dataesr/scientific-paragraphs-categorization huggingface dataset:
Introduction The industrial workshop "Antibody biosimilars"  1  was opened by Hervé Watier (CNRS UMR 7292, Université François-Rabelais de Tours, France), coordinator of the MAbImprove Laboratory of Excellence. He delivered his welcome address, starting with a quick recall of the LabEx MAbImprove 2 story. This LabEx was created in 2011 and funded by "Investment for the Future" program (French "Big Loan"). He then introduced this industrial workshop as a yearly event dedicated to real life in the biopharmaceutical industry, invited to present and to discuss current issues to academics. He invited all attendees to debate in depth on this very timely "Antibody Biosimilars" topic, and to open discussions between the industry developing biosimilars and those who develop only novel products. Finally, he reminded participants that biosimilarity is not only a matter of structure, but also of function and pharmacology, which are the main topics of the LabEx MAbImprove.
Acknowledgments This work has been funded with support by the  French Higher Education and Research ministry  under the program " Investissements d'avenir " Grant Agreement:  LabEx MAbImprove   ANR-10-LABX-53-01. The authors wish to thank individually each of the speakers who participated to the congress and who kindly reviewed the abstract of their contribution. The authors are grateful to the scientific committee, the organization committee and the sponsors for their precious help in organizing the congress. They were responsible for the large part of its success.
Maldi-MS of gel bands The protein bands were exiced from gel and digested with trypsin in ammoniumbicarbonate. Digestion and peptide extraction were performed according to standard protocols  [29]  (S1 Material and Methods). Sample Ms and tandem Ms spectra were acquired on a 4800 Proteomics Analyzer. Data analyses were performed using 4000 Series Explorer and Data explorer software. Protein identification was obtained by applying the Mascot Search Engine against the Swissprot database, taxonomy eukaryotes and implying decoy database searches. The parameters were set to mono-isotopic mass values using peptide charge +1 and the peptide mass tolerance was set to 200 ppm, with a maximum of missed cleavages of two. Methionine oxidation was set as a Variable modification; the significance tolerance threshold was set below 0.
Statistical Analysis FACS data were analysed using Flowjo software and ELISA data were translated into graphical representations using Prism software (GraphPad Prismv. 4. 0, GraphPad Software Inc. San Diego, CA). ELISA experiments were performed minimum of three times with lysates coated in triplicates. Data are presented as mean values ¡ SD. Student's t test was used to compare means. If p. 0. 05, differences were considered significant. Asterisks were used to indicate the degrees of significance (*P,0. 05, **P,0. 01, ***P,0. 001).
Anti-trypanosome Nb library construction and selection of specific nanobody fragments Gene fragments of heavy chain antibodies from the immunized alpaca were cloned into the phagemid vector pHEN4 and used to construct a Nb library containing ,2. 26610 7 individuals by transforming TG1 E. coli cells. Colony PCR showed ,80% of the clones contained the expected insert size (,700 bp). Compared binding capacity of phages from three rounds showed the highest ELISA OD readings at the third round, suggesting a progressive enrichment. Furthermore, ELISA tests with PE extracts of individual clones revealed that 39 colonies out of 49 reacted on 2 different T. evansi lysate (data not shown). VHH genes of these clones were cloned into the pHEN6 vector and sequenced for confirmation. Clones were transformed into WK6 E.
Funding: This work was supported by the  European Union / FP7 Nanotryp  ( FP7-HEALTH 2007-2. 3. 4-1 ) and the  Fund for Scientific Research Flanders (FWO). Work at the  Institut Pasteur  was funded by a  French Government Investissement d'Avenir program ,  Laboratoire d'Excellence ''Integrative Biology of Emerging Infectious Diseases''  ( ANR-10-LABX-62-IBEID ), the  Institut Carnot Maladies Infectieuses  and the  Fondation pour la Recherche Medicale. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
4 NA oil differential interference contrast (DIC) objective lens or a confocal microscope (LSM700) equipped with a 63× Plan Apochromat/1. 4 NA oil objective lens (all from Carl Zeiss). Images were acquired and analyzed with AxioVision or Zen software (Carl Zeiss). For live-cell imaging, cells were cultured in 35-mm-diameter glass-bottomed dishes (MatTek Corporation). Before analysis, Hepes was added to a final concentration of 10 mM. Video microscopy was performed with two spinning-disk confocal microscopes (UltraView VOX and UltraView ERS; Perkin-Elmer) equipped with a FRAP system (PhotoKinesis). TIRF imaging was done with a CellM system (Olympus) with a Plan Apochromat 100×/1. 45 NA objective lens (Olympus). For TIRF experiments, the laser beam was adjusted so that only a thin sheet below the coverslip (100 nm) was illuminated.
Noninvasive imaging required low laser power compensated by a relatively long exposure time. We achieved a frame rate of 2 images/s. FRAP experiments were performed as follows: a single, optically sectioned plane of the cell was imaged every second for 5 frames, and an area of 3-5 µm in size within the cell was then bleached with a laser beam. Fluorescence recovery was then followed, at a frame rate of 1 image/s. Half recovery times and immobile fractions were derived by fitting a doubleexponential model, the simplest model that reliably fitted recovery curves. Quantification and statistical analysis of immunofluorescence and live-cell imaging data We used randomly selected fields acquired with a 63× objective lens to determine the number of NEMO-positive foci. Imaris was used for spot detection.
For the quantification of NEMO and IRAK1 foci (presented in Fig. 5 ), we developed image-processing algorithms in ImageJ to remove background noise, to calibrate the detection filters, to segment the foci and nuclei, and to report the total number of foci and cell counts. The program was validated by comparing visual results with program results; error rates were estimated to be <5%. Colocalization was assessed on randomly selected fields from images, with Fiji  (Schindelin et al. , 2012)  or Imaris (Bitplane AG). The colocalization of NEMO-and p-IKK-positive foci (presented in Fig. 2, B  and C ) is reported as the percentage of NEMO channel pixels displaying colocalization above the threshold. The colocalization of NEMO and activated cytokine receptors (presented in Fig. 4 C ) is reported using thresholded Manders coefficients  (Manders et al.
, 1993; Costes et al. , 2004). Single-focus movements were tracked with the TrackMate plugin of the Fiji image-processing package. Trajectories were then exported and analyzed with MATLAB. The package specifically developed for MSD analysis is publicly available from http://www. mathworks. com/ matlabcentral/fileexchange/40692-mean-square-displacement-analysisof-particles-trajectories. In detail: the MSD function was calculated for each individual trajectory, and its log-log representation was fitted with a linear function, such that if the MSD curve could be modelled by ρ r r t a ( ) = = 2 Γ , then log log r f t 2 ( ) ( ) ( ) = was fitted with  +  log(t). We fitted individual MSD curves and discarded those for which the R 2 coefficient, reflecting the quality of the fit, was <0. 8. These fits supplied us directly with the  values indicated in Fig.
The small desorbed and ionized molecules are accelerated through an electrostatic field, and drift through a field-free tunnel until they reach the mass spectrometer detector. Molecules of different masses and charges will fly at different speeds ("time-of-flight"). The result is a spectral signature, with specific spikes. This signature is then searched for in a database for the identification of the microorganism. 6 ] [10]  The time necessary for the identification in blood is less than 5 minutes,  7, 11  and this technique can be extended to other biological fluids such as cerebrospinal fluid  12  or urine. 13 he most widespread application of MALDI-TOF-MS is bacterial identification from bacterial colonies, and one main interest is the identification of anaerobes and other fastidious organisms, which are poorly identified by current phenotypic methods.
MSL1 and MSL2 are important for Tsix expression To directly assess the functional outcome of MOF-, MSL1-, and MSL2-depletions, we studied the expression of Tsix and Xist in shRNA-treated ESCs. Unexpectedly, only MSL1-and MSL2-, but not MOF-depletion led to pronounced downregulation of Tsix both in male and female ESCs (Figure  6A ; note that in our RNA-seq data set for MSL2-depleted cells, Tsix was among the five most strongly downregulated genes). Downregulation of Tsix was accompanied by moderately elevated Xist RNA levels in MSL1-and MSL2-depleted ESCs whereas depletion of MOF yielded the most pronounced (8-15-fold) upregulation of Xist without affecting Tsix. To determine the effects on Tsix in individual cells, we next performed RNA-FISH with probes against DXPas34 and Huwe1 in female ESCs (Huwe1 was used to mark X chromosomes, for probe references see 'Materials and methods').
Antibodies For MSL1 antibody production, a GST-mMSL1 fusion protein (C-terminal, residues 254-616) was used to immunize rabbits; the final bleed was used in experiments. Antibody specificity was verified with IP and MSL1-specific RNAi followed by Western blot analysis and ChIP assay. We used several commercial antibodies: a-KANSL1 (PAB20355; Abnova, Taiwan), a-KANSL3 (HPA035018; Sigma), a-MCRS1 (11362-1-AP; Proteintech, Chicago, IL), a-MOF (A3000992A; BETHYL Montgomery, TX), a-MSL2 (HPA003413; Sigma), a-NANOG (A300-397A; BETHYL), a-OCT3/4 (sc-5279; Santa-Cruz Dallas, TX), a-REX1 (Ab28141; Abcam, England), a-ESRRB (PP-H6705-00; Perseus Proteomics, Japan), a-KLF4 (Ab72543; Abcam), a-SOX2 (AF2018; R&D Systems, Minneapolis, MN), a-YY1 (A302-779A; BETHYL), a-RNF12/RILM (16121-1-AP; Proteintech) a-GAPDH (A300-639A; BETHYL), a-NESTIN (Ab93666; Abcam), a-CTCF (Ab70303; Abcam), a-H3 (Ab1791; Abcam), a-H4 (Ab10158; Abcam), a-H4K16ac (07-329; Millipore, Billerica, MA).
The quality of the RNA was analyzed using the Bioanalyzer and samples with RIN values between 9 and 10 were used for RNA-seq. For RNA-seq analysis, cDNA libraries were prepared using the Illumina TruSeq Stranded mRNA kit with 3 μg DNase-treated samples. ambiguously mapped reads using samtools  (Li et al. , 2009). We also removed reads mapping to the mitochondrial genome and 'random' chromosomes, as well as known major satellites and duplicated genome regions to avoid coverage biases. For normalization procedures, several modules of the deepTools suite (https://deeptools. github. io) were used  (Ramirez et al. , 2014). To ensure a fair comparison between all data sets, first, the GC bias of all mapped reads was determined and, if necessary, corrected so that input and ChIP samples had similar GC distributions of their reads (correctGCbias module).
In addition, all aligned read files were corrected for sequencing depth using the signal extraction method proposed by  Diaz et al. (2012)  and normalized to the cell-type-specific input (bamCompare module). Peak calling and replicate handling MACS (version 1. 4) was used for peak calling on every sample individually and on the merged files of two replicates  (Zhang et al. , 2008). Only peaks present in both replicates were considered, using the borders and summits defined by peak calling results for the merged replicates. In addition, peaks with -10log 10 (p-values) lower than 50 and false-discovery rate values greater than 0. 1% were excluded from down-stream analyses.
The 3 clusters displayed in the lower part of Figure  4 -figure supplement 2B were obtained similarly: first, a matrix was generated that contained the normalized ChIP-seq values of MOF, p300, H3K4me1 and DNase hypersensitivity sites for all regions of cluster D that did not overlap with ESC enhancers. The regions were then scaled to 1400 bp and mean values were computed for 50 bp bins using the computeMatrix module of deepTools  (Ramirez et al. , 2014). Further processing was done as described above; the resulting dendrogram was pruned to k = 3 and the enrichments of the different factors were computed and visualized for 10 kb regions using the heatmapper module of deepTools.
Acknowledgements We would like to thank  T Jenuwein  from the  MPI-IE, Freiburg  for providing the WT26 ES cell line and  U. Riehle  from the  Deep Sequencing Unit  of the  MPI-IE, Freiburg  for sequencing all samples. We would also like to thank  P Kindle  ( MPI-IE, Freiburg, Imaging facility ),  S Toscano , and  M. Shvedunova  for help with imaging. TC is especially grateful to  A Chatterjee  for providing support and insightful discussions. We thank all members of the labs for helpful discussions. This work was supported by  DFG-SFB992  and BIOSSII awarded to AA and RB; DFG-SFB746 awarded to AA. AA is also a member of the  EU-NoE-EpiGeneSys.
, 2008) : we then verified here that dgCX3CL1 showed a BRET at an amplitude similar that of native CX3CL1 (supplementary material Fig. S1 ). Taken together, these data show that the shortening of the mucin stalk of CX3CL1 and the mutation of the potentially glycosylated residues of the mucin stalk are both deleterious for the adhesive potency of the chemokine to a larger extent than the absence of the cytosolic domain. To understand at the molecular level the reasons underlying this decreased adhesion, we tested three possible causes: lesser accessibility of the CD, change in the supramolecular organization via the cytoskeleton, and impairment of CX3CL1 lateral diffusion. The mucin stalk is maintained extended by glycosylation to present the CD to the receptor COS7 cells transiently transfected with the three different CX3CL1-EYFP chimeras and labeled with anti-CX3CL1-PE antibody were analyzed by FACS.
The pre-and post-bleach images were monitored at low laser intensity (10 to 15% of full power). The fluorescence in the ROIs was quantified using the LASAF Leica software. The analysis of the curve of the resulting fluorescence recovery as a function of time yielded the recovery times that were used to obtain the diffusion coefficients of the diffusing species. The diffusion coefficient is equal to D~r 2 4t where ''r'' is the radius of the circular beam and ''t'' is the time constant obtained from the fit of the curve  (Soumpasis, 1983). In our experiments, each cell was bleached over three different circular regions with diameters of 3, 4, or 5 mm. The characteristic recovery times (t) and fluorescence recovery plateau (F p ) were calculated by fitting the fluorescence recovery curves as previously described  (Soumpasis, 1983; Braeckmans et al.
Flow cytometry The expression of different EYFP-CX3CL1 chimeras was analyzed by flow cytometry using a FACSCalibur (Becton Dickinson, Le Pont de Claix, France) and the FlowJo software (TreeStar, Ashland, OR, USA). Transiently transfected COS-7 or CHOldlD cells were harvested from culture flasks through treatment with cell dissociation buffer (Life Technologies, Saint Aubin, France), washed in PBS, and centrifuged. The cells were fixed in 0. 5 mL of 4% paraformaldehyde in PBS for 10 min on ice, washed with PBS/0. 01% NaN 3 , and incubated at a density of 2. 10 6 cells per mL with a phycoerythrin (PE)-conjugated anti-hCX3CL1 monoclonal antibody (R&D Systems) or a PE-conjugated IgG1 isotype control (both at a concentration of 1. 25 mg/mL Ab in PBS with 0. 1% BSA and 0. 01% NaN 3 ) for 1 h on ice.
Because the ICT is a manual test, the cut-off has to be determined by visual observation. In order to obtain objective ICT results for this study, two different persons independently inspected the bands that appeared on the ICT device. After that, for the positive tests, an index intensity was calculated to enable comparison of the test results. For all samples, a picture was taken using a ChemiDoc apparatus (Bio-Rad laboratories, Hercules, CA, USA) and the intensities of the control and test bands and of the background membrane were recorded, after exposure to Epi-white light (Quantity One 4. 6. 5 software). The relative intensity index was calculated so that batches used for the same sera could be compared. The index intensity calculation in our study differs from that of Sako et al. [19]  because there is no immunochromato-reader in the Chrono-Environnement Laboratory at the Faculty of Medicine and Pharmacy, Besancon, France.
Acknowledgements. We are very grateful to  M. -P. Faivre ,  F. Grenouillet , and  S. Itoh  for technical support and to  S. Rocchi  for the double reading of the ICT tests. This study was supported by the  CNRS/JSPS Bilateral Research Project  and the  International Research Fund  from the  JSPS  to  Pr. A. Ito  ( 21256003 ). We are grateful to  Lois Rose  for editorial assistance. We dedicate this joint paper to  Mrs. Hikari Ito.
The sequences were edited and aligned using the MEGA software, version 5 (http://www. megasoftware. net). Most of the Hcp100 sequences of H. capsulatum were previously reported in González-González et al. [6] , and the other sequences were deposited in a database [GenBank: from JX091346 to JX091370 accession numbers]. All sequences generated by both molecular markers for Pneumocystis spp. were reported by Derouiche et al. [16]  and Akbar et al. [14]. The sequences of the specific markers for each pathogen (i. e. , Hcp100 for H. capsulatum and mtLSUrRNA or mtSSUrRNA for Pneumocystis spp. ) that were obtained in the same animal were the main inclusion criterion for considering bat co-infection.
Acknowledgements  Dr. M. L. Taylor  thanks  L. J. López  and  A. Gómez Nísino  from the  Instituto de Ecología, UNAM , for their help with accessing several Mexican caves, with bat captures and taxonomic determination, and acknowledges the extraordinary help of  Dr. R. Bárquez  from the  Instituto Lillo  to access the  Dique Escaba ,  San Miguel de Tucumán, Tucumán, Argentina. The authors thank  I. Mascher  for editorial assistance. The present research was supported by the following grants:  SEP-CONACYT-ANUIES-ECOS-M05-A03  ( Mexico-France ) and  DGAPA-PAPIIT -Ref. No. IN-203407-3 ,  UNAM, Mexico. A. E. González-González  thanks the  Biological Science Graduate Program of UNAM  and the scholarship of  CONACYT (Ref. No. 23492 ).
2 D ). Finally, the cloned   breaks were mostly located in the 3 part of the   region similar to breaks in the downstream part of S 1 and S 3 for cCSR junctions (Fig. 2 D ). The increased representation of DNA breaks in the 5 part of S  and the 3 part of   or S  might involve a methodological bias whereby PCR cloning of the shortest recombined DNA segment would be favored. Identical phenotype of IgD + IgM  B cells in 3RR-deficient and wt mice Flow cytometry analysis indicated that IgD + IgM  B cells accounted for only 0. 2% of total MLN cells in wt mice (Fig. 3 A ). Consistent with published human data  (Chen et al. , 2009) , a low percentage of IgD + IgM  B cells expressed CD138 (syndecan-1), a hallmark of mature plasma cells (Fig. 3, B  and C ). Furthermore, the vast majority of IgD + IgM  B cells did not express surface B220, CD11b, CD19, CD21, and CD23 markers which (A) DNA dot plot analysis of the genomic sequence encompassing a fragment from the E enhancer to the  exon 2 from a 129 wt mouse (GenBank accession no.
Study design We carried out a multicentre cross-sectional study on sputum samples from 58 CF patients recruited from CF centres in Montpellier (n=23), Nancy (n=20) and the Necker Hospital in Paris (n=15). This study was approved by the regional ethics committee (Nimes, registered under number 2011-A01197-34) and declared to ClinicalTrial. gov (no. NCT01818206).
Molecular genotyping of P. aeruginosa strains Five colonies from sputum samples 03, 04 and 33 were chosen for the molecular analysis (see Supplementary Excel file, genotyping tab). The 16S RNA gene was amplified as previously described [21], with a standard PCR kit (MP Biomedicals), from a single colony. The clonality of these 15 isolates was assessed by repetitive extragenic palindromic-polymerase chain reaction (REP-PCR) adapted to a semi-automated format (DiversiLab TM system, bioMérieux) and fingerprinting profiles were analysed with web-based DiversiLab TM software v. 3. 4 (bioMérieux).
The well recorded worldwide distribution of avian malaria (MalAvi Database,  [83] ), however, provides an unparalleled opportunity to test this hypothesis. We predict that tropical lineages should exhibit lower potential for plasticity and lower response to external stimuli (such as mosquito bites) than temperate lineages. It is important to investigate further the role of the quantity and the quality of the mosquitoes on the reactivation of dormant parasites. Quantity-wise, the threshold number of mosquitoes required for the reactivation to take place should be established. Billingsley et al. [39]  reported an effect of the amount of mosquitoes biting on gametocytaemia of rodent malaria. Quality-wise, it would be interesting to study if plasticity is specific to particular vector species.
Statistical analyses The statistical analyses were run using the R software (v. 2. 14. 0). Analyses were carried out separately for each exposure session. Variation in parasitaemia (log-transformed (RQ+1)) was analyzed using linear mixed-effect models (lme function, nlme package) with bird as a random effect to account for the repeated sampling of individual hosts. A generalized linear mixed-effect models GLMM (glmer function, lme4 package, binomial distribution) was carried out to study variation in gametocytaemia (proportion of gametocytes). Bird and time were included as random and fixed factors, respectively. Variation in the infection prevalence (proportion of individuals harbouring at least 1 oocyst) and the oocystaemia (number of oocysts, only for infected mosquitoes) was analysed using GLMMs (glmer function, lme4 package, with binomial and Poisson distributions, respectively).
(D) Viability of primary pDC during neutralization assay: primary pDC were stained with Live/ Dead to ensure viability of the cells. Means of the percentage of alive CD123-positive cells is represented for non-infected control (Mock), HIV-1 BaL infected cells (HIV), infected cells treated with the reverse transcriptase inhibitor AZT (5 mM), and cells were infected in the presence of various concentrations of anti-HIV Abs. (E) Maturation of primary pDC during neutralization assay: maturation of primary pDC was analyzed by CD83 labeling. Mean of the CD83 MFI (mean of fluorescence intensity) measured in each experiment is represented for pDC treated under the same conditions described in (D). One-way ANOVA showed no significant difference between these conditions. Data are means 6 standard deviation (SD) of independent experiments performed with primary pDC from at least three different healthy donors.
3C ). Table  1  | Inhibitory activity of NAb and NNIAb when primary pDC/MoDC were used as HIV-1 BaL target cells. IC 90 : concentration (mg/ml) of Ab necessary to reduced by 90% the number of infected cells; -, no inhibitory activity detected at 100 mg/ml of Ab. NNNIAb, nonneutralizing non-inhibitory anti-HIV-1 Ab. Values are the mean of 3-7 different independent experiments performed on cells purified from different independent healthy blood donors Altogether, these data demonstrated that FccRIIa at the surface of pDC was not involved in the inhibition of HIV-1 by NAb. between 20 and 600 ng/ml depending on the donors (Fig. 4 ). IFN-a production was strongly inhibited in the presence of anti-gp120 NAb b12 at concentrations over 10 mg/ml (Fig. 4A ). The mutant version of the b12 Ab, LALA, similarly inhibited IFN-a production (Fig.