dataesr/scientific-paragraphs-categorization huggingface dataset:
Event selection, classification and normalization The analysed data were recorded using a minimum-bias trigger requiring signals in both V0A and V0C scintillators in coincidence with the arrival of the proton bunches from both directions. The background events produced outside the interaction region are rejected using the correlation between the SPD clusters and the tracklets reconstructed in SPD. The out-of-bunch pileup was rejected offline using the timing information from the V0 counter. The primary vertex was reconstructed either using global tracks (reconstructed using ITS and TPC information) or SPD tracklets (reconstructed using only the SPD information) with |z vtx | < 10 cm along the beam axis. Events with in-bunch pileup were removed if a second vertex was reconstructed within 8 mm of the primary vertex in the beam direction.
The raw data obtained were converted into ". mfg" files with MSConvert software (ProteomeWizard, version 3. 0. 6090). Peaks were assigned with Mascot (Matrix Science, version 2. 6. 2) against an in-house database containing human entries from SwissProt database (17 March 2017, 20194 entries) and P. aeruginosa PAO1 entries from UniProtKB database (17 March 2017, 5677 entries). Common contaminant proteins such as human keratins and trypsin were added to the database and concatenated with the reverse copies of all sequences. Trypsin was selected as enzyme, one missed cleavage was allowed. Database searches parameters in Mascot search engine and generated PSM validation were performed as previously described  (16). For quantification purpose, the ". raw" files were converted into ". mzDB" files with MS Angel software (version 1.
6. 2). XIC quantification was performed in Proline software (53) using 5 ppm as m/z tolerance for the peptides abundance extraction. Loess smoothing was performed for the LC-MS runs alignments. Cross assignments of peptide ions were performed using 5 ppm as m/z tolerance and 60 s as retention time tolerance. Only proteins identified with at least one unique peptide were considered and only specific peptides were kept for the sum of protein abundances. The contaminants were excluded from the protein list prior to statistical analysis. Experimental design and Statistical Rationale: Statistical analysis was performed using the ProStaR software (version 1. 16. 6) (54). Proteins identified in at least 4 replicates per condition were considered, normalization was performed using median quantile centering mode for all conditions.
Imputation was performed at the protein level SLSA mode for partial observed values per condition and DetQuantile (2. 5 %, factor 1) mode for values missing in entire condition. Welch's T-test was used to identify statistically differentially expressed proteins between two conditions. For each comparison, the p-value calibration was performed using the Benjamini-Hochberg procedure. Proteins with p-value below 0. 001 were considered as differentially expressed, corresponding to a FDR between 1-5 %. Following values were obtained: 2. 35% FDR for ENT, 2. 26 % FDR for TCV, 7. 33 % FDR for TCVL6, 0. 72 % FDR for ALBO and 4. 24% for FERRI. The MS data were deposited to the ProteomeXchange Consortium via the PRIDE partner repository  (55)  with the PXD020378. Reviewer account details: Usernam: reviewer98509@ebi.
Acknowledgments This work was partially funded by the  Centre National de la Recherche Scientifique  and grants from the associations  Vaincre la Mucoviscidose  and  Association Gregory Lemarchal. In addition, these results were generated as part of the work of the  Translocation Consortium  (www. translocation. com),supported by the  Innovative Medicines Joint Undertaking  under Grant Agreement no. 115525 , through financial contributions from the  European Union 's  Seventh Framework Program  ( FP7/2007-2013 ) and contributions in kind from EFPIA companies. The equipment at the IPHC was partly funded by the  French Proteomics Infrastructure  ( ProFI ;  ANR-10-INSB-08-03 ).
Study design and population We conducted a multicentre, retrospective study from September 2008 to September 2018 in three general hospitals (Colmar, Haguenau, and Strasbourg, France). Patients with suspected TTS were identified out of 62 214 coronary angiograms recorded in the cardiac catheterization laboratory database, using the key words 'stress', 'takotsubo', or 'catecholamine'. The diagnosis of TTS was made according to the European Society of Cardiology Heart Failure Association criteria. 5 Exclusion criteria included a diagnosis of acute coronary occlusion, percutaneous coronary intervention, myocarditis, and cardiac arrest at first medical contact. Two cardiologists reviewed all the cases, and the diagnosis of TTS was based on a consensus agreement. Cases were recorded in the Alsace Takotsubo registry.
Flow cytometry (FACS) Dendritic cell (DC) phenotype was determined using flow cytometry. The migrated cells from the MIMIC® PTE module were first incubated with Live Dead Aqua (Thermo Fisher Scientific), a cell viability marker to stain dead cells for 15 min. Thereafter, the cells were rinsed with PBS and then blocked with murine immunoglobulin G1 (IgG1; Sigma) to block Fcγ receptors. Next, the cells were labeled for 20 min with a fluorescent antibody cocktail. Finally, the cells were washed twice in buffer and then evaluated on a flow cytometer. Viable cellular events were acquired on a Fortessa cytometer (BD Biosciences) equipped with FACSDIVA software (BD Biosciences). FLOWJO software (Tree Star Inc. , Ashland, OR) was used to analyze the data.
Cytokine and chemokine analysis Culture supernatants from the MIMIC® PTE module were evaluated for cytokine/chemokine production using a Beadlyte human 22-plex multi-cytokine detection system (Millipore, Billerica, MA). For this purpose, assay samples or cytokine standards were incubated at RT for 2 h with multi-cytokine beads in a filter plate. After a wash step, the beads were incubated with multi-cytokine biotin for 90 min and then Beadlyte strepavidin-PE. After 30 min, supernatants were removed, and the beads were then brought up in 125 ul of assay buffer. Analysis was performed using a Bio-Plex 200 system (Bio-Rad, Hercules, CA). Analyte concentrations were calculated based on relevant standard curves using the Bio-rad BIO-PLEX software manager.
Statistical analyses For mouse study depicted in Fig. 1 , an Analysis of Variance (ANOVA) with Dunnett adjustment for comparison to the MF59 reference was used. Concerning study depicted in Fig. 2 , an Analysis of CoVariance (ANCOVA) was used. Two factors were included in the model, the factor "adjuvant" considered in a categorical way and the factor "dose" considered in a continuous way. Analyses were performed with SAS v9. 1® and v9. 2® software (SAS Institute, Cary, NC). For in vitro studies in the MIMIC® system depicted in Figs. 3  and 4 , statistical analyses and graphs were prepared using GraphPad InStat version 5. 00 (GraphPad Software, San Diego, CA, USA). Analysis of variance and Tukey's honestly significant difference (HSD) were employed to determine statistical significance. In all studies, P values <.
, 1965; Vink, 1986). Then, to purify the samples from potential small molecular weight impurities (e. g. residual traces of polymerization initiators, solvents, unreacted monomer or very low molecular weight polymers) that could potentially affect PAA adjuvanticity, stability and safety, all PAA samples were extensively dialyzed against normal saline solution (150 mM NaCl; pH 7. 0) or PBS pH 7. 4. After this step, product identity and purity were confirmed by NMR. In some PAA batches, traces of poly-3-hydroxypropionate (poly-3HP), with no impact on adjuvanticity, were detected by 1 H NMR analysis (from 0 to 10% w/w; data not shown). Poly-3HP is a known process impurity in the synthesis of PAA, especially when the starting acrylic acid is obtained from 3-hydroxypropionic acid  (Li et al. , 2018).
Statistical analysis, taking into account the antibody and cytokine titers induced at all concentrations, indicated an absence of significant differences in terms of antibody and IFN-γ induction between PAA lot#652979 (Polysciences; Mw = 522 kDa; linear) and PAA    1 , and showing no significant difference between lots#658002, 569589 and 652979, whereas lot#656483 displayed a reduced adjuvant effect (data not shown). Based on antibody isotypes and cytokine profiles, strong Th-1 responses were obtained in these studies with all PAAs of Mw 405kD (lot#658002) and above. From a general safety standpoint, even at the highest injected doses (400 μg of PAA) there were no macroscopic injection site reactions and the immunization regimen with PAA-adjuvanted CMV-gB had no effect on mouse normal behavior and body weight gain.
Acknowledgments The authors are thankful to  Dr. Thomas Shenk  and  Princeton University  for providing the GFP-labeled CMV virus. The authors wish to thank  Stéphanie Guinamand ,  Laurent Revet ,  Séverine Nury ,  Olivier Engel ,  Bénédicte Bourdeau ,  Franck Vallery ,  Isabelle Zamora ,  Isabelle Jaudinaud ,  Sonia Cognet ,  Antonin Asmus ,  Sandrine Painchaud ,  Julie Barrier ,  John Escobar  and  Maria E Boone  for expert technical assistance,  Christophe Charnay  for animal care and  Sylviane Gautheron  for expert statistical analyses. This work was funded by  Sanofi Pasteur.
NDVI dataset The latest version of the Global Inventory Modeling and Mapping Studies (GIMMS) NDVI3g dataset derived from the Advanced Very High Resolution Radiometer (AVHRR) sensors (https://climatedataguide. ucar. edu/climate-data/ndvi-normalized-difference-vegetation -index-3rd-generation-nasagfsc-gimms) was used in this study. NDVI is an indicator of canopy greenness and has been commonly used for vegetation dynamic monitoring at regional and global scales (e. g. Barichivich et al. , 2013; Huang et al. , 2017b). GIMMS has the longest time series of NDVI observations that cover 1982-2015, with a spatial resolution of 0. 083° and a biweekly temporal resolution (Jorge and Compton, 2014). The biweekly NDVI data were composited into monthly series using the maximum value composite (MVC) method.
Climate data and drought variables In this study, we use two drought variables to detect extreme drought events: climatic water deficit (CWD), defined as precipitation minus the potential evapotranspiration (PET)  (Stephenson, 1998) , and the standard precipitation-evapotranspiration index (SPEI), a climatic drought index based on a water balance that includes the effects of temperature variability on drought assessment that has the advantage of combining multiple scales  (Beguería et al. , 2014; Vicente-Serrano et al. , 2010; Vicente-Serrano et al. , 2013)   (Chen et al. , 2011; He et al. , 2020; Yang et al. , 2010). For the CMA site-level dataset, we calculated monthly PET and SPEI (at a time-scale of 3 months) using the Food and Agriculture Organization of the United Nations (FAO-56) Penman-Monteith approach  (Monteith, 1965)  using the SPEI R package  (Beguería et al.
Land cover and digital elevation model (DEM) datasets The land cover map of TP was extracted from the 1:1000,000 digitalized vegetation map of China (Editorial Board of Vegetation Map of China, 2001, http://westdc. westgis. ac. cn), and it was mapped in Figure  1  and in our previous study  (Li et al. , 2020). The elevation data were obtained from the Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model version 2 (http://earthexplorer. usgs. gov/), with a spatial resolution of 30 m. We aggregated the elevation data into a 0. 083° resolution using the bilinear interpolation method. To.
Fragment libraries were sequenced using the Ion Proton Sequencer (ThermoFisher Scientific, Waltham, US), generating a minimum of 20 million high-quality reads of 150 bp per library. Gene abundance profiling was performed by mapping high-quality reads to the 9. 9 million gene integrated reference catalog of the human microbiome  (35)  using Bowtie 2 with a 95% identity threshold  (36). The gene abundance profiling table was generated via a two-step procedure using METEOR. The gene abundance table was processed for rarefaction and normalization using the MetaOMineR (momr) R package  (37). To decrease technical bias due to different sequencing depth and artifacts of sample size on low abundance genes, read counts were rarefied to 14 million reads per sample by random sampling without replacement.
The resulting rarefied gene abundance table was normalized according to the FPKM (fragments per kilobase of exon model per million reads mapped) strategy. Metagenomic species (MGS) are co-abundant gene groups with more than 500 genes corresponding to microbial species. Taxonomical annotation was performed on all genes by sequence similarity using NCBI blast N; a species-level assignment was given if >50% of the genes matched the same reference genome of the NCBI database (November 2016 version) at a threshold of 95% of identity and 90% of gene length coverage. The remaining MGS were assigned to a given taxonomic level from genus to superkingdom level, where more than 50% of their genes had the same assignment level. Microbial gene richness (gene count) was calculated by counting the number of genes detected at least once in a given sample.
MGS richness (MGS count) was calculated directly from the MGS abundance matrix. The functional analysis is led using a MGP pipeline FantoMET (unpublished). Genes of the catalog were annotated using KEGG82 database. KEGG and GMM modules (Gut Metabolic Module) were reconstructed in each metagenomic species using their pathway structures (and potential alternative pathways) (39). Abundance of each detected module in a metagenomic species corresponds to the abundance of the metagenomic species as described in the method section. Abundance of a given module in a sample is computed as the sum of the abundances of the module in each metagenomic species. Fecal short-chain fatty acid (SCFA) concentrations were assessed using a standard gas-liquid chromatography (GLC) protocol, using the 9890A series GLC system (Agilent Technologies, Santa Clara, US) and fecal pH was measured using a pH probe (InLab®, Mettler Toledo probe and FE20 FiveEasy™ Benchtop pH meter).
Peripheral T-cell phenotype Blood samples were collected at baseline and end of trial in sodium-heparin vacutainer tubes (BD Bioscience) and processed within 3 hours. Whole blood was labelled with fluorescently conjugated monoclonal antibodies to detect CD3 T-cells, as well as naïve (CD45RA+) and effector/memory (CD45RA-) CD4 and CD8 T-cells, and Vδ2 unconventional T-cells. The gut-homing integrin α4β7 was detected by labelling with anti-β7  (40, 41). The BD FACSCanto II flow cytometer was used to acquire data, the FACS DIVA software (BD Bioscience) used to collect the data, and Winlist software (Verity, Topsham, ME, US) used to analyze the data.
Data on gut symptoms, HR-QOL, disease activity, inflammatory markers and peripheral T-cell phenotype were analyzed intention-to-treat (ITT), followed by per protocol (PP), the latter consisting of patients who completed the trial, did not violate protocol and were 'always' compliant with dietary intervention. Data on microbiome composition and SCFA concentrations are presented for the PP population. Clinical variables, SCFA and T-cell phenotype data were compared between groups at end of trial using ANCOVA, with corresponding baseline values as a covariate, and are therefore presented as estimated marginal mean (standard error of the mean; SEM). Categorical variables, presented as number (%), were compared between groups using the Chi-squared or Fisher's Exact Test. Statistical analysis was performed using SPSS Version 24.
Background: We aimed to establish a tool predicting parametrial involvement (PI) in patients with early-stage cervical cancer and select a sub-group of patients who would most benefit from a less radical surgery. Methods: We retrospectively reviewed patients from two prospective multicentric databases-SENTICOL I and II-from 2005 to 2012. Patients with early-stage cervical cancer (FIGO 2018 IA with lympho-vascular involvement to IIA1), undergoing radical surgery (hysterectomy or trachelectomy) with bilateral sentinel lymph node (SLN) mapping with no metastatic node or PI on pre-operative imaging, were included. Results: In total, 5. 2% patients (11/211) presented a histologic PI. After univariate analysis, SLN status, lympho-vascular space invasion, deep stromal invasion and tumor size were significantly associated with PI and were included in our nomogram.
Population and Data Analysis We retrospectively reviewed the results from two prospective multicentric studies evaluating the benefit of sentinel lymph node in cervical cancer-SENTICOL I and II. Patients with early-stage cervical cancer (stage IA with lympho-vascular involvement to stage IIA1) were included from seven French gynecological oncology centers between 2005 and 2007 and from 23 centers from 2009 to 2012 for SENTICOL I and II, respectively. The Paris Descartes Ethical Committee (Comité de Protection des Personnes HEGP-Broussais) approved this study. The patients included in the two studies gave a written consent stating the use of data for secondary analyses. We included patients undergoing radical surgery (radical hysterectomy or trachelectomy) with bilateral sentinel lymph node mapping for early stage cervical cancer with no metastatic node or PI on pre-operative imaging.
Patients without radical surgery were excluded since PI was not assessable. Likewise, patients with a clinical or MRI PI were not included. Patients with a pre-operative brachytherapy were also excluded. Patients with early stage cervical cancer from FIGO IA1 with LVSI to FIGO IIA1 were analyzed. We chose to include patients with FIGO IA1 with poor prognosis (LVSI) and FIGO IA2, since no clear recommendations exist on the importance of a parametrectomy in these patients (grade C ESMO/ESGO recommendations). Data were collected regarding: (i) demographic characteristics (age, body-mass index); (ii) surgery (type of surgery, sentinel lymph node, conization); (iii) tumor characteristics (FIGO stage, histological examination, imagery). On the conization specimen information, regarding tumor size, histology type, presence or not of LVSI, DSI and margin status were available.
Optimal Threshold of the Model The optimal threshold of our model, classifying patients as low risk or high risk of PI, was defined using the Youden index  [28]. At this threshold, the sensitivity, specificity, negative predictive values (NPVs) and positive predictive values (PPVs) were assessed. All statistical analyses were carried out using an Excel database and Rstudio, version 1. 1. 447 (https://www. r-project. org/).
Population Characteristics 412 patients were enrolled in 23 French centers from January 2005 to July 2012. Among them, 326 underwent a radical surgery (radical trachelectomy or hysterectomy) Of those enrolled, 115 patients were excluded-78 patients had preoperative brachytherapy, 6 patients had no SLNs detected, 29 patients had SLNs detected on only one side and 2 patients had missing data about parametrial status at final pathologic examination. A total of 211 patients fulfilled the inclusion criteria and were analyzed, as shown in Figure  1. In the whole population, the mean age was 43. 2 years old and the mean BMI (body mass index) was 23. 5 kg/m 2. Patients more frequently underwent a radical hysterectomy (75. 8%) and SLN biopsy with additional pelvic lymphadenectomy (69. 2%). The most frequent surgical route was laparoscopic (88.
7% of patients with a positive SLN had a PI concordant with the 28% found by Strnad et al  [30]. In multivariate analysis, a positive SLN was strongly associated with a PI (OR = 16. 34 IC95% = 1. 33-199. 89, p = 0. 03). Most variables included in our nomogram, such as pathological tumor size, LVSI and DSI, are not available pre-operatively, but they may be assessed on the conization sample. Even if the negative predictive value of LVSI on conization sample is still debated, data are still lacking concerning its predictive power  [31]. Moreover, tumor size can be determined via manual rectovaginal examination, MRI, conization or final pathological analysis, and studies have not yet shown the superiority of one measurement technic. Covens   [1, 18, 19, 32]. All found a low risk groups with a probability of PI of 0-1.
, SHAPE (NCT01658930), which is an international randomized trial comparing the safety and morbidity of radical hysterectomy and pelvic node dissection with simple hysterectomy and pelvic node dissection in early-stage cervical cancer  [40]. Intraoperative SLN status assessment has a variable diagnostic value and frozen sections of SLN are not sufficiently reliable yet, especially for low-volume metastases [21,41-43] even if their prognostic value is still a subject of debate  [44, 45]. Ultrastaging is required to identify missed micrometastases and macrometastases. Moreover, the recommended surgical approach for locally advanced cervical cancer is laparotomy, since the publication of the LACC trial results  [46]. For patients with metastatic SLN, a two-step approach would avoid a useless laparotomy and these patients would be referred to concomitant chemo-radiation.
The current study describes a simple tool to identify patients at low risk of PI, but some limitations must be noted. The retrospective analysis of two prospective databases may suffer from some bias. The small number of patients may limit the power of our work, yet studies evaluating PI are often relatively small, since PI is rare  [2] [3] [4] 18, 19]. Likewise, the small number of events may result in the overfitting of our tool. However, this multicentric study (9 and 23 French centers) is largely generalizable. No external validation was performed for our score. Due to the small percentage of PI (5. 2%) in the general population, we could not split the population into a training and validation cohort. An external validation of our score is therefore needed. Likewise, due to the small number of events, most variables included in our score were not significant after multivariate analysis.
We decided to include them because of their clinical pertinence. Several large studies are currently ongoing to assess the morbidity and safety of a step-down surgery for early-stage cervical cancer, such as SHAPE. Likewise, GOG 278 will assess the morbidity and quality of life of non-radical surgery (NCT01649089). ConCerv is a multi-centric international trial, which aims to determine the safety and feasibility of conservative surgery (i. e. hysterectomy or conization with pelvic node dissection and sentinel mapping). The results have recently been presented and the authors underlined that lymph node status assessment is required and optimal pathological criteria for conservative surgery must still be determined. Our simple tool includes SLN status, which may improve the identification of these patients eligible for conservative surgery.
The Nice Côte d'Azur Metropolis created a data warehouse where all of the collected data (regarding aspects such as security, health, the environment, energy, mobility, and eadministration) are stored and structured. The city uses the data internally to gain efficiency and to provide better quality services, but also trades data with private companies when the project is considered to be beneficial for the city and its citizens. In 2015, Paris launched an innovation program known as "DataCity Paris," which aims to develop and experiment innovative solutions based on collaboration among the local authority, large companies, start-ups, and urban data providers. Every year, several projects are selected to develop concrete solutions for city issues based on data sourced by different actors. Finally, the former Languedoc-Roussillon region, now merged into the Occitanie region, created an association in 1994 to share the geographical data acquisition cost.