir of 2. 0-2. 5 M sodium formate at 293 K. Data from a number of crystals were collected, merged and scaled. The best crystals from across the range were used. Single needle-shaped crystals grow to approximately 700 μm in length over 3-4 days. Crystals were cryoprotected in 7 M sodium formate and then frozen directly into liquid nitrogen.
Crystal structure determination Data were collected on beam line i03 of the Diamond Light Source synchrotron (Harwell Science and Innovation Campus in Oxfordshire). Data from several crystals were scaled and merged using XDS to give a dataset in P1 complete to 2 Å. Data from several crystals were scaled and merged to give a dataset in P1 complete to 2 Å. The structure was solved by molecular replacement using IL-13 from PDB entry 3L5X and a Fab variable region (CDR loops truncated) and constant region from a solved in-house Fab structure. Model building and refinement were completed using Phaser, Coot and Buster software that gave a final model with agreement factors R of 0. 189 and R free of 0. 211  [29] [30] [31] [32] [33] [34]. Ramachandran plot was created within CCP4 using default parameters.
Affinity measurements Experiments were performed on a Biacore T100. The instrument was controlled and the resulting data were evaluated using Biacore T100 control and evaluation software version 2. 0. 1. CM5 S-Series biosensor chips, amine coupling kits, HEPES (4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid) buffered saline based buffer concentrates, and regeneration buffers were from GE Healthcare and were used according to the manufacturer's instructions. Biosensor affinity measurements were performed using protein G′-mediated capture immobilisation of the human antibodies, and the recombinant human IL-13 was flowed (analyte). Recombinant protein G′ was from Sigma (P-4689) and human IL-13 (Pepro-Tech). Preparation of protein G′ surfaces on a CM5 chip was performed essentially as previously described  [35].
Homogeneous time resolved fluorescence (HTRF) assay All HTRF experiments were performed in 384-well white shallow well nonbinding plates (Corning Incorporated, Corning, NY; 4513) in assay buffer containing PBS, 0. 1% (vol/vol) bovine serum albumin (Sigma, St. Louis, MO; A9576), and 0. 4 M potassium fluoride (VWR International, Radnor, PA; 26820). Time-resolved fluorescence at 590 and 665 nm was measured following excitation at 320 nm on an Envision plate reader (PerkinElmer, Waltham, MA) after the indicated incubation periods. Ratio values ([665 nm emission/590 nm emission] × 10,000) were used to calculate % Delta F according to the following equation: Delta F ¼ À sample ratio-negative control ratio ½ = negative control ratio ½ Þ Â 100: Curves were analysed and IC 50 values determined using GraphPad Prism software (GraphPad, La Jolla, CA) using a four-parameter logistic curve-fitting equation.
Computing m 5 We have explored the sets of Turing machines in (n, 2) for n ≤ 5 in previous papers  [5, 16]. For n ≤ 4, the maximum time that a machine in (n, 2) may run upon hating is known  [1]. It allows us to calculate the exact values of m 4. For n = 5, we have estimated  [16]  that 500 steps cover almost the totality of halting machines. We have the database of machines producing each string s for each value of n. So we have applied  (8)  to estimate m 5 (because we set a low runtime). In previous papers  [16, 17] , we worked with D(k), a measure similar to m k , but the denominator of (  8 ) is the number of (detected) halting machines in (k, 2). Using D(5) as an approximation to Levin's distribution, algorithmic complexity is estimated 2  by means of the algorithmic Coding Theorem 1 as K D(5) (s) = -log 2 D(5)(s).
The On-Line Encyclopedia of Integer Sequences (OEIS) The On-Line Encyclopedia of Integer Sequences (OEIS) is a database with the largest collection of integer sequences. It is created and maintained by Neil Sloane and the OEIS Foundation. Widely cited, the OEIS stores information on integer sequences of interest to both professional mathematicians and amateurs. As of 30 December 2016 it contained nearly 280 000 sequences, making it the largest database of its kind. We found 875 binary sequences in the OEIS database, accessed through the knowledge engine WolframAlpha Pro and downloaded with the Wolfram Language. Examples of descriptions found to have the greatest algorithmic probability include the sequence "A maximally unpredictable sequence" with associated sequence 0 1 0 0 1 1 0 1 0 1 1 1 0 0 0 1 0 0 0 0 1 1 1 1 0 1 1 0 0 1 0 1 0 0 1 0 0 1 1 1; or A068426, the "Expansion of ln 2 in base 2" and associated sequence 0 1 0 0 0 1 1 0 1 1 0 0 0 0 0 1 0 1 0 0 1 1 1 0 0 1 0 1 1 1 0 1 1 1 0 0 0 0 0 0.
Results We found that the textual description length as derived from the database is, as illustrated above, best correlated with the AP-based (BDM) measure, with Spearman test statistic 0. 193, followed by compression (only the sequence is compressed, not the description) with 0. 17, followed by entropy, with 0. 09 (Fig. 2 ). Spearman rank correlation values among complexity measures reveal how these measures are related to each other with BDM v Compress: 0. 21, BDM v Entropy: 0. 029 and Compress v Entropy: -0. 01 from 875 binary sequences in the OEIS database. We noticed that the descriptions of some sequences referred to other sequences to produce a new one (e. g. "A051066 read mod 2"). This artificially made some sequence descriptions look shorter than they should be. When avoiding all sequences referencing others, all Spearman rank values increased significantly, with values 0.
25, 0. 22 and 0. 12 for BDM, compression and entropy respectively. To test whether the AP-based (BDM) measure captures some algorithmic content that the best statistical measures (Compress and entropy) may be missing, we compressed the sequence description and compared again against the sequence complexity. The correlation between the compressed description and the sequence compression came closer to that of the AP-estimation by BDM, and BDM itself was even better. The Spearman values after compressing textual descriptions were 0. 27, 0. 24 and 0. 13 for BDM, Compress and entropy respectively. We then looked at 139 546 integer sequences from the OEIS database, avoiding other non-integer sequences in the database. Those considered represent more than half of the database. Every integer was converted into binary, and for each binary sequence representing an integer an estimation of its algorithmic complexity was calculated.
We compared the total sum of the complexity of the sequence (first 40 terms) against its text description length (both compressed and uncompressed) by converting every character into its ASCII code, program length and function lengths, these latter in the Wolfram Language (using Mathematica). While none of those descriptions can be considered the shortest possible, their lengths are upper bounds of the maximum possible lengths of the shortest versions. As shown in Fig. 2 , we found that the AP-based measure (BDM) performed best when comparing program size and estimated complexity from the program-generated sequence.
15 mm). Recordings were done with a linear 16-channel silicon probe (NeuroNexus, A1x16-2mm-50-177) connected to an AlphaLab recording system (Alpha Omega). Raw signal was amplified (200×), filtered between 0 and 9 kHz, and digitalized at 22 kHz. Silicon probes were painted with 2% DiI solution (Sigma-Aldrich) for localization. Analyses were carried out using custom-made scripts in Matlab (MathWorks). When present, slow drift and electrical noise were removed using the Chronux signal processing toolbox  (59). Local field potential data were downsampled to 2200 Hz and filtered between 0. 1 and 500 Hz. Spectral analysis was carried with the Chronux toolbox with a time-frequency product of three and five tapers. Time-frequency analyses were done on a 4-s window moved across the data in 1-s increments.
Cell quantification was done as described in the study of Ducharme et al. (62). Briefly, one section every 120 mm was analyzed, which means that four to six sections were evaluated per animal. This set of sections encompassed the dorsal portion of the hippocampus. Photomicrographs were captured using a fluorescence microscope coupled to an ApoTome module (Zeiss), and all labeled cells were counted bilaterally by an experimenter blinded to the genotype. The cells were identified on the basis of shape and size (roughly 10 to 20 mm in diameter), and cells with a large range of staining intensity were included. The counts were performed for each hippocampal subfield individually using the ImageJ software.
Statistical analyses Analyses were done with GraphPad 6 (Prism). Data are expressed as means ± SEM. Memory index was compared to the 0 chance level (no detection of the new object or spatial change) with a one-sample Student's t test. Unpaired t tests were used to compare genotypes. All the other analyses were done using a two-way ANOVA (with or without repeated measures) except for the exploration time analysis with pharmacological treatment, where three-way ANOVA was used (Matlab). Because NTg-and TgCRND8-vehicle mice do not differ from nontreated animals, they were sometimes pooled together to decrease the number of animals used in the study. In case of significant ANOVA, multiple comparisons among groups were performed using Bonferroni's multiple-comparisons test. The threshold for statistical significance was set at P < 0.
Acknowledgments: We thank  O. Bildstein ,  G. Edomwonyi , and  O. Egesi  for animal care. Funding: This work was supported by a  Career Integration Grant  from the  Marie Curie program  of the  European Research Council  (grant #  PCIG10-GA-2011-303573  to R. G. ), the  Neurex network  (grants to R. G. and C. H. ),  Fondation Fyssen  (to R. G. ),  France Alzheimer Haut-Rhin  (to C. M. ), the  French Ministry of Education and Research  (to V. H. and J. -B. B. ), the  CNRS , and the  Université de Strasbourg. Author contributions: C. M. , J. -B. B. , and R. G. conceived the experiments. V. H. , C. H. , J. -B. B. , and K. H. performed the experiments. V. H. , C. H. , and R. G. analyzed the data. C. S. managed the mouse colony. V. H. , C. M. , and R. G. wrote the paper. Competing interests: The authors declare that they have no competing interests.
Funding. This work was supported by the  French National Research Agency  through the  IDEX and Labex programmes  ( ANR-10-IDEX-0001-02 PSL*  and  ANR-11-LABX-0043  to C. T. ),  Fondation ARC  ( SL220120605293  grant to C. T. and post-doc grant to M. T. ),  ANRS  (2015-1 grant to C. T. ),  NIDA  ( DA040385  grant under subaward from  Johns Hopkins Medical University  to C. T. ),  CIC IGR-Curie 1428 ,  INSERM and Institut Curie  (including PhD grant to J. K. ).
Results and Discussion Enhanced conductivity in the MgZnO/ZnO bilayer. The four-point resistivity of the MgZnO/ZnO/ sapphire bilayer is 0. 006 Ω. cm, which is more than two orders of magnitude lower than that of the constituent MgZnO film and an order of magnitude lower than that of the constituent ZnO (ρ = 3. 0 Ω. cm and 0. 1 Ω. cm for the single-layer MgZnO and ZnO films, respectively). This resistivity value is exceptionally low in absolute terms for a ZnO film without intentional shallow donor doping  18. The reproducibility of the measured resistivity value was confirmed by collecting data at several separate areas of sample with various forward and reverse injection currents and repeating the analysis in three different laboratories. This enhanced conduction is attributed to electron confinement at the smooth MgZnO/ZnO interface.
Acknowledgements This work was supported by  Australian Research Council Discovery , grant  DP150103317. The authors would like to thank (i) V. Pillard,  T. Maroutian  and  P. LeCoeur  at the  Institut d'Electronique Fondamentale (IEF) of the University of Paris Sud  for the AFM measurements, and (ii)  F. Bayle , also of the  IEF , for the SEM measurements.
e. cooking the sections in a temperature controlled microwave for 15 minutes at 100ºC in a pH9 or pH6 Tris/EDTA buffer. Ten monoclonal IgGs and 10 monoclonal IgMs positive for human recombinant TNC in Western blots were provided by ProMab Biotechnologies Inc. (Richmond, CA, USA). All 20 anti-TNC clones; 10 IgG and 10 IgM were diluted 1:10, 1:100 and 1:1000 to determine the optimal dilution. As negative control, the primary antibody was omitted. Slides were incubated with the primary antibodies for 30 minutes at room temperature and with diaminobenzidine for 10 minutes at room temperature using DAKO REAL EnVison, K5007 (Denmark) to detect the tissue bound primary antibody. The sections were counterstained with hematoxylin for 1 minute and cover slipped. The optimal TNC staining, hence the optimal protocol, was selected by comparing the TNC staining results to the images in the Protein Atlas data base of normal tissues  [17].
Dosimetry A convolution of the bio-distribution with the dose point kernel (DPK) will result in a 3D dose distribution  [18]. For computational purposes a kernel with finite voxel size is required and termed herein dose voxel kernel (DVK). Using the MCNPX Monte Carlo code version 2. 6 c  [19] , the DVK of Y-90 in water was simulated in Cartesian cubical geometry at 0. 5 mm, 1 mm and 3 mm voxel sizes, and the DPK was simulated in concentric shells geometry for a near-point-source of 20 µm radius with 20 µm shell thicknesses. The DVK's at 0. 5 mm and 1 mm voxel sizes were used for convolution computations, and the DVK at 3 mm voxel size was used to validate the results by comparison with MIRD-17 S values  [20]  also calculated at a voxel size of 3 mm. The DPK was used to calculate the radius of the sphere (X 90 ) within which 90% of the dose is absorbed.
25 MeV. The electron and photon cutoff energy set to 1 keV. Photons and electrons were tracked and F6 tallies (electron+photon) were used to calculate the dose in each voxel. Ten million histories were followed. The 3D DVK was regenerated using a MATLAB script (The MathWorks, Natick, MA) in a volume of 25 × 25 × 25 mm 3 with a 1 mm voxel size. A hypothetical planning target volume (PTV) was also modeled in the script as a 50 × 50 × 50 mm 3 of water equivalent material with a 1 mm voxel size, a uniform biodistribution of 37Bq/voxel (1nCi/voxel), and surrounded by water. Convolution of the PTV with the 3D DVK was performed using MATLAB to estimate the activity of Y-90 needed to deliver a dose of 100Gy to the PTV. The matrix dimension resulting from the full convolution of the PTV with the DVK is 74 × 74 × 74 mm 3 , permitting the recording of dose in the gradient just outside the PTV in addition to the dose within the PTV.
Acknowledgments Developing new applications for Radiolabeled Immunoglobulin Therapy requires a multidisciplinary team. Huib Vriesendorp wants to acknowledge his long standing collaboration with  Syed M Quadri, PhD , an excellent friend, educator and chemist and  Paul Borchard, PhD , for their valuable contributions to the field of radioimmunotherapy. This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
5 mm). This method was first used to measure blowing snow and is described in detail in  Nishimura and others (2014). It must be noted that the calculation assumes only slope-parallel movement of particles; vertical or lateral movements under turbulent conditions cannot be detected. The data were sampled at 60. 1 kHz (in 2013) or 120 kHz (in 2014) from the ultrasonic anemometer and SPC. The velocity sensors and the impact pressure signals measured by the load cells in the dense flow were recorded at 60. 1 and 3 kHz, respectively.
Avalanche experiment in 2014 The second set of avalanche data was obtained on 5 March 2014. The tripod stood out ∼1. 5 m above the snow cover, with the ultrasonic anemometer and SPC located ∼1. 9 m above the snow surface. Figure  5  shows a snapshot taken when the avalanche head impacted the tripod and Figure  6  shows data recorded during this avalanche including airflow velocity, SPC counts and impact pressure and flow speed of the dense part of the flow. The signals from the ultrasonic anemometer contained periodic 1 Hz noise; hence Figure  6  shows data after noise reduction by means of a 0. 5-1. 5 Hz band elimination filter. The avalanche was released artificially at 13:35. On 3 March, a snowfall occurred between 02:00 and 17:30 providing 21. 6 mm w. e. of solid precipitations. Our weather station measured a mean air temperature of -7.
ACKNOWLEDGEMENTS We thank  F. Ousset  for helpful support in installing the devices and in conducting the experiments. We are grateful to the reviewers,  B. Sovilla  and  B. Turnbull , for their insightful comments. This work was supported by funding from the  MAP3 ALCOTRA INTERREG programme  and partly by  Grants-in-Aid No. 22253001  from the  Ministry  of.
Systematic Review of Available Methods A systematic review of the literature was conducted to determine what methods currently exist for sequencing HCV to detect DAA RASs. Sequencing methods were evaluated according to several methodological parameters. This systematic review was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. (13) As per a previously published systematic review on the sequencing of HCV,  (14)  the PRISMA guidelines were customized (Supporting Table  S2 ) to fit the scope of this study. This protocol has been registered and uploaded to the PROSPERO database (https://www. crd. york. ac. uk/PROSPERO/display_record. asp?ID=CRD42016045548) (Supporting Table  S3 ). A systematic search of MEDLINE (PubMed) and SCOPUS was performed on August 15, 2016, covering   all studies published from January 1, 2011, to that date.
The time period was restricted to capture methods related to current DAA therapy. Backward citation checks were carried out to identify further potentially relevant studies that could have included studies published before 2011. In addition, an invitation was made to researchers and laboratories with unpublished methodologies to contribute their primer sets in consultation with the HCV Resistance Working Group led by the HCV Forum. Medline Search terms were used to search for studies relating to HCV ("HCV" OR "Hepatitis C") and resistance ("antiviral resistance" OR "resistance mutation*" OR "resistance*associated variant*" OR "resistance*associated substitution*" OR "resistance* associated amino acid variant*" OR "polymorphism*") from these two databases. To identify studies that used sequencing as a method, the search term ''primer*'' was also applied because it is related to polymerase chain reaction (PCR) and sequencing.
The lists of studies from each search database were combined, and ineligible articles were removed after title and abstract review based on the following criteria: duplicate reference, review article, abstract or title accessible only, DAA RASs not reported, sequencing not performed, or irrelevant/insufficient method description. Studies were deemed eligible for this analysis if they were published in English, HCV DAA RASs were reported in clinical samples, HCV sequencing (population sequencing, next generation sequencing [NGS], or template-independent amplification) was performed, and PCR/sequencing primer design or location was described. Two reviewers independently determined.
The genome location of primers was recorded in the primer library as reported in the original record. If original records did not describe location, it was recorded in the primer library in reference to the H77 sequence (genotype 1a genome; Genbank accession number AF009606). Primers for which location could not be determined were included in the primer library but not in subsequent amplicon analyses. For studies that described a nested PCR protocol, the innermost primer was recorded in the primer library and used for the amplicon analysis. Where studies described sequencing primers in addition to PCR primers, all sequencing primers were included in the primer library as individual amplicons but only PCR primers were included in the amplicon analysis. Where multiple genotype-specific primer pairs were described, all pairs of primers were included in the primer library as individual sequencing protocols and included in the amplicon analysis.