dataesr/scientific-paragraphs-categorization huggingface dataset:
Protein Identification and Quantification For NanoLC-ESI-MS/MS analysis, three independent biological replicates of WC and EV protein extracts (approximately 30 µg per sample) were resolved using 12% SDS-PAGE and Biosafe Blue Coomassie coloration. Then, gel sections were cleansed with acetonitrile and ammonium bicarbonate solutions and dried under a SpeedVac concentrator (SVC100H, Savant Instruments Inc, New York, NY, United States). The samples were submitted to overnight in-gel trypsinization at 37 • C  [52, 53]. Peptide separation and detection by mass spectrometry were performed according to Tarnaud et al. [54]. The X!TandemPipeline software  [55]  was used to identify peptides (maximum e-value of 0. 05) from the MS/MS spectra. The peptides were searched against the two genomes sequence of S.
aureus NCTC8325 and HG003 (GenBank accessions no. NC_007795. 1 and GCA_000736455. 1). The database search parameters were specified as follows: trypsin cleavage was used and the peptide mass tolerance was set at 10 ppm for MS and 0. 05 Da for MS/MS. Methionine oxidation and serine or threonine phosphorylation were selected as a variable modifications. For each peptide that was identified, a minimum e-value that was lower than 0. 05 was considered to be a prerequisite for validation. A minimum of two peptides per protein was imposed, resulting in a protein false discovery rate (FDR) < 0. 5% for peptide and protein identifications. Note that a protein was considered present in a given condition when it was detected in at least two out of three biological replicates. Each peptide that was identified by tandem mass spectrometry was quantified using the free MassChroQ software (MassChroQ 2.
2. 21, PAPPSO, Jouy-en-Josas, France)  [56]  before data treatment and statistical analysis under R software (R 3. 2. 2, The R Foundation for Statistical Computing, Vienna, Austria). A specific R package called 'MassChroqR' was used to automatically filter dubious peptides for which the standard deviation of their retention time was longer than 30 s and to regroup peptide quantification data into proteins. For XIC-based quantification, normalization was performed to take account of possible global quantitative variations between LC-MS runs. The peptides that were shared between the different proteins were excluded automatically from the dataset as well as peptides that were present in fewer than 85% of the samples. Missing data were then imputed from a linear regression based on other peptide intensities for the same protein  [57].
Then, analyses were performed to investigate the composition and functions that were associated with WC and EV proteomes. The predictions of subcellular localization revealed that cytoplasmic proteins composed from 71 to 84% of the WC proteome, while these values dropped down to 42-55% for EVs (PSORTb, n = 668 vs. 236; SurfG+, n = 808 vs. 287; PRED-LIPO, n = 814 vs. 309) (Figure  2A-C ). In contrast, WC presented less membrane proteins Principal component analysis (PCA) was first performed on peptide quantification values to assess the consistency of the proteomics data (Figure  S2 ). The PCA scatter plot showed that samples from WC and EVs formed separate clusters. All the WC samples formed a unique cluster, while the EV samples were grouped into two clusters depending on whether the EVs were produced at 6 or 12 h.
Acknowledgments: This work was conducted in the frame of  BactInflam International Associated Laboratory between INRAE (France)  and  UFMG (Brazil). It benefited from the facilities and expertise of the MRic-TEM platform [107]. We are grateful to  Agnes Burel  ( Univ Rennes ,  BIOSIT-UMS 3480 ,  US_S 018 ,  Rennes, France)  for sessions with the microscope.
CTC Enrichment and Sensing in PBS Flow Figure  5a  illustrates the sensorgrams of the functionalized plasmonic fiber probe in the continuous PBS flow containing MCF-7 cells of different concentrations from 0 to 500 cells/µL. The sensorgram was acquired at a rate of 20 data points per second and plotted the averaged data by every 15 s. It was found that the sensorgram reached the saturation after a wavelength shift of 5. 6 nm in 15 min when testing the PBS flow with a concentration of 500 MCF-7 cells/µL; this was while the wavelength shift at 15 min were 3. 8 nm and 1. 3 nm for the PBS flows with a concentration of 50 and 10 MCF-7 cells/µL, respectively. It is also noted that there is only a marginal difference of about 0. 1 nm in terms of the shift of resonance wavelength between the sensorgrams of the PBS flow of 1 MCF-7 cell/µL and PBS baseline.
the averaged data by every 15 s. It was found that the sensorgram reached the saturation after a wavelength shift of 5. 6 nm in 15 min when testing the PBS flow with a concentration of 500 MCF-7 cells/μL; this was while the wavelength shift at 15 min were 3. 8 nm and 1. 3 nm for the PBS flows with a concentration of 50 and 10 MCF-7 cells/μL, respectively. It is also noted that there is only a marginal difference of about 0. 1 nm in terms of the shift of resonance wavelength between the sensorgrams of the PBS flow of 1 MCF-7 cell/μL and PBS baseline. To evaluate the LOD of the functionalized plasmonic fiber probe, a logarithm fitting was performed on the relative shift of resonance wavelength recorded after a 15 min enrichment period versus PBS solutions of different MCF-7 cell concentrations.
Funding: This work was supported by the  Innovation and Technology Fund (ITF) of Hong Kong SAR  ( ITS/061/18 ,  ITS/240/21 ); the  Research Grants Council (RGC) of Hong Kong SAR  ( ECS24211020 ,  GRF14203821 ,  GRF14216222 ); the  Shun Hing Institute of Advanced Engineering  ( BME-p3-20/4720264 ) at the  Chinese University of Hong Kong (CUHK ); and the  PHC PRO-CORE-Campus France/Hong Kong Joint Research Scheme  (No. 44683Q ).
Determination of the serum levels of cytokines We measured cytokine levels in serum samples using the mouse ProtocartaPlex 10-plex immunoassay kit (Thermofisher Scientific, Vienna, Austria), following the manufacturer's recommendations. Data were acquired on the MAGPIX®-Luminex XMAP technology (Merck Millipore, Darmstadt, Germany) using the Luminex XPONENT software solutions. The concentration (pg/mL) of each cytokine was determined by interpolating the median fluorescent intensity (MFI) of a dilution standard curve over seven dilution points supplied with the kit and calculated by the ProtocartaPlex Analyst 1. 0 software (eBioscience, Thermo Fisher Scientific, USA). The immune mediators were classified into four categories: T helper-1 cytokines (IL-2, IFN-γ, and TNF-α), T helper-2 cytokines (IL-4, IL-5, and IL-13), T helper-17 cytokine (IL-17A), and regulatory cytokines (TGF-β1 and IL-10).
Bioinformatics Immune-Epitope Database and Analysis Resource (http://www. iedb. org/) was used in order to predict SARS-Cov2-specific T cell epitope positional frequency from the conserved SARS-Cov2 (5ID2697049) spike glycoprotein region (P0DTC2)  (20). The request performed in September 2021 retrieved 231 epitopes and 414 assays from 23 references when using as selection criteria: human host, T cell IFN-γ release assays, and any MHC restriction.
Statistics Continuous data are described as mean ± standard error of the mean (SEM). Differences were analyzed using the t-test or the Mann-Whitney-Wilcoxon test when the normality was absent. Receiver operating curves (ROC) were generated to determine the area under the curve (AUC) and the optimal cut-off values were chosen using Youden's index. The Spearman rank correlation was used to compare techniques. Data were analyzed using GraphPad Prism 9. 2 (La Jolla, CA), and a p < 0. 05 considered significant.
It is absent in sub-Saharan Africa and very rare in East Asia and has a prevalence of about 1% in other regions of the world. Consistent with these findings, the patients with TB due to P1104A homozygosity in the original study were from Latin America, Europe, and the Greater Middle East. They accounted for about 1% of the total number of cases in this highly diverse cohort of patients. In a subsequent study focusing on a European population, homozygosity for P1104A was found to account for about 1% of cases of TB in British individuals after World War II  (Kerner et al. , 2019). This unbiased, population-based study was made possible by the data of the UK Biobank  (Bycroft et al. , 2018). Lifetime penetrance for the development of TB upon infection was estimated at about 80% for P1104A homozygotes.
ACKNOWLEDGMENTS We thank past and present members of the laboratory for stimulating discussions and incessant activity, and  Jacques Fellay  ( University of Lausanne and EPFL, Switzerland ),  Philippe Gros  ( McGill University, Canada ), and  Isabelle Meyts  ( KU Leuven, Belgium ) for very helpful suggestions on an earlier draft of this manuscript;  Helen Hobbs  ( UTSW, TX ) for helpful discussions; members of the  COVID Human Genetic Effort ; three anonymous referees for very constructive comments. The  Laboratory of Human Genetics of Infectious Diseases  is supported by the  Howard Hughes Medical Institute , The  Rockefeller University , the  St. Giles Foundation , the  National Institutes of Health (NIH)  ( P01AI061093 ,  R01AI088364 ,  R01AI095983 ,  R01AI127564 ,  R01AI143810 ,  R01AI163029 ,  R01NS072381 ,  R21AI137371  , andU19AI162568), the  National Center for Advancing Translational Sciences (NCATS) ,  NIH Clinical and Translational Science Award (CTSA) program  ( UL1TR001866 ), the  Fisher Center for Alzheimer's Research Foundation , the  Meyer Foundation , the  JPB Foundation , the  Robertson Therapeutic Development Fund , the  Tri-Institutional Stem Cell Initiative fund (Tri-SCI) , the  French National Research Agency (ANR)  under the  ''Investments for the Future'' program  ( ANR-10-IAHU-01 ), the  Integrative Biology of Emerging Infectious Diseases Laboratory of Excellence  ( ANR-10-LABX-62-IBEID ), the  French Foundation for Medical Research (FRM)  ( EQU201903007798 ), the  French Ministry of Higher Education, Research, and Innovation  ( MESRI-COVID-19 ), the  FRM  and  ANR   GENCOVID  project ( ANR-20-COVI-0003 ),  ANRS Nord-Sud  ( ANRS-COV05 ),  ANR  grants  SEAeHostFactors  ( ANR-18-CE15-0020-02 ),  LTh-MSMD-CMCD  ( ANR-18-CE93-0008 ),  CNSVIRGEN  ( ANR-19-CE15-0009-01 ),  GENVIR  ( ANR-20-CE93-003 ),  GENMSMD  ( ANR-16-C17-005 ),  AABIFNCOV  ( ANR-20-CO11-0001 ), and  GenMIS-C  ( ANR-21-COVR-0039 ), the  ANR-RHU program  ( ANR-21-RHUS-08 ), the  European Union 's  Horizon 2020 research and innovation program  under grant agreement no.
824110  ( EASI-genomics ), the  HORI-ZON-HLTH-2021-DISEASE-04 program  under grant agreement  01057100  (UNDINE), the  Square Foundation ,  Grandir -Fonds  de solidaritepour l'enfance, the  SCOR Corporate Foundation for Science, Fondation du Souffle ,  Institut National de la Sante´et de la Recherche Me´dicale (INSERM) ,  REACTing-INSERM , and the  University of Paris.
Blood sample data processing Data on blood cultures were extracted from the LIS of the laboratories serving these 25 hospitals and merged in a relational SQL-queryable database. A blood culture set (BC set) was defined as the combination of one aerobic and one anaerobic blood culture bottle drawn through the same puncture. A positive BC sets, defined as microbial growth in at least one of the two bottles. A clinically significant episode of BSI was defined as a positive BC set growing a recognized pathogen. (https://www. ecdc. europa. eu/sites/portal/files/media/en/publications/Publications/healthcareassociated-infections-HAI-ICU-protocol. pdf) BC sets growing bacteria belonging to commensal skin microbiota (coagulase-negative staphylococci, corynebacteria and propionibacteria) are generally defined as contaminants, except in specific individual patient clinical situations.
(Beekmann et al. , 2005;  https://www. ecdc. europa. eu/sites/portal/files/media/en/publications/Publications/healthcareassociated-infections-HAI-ICU-protocol. pdf) These BC were not included in the study since clinical data were not available in the LIS. To remove duplicates, only one BSI episode was counted when several BC sets were positive with the same microorganism for a given patient. Antimicrobial resistance was extracted from the LIS, as explained above. All of the involved laboratories participate in the national accreditation process (COFRAC), including internal and external quality assessment programs, and use the EUCAST European quality standards for antimicrobial susceptibility testing (https://eucast. org/clinical_breakpoints/).
Blood cultures Data on the 185,132 BC sets taken during the periods of January-April 2019 and 2020 in the 25 hospitals were reviewed. There was a dramatic increase in the number of blood cultures collected during the COVID-19 period, i. e. 42. 9 BCs per 100 admissions during March-April 2020 vs 23. 6 during January-April 2019 (Table  1 ). This increase was more precisely assessed by computing the rate ratios of BCs per 100 admissions, which was 1. 6 in March 2020 and 2. 37 in April 2020. This represents an increase of 60% (99% CI: 56 to 63) in March and 137% (99% CI: 131 to 142) in April 2020 in comparison to the rates recorded in the periods January-April 2019 and January-February 2020 (Figure  2 ). A similar increase in the rate ratio of positive BCs per 100 admissions occurred during the COVID-19 period (Figure  2 ).
and enterococci. (García-Solache and Rice, 2019) This dual impact is not surprising since a strong correlation between the rates of natural and acquired resistance in BSIs has been established in recent research in European countries. (Jarlier et al. , 2019) Despite the strengths of this study, which covers a large set of regional hospitals, we should acknowledge several limitations. First, the scale of the study that dealt with the approximately 120,000 patients admitted in March and April 2020 made an analysis at the individual level (invasive procedures, antibiotics prescriptions…) impossible. The research therefore captured the overall impact of COVID-19 pandemic, without patient stratification, on four indicators in the 25 hospitals. More specifically, stratification of BCs and BSIs by COVID-19 status was not performed because of lack of a unified comprehensive clinical, and microbiological database.
Erythrocytes were then lysed using Easylyse (Dako). The cells were labeled with Di Aminido Phenyl lndol (DAPI) (Sigma-Aldrich) to exclude dead cells, and precision count beads (BioLegend) were added after staining to calculate the absolute number of cell subpopulations. Gating strategies are displayed in SI Appendix, Fig. S2. A Fortessa ×20 flow cytometer (Becton Dickinson) was used to run all samples. The data were analyzed using Kaluza 2. 0 software. Peripheral blood T Cell growth. Peripheral blood mononuclear cells (PBMC) were isolated by centrifugation using Ficoll (Eurobio) density gradient. The quantification of T cells was obtained by staining PBMC with a CD3e (145-2C11) antibody (Becton Dickinson). A 96-well round-bottom plate was precoated with an anti-CD3e (145-2C11, 5 μg/mL, eBioscience) for 2 h at 37 °C.
The spleen and kidneys were harvested by sterile technique, weighed, and homogenized with a sterile tissue grinder (Ultrathurax). Viable bacterial counts were determined in bronchoalveolar lavage fluid (BALF), kidneys, and spleen after being seeded on tryptic soy agar plates (Oxoid) and incubated at 35 °C under aerobic conditions. MRSA colonies were counted after 24 h incubation. Growth was calculated as colony-forming units/mL for BAL or as colony-forming units/g for kidneys and spleen. The severity of pneumonia was quantified using ALI score of lungs fixed with PFA 4% and harvested to perform a histologic analysis of hematoxylin and eosin stained lung specimens  (52). A survival study of mice within 4 d following pneumonia initiation was performed. Statistical Analysis. All data were analyzed with GraphPad Prism 9.
ACKNOWLEDGMENTS. This work was supported by funding from the  Soci et e de R eanimation de Langue Francaise (SRLF , Bourses Master 2 SRLF). We also thank the animal house  Animalerie Rennaise Centre d'H ebergement et d'Exp erimentation (ARCHE)  platform and H2P2 platform ( Structure F ed erative de Recherche [SFR] Biosit ), and  Aude Bodin  for her help with mitochondrial functions analysis.
The development of high-resolution profiling approaches including single-cell technologies have significantly enhanced information obtained from limited human biological specimens. The use of massively parallel single-cell genomics assays can now routinely profile the transcriptome of tens of thousands of cells. Beyond RNA, it is possible to measure DNA, protein and epigenomic profiles with single cell resolution  (32). Spatial mapping technologies, which inform on cellular organization and interactions in tissues, provide additional layers of information. Significant progress is being made in the development of robust computational methods to determine cell types, states and spatial location, including through the possibility to integrate multiple datasets made publicly available (50-52).
Acknowledgments The authors warmfully thank  Pr Regis Josien  ( CR2TI ,  Nantes Universite ́)  for his critical reading of the manuscript and suggestions. JM is supported by  NExT  " Junior Talent ",  ANR JCJC  ( ANR-20-CE17-0009 ) and  ARC Programmes labellise ́s (PGA). NC is supported by a  Fondation pour la recherche me ́dicale (FRM)   PhD-fellowship  ( FDM202106013475 ).
Acknowledgments: We thank the  Natural Science Foundation of China , the  Beijing Xisike Clinical Oncology Research Foundation , the  Technology Development Program of Guangdong province and the Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation  for generous funding. And we appreciate the assistance in  Sun Yat-Sen Memorial Hospital  and the kindly help from  Inserm   U1151-CNRS UMR 8253.
Population, Setting, and Intervention For management at the TBD-RC, a medical file and a letter from a physician who referred the patient was requested prior to consultation, enabling the team to analyze all previous consultations, hospitalizations, and performed tests. Data on previous treatments were collected. Non-recommended treatments were defined as an antibiotic therapy longer than eight weeks and/or associated antimicrobials (≥2 prescribed concomitantly). There were no limitative criteria to receive patients, especially regarding positive or negative Borrelia serology. After a dedicated and multidisciplinary one-hour consultation with a meticulous physical exam, a medical summary was made and a first orientation offered in a one-day hospitalization, a conventional hospitalization, or an outpatient management.
Patient Data We collected patient data in standardized medical files (tick-exposure, past history of tick-bite, past-history of erythema migrans, delay between the tick-exposure and the symptoms, detailed clinical signs and symptoms, serological results for LB, past history of treatments etc. ) at the TBD-RC independently of the study. Anxiety and sadness were measured with the MADRS scale, STAI form, and QIDS-SR16 scale, and asthenia with the FSS-11 score  [34] [35] [36].
Approval of the Ethics Committee The local ethics committee of the University Intercommunal Hospital of Créteil, France, gave its approval for this research. All included patients gave their consent to use their medical data for research purposes prior to their management at the TBD-RC. The research sponsor signed a commitment to comply with the "Reference Methodology MR004" of the French Data Protection Authority, CNIL declaration number 2216096v0 (10 December 2019).
Acknowledgments: We are grateful to the following persons for their contribution and support to the  TBD-RC  and this study: The  Tick-Borne Diseases Reference Center-Paris  and  Northern Region Working Group  ( Agathe Bounhiol ,  Kevin Diallo ,  Danielle Jaafar ,  Claudine Badr ,  Soline de Monteynard: Department of Infectious Diseases ;  Romain Jouenne ,  Emmanuel Dossou : Department.
In the last set of experiments, animals were injected with MSU crystals into the tibiofemoral joint and after 6 h of MSU injection mice were post-treated with P140 peptide (100 µg/mouse i. v. ) or dexamethasone (2 mg/kg; intraperitoneally (i. p. ). Sigma-Aldrich D4902, St. Louis, MO, USA) used as positive control. After 15 h of MSU injection, mice were euthanized, and inflammatory parameters were evaluated. The timelines of the treatments of each experiment are displayed in the respective figure. Number of animals used in this study were calculated using a statistical software (GPOWER 3. 1. 9. 2), considering the variation of number of neutrophils in the knee lavage in our previous publications. We detailed the number of animals in the figure legends of each graph. Animals were not randomized since they are all genetically identical.
Assessment of Neutrophil Apoptosis The evaluation of neutrophil morphology was carried out using the first animal model described in our study. At sacrifice, the knee cavity was washed with PBS (2 × 5 µL) to collect cells. To analyse the apoptotic morphology of these cells, cytospin preparations of neutrophils were examined after May-Grünwald-Giemsa staining. The typical morphologic changes indicating apoptosis, such as cell shrinkage and chromatin condensationyielding fragments, were recorded in at least 100 cells per slide. The data were reported as the percentage of apoptotic neutrophils.
5 µg/mL; Cell Signaling Technology, Cat. No. 12994, Beverly, MA, USA), HSPA8 (0. 5 µg/mL; Abcam, ab51052), phospho-NFκB p65 (1 µg/mL; Cell Signaling Technology, Cat. No. 3031, Beverly, MA, USA) and annexin-A1 rabbit (1 µg/mL; Invitrogen, Cat. No. 713400, Carlsbad, CA, USA). After washing, membranes were incubated with appropriate horseradish peroxidase-conjugated secondary antibody (Santa Cruz, Cat. No. sc-2357, CA, 1:3000). Immunoreactive bands were visualized by using the Clarity Western ECL transfer substrate (BioRad, Cat. No. 1705061, Hercules, CA, USA). Expression levels of proteins in neutrophil lysates were normalized by densitometry relative to the total protein level, using Image Lab (Bio-Rad) software.
Data Availability Statement: All data needed to evaluate the conclusions of the paper are present in the paper. Additional data related to this paper may be requested from the corresponding author. Acknowledgments: A. T. V. thanks Ilma Marçal (ICB/UFMG) for technical support. S. M. acknowledges support from the French Centre National de la Recherche Scientifique; the University of Strasbourg Institute for Advanced Study (USIAS); the TRANSAUTOPHAGY COST Action (CA15138); the Club francophone de l'autophagie; the European Regional Development Fund of the European Union in the context of the INTERREG V Upper Rhine program, the FHU ARRIMAGE, and the OMAGE project granted by Region Grand-Est (France) and FEDER. All individuals included in this section have consented to the acknowledgement.
Funding: The authors are very grateful to Region Grand-Est (France) and CAPES-PRINT (for their support for the visiting position in sabbatical year of A. T. V. in Strasbourg that significantly contributed to the research activities reported in this paper. This study was financed in part by Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) grants (402530/2020-9) and (420350/2018-7) to A. T. V. ; and Fellowship, Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) finance code 001, Fundação de Amparo à Pesquisa de Minas Gerais (FAPEMIG) (APQ-03328-18), Pro-Reitoria de Pesquisa da Universidade Federal de Minas Gerais -PRPq, Instituto Serrapilheira (Serra-1912-31552). It was also supported by ITI 2021-2028 program, University of Strasbourg-CNRS-Inserm, IdEx Unistra (ANR-10-IDEX-0002) and SFRI (STRAT'US project, ANR-20-SFRI-0012) to S.