dataesr/scientific-paragraphs-categorization huggingface dataset:
ACKNOWLEDGMENTS The DESIR cohort is conducted under the control of  Assistance Publique Hopitaux de Paris via the Clinical Research Unit Paris Center  and under the umbrella of the  French Society of Rheumatology and Institut National de la Santé et de la Recherche Médicale (INSERM). Database management is performed within the  Department of Epidemiology and Biostatistics (Jean-Pierre Daures, Nimes, France). We also thank the different regional participating centers:  Maxime Dougados  ( Paris-Cochin B), Andre Kahan (Paris-Cochin A), Philippe Dieudé (Paris-Bichat ),  Bruno Fautrel  ( Paris-La Pitie-Salpetriere ),  Francis Berenbaum (Paris-Saint-Antoine), Pascal Claudepierre (Creteil) ,  Maxime Breban  ( Boulogne-Billancourt ),  Bernadette Saint-Marcoux  ( Aulnay-sous-Bois ),  Philippe Goupille  (Tours),  Jean Francis Maillefert  (Dijon),  Emmanuelle Dernis  ( Le Mans ),  Daniel Wendling  (Besancon),  Bernard Combe  (Montpellier),  Liana Euller-Ziegler  (Nice),  Pascal Richette  ( Paris Lariboisière ),  Pierre Lafforgue (Marseille) ,  Patrick Boumier  (Amiens),  Martin Soubrier  ( Clermont-Ferrand ),  Nadia Mehsen  (Bordeaux),  Damien Loeuille  (Nancy),  Rene-Marc Flipo  (Lille),  Alain Saraux  (Brest),  Xavier Mariette  ( Le Kremlin-Bicêtre ),  Alain Cantagrel  (Toulouse), and  Olivier Vittecoq (Rouen).
Sequencing Whole genomic DNA was extracted from 300-µL aliquots of Amies solution as previously reported  [17]. High-throughput amplification and sequencing of the V3-V4 hypervariable regions of the 16S ribosomal RNA gene were performed using a validated and improved dual-indexing approach  [25]. Further bioinformatic processing followed the DADA2 Workflow for Big Data and dada2 (version 1. 5. 2) (https://benjjneb. github. io/dada2/bigdata. html [26] ) as previously reported  [27]. Taxonomy was assigned to each amplicon sequence variant generated by dada2 using SpeciateIt (version 1. 0, http://ravellab. org/SpeciateIt). Read counts for amplicon sequence variants assigned to the same taxonomy were summed for each sample. Data analyses include hierarchical clustering of each community profiles using Euclidian distance and assignment to one of the CSTs described previously  [16, 17] , and community diversity estimation using the Shannon diversity index  [28].
Statistical Analyses Analyses were carried out on samples with a total read count of at least 1000, and on phylotypes present in at least 2 samples. Baseline characteristics between CHARM participants who were lost to follow-up after the first visit and those who did not were compared using Fisher tests. To compare vaginal microbiota composition and structure among different groups, we conducted analyses at the CST and at the phylotype levels. At the phylotype level, we fitted negative binomial regression models for each phylotype present in at least 20% of all samples, using the DESeq2 package in R  [29]. At the CST level, we fitted logistic regression models to compare vaginal microbiota of CHARM visit 1 (CT positive) or CHARM visit 2 to those of the VM400 controls. We applied a mixed-effect logistic regression model to compare CHARM visit 1 and visit 2 taking into account intrawoman correlation between samples, using the lme4 package in R.
For the CHARM cohort, we obtained 7 396 180 high-quality sequences with an average of 18 725 (standard deviation [SD], 18 325) sequences per sample. For the VM400 controls, we generated 3 349 907 sequences with an average of 33 837 (SD, 17 024) sequences per sample. A total of 319 phylotypes was identified in the combined CHARM and VM400 datasets. The relative abundance of each phylotype is illustrated in Figure  1  (data available at https://github. com/ravel-lab/charm_longitudinal).
Vaginal Microbiota Composition Association With Prevalent CT Infection To lower the dimensionality of the dataset, samples were assigned to CSTs. CST I and III are often dominated by Lactobacillus crispatus and Lactobacillus iners, respectively, whereas CST IV lacks Lactobacillus spp and includes a diverse array of facultative and strict anaerobes. Further refinement revealed subtypes CST III-A/B and IV-A/B (Figure  1 ). Broadly, in CST III-A, L. iners is dominating the vaginal community at a relative abundance higher than approximately 80%, whereas in CST III-B, L. iners remains the dominant species but at lower abundance while anaerobes are also present. Within CST IV, CST IV-B is represented by a higher abundance of Gardnerella vaginalis. Using a logistic regression model, we found that the frequencies of each CST in CHARM visit 1 and VM400 cohort control samples were significantly different (Supplementary Table  2 ).
vaginalis, Atopobium vaginae, bacterial vaginosis-associated bacterium (BVAB) 2, and Mobiluncus curtisii, whereas Lactobacillus spp were overrepresented in VM400 CT-negative samples. Figure 1. Heatmap representing the relative abundance of the 20 most abundant phylotypes found in the vaginal microbiota of 395 samples collected every 3 months for 9 months after azithromycin treatment for Chlamydia trachomatis by 149 young females in the Chlamydia Adolescent/Adult Reproductive Management prospective cohort, Baltimore, Maryland, and 99 samples from 99 women enrolled in the VM400 cross-sectional control study, Baltimore, Maryland  [30]. Ward linkage clustering was used to cluster samples based on their Euclidian distance calculated in the "vegan" package in R. The 4 bars on top indicate community state types, according to the previous naming convention  [30] , Nugent Score, vaginal pH, and visit number.
, 2007). However, the effect of treatment on clinical sequelae was evaluated only on live born infants, and the study suffered from bias due to heterogeneity of data. On the other hand, Hotop et al. found delayed treatment (N 8w after seroconversion) to be a risk factor for symptomatic CT  (Hotop et al. , 2012). Of note, the introduction of monthly systematic screening for toxoplasmosis in pregnancy in France has resulted in an overall decrease in the rate of MFTP from 29% before 1992 to 24% after 1992, and an impact of immediate introduction of PYR-SDZ treatment on the reduction of clinical CT cases from 11% before 1995 to 4% after 1995  (Wallon et al. , 2013). Austria, another European country with a decades-long national screening program for toxoplasmosis in pregnancy accomplished a fascinating reduction in MFTP among prenatally diagnosed and treated women -9% in comparison to previously 51% in untreated women, according to the Austrian Toxoplasmosis Register data  (1992-2008 period)   (Prusa et al.
| Bioinformatic and statistical analyses Bioinformatic and statistical analyses were performed as described previously  (Dietrich et al. , 2017), with MOTHUR v. 1. 38. 1 following the MiSeq SOP Pipeline  (Kozich, Westcott, Baxter, Highlander, & Schloss, 2013; Schloss et al. , 2009)  and R software (R Core Team, 2013), primarily with the vegan, Rcmdr and ggplot2 packages  (Fox, 2005; Oksanen et al. , 2015; Roberts, 2015; Wickam, 2016). Assembled reads were quality trimmed based on their length prior to alignment against the MOTHUR-formatted SILVA database. Preclustering of the data was performed using a 4-bp difference, following by the detection and removal of chimeras using the UCHIME algorithm  (Edgar, Haas, Clemente, Quince, & Knight, 2011). We then classified sequences using the MOTHURformatted version of the RDP training set (v.
9), and any unknown, chloroplast, mitochondrial, archaeal, or eukaryotic sequences were removed. Sequences were clustered into phylotypes using a 97% identity threshold. Based on the analysis of negative controls, potential exogenous phylotypes were identified using the same approach as in  Dietrich et al. (2017) , and we produced four datasets corresponding to different levels of exogenous DNA removal (i. e. , none, two, 51 and all exogenous phylotypes removed). After checking for consistency among results from these four datasets, results are presented for the dataset where exogenous phylotypes with a relative abundance >10% in the controls (n = 2) were removed. Phylotype tables were rarefied at the smallest library (8,340 sequences per sample when urine and feces samples were analyzed together, 8,340 and 18,727 sequences per sample for the separate analyze of urine and feces datasets, respectively).
We calculated alpha-diversity using the inverse Simpson diversity index and performed comparison between excreta samples (i. e. , urine and feces) using a Generalized Linear Model (GLM) including a Gaussian distribution and sampling month as an explanatory variable (Supporting Information Table  S1 , available from the Dryad Digital Repository: https://doi:10. 5061/dryad. k2v2006). To analyze the structure of microbiota, we used beta-diversity measurements and tested structure among the two excreta samples. For that, permutational MANOVA (PERMANOVA) tests with 999 permutations were performed and non-metric multidimensional scaling (NMDS) ordinations were conducted on Bray-Curtis dissimilarities, calculated from rarefied sequence counts, after square root transformation and Wisconsin standardization, to produce plots.
| Bat samples and phylotype classification A total of 35 bat samples were collected, including 21 samples (16 urine and five feces) directly from bats in hands, and 14 other samples (eight urine and six feces) using indirect sampling in the cave (Supporting Information Table  S2 , available from the Dryad Digital Repository: https://doi:10. 5061/dryad. k2v2006). The average number of assembled reads per sample was 31,950 and was not different between sampling approaches (ANOVA: F = 0. 445, p = 0. 509). Bacterial communities in the 35 bat samples and the 3 DNA extraction negative controls were classified into 748 phylotypes. Among them, 24% (n = 177) were present in the negative controls, with the genera Escherichia-Shigella and Pseudomonas being the two most dominant phylotypes. Further results are presented when both these phylotypes were removed from the dataset.
Geldenhuys, S. McCulloch, M. Mortlock, and the staff of the Centre of Emerging Zoonotic and Parasitic Diseases, National Institute for Communicable Diseases (NICD): J. Paweska, P. Jansen van Vuren, N. Storm, A. Kemp, B. Mogodi and J. Kgatitsoe. This work was supported by the National Research Foundation (NRF) of South Africa [Grant UID 78566 (NRF RISP grant for the ABI3500), UID 91496, UID 92524 and UID 98339], and by the Cooperative Agreement [5 NU2GGH001874-02-00], funded by the Centers for Disease Control and Prevention, Global Disease Detection Program. The findings and conclusions in this report are those of authors and do not necessarily represent the official position of the funding agencies. MD's postdoctoral fellowship was funded by a Capacity Building Grant from the National Research Foundation, South Africa [Grant UID 92524].
However, this has yet to be demonstrated. Once activated, CAFs enhance the development, progression and invasion of PDAC through their extensive crosstalk with the tumor, resulting in reciprocal stimulation and therapy resistance [21], [22]. Recent data in PDAC has shown that CAF cells, via their secretome, can increase parenchymal tumor cell (CPC) invasion [23], [24], [25], [26], reduce their growth [23], [27] and modify their epigenetic and metabolic phenotypes [24, 27]. Only one study [27] measured the effect of the combination of CAF secretome and high levels of ECM collagen I on parenchymal PDAC cell lines (CPCs) but did not determine the individual roles of collagen I and the CAF (Conditioned Medium). Importantly, those in vitro experiments were not performed on CSCs and, therefore, the effect of CAFs on CSC behavior in PDAC is completely unknown.
Statistical analysis GraphPad Prism 5 (GraphPad Software) to perform a two-tailed Student's t test assuming unequal variances to compare the effects of CAF CM on Panc1 CPCs and CSCs and to determine whether the differences between two groups were statistically signi cant. P-values < 0. 05, 0. 01, or 0. 001 are indicated as *, ** or ***, respectively when compared to each control for each matrix and †, † † or † † † compared to the same CM treatment on 90% Matrigel:10% Collagen I.
The results in Figure  4B , in which EV fractions from HTLV-1-infected cells were added to Jurkat recipient cells, demonstrated a trend similar to that observed in CEM recipient cells for all measured proteins. Interestingly, in both CEM and Jurkat cells, fraction 18 from IR treated HUT102 cells did not elicit the expression of p19 in recipients (  Figures 4A, B ; lane 22). Altogether, these data suggest that while fractions isolated from HTLV-1-infected cells contain viral proteins and RNA, only fraction 18 may have the potential (C) RT-qPCR was conducted on WCE from Jurkat, CEM, and HUT102 cells (controls; lanes 1, 2, and 3, respectively). Jurkat cells (±IR) treated with fractions 6 (lanes 4 and 5), 12 (lanes 6 and 7), and 18 (lanes 8 and 9), and CEM cells (±IR) treated with fractions 6 (lanes 10 and 11), 12 (lanes 12 and 13), and 18 (lanes 14 and 15) for the presence of env RNA.
EVs From HTLV-1-Infected Cells Promote Cell-to-Cell Contact We have previously shown that EVs have functional effects on recipients cells  (Narayanan et al. , 2013; Sampey et al. , 2016; Anderson M. R. et al. , 2018). Although our data suggest that HTLV-1 EVs may not be infectious in T-cells, env RNA was still detected in recipient cells, therefore we asked whether EVs may have functional effects on neighboring recipient cells (i. e. , cargo delivery). During prior treatments of recipient cells with HTLV-1 EVs, increased cell aggregation was noted. We hypothesized that HTLV-1 EVs might promote increased cell-to-cell contact of recipient uninfected cells. It was first necessary to track HTLV-1 EVs to determine if they colocalized with recipient cells. EVs derived from donor CEM cells (Control EVs), HUT102 cells (HTLV-1 EVs), or HUT102 IR-activated cells (HTLV-1/IR EVs) were fluorescently labeled with BODIPY, and added to recipient CEM cells at EV concentrations normalized to volume to better resemble physiological conditions (Figure  6A ).
We next explored whether CD45 and/or ICAM-1 are present in HTLV-1 EVs (±IR), hence contributing to viral spread. Supernatant from 5-day old cultures in biological triplicate were separated and enriched for EVs by NT080/082 (Figure  8C ). WB analysis revealed trace amounts of CD45 in HTLV-1 EVs (Figure  8C ; lanes 1 and 3) and no significant difference in HTLV-1/IR EVs (Figure  8C ; lanes 4-6). ICAM-1 was detected in HTLV-1 EVs and HTLV-1/IR EVs (lanes 1-6). These data show the potential presence of CD45 and ICAM-1 in HTLV-1 EVs (±IR), supporting prior observations about their potential role in mediating increased levels of cell-to-cell contact. Finally, two distinct donor PBMC cultures were treated with IL-2 and PHA for 3 days prior to treatment with HTLV-1/IR EVs (as described previously; 1:10,000; Cell:EV ratio) and neutralizing antibodies (α-CD45 or α-ICAM-1) were added in fresh EV-depleted RPMI media for 4 days.
The next day, membranes were washed and incubated with the appropriate HRP-conjugated secondary antibody for 2 h at 4 • C and developed using Clarity or Clarity Max Western ECL Substrate (BIO-RAD). Luminescence was imaged on a ChemiDoc Touch Imaging System (BIO-RAD). Raw densitometry counts were obtained using ImageJ software and by subtracting the background of each membrane. Data was normalized to Actin inputs for each protein of interest.
ZetaView Nanoparticle Tracking Analysis (NTA) Nanotracking analysis for EV quantification and sizing was performed using ZetaView R Z-NTA (Particle Metrix) with its corresponding software (ZetaView 8. 04. 02). Calibration was performed using 100 nm polystyrene nanostandard particles (Applied Microspheres) prior to sample readings at a sensitivity of 65 and a minimum brightness of 20. Instrument parameters were set as previously described  (DeMarino et al. , 2018; Pleet et al. , 2018b)  for each reading. For each sample, 1 mL of sample diluted in DI water was loaded into the cell, followed by measurements of size and concentration of particles at 11 unique positions throughout the cell in three independent reads. After automated analysis and removal of any outliers, the mode diameter size and the concentration of the sample were calculated by the machine software.
METHODS It is an observational cross-sectional study using the simulated patient method of a case of acute uncomplicated cystitis. We evaluated the rate of antibiotic prescribing in Lebanese community pharmacies and we assessed the prescribing practices for conformity with international guidelines. At the time of data collection, no national guidelines were available. 6] [17]  We defined the global conformity of the antibiotic prescribed to the aforementioned international guidelines as meeting the three types of conformity simultaneously: choice, dose and duration. Choice conformity was met whether the prescribed antibiotic belonged to the first-line or secondline agents.
Sampling and data collection We obtained a list of all Lebanese community pharmacies from the Order of Pharmacists of Lebanon. We obtained a random sample through stratifying Lebanon into its six distinct provinces (Beirut, Mount Lebanon, North Lebanon, South Lebanon, Bekaa and Nabatiyeh), followed by a proportional systematic random sampling in each province. The distribution of community pharmacies in Lebanon is previously reported in a similar study (18). We included 250 community pharmacies, assuming that the expected rate of dispensing was 75%. 12  We set the acceptable margin of error to 5% and the confidence level 95%. We collected data from February 2017 to late May 2017. There were two investigators (who are among the authors and are pharmacists) responsible for data collection. Each investigator had an exclusive and defined role.
Data analysis We performed all the data analyses using IBM SPSS Statistics for Windows, Version 21. 0 (IBM Corp. , Armonk, NY, USA). We reported the descriptive data as percentages and means with standard deviations (SD). We conducted bivariate analyses to evaluate antibiotic prescribing rate with each sociodemographic characteristic such as the participant, gender and province of the pharmacy. We conducted the same analyses for the number of questions asked. We studied the differences between pharmacists and assistants in the diagnosis, counseling points, referral and conformity rates. We used the Pearson chi-squared test for the qualitative dichotomous variables and Fisher's exact test when the expected values within cells were less than 5. For the quantitative variables, we used the Student's t-test.
5-mm transwell inserts with 3-mm pore polycarbonate membranes (Corning) was performed as described  (17). Transmigrated neutrophils were labeled for GR1, and eight random fields of view were photographed and counted (320 magnification; EVOS imaging system). ARAP3 knockdown in aIIbb3-expressing Chinese hamster ovary cells aIIbb3-Expressing Chinese hamster ovary (CHO) cells were transduced with lentiviral short hairpin RNAs (shRNAs) directed against mouse ARAP3. shRNA sequences (shRNA1, 59-CTCCGGCTGGAAGGTGTATAT-39 and 59-GGAATCCGCAAGAAGTTAAA-39; shRNA2, 59-GCAGAAGT-GTGCGTCTCTAAA-39 and 59-TGTATGAAGAGCCAGTATATG-39) identified from the Broad Institute RNA interference consortium database (https://portals. broadinstitute. org/gpp/public) were used alongside a nontargeting control (NTC; 59-GCGCGATAGCGCTAATAATTT-39).
Direct analysis of integrin activity status Activated b1 integrin was detected using an activation epitope-specific Ab (clone 9EG7; BD Biosciences) with an AF488-conjugated secondary Ab (Invitrogen). Images were acquired with a 633 objective using a Zeiss LSM780 confocal microscope with Zeiss Zen Black software. The corrected total cellular fluorescence was calculated using ImageJ by selecting regions for each cell and nearby regions of background and applying the following formula: corrected total cellular fluorescence = integrated density -(area of selected cell 3 mean fluorescence of background readings). Neutrophil binding to an AF647-labeled fibronectin fragment was performed essentially as described  (19)  using flow cytometry using a 5L LSRFortessa (BD Biosciences). Analysis was performed using FlowJo software (version 10) by gating for singlets, selecting neutrophils based on forward-and side-scatter profile, and measuring the geometric mean fluorescence intensity.
For imaging, lungs were perfused with low-melting-point agarose, allowed to set on ice, dissected, and fixed with formaldehyde. Left lungs were precision-sliced 300 mm thick using a vibratome (5100 MZ; Campden Instruments), permeabilized, blocked, and labeled for PECAM-1 (clone 2H8; Abcam) and S100A9/MRP14 (Hycult Biotech) with DAPI counterstaining. Following brief formaldehyde postfixation, slices were mounted using Mowiol containing 2. 5% (w/v) DABCO in gaskets and analyzed using a confocal laser scanning microscope to produce tile-scanned z-stacks (LSM 880 nonlinear optical Airyscan Fast using a 203 plan Apo 1. 0 numerical aperture, water immersion objective and 405-, 488-, and 561-nm continuous wave lasers and acquiring in Airyscan Fast mode; Zeiss). Image analysis was performed using IMARIS software (versions 8 and 9, Bitplane; Oxford Instruments).
3A ). ROS production is dependent on PIP3-activated Rac guanine nucleotide exchange factors, inhibition of which could potentially explain the above result. We therefore also analyzed the PI3K dependency of degranulation with control and ARAP3deficient neutrophils that been stimulated by being plated onto fibronectin in the presence or absence of TNF-a. Inhibiting class IA PI3Ks also reduced the enhanced degranulation that is characteristic of ARAP3-deficient cells; in particular, following PI3Kd inhibition, no significant difference remained between genotypes (Fig. 3B ). We analyzed adhesion and spreading of control and ARAP3deficient neutrophils after PI3K inhibition to fibronectin-coated plastic. Inhibiting PI3Kb/d did not significantly affect the ability of neutrophils to adhere to fibronectin, in keeping with an earlier report that had analyzed neutrophil adhesion to immobilized immune complexes [(28), data not shown].
6E , Supplemental FIGURE 4. Integrin-PI3K-ARAP3 negative feedback signaling improves neutrophil polarization. Neutrophils were prepared from bone marrow of mock ( +/+ ) and tamoxifen-induced ( 2/2 ) inducible Arap3-knockout mice expressing a GFP-PKB-PH PIP3 reporter. Cells were allowed to settle on a glass coverslip and then subjected to a point source of chemoattractant (micropipette). Cells were imaged using a Perkin Elmer spinning disk Nikon Eclipse TE2000E confocal microscope using a 1003 oil immersion objective. Images were acquired every second for 5 min using a Hamamatsu cooled charge-coupled device camera. (A) Stills taken from a representative control and ARAP3deficient neutrophil. Yellow asterisk symbols indicate polarization. (B) The distribution of the PIP3 probe along the edge of each frame of the video was analyzed using QuimP software, measuring the image intensity at 100 nodes around the plasma membrane.
Acknowledgments We thank  Len Stephens  and  Phillip Hawkins  ( Babraham Institute ) for helpful discussions,  Simon Walker  ( Babraham Institute ) for help with imaging,  Shonna Johnston ,  Will Ramsay , and  Mairi Pattison  for help with flow cytometry,  Simon Andrews  ( Babraham Institute ) and  Matthieu Vermeren  for bioinformatics, and  Ian Handel  for help with statistics. We thank  Sanford Shattil  ( University of California, San Diego ) and  Robert Weinberg  ( Whitehead Institute ) for providing CHO cells expressing human aIIbb3 and pLKO. 1 puro, respectively.