dataesr/scientific-paragraphs-categorization huggingface dataset:
Domain structure of Kelch protein (K13), phosphatidylinositol 3-kinase (PI3K), cGMP-specific phosphodiesterase (PDE1), serine/threonine protein kinase (ARK2), autophagy related protein (Atg18 and Atg7), recovered from Pfam database server. Amino acid substitution and position in the protein are given for all non-synonymous mutations. Color code of mutations: black, not significant in any subpopulation; green, significant in only one subpopulation; red, significant mutations observed in several subpopulations there is little evidence of P. falciparum resistance to this antibiotic in Cambodia. Doxycycline resistance in P. falciparum can be explained in part by pfmdt and pftetQ copy number (PFE0825w and PFL1710c, respectively) and polymorphisms on pftetQ, which encode transporters  [63]. None of these two genes show any variation in the 167 isolates, but copy number was not evaluated.
of uncertain ALT allele frequency. All the SNPs with uncertain ALT allele frequency greater than 40% (dotted blue line at 0. 4) were removed from the analyses. b Represents a schematic diagram of different cases considered for SNPs with uncertainties and the decision of substitution taken. Uncertainties were substituted with the most frequent ALT value or REF value in around 17% of the SNPs at this step. c Represents the pie chart with percent of certain SNPs, substituted SNPs and removed SNPs. Database presenting the list of 21,257 non-synonymous SNPs found in the 167 Cambodian isolates. Calling of SNPs is described in the "Methods" section. See full legend in the corresponding excel sheet. Classification of 167 samples into artemisinin resistant and sensitive Cambodian subpopulations. a Dendrogram representing the classification of 167 parasite isolates into 8 clusters (k = 8).
[34] table is based on the co-expression interaction network (confidence score ≥ 0. 5) recovered from STRING v10 database server. The unconnected nodes (genes) were not considered in the analysis. The maximum expression data is based on the transcriptomic study by Le Roch et al. [34]and is recovered from PlasmoDB. Data for early and late forms of the three blood stage ring, trophozoite and schizogony is available. Some of the genes are not classified in the interaction network.
Funding DBR and EC were supported by the  ANR (Agence Nationale de la Recherche  " Investissements d'avenir/Bioinformatique "):  ANR-11-BINF-0002  ( Institut de Biologie Computationnelle ). AD was funded by  Erasmus Mundus Action  2: Svaagata. euproject: India, funded by the  European Commission  (ref. nrAgreement Number:  2012-2648/001-001-EM Action 2-Partnerships ).
Additional file 7. Additional file 8. 78 of uncertain ALT allele frequency. All the SNPs with uncertain ALT allele frequency greater than 40% (dotted blue line at 0. 4) were removed from the analyses. b Represents a schematic diagram of different cases considered for SNPs with uncertainties and the decision of substitution taken. Uncertainties were substituted with the most frequent ALT value or REF value in around 17% of the SNPs at this step. c Represents the pie chart with percent of certain SNPs, substituted SNPs and removed SNPs. Database presenting the list of 21,257 non-synonymous SNPs found in the 167 Cambodian isolates. Calling of SNPs is described in the "Methods" section. See full legend in the corresponding excel sheet. Classification of 167 samples into artemisinin resistant and sensitive Cambodian subpopulations.
StcO 2 recording began within the first 6 hours after initiation of ECMO and ended at the discontinuation of ECMO support. Data were gathered at the end of each recording. The INVOS Analytics Tool software was used to analyze all the data; the following main parameters were measured: mean StcO 2 , the duration of oxygen desaturation below the threshold of 20% from baseline and the duration of oxygen desaturation below the StcO 2 value of 50%. The mean StcO 2 value typically fluctuated between 60%-70% in normal conditions. The calculation of the oxygenation index [(MAP x FiO 2 )/PaO 2 ] was performed by measuring the PaO 2 of arterial blood gas before placement on ECMO. If an arterial blood gas was not available, we used a specific scale for estimating the PaO 2 with the pulse arterial oxygen saturation according to the method described by Severinghaus  [17].
Magnetic resonance imaging (MRI) was performed after the discontinuation of ECMO and withdrawal of cannulas in all surviving patients. Brain injuries were defined as ischemic or hemorrhagic lesions based on the extent and topography of the affected regions. The French Research Ethics Committee (Comitede Protection des Personnes Ile-de-France) approved this study without any further requirements owing to the lack of interventional procedures. Parents were informed of the protocol in progress and were able to present their objection to the collection of any data regarding their infants. Consents to participate are not applicable because it is an non-invasive observational study.
Acknowledgments Francois Dion and  Christopher Dumayne  contributed equally to this work. This work was presented in part at the 76th Scientific Sessions of the American Diabetes Association (June 10th to June 14th 2016). The authors would like to thank  Naoual Elftouh  and  Jean-Philippe Lafrance  for statistical analysis,  Julie Dubeau  and  Marie-Laure Durand  for skillful technical work,  Marie-E `ve Gingras  for helpful discussions and  Heather Melichar  for revising the manuscript.
A search is presented for an excess of events with heavy-flavor quark pairs (tt and bb) and a large imbalance in transverse momentum in data from proton-proton collisions at a center-of-mass energy of 13 TeV. The data correspond to an integrated luminosity of 2. 2 fb -1 collected with the CMS detector at the CERN LHC. No deviations are observed with respect to standard model predictions. The results are used in the first interpretation of dark matter production in tt and bb final states in a simplified model. This analysis is also the first to perform a statistical combination of searches for dark matter produced with different heavy-flavor final states. The combination provides exclusions that are stronger than those achieved with individual heavy-flavor final states.
This paper describes a search for DM produced with a tt or bb pair in pp collisions at √ s = 13 TeV with the CMS experiment at the LHC. A potential DM signal is extracted from simultaneous fits to the p miss T distributions in the bb + p miss T and tt + p miss T search channels. Data from control regions enriched in SM tt, W + jets, and Z + jets processes are included in the fits, to constrain the major backgrounds. The top quark nearly always decays to a W boson and a b quark. The W boson subsequently decays leptonically (to charged leptons and neutrinos) or hadronically (to quark pairs). The dileptonic, lepton( )+jets, and all-hadronic tt final states consist, respectively, of events in which both, either, or neither of the W bosons decay leptonically. Each of these primary tt final states are explored.
Modeling and simulation The associated production of DM and heavy-flavor quark pairs provides rich detector signatures that include significant p miss T accompanied by high-p T jets, bottom quarks, and leptons. The largest backgrounds in the tt + p miss T and bb + p miss T searches are SM tt events, inclusive W boson production in which the W decays leptonically (W( ν) + jets), and inclusive Z boson production in which the Z decays to neutrinos (Z(ν ν) + jets). Simulated events are used throughout the analysis to determine signal and background expectations. Where possible, corrections determined from data are applied to the simulations. Monte Carlo (MC) samples of SM tt and single t backgrounds are generated at next-to-leading order (NLO) in quantum chromodynamics (QCD) using POWHEG v2 and POWHEG v1  [39] [40] [41] , respectively.
Event selection Signal events are expected to exhibit both large p miss T from the production of two noninteracting DM particles and event topologies consistent with the presence of top quarks or b quark jets. Data are therefore collected using triggers that select events containing large p miss T or high-p T leptons. Data for the dileptonic and + jets tt + p miss T searches are obtained using single-lepton triggers that require an electron (muon) with p T ≥ 27  (20)  GeV. These trigger selections are more than 90% efficient for PF-reconstructed electrons and muons that satisfy the p T , identification, and isolation requirements imposed. The trigger used for the bb + p miss T and all-hadronic tt + p miss T searches selects events based on the amount of p miss T and H miss T reconstructed using a coarse version of the PF algorithm.
The H miss T variable is defined as the magnitude of the vector sum of the p T of all jets in the event with p T > 20 GeV, |η| < 5. 0. Jets reconstructed from detector noise are removed in the H miss T calculation by additionally requiring neutral hadron energy fractions of less than 0. 9. The p miss T and H miss T requirements for this trigger are 120 GeV. The trigger is nearly 100% efficient for events that satisfy subsequent selections based on fullyreconstructed PF p miss T. Additional selections, described in Section 4. 1 and summarized in Table  1 , are applied to define eight independent regions of data that are sensitive to DM signals: two bb + p miss T , one + jets tt + p miss T , three dileptonic tt + p miss T , and two all-hadronic tt + p miss T regions. Control regions (CRs) enriched in various background processes are also defined and are used to improve background estimates in the aforementioned signal regions (SRs).
Signal extraction A potential DM signal could be revealed as an excess of events relative to SM expectations in a region of high p miss T. The shape of the observed p miss T distribution provides additional information that is used in this analysis to improve the sensitivity of the search. A potential signal is searched for via simultaneous template fits to the p miss T distributions in the SRs and the associated CRs defined in Sections 4. 1 and 4. 2. Signal and background p miss T templates are derived from simulation and are parameterized to allow for constrained shape and normalization variations in the fits. The fits are performed using the ROOSTATS statistical software package  [59]. The effects of un-    2 ) is used to constrain the dileptonic tt background in the + jets tt + p miss T signal region, while the 1 lepton, 0 b tag control region (slB) constrains W + jets background.
• b tagging efficiency: The b tagging efficiency and its uncertainty are measured using independent control samples. Uncertainties from gluon splitting, the b quark fragmentation function, and the selections used to define the control samples are propagated to the efficiency scale factors  [31]. The corresponding normalization uncertainty ranges from 2. 2 to 12%. • Lepton identification and trigger efficiency: The uncertainty in lepton identification and triggering efficiency is measured with samples of Z bosons decaying to dielectrons and dimuons  [34]. The corresponding normalization uncertainty ranges from 2 to 4%. • p miss T trigger: Uncertainties of 0. 3-2% (depending on the SR) are associated with the efficiency scale factors of the p miss T trigger. The efficiency of this trigger is measured using data collected with the single-lepton triggers.
Summary A search for an excess of events with large missing transverse momentum (p miss T ) produced in association with a pair of heavy-flavor quarks has been performed with a sample of protonproton interaction data at a center-of-mass energy of 13 TeV. The data correspond to an integrated luminosity of 2. 2 fb -1 collected with the CMS detector at the CERN LHC. The analysis explores bb + p miss T and the dileptonic, + jets, and all-hadronic tt + p miss T final states. A resolved top quark tagger is used to categorize events in the all-hadronic channel. No significant deviation from the standard model background prediction is observed. Results are interpreted in terms of dark matter (DM) production, and constraints are placed on the parameter space of simplified models with scalar and pseudoscalar mediators.
Acknowledgments We congratulate our colleagues in the CERN accelerator departments for the excellent performance of the LHC and thank the technical and administrative staffs at  CERN  and at other  CMS institutes  for their contributions to the success of the CMS effort. In addition, we gratefully acknowledge the computing centers and personnel of the  Worldwide LHC Computing Council and Horizon 2020  Grant, contract No. 675440  ( European Union ); the  Leventis Foundation ; the A. P. Sloan Foundation; the  Alexander von Humboldt Foundation ; the  Belgian Federal Science Policy Office ; the  Fonds pour la Formation à la Recherche dans l'Industrie et dans l'Agriculture (FRIA-Belgium) ; the  Agentschap voor Innovatie door Wetenschap en Technologie (IWT-Belgium) ; the  Ministry of Education, Youth and Sports (MEYS)  of the Czech Republic; the  Council of Science and Industrial Research, India ; the  HOMING PLUS program  of the  Foundation for Polish Science , cofinanced from  European Union, Regional Development Fund , the  Mobility Plus program of the Ministry of Science and Higher Education , the  National Science Center (Poland) , contracts Harmonia  2014/14/M/ST2/00428 ,  Opus 2014/13/B/ST2/02543 ,  2014/15/B/ST2/03998 , and  2015/19/B/ST2/02861 , Sonata-bis  2012/07/E/ST2/01406 ; the  National Priorities Research Program  by  Qatar National Research Fund ; the  Programa Clarín-COFUND del Principado de Asturias ; the Thalis and Aristeia programs cofinanced by  EU-ESF  and the  Greek NSRF ; the  Rachadapisek Sompot Fund for Postdoctoral Fellowship, Chulalongkorn University  and the  Chulalongkorn Academic into Its 2nd Century Project Advancement Project (Thailand) ; and the  Welch Foundation , contract  C-1845.
sec coupled to Multi-angle laser light scattering Size-exclusion chromatography (SEC)-MALLS/QELS experiments were performed on a multi-angle laser light scattering detector (miniDAWN TREOS, Wyatt Technologies) coupled in-line with SEC and an interferometric refractometer (Optilab T-rEX, Wyatt Technologies). A Superdex S75 or S200 10/300 GL column (total volume 24 mL, GE Healthcare) with a flow rate of 0. 5 mL/min was used to separate the sample before performing the MALLS/QELS measurement. Experiments were done with 50-100 µL receptor-DNA complex samples at concentrations between 1 and 3 mg/mL in 20 mM Bis Tris pH = 7. 0, 120 mM KCl, 1 mM MgCl2, 0. 5 mM CHAPS, 1 mM TCEP. The molar mass was determined by construction of Debye plot using Zimm formalism [plot of K*c/R(θ) as a function of sin 2 (θ/2)] at 1-s data interval.
Samples were diluted to 5 µM in 150 mM ammonium acetate, pH = 7. 1 buffer and directly infused into the mass spectrometer. Instrumental parameters were optimized for the detection of labile non-covalent complexes by raising the interface pressure to 6 mbar and the cone voltage to 140 V. Data treatment was realized with MassLynx 4. 1 software (Waters, Manhester, UK).
nuclear Magnetic resonance Nuclear magnetic resonance experiments were recorded at 700 MHz on an Avance III Bruker spectrometer equipped with a TCI z-gradient cryoprobe. NMR data were processed using TopSpin (Bruker) and analyzed with Sparky software packages  (36). NMR experiments were performed in 50 mM sodium phosphate buffer (pH 7. 0), 5 mM MgCl2, and 1 mM TCEP in 90/10 H2O/D2O. PAGE-purified DNAs were annealed by heating at 95°C and snap-cooled at 4°C. The concentration of DNA samples was measured using a Nanodrop Spectrometer and calculated with molar extinction coefficients. DNA samples volumes were 150 µL in 3-mm NMR tubes. 1 H assignments were obtained using standard homonuclear experiments. NMR data were acquired at 15°C and 20°C. Solvent suppression was achieved using the "Jump and Return" sequence combined to WATERGATE  (37) (38) (39).
S1B ) using a 0. 2 mM sample of U-[ 2 H],[ 13 CH 3 ] b -Ala-labeled TET2. The initial data collected immediately after the jump to neutral pH revealed spectral characteristics of a poorly structured protein (Fig. 1C ), indicating that the crossing of the isoelectric point destabilized the monomer. This first intermediate state disappeared rapidly (fig. S2 ) with the concomitant buildup of well-dispersed NMR signals corresponding to folded oligomeric intermediates and native dodecameric TET2 peptidase (Fig. 1 , D to F). NMR data were complemented and corroborated by "isotopic hybridization" MS analyses to identify the oligomerization state of the short lifetime initial intermediate (Fig. 2 ). Negative staining EM snapshots were also captured every 30 s to identify the shapes and oligomeric states of the TET2 protein during the self-assembling process.
NMR data acquisition and processing All 1 H NMR experiments were performed on an Inova spectrometer (Agilent) operating at 800-MHz frequency and equipped with a cryogenic probe. All experiments were acquired at 50°C. SOFASTmethyl-TROSY (18) was acquired with PC9 shape pulse with flip angle of 30°and length d of 4. 26 ms. The interscan delay (d 1 ) was set to 290 ms. Each spectrum in kinetic dimension was acquired with spectral width of 1600 Hz and 20 complex points in 13 C dimension. The total acquisition time of one 2D spectrum was 14. 4 s. Each experiment was performed with only one scan per increment in t 1 , ensuring highest repetition rates of experiments, and the sign of the 13 C excitation pulse phase and receiver phase in SOFAST-methyl-HMQC (heteronuclear multiple-quantum coherence) was alternated between subsequent experiments  (18).
Spectra were processed and analysed using NMRPipe (34) and nmrglue  (35)  module of the Python programming language  (36). Two succeeding spectra (1 and 2, 2 and 3, 3 and 4,…, n -1 and n) along the kinetic time were added before processing of 2D kinetic planes. Such data treatment removes spectral artifacts, such as axial peaks or t 1 at the water frequency and improves the baseline, allowing a more accurate and precise measurement of spectral parameters, such as peak positions and intensities  (18).
NMR data fitting All numerical modeling and fitting were performed using the NumPy and SciPy (37) Python modules. Signals of Ala 194 , Ala 281 , Ala 145 , and Ala 314 in the spectra of the dodecamer  (38)  were integrated (fig. S2A , signals delimited by cyan boxes) and were used as reporters for the evolution of the population of final dodecamer and oligomeric intermediates (Fig. 1F ). The normalized buildup of dodecamer and dodecamer-like species was numerically fitted with double exponential (fig. S3 ) and used for subtraction of dodecamer/dodecamer-like contribution from the kinetic spectral series (fig. S2 ). To minimize noise contribution introduced by these combinations of spectra on each 2D kinetics plane, we performed the subtraction using a 2D SOFAST-methyl-HMQC (fig. S2B ) of the final dodecamer recorded at the end of the self-assembly experiment with high signal-to-noise ratio (acquisition time, 1 hour).
MS analyses were carried out on a quadrupole time-of-flight mass spectrometer (Q-TOF Ultima, Waters Corporation). The instrument was modified for the detection of high masses  (41, 42). The following instrumental parameters were used: capillary voltage, 1. 2 to 1. 3 kV; cone potential, 40 V; RF lens-1 potential, 40 V; RF lens-2 potential, 1 V; aperture-1 potential, 0 V; collision energy, 30 to 140 V; and microchannel plate, 1900 V. All mass spectra were calibrated externally using a solution of cesium iodide (6 mg/ml in 50% isopropanol) and were processed with the MassLynx 4. 0 software (Waters Corporation) and Massign  (43). Assignment of the number of labeled subunits in protein complexes by native MS To determine the number of labeled subunits, the molecular weights of protein complexes were calculated by the analyses of the MS and tandem MS spectra (shown in Fig.
Acknowledgments: We would like to thank  R. Awad ,  I. Ayala ,  A. Favier ,  C. Mas ,  A. Hessel ,  J. Perard , and  L. Signor  for technical help on the  Integrated Structural Biology, Grenoble (ISBG)  platforms and  B. Brutscher ,  K. Embrey ,  P. Gans ,  M. Plevin , and  P. Schanda  for comments and stimulating discussions. Funding: The research leading to these results has received funding from the  European Research Council  under the European Union's  Seventh Framework Programme   FP7/2007-2013  grant agreement no. 260887. C. M. benefited from.
Methods: Four friction isolation interfaces, namely, marble-marble, marble-high-density polyethylene, marble-rubber sheet, and marblegeosynthetic were involved. Those interfaces differ for the friction coefficient, which was experimentally obtained through the aforementioned research. The FE model adopted here is based on a macroscopic approach for masonry, which is assumed as an isotropic material exhibiting damage and softening. The Concrete damage plasticity (CDP) model, that is available in standard package of ABAQUS finite element software, is used to determine the non-linear behavior of the house under non-linear dynamic excitation.
Although HCV protein expression in our model is hepatocyte-restricted, this peripheral effect may result from the endocrine effects of inflammatory cytokines (  56  A, Ser(P) 256 -FoxO1 assessed by Western blotting and quantified in liver extracts from WT and HCV-tg mice injected with insulin or vehicle and normalized using ␥-tubulin expression (representative animals). B, quantitative results for Ser(P) 256 -FoxO1 levels. C, indirect immunofluorescence on cultured primary mouse hepatocytes from WT and HCV-tg mice. Cells were treated with insulin or PBS (no insulin) for 20 min prior to analysis. Ser(P) 256 -FoxO1 antibody was detected using a secondary antibody coupled to Alexa 498. Nuclei were stained using DAPI. D, quantification of fluorescence intensity within the cytoplasm and the nucleus of primary hepatocytes using ImageJ software.
Total RNA isolation and RT-qPCR Total RNA was isolated from frozen mouse livers using the Ambion PARIS RNA and protein isolation kit (Thermo Fisher Scientific, Waltham, MA), according to the instructions of the manufacturer. Then RNA quality and quantity were assessed by means of a 2100 Bioanalyzer and RNA Nano Chips (Agilent Technologies, Santa Clara, CA). RNA integrity number was calculated using Agilent software, and samples displaying an RNA integrity number below 6 were discarded. 1 g of RNA was reverse-transcribed using the high-capacity cDNA reverse transcription kit (Thermo Fisher Scientific). Real-time quantitative PCR was performed using TaqMan reagents and an Applied Biosystems 7300 thermal cycler (Applied Biosystems, Carlsbad, CA). Specific primers and probes were purchased from Applied Biosystems (supplemental Table  1 ).
The primary antibodies used are listed in supplemental Table  2. The membranes were incubated with the corresponding secondary antibodies coupled to HRP-conjugated donkey anti-rabbit IgG or sheep anti-mouse IgG (GE Healthcare). Labeled antibodies were detected with ECL Prime detection kits (GE Healthcare). Chemiluminescent signals were detected and quantified using an Image Quant Las 4000 minicamera and Image Quant software (GE Healthcare). A polyclonal mouse ␥-tubulin antibody (supplemental Table  2 ) was used as a loading control for total lysates. Akt kinase assay was performed as described previously (46) using an Akt non-radioactive kinase kit (Cell Signaling Technology, Danvers, MA). Briefly, hepatic samples (0. 5 mg) were lysed and active Akt was immunoprecipitated, and its ability to phosphorylate GSK-3 in vitro was analyzed by Western blotting.