dataesr/scientific-paragraphs-categorization huggingface dataset:
The dilepton triggers require either ee, µµ, or eµ pairs. In each case, one lepton must satisfy p T > 17 GeV and the other lepton must satisfy p T > 8 GeV. Trigger efficiencies are measured in data and applied to simulated events. The integrated luminosity, after data quality requirements, is 19. 5 ± 0. 5 fb -1 for the single-lepton states and 19. 7 ± 0. 5 fb -1 for the dilepton final states  [16]. The SM background processes of relevance to this analysis are tt, W+jets, Z/γ * → + -(denoted Drell-Yan, or DY), single top, diboson, triboson, and tt + boson(s). They are simulated by the MADGRAPH  [17]  (v5. 1. 3. 30) and POWHEG  [18]  event generators, with CTEQ6L1  [19]  and CT10  [20]  parton density functions (PDF) respectively. Simulated event samples with signal mass points chosen on a grid of (m( t 1 ), m( χ 0 1 )) values are generated, where the mass of the t 1 varies between 100 and 1000 GeV, and the mass of the χ 0 1 varies between 0 and 700 GeV; as mentioned in Section 1 (see Eq.
(  1 )), three different mass hierarchies are considered for the bbWW decay mode. The generation of signal samples is performed using MADGRAPH with CTEQ6L1 PDF. Parton shower and hadronization are simulated using PYTHIA  [21]  (v6. 4. 26 for background and v6. 4. 22 for signal) with the tune Z2 *  [22]. All simulated events are propagated through the CMS detector model either with the GEANT4 package  [23] , or, in the case of the signal samples, with a fast parametric simulation  [24]. The next-to-leading-order (NLO) plus the next-to-leading-log (NLL) cross sections for top squark pair production are calculated with PROSPINO  [25] [26] [27] [28] [29] [30]. To ensure agreement with data, simulated events are weighted so that the distribution of the number of proton-proton interactions per beam crossing agrees with that seen in data; they are additionally weighted by the trigger efficiency and the lepton identification and isolation efficiencies.
Background estimation The SM background processes in the single-lepton search can be divided into four categories. At preselection, the dominant contribution (∼ 66% of the total) is the tt production with one lepton; we include single top-quark production in this category and call the combination the "tt → 1 " component. The second most significant background (23%) comes from tt events with two leptons, where one lepton escapes detection; we will call this the "tt → " component. The third background (7%) is the production of W in association with jets, which we will denote "W+jets". Other backgrounds are labeled as "rare". We use data to estimate the event yields of the first three categories, starting with distributions obtained from simulation, and normalizing these with scale factors (SF) determined in control regions.
Background prediction For the M T2 signal regions used in this search, the dominant background is tt. Other backgrounds also contribute, including DY, single-lepton events with an additional misidentified lepton (see Section 5. 2. 3), and rare processes. The rare processes include single top quarks produced in association with a W boson; diboson production, including W or Z production with an associated photon; triple vector boson production; and tt production in association with one or two vector bosons. The normalization of the tt and DY backgrounds, and the normalization and shape of the misidentified lepton backgrounds, are evaluated from data using control samples. The shapes of the tt and DY backgrounds, and the normalization and shapes of less common processes, are all estimated from the simulation.
We then measure the prompt lepton rate, which is the efficiency for isolated and prompt leptons to pass selection requirements, in a data sample enriched in Z → + -events. As with the misidentification rate, the prompt rate is determined by counting the rate at which loose leptons pass tight selection requirements. Both the measurements of the lepton misidentification rate and the prompt lepton rate are performed as functions of lepton p T and |η|. For each dilepton event where both selected leptons pass at least the loose selection requirements, the measured misidentification and prompt rates directly translate into a weight for the event. These weights depend upon whether neither, one, or both loose leptons also passed the tight selection requirements. The shape and normalization of the misidentified lepton background is then extracted by first applying these derived weights to the data sample where both selected leptons pass at least the loose selection requirements, and then calculating the weighted distribution of relevant variables such as M T2.
Individuals have received support from the  Marie-Curie  programme and the  European Research Council and EPLANET (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  Agence Nationale de la Recherche   ANR-12-JS05-002-01  (France); the  Ministry of Education, Youth and Sports (MEYS)  of the Czech Republic; the  Council of Science and Industrial Research, India ; the  HOMING PLUS programme of the Foundation for Polish Science , cofinanced from  European Union, Regional Development Fund ; the  OPUS programme of the National Science Center (Poland) ; the  Compagnia di San Paolo (Torino) ; the  Consorzio per la Fisica (Trieste) ;  MIUR  project  20108T4XTM  (Italy); the Thalis and Aristeia programmes cofinanced by  EU-ESF  and the  Greek NSRF ; the  National Priorities Research Program  by  Qatar National Research Fund ; the  Rachadapisek Sompot Fund for Postdoctoral Fellowship, Chulalongkorn University (Thailand) ; and the  Welch Foundation , contract  C-1845.
2  Myanmar ranks seventeenth among the 22 high TB burden countries, and has one of the most severe HIV/ AIDS (acquired immune-deficiency syndrome) epidemics in Asia, with a prevalence of 0. 53% in adults. 1, 3 s a result of this dual epidemic, there is likely to be a significant burden of HIV-associated TB. In 2013, according to the WHO report, only 16 882 (12%) of the notified TB patients in the country were HIV tested; 5413 were found to be HIV-positive, of whom 4006 (74%) were recorded as being on ART during ATT. 3  For the 2011 TB cohort, only 65% of HIV-infected TB patients successfully completed treatment, which was much lower than the rate of 89% amongst newly diagnosed TB patients overall. These data suggest that 1) there is a significant pool of patients with TB-HIV who are not diagnosed or offered HIV care, and 2) for those who are diagnosed and treated, outcomes are poor.
Data variables, sources of data and data collection The source of data was the Mandalay central electronic database, and data were extracted between March and November 2015. Data variables included the IHC registration number; the start date of ATT; the start date of ART; the age at the time of ATT initiation; sex; CD4 cell count and body mass index (BMI) before or after 6 months of ATT initiation; haemoglobin, hepatitis B and hepatitis C status at the time of registration at the IHC clinic; the category and site of TB; and TB treatment outcomes. The classification of anaemia and BMI (for Asian populations) were per WHO recommendations. 11,12.
Analysis and statistics Data were extracted into Excel (Microsoft Corp, Redmond, WA, USA) and imported into EpiData analysis software version 2. 2. 2. 183 (EpiData Association, Odense, Denmark). Univariate analysis and adjustment for single confounders was performed using Epi-Data analysis software. Multivariate analysis was performed using STATA version 12. 1 (STATA Corp, College Station, TX, USA). Analyses were performed in relation to the two groups of TB-HIV patients: ATT first and ART first. Within each group, frequency and proportions were used to summarise baseline characteristics and ATT outcomes. The median interquartile range (IQR) was used to summarise the time between ATT and ART. Associations between ATT outcomes and time between ART and ATT (including baseline characteristics) were summarised using relative risks (adjusted for confounding wherever applicable using the Mantel Haenszel method) and 95% confidence intervals (CI).
Public Health Action Timing of ART in TB-HIV 114 10% of the patients. There was a high proportion of missing data for TB treatment outcome dates, which precluded a time to event analysis. As data on the ART regimen at the time of ATT initiation were not readily available, we could not determine the effect of ART regimens on treatment outcomes. Data on haemoglobin were recorded on entry to the IHC clinic and not during ATT initiation. There were some important findings in this study. First, baseline anaemia at entry to the IHC clinic was common and an independent risk factor for unsuccessful ATT outcomes in those starting ATT first. Moderate to severe anaemia at entry into HIV care increases the risk for TB among HIV-infected patients. 14 ] [17] [18] [19]  Second, the timing of ART in relation to ATT was not an independent risk factor for unsuccessful outcomes.
Compared to spectral or polarisation ratiometric techniques, FLIM requires more detected photons to achieve a given accuracy, so this is a slower modality for mapping and quantifying FRET in high content analysis. However, FLIM can also provide more quantitative readouts in a single spectral channel since the fluorescence decay profiles can be fitted to complex models in order to obtain the FRET efficiency and the interacting population fraction. Time-resolved measurements can be extended to analyse homoFRET and polarisation anisotropy decays using appropriate models. Fitting lifetime data to complex models typically requires 10,000's of photons -compared to ~200 photons required to fit to a monoexponential decay model 12 -and it is not possible to detect such high photon numbers per pixel from biological samples such as cells labelled with fluorescent proteins before photobleaching and phototoxicity ensue.
The unquenched donor lifetime was determined using data from the cells transfected only with RASSF1-6 and this component was fixed during the global fitting. The donor lifetime quenched by FRET was allowed to vary, but was constrained to be spatially invariant across all cells within a given experimental condition. Thus, the fraction of interacting molecules (β term in equation 2) could be estimated and these results are presented in the box plots shown in Fig. 10A  (the full list of parameters obtained from this analysis are presented in the Supplementary information). Owing to the challenges associated with quantifying FRET interactions between fluorescent proteins that are applicable to all such assays  38  , these values should be treated as estimates. Although they show relatively broad distributions, they indicate a lower fraction of bound molecules in the case of the RASSF interaction with the full length MST1 protein compared to the isolated SARAH MST1 domain.
Conclusions We have developed a high content assay utilising FLIM FRET to screen for binding partners of MST1 kinase among the RASSF protein family and to quantify the relative interaction affinities. Our custom automated FLIM multiwell plate microscope based on time gated detection is capable of rapid automated image acquisition and therefore facilitates systematic studies of bimolecular processes to provide statistically robust readouts that quickly highlight any systematic errors and effectively average over biological variations. We note that the results presented here and in our previous work  11, 35  highlight that the ability to apply global fitting over such large data sets enables us to take advantage of FRET assays with modest lifetime changes (100-200 ps). We have demonstrated how a relatively simple wide-field FLIM plate microscope can be applied with fitting to monoexponential decay models to provide robust qualitative readouts of FRET, enabling protein interactions to be identified.
This is of practical significance since fitting to monoexponential decay models is much less sensitive to system errors such as variations in the instrument response function, compared to fitting to more complex models and there is a wide range of software tools available to fit FLIM data to a monoexponential decay models on a pixel-wide basis. We also note the importance of plotting the ratio of acceptor to donor fluorescence intensities as a function of donor lifetime to elucidate the impact of relative concentrations, e. g. due to variations in transfection efficiency. For more quantitative measurements, the global fitting capabilities of software tools such as FLIMfit complement the capacity of the FLIM plate reader to acquire 100's-1000's of FOV and permit the population of FRETing donors to be estimated.
bu. edu/cluster) were used for rigid body docking and to run simulations of the heterodimers consisting of the monomer structures of MST1 (PDB: 2JO8) and the RASSF SARAH homology models from ref. 15. Each run generated 100 or more solutions that were ranked by cluster sizes and the top two ranked models were selected and analysed using naccess (http://www. bioinf. manchester. ac. uk/naccess/). Cells. COS7 cells (ECACC) were grown in DMEM supplemented with 10% fetal calf serum, 2 mM glutamine, 1 mM sodium pyruvate and 1% penicillin-streptomycin and were used for all experiments. All fluorescent constructs were transfected via electroporation. Typically, 1-1. 5 × 10 6 cells were suspended in 100 μ l homemade electroporation buffer (140 mM KCl, 8 mM NaCl, 0. 88 mM MgSO 4 , 2. 97 mM Na 2 HPO 4 , 1.
, UK) and the resulting gated images at the phosphorus screen were imaged to a cooled CCD camera (Orca ER II, Hamamatsu, Japan). The GOI gating voltage signal is synchronised and delayed with respect to the laser excitation pulses under computer control. For the work reported here, the GOI gate width was set to 1 ns and typically time-gated images of EGFP fluorescence were acquired at 5 different delays after excitation while only one time gated image (at the beginning of the decay) was acquired for the mCherry emission. The integration time of the CCD camera was set to 1-2 s per gate delay for EGFP and 5-6 s for the mCherry image acquisition such that the dynamic range of the CCD was utilised. For the optically sectioned FLIM acquisitions used to provide the data for the K D calculations, the instrument was configured to incorporate a spinning Nipkow disk unit (CSU-X1 Yokogawa Electric Corporation, Japan), as described in refs 63-65, with a 40× air objective (Olympus, LUCPLFLN 40) with an NA of 0.
6. The pulsed excitation was directed via a polarisation-preserving single mode optical fibre to the input of the spinning Nipkow disk unit and the fluorescence image was relayed onto the GOI where the time-gated images were acquired as for the wide-field configuration. In addition to the time-gated FLIM FRET data, a FLIM acquisition of a scattering sample detected at the excitation wavelength was acquired to provide an instrument response function (IRF) for the data analysis. Time-gated FLIM was also applied to a well containing only PBS in order to determine the time varying background. FLIM data acquisition and analysis. The instrument is controlled using a programme written in LabVIEW (National Instruments, USA). This controls the automatic movement of the stage, the autofocusing of each field of view, the automatic change of the excitation filters, of the filters and dichroics in the filter cube wheel, the objective lens change, the GOI gating and the CCD camera acquisition.
A "prefind" scan was implemented to image the well plate using fluorescence intensity to identify and localise cells and to acquire donor and acceptor intensity images. Specific fields of view in various wells were selected for subsequent FLIM after applying an intensity threshold. FLIM data analysis was performed using the custom written open source software, FLIMfit, described in detail in ref. 35 and freely available at www. openmicroscopy. org/site/products/partner/flimfit. For the work reported here we utilised the following capabilities of FLIMfit: cell segmentation based on donor and/or acceptor intensity; calculation of average fluorescence intensity of donor and acceptor per cell; fitting the donor fluorescence intensity decays to monoexponential and to double exponential decay models (including instrument response function (IRF) and time-varying background correction); global fitting of donor fluorescence intensity decays across multiple fields of view and wells; visualisation of FLIM data (including rendering of plate maps showing mean EGFP decay times per well and images of one field of view per well).
Acknowledgements The authors gratefully acknowledge funding from the  UK Biotechnology and Biological Sciences Research Council  ( BBSRC BB/E003621/1  and  BB/H00713X/1 ), the  UK Engineering and Physical Sciences Research Council (EPSRC Pathways  to Impact grant) and the  Wellcome Trust  ( WT 095931/Z/11/Z ). DK and SW acknowledge PhD studentships from the  Institute of Chemical Biology EPSRC funded Doctoral Training Centre.
Image Analysis and Processing Image processing was performed by 2 technicians using the MUSIC software (Liryc-Université de Bordeaux/Inria-Sophia Antipolis, France). 1] [12]  Briefly, the cardiac chambers, ventricular epicardium, ascending aorta, and coronary sinus (CS) were segmented using semi-automatic methods. 10 n patients undergoing epicardial procedures, additional segmentation was performed to extract the coronary arteries (CAs) and left phrenic nerve (PN). 11 In case both CMR and MDCT had been performed, datasets were registered prior to segmentation. 10 In ICM and NICM, the structural substrate was defined as wall thinning (WT) on MDCT and LGE on CMR. To provide anatomical substrate heterogeneity, WT areas were divided into severe WT (<2 mm) and moderate WT (2-5 mm),  6  and LGE areas were divided into dense scar (>50% maximum signal intensity) and gray zone (35-50% maximum signal intensity).
Statistical Analysis Quantitative data are expressed as the mean±SD or median [interquartile range (IQR)] based on the distribution of the values. Comparison between groups was analyzed by using unpaired Student's t-test or Wilcoxon rank-sum test. Categorical variables were compared using chi-square or Fisher exact tests. The relationship between variables was analyzed by using Pearson or Spearman correlation coefficients. Cox proportional hazards regression models were used for multivariable analysis of the predictors of VT recurrence. All tests were 2-tailed, and P < 0. 05 was considered significant. Statistical analyses were performed using the MedCalc software package, version 11. 2 (Mariakerke, Belgium).
Feasibility of Image Integration for VT Ablation The characteristics of the studied population are representative of typical cases undergoing VT ablation. 18, 19 This study was made feasible thanks to the development of dedicated software enabling the integration of relevant patientspecific data on cardiac anatomy and myocardial structural substrate. Current commercialized software only enables the integration of gross anatomy of cardiac chambers, but the segmentation of CAs and left PN and the multimodal characterization of scar are not supported. To accommodate the broad spectrum of VT etiologies we used multiple imaging modalities to delineate substrate, i. e. , WT or HA from MDCT, and LGE from CMR. These segmentation methods have been validated in past studies. 6, 10, 12 In our center, the processing of imaging data is performed by technicians, aiming at rendering in 3D the report provided by the physician.
1a ). The increase of the molecular weight of the polymerase (B40 kDa) suggests that SUMOylated polZ may contain more than one SUMO moiety. Mutation of K11 of SUMO3 to arginine (R), which prevents the formation of SUMO chains  26  , did not modify the apparent size of the modification (Supplementary Fig. 1b ), showing that it is mono-SUMOylation(s). The two Ks SUMOylated in Caenorhabditis elegans polh-1 are conserved in human polZ; however, their mutations did not prevent its SUMOylation (Supplementary Fig. 1c ). To identify the SUMO acceptor site(s), we performed in silico analysis with three SUMOylation site-prediction software programs (SUMOplot http://www. abgent. com/sumoplot, seeSUMO  27  and SUMOsp  28  ) and tested K to R mutants of the common predicted sites. We identified K163 as the SUMO acceptor site using denaturing Ni pull-down (Fig.
4a-d. (e) XPV, polZ WT and polZ K163R cells were irradiated with ultraviolet-C at the indicated doses and incubated for 72 h in medium supplemented or not with 0. 38 mM caffeine. Living cells were counted in the presence of trypan blue. Data  re expressed as the percentage of living cells compared with mock-treated cells (mean ± s. d. of four independent experiments). Rad18 nls1-460 ). Disruption of the polZ BD abrogated polZ SUMOylation, independently of the presence of a NLS (Fig. 8e, f ). Rad18 nls1-460 was able to promote polZ SUMOylation as efficiently as Rad18 WT , indicating that the last 50 aa of Rad18 were not required. Interestingly, Rad18  was able to interact with polZ (Supplementary Fig. 9c ) but failed to promote its SUMOylation, indicating that the nuclear localization of Rad18 is important.
For analysis of 53BP1 NBs or CENPA detection, cells were directly fixed in 4% paraformaldehyde and permeabilized for 10 min in PBS supplemented with 0. 5% Triton x100. Cells were immunostained with rabbit anti-53BP1 (1/300) þ mouse anti-cyclin A (1/200) or with mouse anti-CENPA (1/500), all from Abcam (#ab21083, #ab16726, #ab13939). For analysis of RPA foci, cells were pulse-labelled with 10 mM EdU for 15 min, extracted with CSK100 and fixed. EdU was detected with the Click-iT EdU Alexa Fluor 488 Imaging kit (Molecular Probes), according to the manufacturer's instructions. Cells were then stained for RPA32 (rabbit anti-RPA32, Bethyl #A300-244A, 1/2,000, detected with goat anti-rabbit AF594). Coverslips were mounted in fluorescent mounting medium (DAKO) supplemented with DAPI. Images were acquired on an Axio Imager Z1 microscope using the Axio Vision software (Zeiss).
Intensity was quantified with ImageJ software. In situ proximity ligation assay. Cells were pulse-labelled with 10 mM EdU for 5 min before pre-extraction and fixation as described above. PLA with nascent DNA was described elsewhere  69. Briefly, cells were blocked with 3% BSA in PBS. Biotin-azide was conjugated to EdU by click chemistry and cells were incubated with primary antibodies against polZ and biotin (rabbit anti-polZ 1/300, Santa Cruz H300, and mouse anti-biotin 1/6,000, Jackson ImmunoResearch #200-002-211). PLA and EdU counterstaining were performed according to the manufacturer's instructions using the Duolink In Situ Red kit (Sigma) and goat anti-mouse Alexa Fluor 488 antibody. In vitro transcription/translation of human polg and TLS assay. In vitro transcription/translation of full-length WT or mutant polZ was performed using a TNT-coupled reticulocyte lysate system (Promega) according to the manufacturer's instructions.
8), 7 mM MgCl2, 1 mM DTT, 4 mM ATP, 500 mM of dNTPs, 40 mM creatine phosphate, 100 mg per ml creatine kinase. The reaction was stopped by adding an equal volume of proteinase K-SDS (4 mg ml À 1 -2%) and incubated for 30 min at 37 °C. Purified replication products were further digested with EcoRI and PvuII restriction enzymes and analysed by electrophoresis on a polyacrylamide-7 M urea denaturing gel. Radiolabelled products were visualized and quantified after phophorimaging (Typhoon FLA9500) using the ImageQuant TL software.