dataesr/scientific-paragraphs-categorization huggingface dataset:
6 A ˚, b = 86. 6 A ˚, and c = 45. 1 A ˚. A complete data set was collected to a resolution of 2 A ˚on the ESRF beamline ID23. 2. Crystals of the ternary complex WDS 50-361 with NSL1 peptide (714-GSDYLCS RARPLVLSE-729) and NSL2 peptide (155-YRDDDEIDVVSPH-166) belong to the space group P2 1 2 1 2, with unit cell dimensions a = 81. 5 A ˚, b = 86. 2 A ˚, and c = 47. 6 A ˚. A complete data set was collected to a resolution of 2. 3 A ˚on beamline BM14 at the ESRF. The data were processed using XDS (Kabsch 2010). The structures were solved by molecular replacement with Phaser (McCoy et al. 2005) using the structure of WDR5 (Protein Data Bank [PDB] code 2G99).
Acknowledgments We thank the  Grenoble European Molecular Biology Laboratory (EMBL)-European Synchrotron Radiation Facility (ESRF)-Institut Laue-Langevin (ILL)-Institut de Biologie Structurale (IBS) Partnership for Structural Biology (PSB)  for access to structural biology instrumentation-notably L. Signor of the  IBS  for his help with mass spectrometry, and the  High-Throughput Crystallisation Laboratory (HTX) group of EMBL Grenoble  for performing initial screening crystallization trials. We thank  A. Palencia  for help with the ITC, and  K. Dzeyk  of  EMBL Heidelberg  for help with mass spectrometry. We thank  M. Shvedunova  and  H. Holz  for the initial help with baculoviruses. We thank  S. Chlamydas  and  T. Lingg  for technical support, and other members of both laboratories and  Ramesh Pillai  for useful advice and fruitful discussions.
We thank  R. Sawarkar  and  R. Paro  for providing the Trx antibody. We thank the  ESRF-EMBL Joint Structural Biology Group  for access to and assistance on the ESRF synchrotron beamlines. This work was supported by the  EU   FP7-funded Network of Excellence EpiGeneSys  awarded to S. C. and A. A. , and  SFB746  and  SFB992  awarded to A. A. A. A. is also part of the  BIOSS II excellence initiative.
In recent work, an extrinsic fiber-based Fabry-Perot interferometric sensor has been developed for small displacement measurement without directional ambiguity  [5]. In this work, we, however, exploited the fiber interferometer with a quadrature phase condition generated optically subject to three different excitation regimes (sinusoidal, triangular, and square waves) for investigating the dynamic displacement analysis. These waveforms were induced by a classical function generator at an excitation frequency of about 125 Hz but varied the amplitude for driving a mechanical vibrator. To obtain the displacement information, a demodulation program written in MATLAB was developed for plotting the displacement curve with a resolution of λ/64 based on the modified zero-crossing fringe counting  [16].
Retro-reflective surfaces have been used to ensure optimum retro-injection of the sensing beam back into the fiber arm. However, the proof-of-concept of our proposed technique was then demonstrated by using a program developed in MATLAB for simulating and analyzing the dual optically quadrature phase-shifted interference signals (E x and E y ). Consequently, the final demonstrated results were then plotted out as a displacement curve for the sensor with and without optical manipulation of the states of polarization of two orthogonal fields, as clearly illustrated in Fig. 2. For non-ambiguous measurement, the time difference between the two interference fringes (∆t) was used to indicate the target direction, and ∆t (>0 = movement of target away from sensor and <0 = target approaching sensor) has been pre-selected to represent the corresponding phase difference (lead or lag) between the first and second channels on the left and right halves of the oscilloscope trace, respectively.
This has the consequence that the program could not further distinguish these points. This effect easily contributes to the wrong positional plotting of the displacement curve leading to the measurement errors. To improve the inherent errors due to data overlapping, we employed zero-phase digital filtering in our algorithm which was written in MATLAB to remove the system noise from the output interference fringes. The algorithm is illustrated in Fig. 5 , showing only the major processing steps such as calculating a mean intensity value, counting the number of fringes, plotting the displacement measured, and also determining the target directional movement.
Hence, two sets of interference signals due to the E x and E y waves were generated and made to interfere with their reference pairs reflected off the fiber-air interface at the photodetectors, respectively. The detected interference signals were then displayed on a digital oscilloscope, and the fringes were tracked via a dedicated computer to extract the desired displacement information simultaneously. A commercially-available reference (Philtec D63 displacement sensor with a far-side sensitivity of -2. 786 mV/µm and a far-field noise limit of 80 nm) was used as the reference for comparison of the data obtained from the fiber interferometer.
Multi-parton interactions (MPI) are simulated in both PYTHIA and HERWIG. The free parameters describing MPI are obtained from tunes  [32]  to measurements in pp collisions at the LHC. The PYTHIA 6 generator with the tune Z2*  [33]  uses the CTEQ6L1 PDF set  [34]  and applies a new model  [35]  where MPI are interleaved with parton showering. The PYTHIA 8 generator is used with the tune 4C  [36]  based on underlying event data from the LHC, using the CTEQ6L1 PDF set. It implements a more sophisticated model for MPI with respect to PYTHIA 6, by introducing color reconnection and rescattering between the partons  [37]. The HERWIG++ generator tuned to LHC data (tune LHC-UE-EE-3  [29, 38] ) with the MRST2008LO** PDF set  [39]  is also used for comparison. The data are also compared to perturbative NLO dijet QCD predictions obtained with the POWHEG package  [40, 41].
PYTHIA and HERWIG use a 2→2 O(α 2 S ) ME, SHERPA uses up to 2→3 and MADGRAPH uses up to 2→4 MEs. POWHEG is a NLO prediction for dijets, using 2→2 and 2→3 MEs, but the selection of four-jet final states requires at least one jet originating from the parton shower. In MADGRAPH, the four jets can originate from the matrix element, while in all the other simulations at least one jet must come from the parton shower or MPI. Since exactly four jets are required in the selection (and a veto is applied on additional jets), only calculations that simulate jets beyond the four selected jets can be used for comparison with our data. The detector response is simulated in detail by using the GEANT4 package  [52]. All simulated samples are processed and reconstructed in the same manner as done for collision data.
Conclusions Measurements of observables for the production of exactly four jets have been performed based on data collected with the CMS experiment in 2010 with an integrated luminosity of 36 pb -1. The cross section for a final state with a pair of hard jets with p T > 50 GeV and another pair with p T > 20 GeV within |η| < 4. 7 is measured to be σ(pp → 4j + X) = 330 ± 5 (stat. ) ± 45 (syst. ) nb. The differential cross sections as a function of p T and η of each of the four jets together with the normalized differential cross sections, as a function of correlation variables ∆φ soft , ∆ rel soft p T , and ∆S, are compared to several theoretical predictions. The models considered are able to describe the differential cross sections only in some regions of the phase space. Although the predictions of the differential cross sections at large transverse momenta are reasonable, significant differences arise at smaller p T especially for the subleading and soft jets.
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 centres and personnel of the Worldwide LHC Computing Grid for delivering so effectively the computing infrastructure essential to our analyses. Finally, we acknowledge the enduring support for the construction and operation of the LHC and the CMS detector provided by the following funding agencies:  BMWF  and  FWF (Austria) ;  FNRS  and  FWO (Belgium) ;  CNPq ,  CAPES ,  FAPERJ , and  FAPESP (Brazil) ;  MES (Bulgaria) ;  CERN ;  CAS, MoST , and  NSFC (China) ;  COLCIENCIAS (Colombia) ;  MSES  and  CSF (Croatia) ;  RPF (Cyprus) ;  MoER ,  SF0690030s09  and  ERDF (Estonia) ;  Academy of Finland ,  MEC , and  HIP (Finland) ;  CEA  and  CNRS/IN2P3  (France);  BMBF ,  DFG , and  HGF (Germany) ;  GSRT (Greece) ;  OTKA  and  NIH (Hungary) ;  DAE  and  DST (India) ;  IPM (Iran) ;  SFI (Ireland) ;  INFN (Italy) ;  NRF  and  WCU (Republic of Korea) ;  LAS (Lithuania) ;  CINVESTAV ,  CONACYT ,  SEP , and  UASLP-FAI (Mexico) ;  MBIE (New Zealand );  PAEC (Pakistan) ;  MSHE  and  NSC (Poland) ;  FCT (Portugal) ;  JINR (Dubna) ;  MON, RosAtom, RAS  and  RFBR (Russia) ;  MESTD (Serbia) ;  SEIDI  and  CPAN (Spain) ;  Swiss Funding Agencies (Switzerland) ;  NSC (Taipei) ;  ThEPCenter, IPST, STAR  and  NSTDA (Thailand) ;  TUBITAK  and  TAEK (Turkey) ;  NASU (Ukraine) ;  STFC  ( United Kingdom );  DOE  and  NSF (USA).
Santiago Lamas, CIB) were collected and used for control and patients human keratinocytes infections (three controls and three patients). Two rounds of seven hours infections were performed and keratinocytes were grown until confluence with keratinocyte medium (percentage of infection was higher than 75%). GFP positive cells were analyzed by flow cytometry (LSRFortessa, BD Biosciences, USA) either in basal state or after addition of 12. 5 μM hydrogen peroxide solution. Cells were excited with 405 and 488 nm lasers and the ratio of emissions in the green channel was calculated. Flow cytometry data were analysed using FlowJo version 7. 6. 1.
(g-i) Malondialdehyde (MDA) levels were measured by HPLC-UV in SK1 (g), SK2 (h), and SK3 (i) and their matched controls. Results represent the means and SD from two independent experiments in triplicate samples. *p < 0. 05: statistically significant difference from control value, after t-student test. assess mitochondrial function, the membrane potential was studied in control and KS keratinocytes using the JC-1 probe. The analysis showed a significant reduction of the membrane potential in KS cells compared to controls as determined by the red-to-green JC-1 dye shift (Figure  4c -e and Additional file 2: Figure  S3 ). Overall, our data indicate that mitochondria in KS keratinocytes are not only altered in structure, but also in their distribution and functionality.
Acknowledgements FL was supported by grants from  Instituto de Salud Carlos III  ( PI11/01225 ) and  Comunidad de Madrid  ( S2010/BMD-2359 ; SKINMODEL). MDR was supported by grants from the  Science and Innovation Ministry of Spain  ( SAF2010-16976 ),  Comunidad de Madrid  ( S2010/BMD-2420 ; CELLCAM), GENEGRAFT -contract  N°HEALTH-F2-2011-261392  and  CIBERER ACCI 13-714/ 172. 04. MG is supported in part by  ERA-NET  grant:  E-Rare-2  (SpliceEB). EZ was in part supported by a fellowship from  CIBERER  and  SAF2010-16976. We are grateful to  Blanca Duarte  for her excellent technical support and to  Dr. Rafael Garesse  from  CIBERER  for helpful scientific discussion and advice.
S1B  and Video S1). Device fabrication. Microfluidic devices were fabricated with PDMS (Momentive Performance Materials -RTV615) by conventional multilayer soft lithography techniques  [24] [25] [26]  using two layers and the push-down approach. Device control. Pressure for the control lines was switched between 0 and 30 psi using microsolenoid valves (SMC) and controlled with a custom 32-bit breakout board via NI-cDAQ chassis with NI 9477 module (National Instruments). The software for both manual control and automated switching of media types at specified time points was written in LabVIEW (National Instruments).
Microscopy All images were acquired using a motorized Leica DMI 6000B microscope with a Leica HCX PL FLUOTAR, 63x/0. 70 corr, air objective and Roper Scientific NTE/CCD-512-EBFT-GR-1 camera (S/N: A040110). Fluorescence illumination was achieved using an Osram HXP-R 120W/45C VIS Mercury short-arc reflector lamp at minimum intensity. The equipment and microfluidics device were kept at constant temperature (30uC) by surrounding the microscope apparatus with an incubation chamber (Leica tempcontrol 37-2 digital). The microscope was placed on a Vibraplane (Kinetic Systems) anti-vibration table. Image acquisition was driven by Metamorph 7. 5 software (Molecular Devices). Images were acquired in two different ways. For images acquired at 60 sec intervals over 14 hours, each time point consisted of one image acquired in the fluorescent channel that was complemented by a stack of 40 images (0.
Image Analysis Custom software for automated quantification of cells containing p-bodies (Fig. 1D ) was developed using MATLAB (Mathworks, Natick, MA). This software detects cells and p-bodies from the bright field and fluorescence images, respectively, and quantifies the number of cells that contain a p-body. First, spots are detected from fluorescence microscopy images using a modification of a band-pass filtering based detection method  [27]. The band-pass filtering is implemented as a Difference of Gaussians (DoG), where difference of two low-pass filtered images was taken and the resulting difference image was thresholded into a binary image. The DoG filtering is controlled by setting two Gaussian low pass filters. The filter widths  (3 and 9)  were determined empirically such that the resulting image contains only the spots, and thus the thresholding could be done with a constant value determined experimentally for each image set.
Images were first analyzed manually by tracking p-bodies with the MtrackJ plugin for ImageJ  [30]. For the automated high throughput analysis, fluorescent foci were identified using customized MATLAB (Mathworks, Natick, MA) scripts. Briefly, fluorescence microscopy images were analyzed to coarsely isolate individual foci using a watershed-based segmentation algorithm  [31] , then the position and size of each focus found was determined using a Gaussian point-spread fitting function. False-positives were removed by assigning a score to each focus proportional to the ratio between peak intensity and standard deviation of the fitting function, such that only bright, well-localized foci were kept for analysis. All image analysis scripts are freely available upon request.
Data Analysis To characterize p-body movement, the segmented individual pbody trajectories within single cells were processed using in-house developed software that was implemented in C++ and statistically evaluated using the R environment (version 2. 15. 0). The image extracted data structure was consistent with the interpretation of movement as a random walk in 2 dimensions. To split data points into separated clusters, we applied the k-means clustering algorithm of the R package (R-clv-0. 3_2-1 RPM for x86_64) and correlated the cluster affiliation of each spatial coordinate with its corresponding observation time. The resulting temporal cluster affiliations allows for quantifying transitions between clusters by the reversibility rate. Cluster betweenness, as a measure of how separated the identified clusters are, is defined by J 4 = tr(S b )/tr(S w ) where S b and S w are the between-class matrix and within-class matrices, respectively  [32].
For biophysical interpretation, the extracted trajectories were processed by the in-house developed pipeline with respect to the step size of the considered random walk, velocities and temporal resolved distance of the p-body from the bud. To ensure stationarity, we increased the sample rate from one image per minute to one image per 10 seconds. Step size and velocities were directly calculated from two successive spatial coordinates and not estimated from assumed distributions. To compare p-body movement statistically across different granules of diverse cells and different strains, the mean square displacement (MSD) and related diffusion coefficient  [33]  were individually calculated and averaged. Statistical significance was tested by Kolmogorov-Smirnov test using R. All data analysis scripts are freely available upon request.
Data is from the high resolution imaging experiments as described in the main text and Figure  3. (TIF) Figure  S4  Area of wild-type daughter cells depending on PB status. Area of cells that had received a PB (blue), had not received a PB but later formed one de novo (gray), and completely lacked a detectable PB (red). Area was calculated immediately prior to the emergence of the first bud from these daughter cells (as a measure of the maximum growth of that cell). The population of cells that did not received a PB during cell division was smaller than cells that did received a PB (p = 0. 029) or formed a PB de novo (p = 0. 068). (TIF) Images of a myo4D haploid strain expressing Edc3-GFP acquired every 60 seconds during 161 min. Images in Fig. 3A  were extracted from this series. Part II: P-body movement in a she3 deletion strain.
A neighbour-joining (NJ) tree was constructed using PAUP* software version 4. 0. The Hasegawa, Kishino & Yano model with gamma distribution was selected using the Modeltest 3. 7 software. The NJ tree was evaluated by bootstrap analysis of 1,000 replicates. Novel nucleotide sequences identified in the present study were deposited in GenBank under the accessions JX184913-JX184924. Of 425 patients who were invited to take part in the study, 402 (94. 6%) agreed to participate. The study population ranged in age from three-86 years (average 44. 1 years). Most patients were males (71. 9%) and non-white (65. 9%). Among adults (≥ 15 years old), 42% were single, 63. 5% reported a familial income of US $300 and 79. 8% had received nine years or less of formal education. Among the 402 TB patients, six (1.
EXPERIMENTAL PROCEDURES Yeast Two-hybrid Screening-Yeast two-hybrid system Cyto-Trap (Stratagene), also designated Sos recruitment system, which was adapted to identify PTF1a-interacting proteins was used. pSos vector (Stratagene), was modified using the Gateway vector conversion system (Invitrogen). PTF1a cDNA was transferred from the pENTR/FLAG-PTF1a vector into pSos vector by recombination using Gateway cloning technology (Invitrogen). pSos-PTF1a was used as bait to screen a human testis cDNA library (catalogue no. 975205, Agilent) constructed into the pMyr vector. After co-transfection into Saccharomyces cerevisiae strain cdc25H, 5 ϫ 10 6 clones were screened, and several positives were identified. All clones were PCR-amplified. Their sequences were identified by comparison with the GenBank TM repertoire.
All yeast transformations were done by the standard lithium acetate method. The CytoTrap screening was performed as previously described  (29). Positive clones were grown, plasmids were isolated using Wizard Plus SV Miniprep kit (Promega), and sequencing was carried out using the services of Genome Express. Identification of inserts was done by database searches at the NCBI BLAST Network Service. Cell Culture-HEK-293T cells, HEK-293FT cells, and AR42J cells (clone B13) provided by Prof. Timo Otonkoski (University of Helsinki, Helsinki, Finland) with the permission of Dr. Itaru Kojima (Gunma University, Maebashi, Japan) derived from an azaserine-induced pancreatic acinar tumor and acinar pancreatic 266. 6 cells (derived from a mouse tumor induced with an elastase I/SV40 (simian virus 40) T-antigen fusion gene) were used.
The cells were cultured in DMEM 4. 5 g/liter D-glucose (Invitrogen) supplemented with 10% (v/v) fetal bovine serum, nonessential amino acids, 50 IU/ml penicillin, and 50 g/ml streptomycin in a 5% CO 2 and 95% humidified atmosphere at 37 °C. Plasmids-Full-length human TRIP12 cDNA (accession number D28476) was obtained from the Kazusa DNA Research Institute  (30). TRIP12 cDNA was subcloned into Gateway pcDNA TM -DEST47 vector that contains a GFP tag (pDEST47) (Invitrogen). Full-length human PTF1a cDNA was subcloned into pcDNA3. 1 vector. For the different deletion mutants of TRIP12, DNA sequences corresponding to different regions were amplified by PCR with appropriate primers (Table  1 ) from the above constructs and subcloned into pcDNA™-DEST47 vector. The TRIP12-C1959A mutant with a cysteine to alanine substitution at the conserved cysteine 1959 and the PTF1a mutants with a lysine to alanine substitution on lysine 290, 312, or both were generated by introducing a point mutation using QuikChange kit (Stratagene) according to the manufacturer's instructions.
Acknowledgments-We thank  R. J. MacDonald  and  G. Swift  ( University of Texas Southwestern Medical Center, Dallas, TX ) for the HEB and mouse Rbpsuh-L plasmids; FX Real ( CNIO, Madrid, Spain ) for the 6XA26-Luc reporter construct;  R. F. Kikuno  and  O. Ohara  ( Kazusa DNA Research Institute, Chiba, Japan ) for TRIP12 clone; and  C. Lafargues  ( INSERM U1037, Toulouse, France ) for technical assistance.
Data Collection Data on history, physical findings, and laboratory investigations were obtained by retrospective medical record review using a standardized protocol, as described. 19 The project was approved by the CHUM Research Ethics Committee. Written consent was obtained from treating physicians to communicate with and examine patients for further data collection. For the present study, chart review was extended until August 2013. The focus of data collection was the description of the DM features of the cohort. Specifically, we recorded the extent and natural history of the DM rash, the presence of adermatopathic DM, the appearance of DM-type calcinosis on follow-up, the presence of perifascicular atrophy on muscle biopsy, the appearance of cancer within 3 years of the diagnosis of myositis and death.
Serum Autoantibodies Coded serum samples were biobanked at À80 °C, and all studies for autoantibodies were done without knowledge of clinical data or diagnosis. Antinuclear autoantibodies and anticentromere autoantibodies were determined by indirect immunofluorescence on HEp-2 cells (Antibodies Inc. , Davis, CA), and anti-topoisomerase I by ELISA, as described. 10 ddressable laser bead immunoassay (ALBIA) allowed detection of autoantibodies to Jo-1, U1RNP, topo, Ro (Ro60 + Ro52), La, and Sm. The assay was performed by 1 of us (MJF) at the Mitogen Advanced Diagnostics Laboratory (http://mitogen. ca), Calgary, Alberta, Canada. 10 8] [19]  These immunoassays detect all of the described antisynthetases (Jo-1, PL-7, PL-12, OJ, EJ, KS, Tyr, and Zo), anti-PM-Scl, anti-SumoAE, anti-RNA polymerase III, anti-Th/To, anti-U2RNP, anti-U3RNP, anti-U5RNP, anti-SRP, anti-Mi-2, anti-p155/140, and anti-MJ.
Statistical Analysis Chi-square analysis was performed for frequency comparisons among subsets (using the Fisher 2-tailed exact test, where applicable). Positive (PPV) and negative predictive values (NPV), odds ratios (OR), and likelihood ratios were calculated using InStat and Prism 6. 0 softwares (GraphPad Software Inc. , San Diego, CA). The Mann-Whitney U test was used for comparison of group means. Kaplan-Meier curves were constructed to estimate survival, and cumulative survival curves were compared using the log-rank statistic (Cox-Mantel), as described. 15 The effects of age, sex, and AIM subsets on survival were assessed using Cox proportional hazards regression analysis using WinSTAT software (R. Fitch Software, Bad Krozingen, Germany). 15.