dataesr/scientific-paragraphs-categorization huggingface dataset:
19, 24 Thus, it can be assumed that here, most of the ILI cases reported were actually due to influenza infection. Second, our study was limited to the 2017-2018 influenza epidemic. As for any study on influenza, we cannot anticipate what would have been the results on a different year, even though the epidemic pattern is quite reproducible since many years in France. 19, 24 Third, GrippeNet. fr is only based on declarative data concerning symptoms reported by individuals from the general population, but not validated by physicians. Therefore, this could have induced declaration biases. However, we tried to limit this bias by collecting only simple symptoms that are easily identifiable by the participants instead of asking for ILI syndrome. Moreover, it has been previously shown that epidemic trends from the GrippeNet.
To simulate a solid tumor microenvironment, we tested the activity of CYT-303 in a tumor spheroid assay, and the data showed that the PBNK cell's killing of Hep3B tumor spheroids was enhanced by CYT-303 in a dose-dependent manner (Figure  6 ). We then evaluated the activity of CYT-303 in an NK serial killing assay simulating the ability of NK cells to mediate multiple rounds of killing against tumor cells in the tumor microenvironment. For each round of tumor killing, the same PBNK cells were harvested each time and incubated with freshly added Hep3B tumor cells at the same E/T ratios, and tumor lysis was evaluated in each round of tumor killing for up to 44 h. PBNK cells lost their cytotoxic activity over time in subsequent rounds of serial killing of tumor cells, suggesting that these NK cells become dysfunctional over time.
Acknowledgments: The authors thank  Mitchell Ho  for providing information and discussions on the hYP7 antibody;  STC Biologics  for producing CYT-303 for this study;  Elisabetta Burchi  and  David Calligaris  for their assistance in editing the manuscript;  Tom Teper  for his contribution in preparing the graphic abstract; and SNBL for performing the toxicology studies in the cynomolgus monkeys.
ACKNOWLEDGEMENTS We would like to thank  Dea Garcia-Hermoso  and  Marie-Elisabeth Bougnoux  for their assistance with the identification of the fungal species,  Pr Dany Anglicheau  for helping care for the patient, and  Pr Salvatore Cisternino  and  Dr Joel Schlatter  for their participation in providing the topical voriconazole formulation. The authors have no conflicts of interest to declare.
UCPVax is a therapeutic cancer vaccine developed by our team and composed of two separate peptides called UCP2 and UCP4 derived from telomerase. This vaccine, evaluated in two early clinical trials (NCT02818426  [17] , NCT04280848), displays a good safety profile and improves anti-TERT CD4 Th1 in peripheral blood. We have elaborated a collaborative network to investigate the clinical impact of this Th1-inducer vaccine with atezolizumab in tumors where telomerase reactivation contributes to an oncogene addiction: human papilloma virus (HPV)-induced cancers and HCC. Our team has already promoted a phase II clinical trial (VolATIL study, NCT03946358  [18] ) in HPV + cancers. This study combining the anti-telomerase vaccine with atezolizumab shows a favorable safety profile and promising long-lasting response and HPV ctDNA complete disappearance in the interim analysis.
Methods and analysis TERTIO study is a multicentre, non-comparative, randomized, open-label phase II trial, to evaluate a strategy combining UCPVax, atezolizumab and bevacizumab in advanced patients with unresectable HCC. This study was developed by the "National Institute of Health and Medical Research (INSERM), Unit 1098" and "Clinical Investigational Center (CIC) 1431". The study is sponsored by University Hospital of Besançon and supported by INCa and DGOS (PHRC-K22-127), by the GERCOR collaborative group and A. R. C. A. D. Foundation. The data management, the methodology and the statistical analyses are undertaken by the "Methodology and Quality of Life Unit in Oncology" of the University Hospital of Besançon. The trial is registered on the clinicaltrials. gov database (NCT05528952). The study has received the approval from Committee for Protection of Persons and by the French National Agency for the Safety of Medicines and Health Products on August 10, 2022 by Clinical Trials Information System (CTIS) portal, and will be conducted in accordance with the Declaration of Helsinki and the Good Clinical Practice.
Evaluation, Laboratory tests and follow-up Tumor assessment will be carried out according to RECIST v1. 1 criteria using total body CT scan performed every 8 weeks until progression, at end of vaccination visit, and at end of atezolizumab plus bevacizumab treatment visit. If progressive disease, it could be confirmed by another total body CT scan 4 to 8 weeks after the precedent. A liver MRI will be also planned at baseline, at W9, and at M6. Radiological assessments will be anonymized by the investigational centers and all imaging data will be collected at the end of the study for centralized review.
The Monitor will perform source document verification and validation and request clarification to ensure the accuracy, completeness, and reliability of data. The Investigator guarantees the Sponsor or its representative direct access to source documents. Throughout the study, data electronically captured via eCRF will be regularly checked for consistency, and queries on data clarification will be generated through eCRF. At the end of the data handling process, a data review meeting will be held to prepare the database lock. After database lock, data will be transferred into SAS format to produce statistical analyses.
Study population Blood samples for PBMC and serum isolation were collected from SLE patients attending the University College London Hospital (UCLH) rheumatology clinic, and from healthy volunteers following informed consent. Ethical approval was obtained from the UCLH Health Service ethical committee, under REC reference no. 14/SC/1200. Sample storage complied with requirements of the Data Protection Act 1998. The study was designed in a cross-sectional manner. During the period 2009-2020, 501 patients were recruited at University College London Hospital (UCLH) rheumatology clinic. All patients had to have a diagnosis of SLE satisfying at least 4 of the 11 American College of Rheumatology classification criteria and updated in 1997, with a disease duration of R6 months. 43, 44 Patients were positive for antinuclear antibody (ANA or anti-double-stranded DNA (dsDNA) antibodies.
QUANTIFICATION AND STATISTICAL ANALYSIS Flow cytometric data were analyzed with FlowJo software v. 10. 4. 1 (TreeStar). Statistical analysis was performed with GraphPad Prism (La Jolla, USA), using unpaired t tests or non-parametric analysis using the Kruskal-Wallis test with Dunn's multiple comparison test for multiple comparisons, or one-way ANOVA for data passing Shapiro-Wilk normality tests. Correlations were assessed with non-parametric Spearman correlation coefficient. A p value of <0. 05 was considered as significant. ns: not significant, *p < 0. 05, **p < 0. 01, ***p < 0. 001, ****p < 0. 0001.
ACKNOWLEDGMENTS This work is funded by a  Versus Arthritis UK program  grant ( 21140 ) to C. M. ; the  Versus Arthritis UK   Research Award  ( 21786 ) to C. M. and M. M. ; the  Academy of Medical   Sciences Springboard Award  ( SBF006\1165 ) to M. M. ; the  European Regional Development Fund  (project no. 2014-2020. 4. 01. 15-0012  and the  Center of Excellence in Genomics  [EXCEGEN] framework) to L. H. , P. P. , and K. K. ; and  Estonian Research Council  grants  PRG1117  to K. K. and  PRG377  to P. P. H. F. B. is funded by a  UCB   BIOPHARMA SPRL/BBSRC PhD Studentship  ( BB/P504725/1 ). We thank Immunoqure for the provision of monoclonal Abs (mAbs) for the pan-IFNa assay under an  MTA  to  D. D. D. D. acknowledges support from the  ANR  ( CE17001002 ). We thank  Drs. Diego Catalan  and  Christopher Piper  for critically reviewing the manuscript.
Integrase inhibitors (INIs) are a potent option for HIV treatment. Limited data exist on INI resistance in West Africa, particularly in children living with HIV/AIDS. We determined the prevalence of integrase gene polymorphisms and the frequency of naturally occurring amino acid (aa) substitutions at positions associated with INI resistance. Dried blood spot (DBS) samples were obtained from one hundred and seven (107) HIV-1-infected children aged less than 15 years old in two West African countries, Benin and Mali. All children were naïve to INI treatment, 56 were naïve to anti-retroviral therapy (ART), and 51 had received ART. Genetic sequencing of HIV integrase was successful in 75 samples. The aa changes at integrase positions associated with INI resistance were examined according to the Stanford HIV Genotypic Resistance database.
Since the implementation of INI regimens, surveillance of INI-selected mutations has gained in importance  [13]. Several INI-resistance-associated mutations (RAMs) have been reported  [7]. Three groups (major, accessory, and other mutations) have been classified in the Stanford HIV Drug Resistance Database (http://hivdb. stanford. edu, accessed on 2 January 2023) based on their associations with reduced drug susceptibility: (1) major mutations represent non-polymorphic mutations that, by themselves, reduce susceptibility to one or more INIs; (2) accessory mutations represent polymorphic or non-polymorphic mutations that can reduce INI susceptibility in combination with major RAMs; (3) other mutations are polymorphic or non-polymorphic mutations that can be selected under INI-based therapy and which may or may not potentially reduce susceptibility  [1].
stanford. edu/, accessed on 2 January 2023). Some uncommon nonpolymorphic accessory mutations, such as M50I/L/P, H51Y, and F121Y, alone, do not reduce INI susceptibility  [15]. We also analyzed 19 natural polymorphisms (I72V, L74I/M, T97A, T112I, A128T, E138K, Q148H, V151I, S153Y, S153A, M154I, N155H, K156N, E157Q, G163R, V165I, V201I, I203M, and T206S)  [16]. HIV-1 strains were defined as resistant if they carried at least one major transmitted drug-resistance (TDR) mutation or natural polymorphism. The overall prevalence was defined as the percentage of HIV-1-infected patients with any strain with a TDR mutation or natural polymorphism. All sequences were submitted to GenBank and registered under accession numbers OQ435656-OQ435729.
Acknowledgments: We would like to acknowledge the  Agence Nationale de la Recherche sur le SIDA et les Maladies Infectieuses Emergentes  ( ANRS MIE ) for her support through the  Laboratory of virology Saint-Antoine Hospital in Paris  and the " Building the Next Generation of Researchers in TB/HIV Diagnostics in Mali (B-NextGen) Mali ", under award number  D43TW010350. The authors are also grateful to the  Northwestern University's Institute for Global Health Catalyzer program , the  National Institutes of Health , and the  HBNU Consortium.
We notably highlighted that tissue resident macrophages (LYVE1 + CD206 + ) in perivascular synovial niches encompassing specific subsets of vascular cells, fibroblasts and immune cells vanished in active RA but were recovered in response to DMARDs treatment. Combined ligand-receptor analysis of single-cell RNA sequencing datasets identified that IL10, C-type lectin or TAM (TYRO3, AXL and MERTK) receptors were particularly involved in the restoration of these spatial cell interactions in the context of clinical remission. In addition to providing an unprecedented synovial spatial mapping, our work uncovered novel potential cellular and molecular targets for the development of therapies for RA.
For the first time, we provided a comprehensive characterization of synovial cells in the lining, sublining and ELS niches across healthy and disease conditions. We found that LYVE1 + CD206 + TRM population was disturbed in the synovium of early treatment-naive patients and significantly reestablished in a distinct cellular neighborhood following MTX treatment. Furthermore, using ligandreceptor analysis strategies of public scRNAseq databases, we highlighted that LYVE1 + CD206 + TRM cell interactions specifically observed in responder RA patients may involve several mediators, such as IL10, C-type lectin receptors and TAM receptors (TYRO3, AXL and MERTK). Overall, this study provides insights into the spatial distribution and the pathogenic connections between synovial niches and highlights key pathways relevant for better understanding RA pathogenesis and for the development of novel therapeutic strategies.
1D ). The different cell subsets determined by IMC were also compared to the cell clusters determined using public scRNAseq datasets covering 23,759 synovial cells dissociated from the synovium of RA patients (n=11) (Fig. 1E )  (7, 15). Using a clusterization approach based on the same markers as in previous IMC analysis, we found similar cell clusters in public scRNAseq datasets, including TRMs, IMs, T and B cells, fibroblasts, endothelial and mural cells comprising smooth muscle cells and pericytes (Fig. 1E ,F and Fig. S2C ). Therefore, in addition to confirming the presence of synovial single-cell clusters previously highlighted using scRNAseq  (7, 15) , IMC provides further insights into their spatial organization. Importantly, we distinguished two distinct lining TRM cell subsets based on their differential expression of TIM4 and MERTK.
Combined spatial synovial mapping and scRNAseq ligand-receptor analysis underline SL-TRM3 cellular pathways linked to csDMARD treatment response. To further highlight the pathways that govern cell communications within the synovial niches, we further analyzed the public scRNAseq datasets of synovial cells dissociated from the synovium of patients with active RA (n=8) and in remission (n=3) introduced previously (Fig. 1E ,F)  (7, 15). We compared the differential ligand-receptor interactions between active and remission RA samples (Fig. S6 ). Interestingly, several ligand-receptor interactions were induced in the synovial tissue of RA patients in remission when compared to active RA, such as interactions involving SL-TRM3 (Fig. 5A ), in line with the spatial analysis presented above (Fig. 4 ).
Importantly, csDMARD treatment was able to induce a partial recovery of the basal homeostatic synovial cartography i. e. part restoration of SL-TRM3 cells, allowing, for example, the reorganization of lining fibroblasts and TRMs cells similar to the healthy or OA situation. The homeostatic proportion of SL-TRM3 was indeed partly recovered 6-months after MTX treatment, and these cells established strong interactions with IMs, TRMs, lymphoid and stromal cells. Perivascular SL-TRM3 cells are positive for the hyaluronan receptor LYVE1 and the mannose receptor CD206, and are thought to control homeostatic collagen production, prevent leukocyte infiltration and fibrosis  (11, 33, 34). They are therefore well adapted to exert beneficial roles in response to treatment. To overcome the technical limitation that currently restricts the maximum number of markers that can be simultaneously analyzed using the IMC approach (33 antibodies in this study), we further dissected the molecular basis of synovial cell communications by combining IMC with public scRNAseq datasets analysis and explored a large number of cell-cell communications based on ligand-receptor interactions.
Further studies should assess whether tissues presenting other histopathological profiles (pauci-immune and diffuse-myeloid (  5 ) exhibit specific disease-and treatment-response related cellular and molecular pathways. Moreover, although one of the strengths of our study consist in the comparison of the expression of 33 proteins between paired synovial samples of active treatment-naïve and csDMARD-treated responders RA patients, our combined scRNAseq analysis based on public datasets focused on the comparison between active and remission RA patients. In accordance with the IMC data, the scRNAseq analysis validated our key findings in an independent cohort, further supporting the robustness of out findings. In summary, we provided an unprecedented single-cell profiling of the synovial tissue in homeostatic conditions and in the context of RA before and after csDMARD treatment.
Imaging Mass Cytometry acquisition Images were acquired with the Hyperion Imaging System (Fluidigm, Standard Biotools) according to the manufacturer's instructions. After choosing the ROI in the section, the ROI was ablated with a UV laser at 200Hz. Data were exported as MCD files and visualized using the Fluidigm MCD™ viewer v1. 0. 560. 6. The minimum and maximum thresholds were adapted for each marker and for each tissue for optimal visualization.
Finally, similar sub-clusters were merged, annotated and the macrophages and non-macrophages populations were reunited in a single data frame for further analyses. A t-SNE (Barnes-Hut t-SNE method) dimensional reduction was performed to visualize the data on 2D maps, after a concatenation and a 99 th percentile normalization of the data (initial dimensions = 110; perplexity = 30; theta = 0. 5; max iterations = 1000). Scatter plots of the mean intensity for each marker and proportion of expressing cells were generated using the ggplot2 package (v3. 4. 0).
Distances and cell-cell interactions Each cell was assigned a minimum distance value from either vascular cells or lining cells (L-TRM1 cells and L-fibroblasts) using the minDistToCells function of the R package imcRtools (v1. 5. 2)  (50). Data were represented using the ggplot2 package (v3. 4. 0). Cell-cell interactions were determined and visualized using the R packages imcRtools (v1. 5. 2) and cytomapper (v1. 8. 0)  (51) , respectively. A permutation test was performed to define the positive or negative interactions with neighboring cells. Cells were considered as neighbors within the 5 nearest cell neighbors (k=5) and a distance threshold of 20 µm, using the Histocat knn interaction graph method. The plotSpatial function was used to visualize cells' centroids and cell-cell interactions.
Single-cell RNA-seq analysis Preprocessed scRNA-seq count data were retrieved from two public datasets (E-MTAB-8322  (7) , GSE200815 (  15 )) covering single synovial cell data from patients with active RA (n=8) and remission RA (n=3). Active RA patients included both treatment-naïve patients (n=5) and DMARDs-resistant patients (n=3), the latter being treated for more than 6 months and resistant to both MTX and TNF inhibitors. Cells characterized by the expression of less than 200 genes or more than 20% mitochondrial genes were removed. Count data were SCTransformed using Seurat (v4. 2. 0). We then corrected sample-driven batch effects with the Harmony (v0. 1. 0) function and projected the cells into two dimensions with UMAP using 50 principal components. Seurat was used to identify clusters with a resolution setting of 0.
6. Macrophages and T cells were sub-clustered with a resolution setting of 0. 3. The clusters were manually annotated according to IMC clusters by identifying the differentially expressed genes using the FindAllMarkers function in Seurat and focusing on the markers used for IMC. Clusters annotated as "fibro", "prolif", "undefined" and "T cells" in Fig. 1E  were not considered for further analyses. Scatter plots of the mean expression for each marker and proportion of expressing cells were generated using ggplot2. Ligand-receptor analysis were performed using the CellChat (v1. 6. 1) R package workflow using default settings, adding the S100As ligand-receptor interactions (52) into the CellChatDB interaction file. We compared active RA versus remission RA samples. All outgoing / incoming signaling patterns and differential interactions were first computed.
Statistics Statistical analyses were performed using GraphPad Prism v8 statistical software. P-values of <0. 05 were considered significant and data were expressed as mean ± standard error of mean (SEM). Differences in quantitative variables were evaluated by the Mann-Whitney U test. Paired Student's t-test was used to perform paired-analysis of cell frequencies at baseline and 6 months after treatment. The investigators were blinded to sample group allocation during experiments and analysis.
Acknowledgements: We are thankful to the  MicroPICell facility  for advice on IF and confocal microscopy ( S. Nedellec  and  P. Paul-Gilloteaux ), the " Institut de la Main Nantes Atlantique"  ( L. Ardouin ), and the department of orthopedic surgery of the  Nantes University Hospital  (D. Waast) for providing biopsies. The authors also acknowledge the SC3M plateform from the  Inserm/NU/ONIRIS UMR1229 RMeS Laboratory  and  SFR   François Bonamy -UMS 016  for their help to manage bio-informatic datasets, biopsies, and prepare slides ( J. Veziers ,  Y. Le Guennec  and  M. Dutilleul ).
Funding: The funding for this project was provided by  French « Agence Nationale de la Recherche » (ANR , grant  SyMAC ANR-18-CE14-0042 ),  Novartis-Société Française de Rhumatologie (SFR ,  Dreamer grant ),  Institut National de la Santé et de la Recherche Médicale (Inserm)  and  Nantes University. ALP was a recipient from the  Nantes University Hospital  internship. MAB was funded by the  « Fondation pour la recherche médicale »  [grant number  ARF202004011786 ] and by the  Inserm « ATIP-Avenir » program. A. N. was funded by  « Versus Arthritis » Clinical Lectureship in Experimental Medicine  and Rheumatology [grant number  21890 ]. Medical Research Council (MRC)  support has been obtained for the development of the PEAC cohort [grant number  36661  to CP] and  « Versus Arthritis  » has supported the  Experimental Arthritis Treatment Centre  [grant number  20022  to CP].
Alignment of multiple amino acid sequences The Homo sapiens ezrin (NP_003370. 2) amino acid sequence was aligned with other ezrin sequences with the Basic Local Alignment Search Tool and the protein database of the US National Center for Biotechnology Information (blast. ncbi. nlm. nih. gov/Blast. cgi). Multiple sequence alignment was performed with AlignmentViewer, a program for multiple sequence alignment (alignmentviewer. org), with the ezrin amino acid sequences of Mus musculus (NP_033536. 2), Struthio camelus (KFV87607. 1), Chelonoidis abingdonii (XP_032649155. 1), Callorhinchus milii (AFO94923. 1), Danio rerio (NP_0010183 26. 1), Latimeria chalumnae (XP_014352395. 1), and Petromyzon marinus (ENSPMAP00000008006).
Mass cytometry Staining and data acquisition. In total, 5 3 10 6 PBMCs were stained with Cell-ID Cisplatin-195 Pt (Fluidigm [now Standard BioTools], South San Francisco, Calif) to detect dead cells. The PBMCs were then subjected to FcR blockade with Human TruStain FcX blocking solution (BioLegend, San Diego, Calif), stained with the antibody mixture, as previously described  16  (see Table  E1  in this article's Online Repository at www. jacionline. org), fixed with 1. 6% paraformaldehyde, and stained with Cell-ID intercalator-Ir. The stained PBMCs were then analyzed in a Helios CyTOF 3. 0 cytometer (Fluidigm) at the Vanderbilt University Cancer and Immunology Core. The data were exported as a flow cytometry standard (FCS) file and normalized against EQ bead standards (Fluidigm) according to the manufacturer's protocol.
Data analysis. For the multidimensional analysis, the data were pregated to remove dead cells and debris, and leukocytes were selected by FlowJo v10. 7. 2 (Becton Dickinson, Franklin Lakes, NJ), as previously described. 16 The pregated data were exported as an FCS file and imported into RStudio (rstudio. com). We used the CATALYST package  17  for the arcsine transformation of marker intensities with a cofactor of 5 and subsequent analysis. FlowSOM was used for unsupervised clustering,  18  the R package 'ggplot2' was used for data representation, and MEM  19  was used for the characterization of the different clusters. Manual gating was performed in FlowJo, as previously described. 16 Population frequencies were exported from FlowJo and analyzed by Prism 9 (GraphPad Software, La Jolla, Calif).