dataesr/scientific-paragraphs-categorization huggingface dataset:
In order to identify more relevant sequences, the Spider algorithm from PEAKS Studio software was used to find additional mutations or to correct the sequences. This algorithm corrects the sequences stored in transcriptomic database with de novo sequences based on MS/MS spectra, which allowed to identify post-translational modifications (PTMs) and mutations. Minimum ion intensity for mutation and PTMs was set to 5%, and ALC score ≥ 90 for de novo sequences leading to low precursor mass error in order to identify reliable PTM's and potential mutations.
2) into oocytes was performed using a third microelectrode (in order to eliminate any Ca 2+ -activated Cl current). Under these conditions uncontaminated Ba 2+ currents can be recorded. Ba 2+ currents were elicited by series of depolarizing steps of 400 ms duration from a holding potential of -100 mV, to 10 mV every 10 s. Voltage-protocol and ionic currents were generated and recorded using the Clampex software (pClamp, ver 7. 0, Axon Inst) (Molecular Devices, San Jose, CA, USA). Venom solution to be tested were prepared just prior to the experiment by adding the desired concentration in the BANT10 physiological solution. The different concentrations of venom (0. 01, 0. 1, and 1 µM) were then applied manually in a static bath using a pipette delivering a dose from about 20 µL. The effect of administered venom was measured when steady state was reached (after about 1 to 2 min, i.
Lymphoid, myeloid cells and tumor cell digests from tumor tissue were assayed using flow cytometry or quantitated using a cytometric bead array. Tumor density, necrotic and viable areas were quantitated using the ImageJ software. Results In a discovery-driven effort to address these problems we introduce a heretofore unrecognized binary complex comprizing SEG/SEI SAgs linked to the endogenous human MHCII HLA-DQ8 allele in humanized mice. By contrast to staphylococcal enterotoxin A (SEA) and staphylococcal enterotoxin B (SEB) deployed previously in clinical trials, SEG and SEI does not exhibit neutralizing antibodies in humans or TNFα-mediated toxicity in humanized HLA-DQ8 mice. In the latter model wherein SAg behavior is known to be 'human-like', SEG/ SEI induced a powerful tumoricidal response and longterm survival against established melanoma in 82% of mice.
HLA-DQ8 tg mice received 2. 5×10 5 live B16-F10 cells IP on day 0, followed by the treatment with SEG/SEI, 50 µg of each, on days 6 and 9. Controls were inoculated with tumor but received no treatment. On day 13, tumors were excised and assayed for (A) CD3 +CD8+cells, (B) CD8 + granzyme B + cells, (C) CD25 + FoxP3 + cells, (D) CD11b + Gr1 + cells. ANOVA with Tukey post test. n=3. *P<0. 05, **p<0. 01,. Ratio of CD8 + granzme B + cells to CD25 + Foxp3 + cells ≥10:1 (n=4, p=0. 01) and ratio CD8+ granzyme B+ cells to CD11b+GR1+cells=3. 9:1 (n=4, p=0. 03). Data expressed as mean±SD, Student's t test, two tailed. ANOVA, analysis of variance; ns, not significant. Open access efficient in chemotaxis of activated T cells. 47 9] [50]  Collectively, these findings suggest that the intratumoral chemokine constellation identified here after SEG/SEI treatment contributed to the recruitment T effector cells in the TME.
Flow cytometry Cells were washed with Hanks balanced salt solution (HBSS), stained with Ghost Dye (TONBO) for viability, FC blocked (BioLegend) and stained for extracellular antigens. Cells were fixed and permeabilized using FoxP3 staining buffer kit (TONBO) for intracellular cytokine and transcription factor analysis. Fluorescence minus one (FMO) and single stained controls were used for gating and compensation. Gating strategies are indicated within each experiment. In general, doublets and cell debris were excluded, and only Ghost Dye negative cells were used for analysis. Samples were analyzed using a BD LSRII or Symphony A3 flow cytometer at the North Dakota Flow Cytometry and Cell Sorting Core. Data were analyzed using FlowJo software.
Histology and quantification of tumor density and necrosis Tumors were fixed with formalin and embedded in paraffin. Serial sections 5 µm thick were cut floated onto charged glass slides (Super-Frost Plus, Thermo Fisher Scientific) and dried overnight at 60°C. Sections were stained with H&E. Slides were scanned at 1200 dpi and photographed as a TIFF image. The necrotic and viable areas of these sections were identified histologically with a Leitz Diaplan microscope and corroborated using ImageJ software. Necrotic tumor area was expressed as the percentage of pixels in the total tumor area minus the area of the viable tumor cells in the section. 77 For determination of tumor density, all visible omental tumors were excised, and sections were stained, scanned, and photographed as TIFF images as described above.
Figure3Evaluation of T cells and myeloid cells in B16-F10 tumors from HLA-DQ8 tg mice treated with SEG/SEI is shown. HLA-DQ8 tg mice received 2. 5×10 5 live B16-F10 cells IP on day 0, followed by the treatment with SEG/SEI, 50 µg of each, on days 6 and 9. Controls were inoculated with tumor but received no treatment. On day 13, tumors were excised and assayed for (A) CD3 +CD8+cells, (B) CD8 + granzyme B + cells, (C) CD25 + FoxP3 + cells, (D) CD11b + Gr1 + cells. ANOVA with Tukey post test. n=3. *P<0. 05, **p<0. 01,. Ratio of CD8 + granzme B + cells to CD25 + Foxp3 + cells ≥10:1 (n=4, p=0. 01) and ratio CD8+ granzyme B+ cells to CD11b+GR1+cells=3. 9:1 (n=4, p=0. 03). Data expressed as mean±SD, Student's t test, two tailed. ANOVA, analysis of variance; ns, not significant. on April 15, 2022 by guest.
Flow Cytometry Staining Spleen and lymph node cells (5. 10 5 ) were seeded in 96-well plates in 200 µL PBS containing 5% Fetal Calf Serum (PBS-FCS) for 15 min at 4 • C, and then stained in the same medium. After centrifugation, antibodies were added for 30 min at 4 • C in a final volume of 100 µl at the recommended dilutions. After two washes in PBS-FCS, cells were resuspended in 200 µl PBS for analysis. For each sample, at least 10,000 events were acquired and analyzed using the Flowlogic software (Miltenyi Biotec). Purified antibodies and hybridoma supernatants were used to characterize the splenocytes, lymphocytes and APC populations.
Statistical Analysis GraphPad Prism software was used to analyze the variation between groups. Normal distribution was test using Shapiro-Wilk test. One-way Anova and non-parametric Kruskall-Wallis tests were used to analyze cytokine secretion and parasitic load. Paired T-tests were used to analyze flow cytometry stainings. Two-way Anova and Tukey's multiple comparisons test was used to analyze IgG secretion. For all statistical tests a value of p < 0. 05 is considered statistically significant and will be followed by the appropriate post-test.
ACKNOWLEDGMENTS Special thanks go to  Sylvie Bigot  for administrative support,  Michel Olivier  ( ISP 1282 ,  INRAE ), and all the animal team of  PFIE (INRAE, Nouzilly)  for technical support. Thanks to  Aurélien Dumètre ,  IHU-Méditerranée Infection , for providing us oocysts and  Isabelle Schwartz-Cornil ,  Virologie et Immunologie Moléculaires INRAE , for antibodies. We are grateful to  Mike Howsam  for English proofreading. In addition, we wish to thank  Emeline Salmon  and  Stéphanie Roucheray , master students for their involvement.
Image Processing and Analysis Image J software was used to analyze immunofluorescence images, to quantify fluorescence in real-time microscopy and to determine the cell surface after frustrated phagocytosis. A line over plasma and phagosomal membrane was drawn and the ratio between fluorescence at the phagosomal membrane (minus background) and fluorescence at the plasma membrane (minus background) was calculated for each time point. Co-localization was analyzed using the JACoP ImageJ plugin  (Bolte and Cordelières, 2006). A negative control was made by recalculating the Pearson coefficient using the NOX2 image rotated by 180 •  (Dunn et al. , 2011). Direct stochastic optical resolution microscopy analysis was performed using thunderSTORM software  (Ovesný et al. , 2014). First, images were filtered using the "difference of averaging" filter.
Data Analysis Graphpad prism8 software (GraphPad Software, United States) was used for statistical analyses. Since the values were not normally distributed, Mann-Whitney tests were performed to compare 2 groups, and Kruskal Wallis tests were used to compare multiple groups. For the live-imaging experiments, ratio-paired t-tests were used to compare fluorescence ratios at the different times. Differences were considered significant when p < 0. 05. Statistical test results are indicated in the figure legends.
The cells were then stained for NOX2 by immunofluorescence and imaged using a dSTORM approach with a TIRFM configuration. TIRFM allows the imaging of the fluorophores in the membrane in proximal contact with the coverslip while avoiding potentially confusing contribution from cytoplasmic fluorophores. A density-based representation of dSTORM images revealed that NOX2 distribution was similar in the 3 conditions: non-activated, frustrated phagocytosis for 1 or 10 min (Figure  4A  and data not shown). The spatial distribution of NOX2 analyzed using the DBSCAN cluster detection analysis implemented in SR-Tesseler software (materials and methods) indicated that NOX2 organized in nanoclusters. These clusters had a similar size distribution in the cell membrane in each condition (Figure  4B ). The mean diameter of the nanoclusters was about 60 nm in each condition (60.
FUNDING This work was supported by the  CNRS  and the  Université Paris-Saclay. The present work has benefited from the  Imagerie-Gif core facility  supported by l' Agence Nationale de la Recherche  ( ANR-11-EQPX-0029 /Morphoscope ,  ANR-10-INBS-04 / FranceBioImaging ;  ANR-11-IDEX-0003-02/Saclay Plant Sciences ) and the platform  SpICy at Institut de Chimie Physique.
VA014 biofilm maturation step and left for 2 h under static conditions at 22 • C. For each experiment, the culture supernatant was replaced with sterile culture medium in the negative controls. Microscopic observations were performed by confocal laser scanning microscopy (CLSM) using a TCS-SP2 system (Leica Microsystems, Mannheim, Germany). The biofilms formed were observed by staining the bacteria with 5 µM Syto 61 red for 10 min. The biofilm stacks were analyzed with the COMSTAT software (developed in MATLAB  [40] ) to estimate the maximal and average thicknesses (µm) and the biovolume (µm 3 µm -2 ) of the biofilm. Each experiment was repeated three times, and three zones of each channel were analyzed per experiment.
Collectively, these datasets suggest that both glycolysis and oxidative phosphorylation are a fundamental part of the baseline tTreg cell metabolic program. In comparison, acutely activated human tTreg cells in the in vitro setting initially reduce their rate of ECAR and OCR in comparison to Teff cells  (43). However, after a ∼1week stimulation with anti-CD3 antibody, IL-2, and antigenpresenting cells (APCs), these Treg cells had significantly higher rates of ECAR and OCR than corresponding Teff cells. The activated Treg cells also took up more of the fluorescent glucose dye than Teff cells despite having similar levels of Glut1 expression. Moreover, the importance of FAO was demonstrated in these Treg cells too as the addition of palmitate to cultures further increased the OCR. Put together, these data suggested that tTreg cells were better equipped than Teff cells to meet their additional metabolic requirements through upregulating both glycolysis and FAO upon acute activation (Figure  2 ).
FUNDING MA is funded by the  European Association for the Study of the Liver (EASL) Juan Rodes Ph. D. Fellowship. MM and GG are supported by the  Programme Hospitalier de Recherche Clinique  (PHRC:  AOR17082 ,  PHRCN 190321 ),  DIM Thérapie Génique Ile de France and AFPCA (Association Française de la PolyChondrite Atrophiante ).
Statistics Data analysis was performed by GraphPad Prism 6. 01 software. Patient parameters were expressed as medians and ranges, or/and means ± standard error of the mean (SEM). The Chi-2 test was used. For continuous variables, a Mann-Whitney U-test or a Kruskal-Wallis test followed by Dunn's post-hoc test was performed. The tests used are indicated in the legends of figures and tables. A value of p < 0. 05 was considered statistically significant.
Characteristics of Patients With a Monoclonal IgA In this retrospective study, 35 patients with a monoclonal IgA were recruited (6 MGUS, 29 myeloma). Annotated clinical data were available for 26 patients (6 MGUS, 20 myeloma); the biological and clinical characteristics of patients are shown in Table  1. The male/female ratios were 33. 3% for MGUS and 45. 0% for myeloma, and the median age of MGUS and myeloma patients with monoclonal IgA at the time of diagnosis was 76. 6 and 75. 1, respectively. Thus, in this cohort, patients with IgA myeloma were older than in the series of 135 IgG myeloma patients we studied previously (median age at the time of diagnosis: 75. 1 years for IgA myeloma vs. 63. 8 years for IgG myeloma)  (12, 21). Compared to IgG myeloma, the quantity of monoclonal Ig produced at the time of diagnosis of IgA myeloma was low (median quantity of monoclonal Ig: 17.
ACKNOWLEDGMENTS We thank all the colleagues from the  Departments of Hematology or Internal Medicine of the University Hospitals in Tours and Bordeaux , who contributed to the diagnosis and care of patients in this study, and  Novartis (Basel, Switzerland)  for providing seven IgA myeloma serum samples. We also thank  Dr. Pierre Weigel  and  Dr. Cathy Charlier  ( CNRS UMR6286 ) and the  IMPacT  platform (impact-plateforme. com)at the  University of Nantes, in Nantes, France.
Study design and patient management In this retrospective case-controlled study, data of children treated with IFX between 2004 and 2019 were collected between 2015 and 2019 from centres in Europe and Canada as a PIBD Porto group of ESPGHAN initiative. For the young patient (YP) group, PIBD patients were eligible if IFX treatment was started for active disease before age of 10 years. These data were compared with a control group of paediatric IFX treated IBD patients above age of 10. This cut-off was based on age groups classified by the Paris classification  [15]. OP were selected based on the time period IFX treatment was started. Patients were excluded if data on IFX dosing or levels were missing or if a patient was diagnosed with a monogenetic disease. Investigators from participating centres were asked to enter all patient information into Castor, an electronic data capturing tool (Amsterdam, the Netherlands).
015). Seventy-seven percent (85/110) of YP and 90% (95/105) of OP received 5 mg/kg. In 11% (12/ 110) of YP, already a dose of ≥ 8 mg/kg was started, while this was done in 3% (3/105) of OP. YP were included in 14 different centres (median 6 [IQR 4-8] patients per centre), and OP were included in 9 centres (median 10 [IQR-3-10]). In multivariate analyses, IFX trough levels were not significantly different between UC and CD patients; thus, the data of patients with both diagnoses are pooled (β -0. 29; 95% CI -0. 640 to 0. 059, p = 0. 101); Table  2 ). In addition, a separate analysis for UC and CD patients is shown in Table  3.
Discussion We analysed data of 622 IFX trough levels measured among 110 young (< 10 years) PIBD patients. Moreover, to examine differences in age groups, we compared young to older (≥ 10 years) PIBD patients (105 patients, 295 IFX trough levels). This resulted in a unique overview of clinical efficacy and trough levels of IFX treatment in very young PIBD patients. In our study, 23% of young PIBD patients had primary nonresponse or secondary loss of response within the first year. This is in line with previous literature, where in 4. 5-30% of older PIBD patients, IFX was discontinued  [7, 10, 22]. On the other hand, a retrospective study in children ≤ 7 years by Kelsen et al. (n = 33, 61% CD; median age at start 5. 6; collected between 1999 and 2011)  [9]  found a very high loss of response to IFX treatment of 64% in their population.
However, a limitation of this study is its retrospective design. Data collection and TDM were not performed in a standardized manner (proand reactively) which increased the risk for bias. However, a prospective study in this special population will require a very long time. As a consequence of this design, not all patients started with the same dose and were we unable to compare trough levels of YP and OP at the important time point of week 14. Moreover, IFX trough levels and ATI were determined with different assays at the local centres. Comparison of different methodologies in Europe demonstrated significant concordance. Therefore, we estimate this effect to be marginal  [34, 35]. Despite concordance between ATI assays, different measurement units made it impossible to compare the effect of ATI levels on a continuous scale  [36].
Moreover, if the IFX serum concentration could be detected in a serum sample, ATIs were usually not determined. This may have resulted in a negligible underestimation of the absolute number of ATI positive patients in both groups. Evaluation of disease activity was limited. PGA was used to evaluate clinical disease activity while endoscopic data and faecal calprotectin levels were missing. Lastly, only 13% of the YP were VEO-IBD patients (< 6 years) which makes it impossible to draw conclusions for this very small but extra vulnerable part of the population in whom IFX is only available for off-label use.
Materials and methods Samples of organic waste (OW) was collected, aliquoted and filtered with 0. 45 μm syrin m syringe filters. The filtrate were tested for phage activity against P. syringae GAW0113 using a double agar overlay assay  [7]. Plaques with distinct appearance or size were purified thrice. The phage DNA was extracted from lysate, as previously described  [7]  Phage DNA libraries were prepared using NEBNext Ultra II FS library Prep and Kit for Illumina (New England Biolabs, Ipswich, USA). The sequencing was performed on the Illumina iSeq platform as part of a flowcell (2 x 151, 300 cycles; Illumina). The genomes were trimmed and assembled in CLC Genomics Workbench version 12. 0. 3. Blastn  [8]  were used to search for sequence similarity against the non-redundant NCBI databases.
Three of the phages are presented here because of low similarity with other known phages, but high similarity with each other. The position of the terminal repeats were identified by the presence of two distinct spikes in read-start coverage at two nearby sites in the genome, encompassing areas with approximately double readcoverage. Open reading frames (ORFs) were identified automatically with GeneMark  [9]  and Glimmer  [10]  and revised manually in DNA Master  [11]. The genomes were searched for tRNA sequences using Aragorn  [12]  and tRNAscan-SE  [13] , but none were found. The ORFs were manually annotated using both HHPred  [14]  against three downloaded databases the pFam 32. 0, SCOP70 between Autographivirinae phages was made with Gegenees version 3. 1. 0 (500 nt fragment size and 500 nt step size )  [15].
(which was not peer-reviewed) is the author/funder, who has granted bioRxiv a license to display the preprint in bioRxiv preprint first posted online Jan. 20, 2020; doi:. http://dx. doi. org/10. 1101/2020. 01. 20. 910588 The copyright holder for this perpetuity. It is made available under a. CC-BY-NC 4. 0 International license 1. 75 and PDB70 databases and blastp against the NCBI databases[8]. The nucleotide similarity heatmap 2 preprint.
Methods We used published 16S rRNA gene (16S) sequencing data on the microbiomes of engorged larvae and nymphs of Ixodes scapularis ticks. These data sets were generated by the same research group using comparable methodologies and were obtained by amplicon sequencing bacterial 16S rRNA gene, using barcoded universal primers (515F/806R) and sequenced on an Illumina MiSeq system that generated 250-base paired-end reads. The raw data were obtained in the frame of three different experiments: (1) the study by Narasimhan et al. [21] , including engorged tick larvae that were infected under laboratory conditions with Borrelia burgdorferi s. s. and pooled in groups of 5 before DNA extraction. For our study, we used the 'control' data set generated from larvae that fed on ovalbumin-immunized and B.
The complete workflow described below is schematically outlined in Figure  1. Figure  1. Workflow illustrating the analytical steps of the study. Three data sets were selected from published studies on the microbiome of Ixodes scapularis, fed on mice, from similar lab conditions and protocols. Raw data were obtained from available repositories online, consequently, were processed following the QIIME2 pipeline, i. e. , were denoised and identified at the levels of amplicons sequence variant (ASV) and annotated taxonomically based on SILVA 132 database. The ASV profiles and sequences were used to predict the metabolic profile from those microbiomes, based on the bioinformatic tool PICRUSt2. In addition, the taxonomic profiles were compared using the statistical method ALDEx2. The taxonomic profiles were also used to infer co-occurrence networks, from which three modules were extracted in each data set and used to predict their functional profiles.
Finally, integrative analyses were performed, linking taxonomic and functional profiles, to assess functional redundancy and functional similarity in each data set. Workflow illustrating the analytical steps of the study. Three data sets were selected from published studies on the microbiome of Ixodes scapularis, fed on mice, from similar lab conditions and protocols. Raw data were obtained from available repositories online, consequently, were processed following the QIIME2 pipeline, i. e. , were denoised and identified at the levels of amplicons sequence variant (ASV) and annotated taxonomically based on SILVA 132 database. The ASV profiles and sequences were used to predict the metabolic profile from those microbiomes, based on the bioinformatic tool PICRUSt2. In addition, the taxonomic profiles were compared using the statistical method ALDEx2.
Processing of Original Raw Sequences We performed de novo taxonomic annotation of all the 16S data sets. To this end, the sequences were downloaded from SRA repository  [23] , extracted and de-interlaced in two fastq data sets containing only the first or second mate read  [24]  using the data analysis platform Galaxy (http://usegalaxy. org). Demultiplexed fastq files were pre-processed and analyzed using QIIME2 pipeline (v. 2019. 1) [25]. Briefly, the DADA2 software package  [26]  was used (via q2-dada2) for denoising the fastq files, merging mate reads and chimera removal using the consensus method, which is the equivalent to "default parameters". The amplicon sequence variants (ASVs) were annotated using the q2-feature-classifier plugin classify-sklearn naiïve Bayes taxonomy classifier  [27]  against the 16S SILVA database (release 132)  [28].
Prediction of Functional Traits in Tick Microbiome The 16S amplicon sequences were used to predict the metabolic profiling of each sample. PICRUSt2  [29] , a robust bioinformatic tool, was used to predict the genomes from 16S amplicon sequences. The ASVs were placed into a reference tree (NSTI cut-off value of 2) containing 20,000 full 16S sequences from prokaryotic genomes, which is then used to predict individual gene family copy numbers for each ASV. The predictions are based on several gene family catalogs, like Kyoto Encyclopedia of Genes and Genomes (KEGG) orthologs (KO)  [30] , Enzyme Classification numbers (EC)  [31]. Pathway profiles were inferred from structured pathway mapping based on MetaCyc database  [32]. Different from other databases, like SEED subsystem  [33]  and COG  [34] , the MetaCyc database does not organize the functional features into standard hierarchical categories (i.