dataesr/scientific-paragraphs-categorization huggingface dataset:
vituli, L. africanus, H. eurysternus, S. capillatus, C. meleagridis, Go. gigas, Me. stramineus, M. gallinae, G. gallinae, Li. caponis, and P. humanus corporis. Samples were subjected to blind test analysis against the upgraded database (Table  4 ). MALDI-TOF MS identification was considered correct when there was concordance between the morphological identification and molecular identification, when the latter was possible, that is when sequences were available in GenBank and were considered reliable. In this study, we obtained 305 specimens with good quality spectra, of which 57 spectra were added as reference spectra and 248 specimens used for the blind test with an average LSV of 2. 115 and correct identification percentages between 76% and 100% (Table  4 ). In all, 103 of the 408 samples (25.
25%) tested had poor quality spectra and these were removed for this proof-of-concept (Supplementary Data 1). Nevertheless, specimens with low quality spectra were correctly identified with an average percentage of 61. 11% and with low LSVs, highlighting the quality of the database created (Supplementary Data 1). The controls of fresh and non-engorged fresh P. humanus corporis lice were well identified at each test. The intra-species reproducibility and inter-species specificity of the MALDI-TOF MS profiles were further objectified using MALDI-Biotyper software cluster analysis. Dendrogram analysis revealed specific clustering on distinct branches of lice according to species. Lice belonging to the same genus were grouped in the same part of the MSP dendrogram (Fig. 6 ).
Discussion and conclusion The morphological identification of lice is very complex because the species are morphologically close to one another. For the first time, MALDI-TOF MS was used as an additional tool for lice identification. In this study, we successfully identified 14 species of lice using MALDI-TOF MS. Morphological identification was molecularly confirmed by targeting a fragment of louse 18S rRNA gene sequences. The choice of the 18S rRNA gene is based on previous results that proved the relevance of this gene for louse identification and the presence of reference sequences in GenBank  [21]. However, 5/13 of the lice species studied in this work had no sequence available in GenBank, highlighting the drawbacks of using molecular biology alone for louse identification. Only 4/13 species of lice presented correct identification using the 18S rRNA gene.
The remaining 4/13 species of lice resulted in incorrect identification despite the fact that their reference sequences were present in GenBank. Further analysis of the GenBank reference sequences of each of these species revealed that they were all of poor quality. This study allowed us to add five new sequences that did not exist on GenBank, and eight additional complementary sequences for which a reference was already available (Table  3 ). Five of the 13 sequences of lice namely Go. gigas, B. bovis, B. ovis, B. caprae, and Chelopistes meleagridis were already published under new genera (Table  5 )  [14, 34, 38, 42, 47]. A preliminary MALDI-TOF MS database containing the spectra of 14 species was hereby created and the database will be regularly updated with the spectra of new specimens.
The spectra files are available on request and transferable to any Bruker MALDI-TOF MS device. The MALDI-TOF MS arthropod database can be shared through scientific collaboration projects; it will be possible to freely query this database online in the future. For use in entomology, the choice of arthropod body parts to be used for the MALDI-TOF MS test is a very important criterion. For ticks and mosquitoes, MALDI-TOF MS identification of the arthropod species is based on leg spectra. Other body parts had to be carefully selected for other arthropods when the legs did not provide satisfactory spectra  [10, 13, 22]. Here, the spectral profiles generated from the cephalothorax-legs of the lice subjected to MALDI-TOF MS were reproducible. Spectral analysis highlighted intra-species reproducibility and inter-species specificity, which was consistent with the morphological classification.
4 ). This can be explained by the fact that some parts of arthropods yield better spectral qualities than others, as has been demonstrated by several studies  [10, 13, 22, 43]. In this study, we included only good quality spectra. Indeed, at this stage, only high-quality spectra can be included to validate the results and create a reliable database. The number of specimens with low quality spectra can be explained by the fact that all these samples had to be frozen and thawed several times for various analyses including long morphological identification, molecular biology, and MALDI-TOF MS assays. These repeated thawing steps could have caused protein alterations responsible for the poor quality of the spectra. This hypothesis is supported by the fact that the groups of samples that were manipulated first have a greater number of high-quality spectra.
This should not be an issue when applied to entomological studies since molecular biology is not always required and when a comprehensive MALDI-TOF MS database is available, the quality of the spectra will be improved. Nevertheless, many specimens with low quality spectra were correctly identified, reaching 100% correct identification for some species such as Menopon gallinae (average: 61. 11%) (Supplementary Data 1). The performance of the identification despite the many thawing steps is a validation of the quality of the database created, which will be continuously strengthened with new field specimens. MALDI-TOF MS enables the identification of lice without any entomological knowledge  [25] , as long as the database is comprehensive. Furthermore, the MALDI-TOF MS sample preparation method is simple and the speed of data analysis makes it possible to obtain quick and reliable identification results  [50].
This study points to new possibilities for improving the knowledge of animal lice in Algeria by using several identification tools. We have also illustrated the limitations of molecular biology with the lack of comprehensiveness of the NCBI GenBank database, which is a major setback to using this method. To circumvent these limitations, we have deposited our new sequences in the NCBI GenBank database (Table  3 ). This fast and accurate low-cost tool identifies not only the different immature stages of the arthropod's life cycle  [6, 13] , but also the origin of blood meal sources from arthropods  [31]. Recently, preliminary studies have examined the ability of MALDI-TOF MS to detect Plasmodium parasites in Anopheles mosquitoes  [23] , differentiate ticks infected or not infected with Borrelia spp.
Acknowledgements. We are grateful to all the people who supported this study. We also thank  Azzedine Ouarti  who kindly helped us to access livestock, local guides and lice collection to facilitate our work. This study was supported by the  Institut Hospitalo-Universitaire (IHU) Méditerranée Infection , the  French National Research Agency  under the " Investissements d'avenir" program , reference  ANR-10-IAHU-03 , the  Provence-Alpes-Côted'Azur region, and European ERDF PRIMI  funding.
1) 95. 86% MH377329. 1 Menacanthus stramineus a 19 Menacanthus sp (AF385066. 1) 99. 79% MH377333. 1 Menopon gallinae c 5 Menoponidae sp (JQ309930. 1) 100% MH377334. 1 Chelopistes meleagridis a 9 Rhynonirmus sp. (AF385048. 1) 98. 98% MH377335. 1 Goniocotes gallinae a 5 Goniodes aff. dissimilis/gigas (AY077767. 1) 97. 69% MH469486. 1 Goniodes gigas a 2 Goniodes aff. dissimilis/gigas(AY077767. 1) 97. 69% MH469487. 1 Lipeurus caponis a 6 Rhynonirmus sp. (AF385048. 1) 99. 79% MH469485. 1 13 species 159 / / / N: Number of specimens used for molecular biology. a Species with sequences not available in GenBank. b Species with correct identification using the 18S rRNA gene. c Species with incorrect molecular identification. 6 B. Ouarti et al. : Parasite 2020, 27, 28.
CFU counts were recorded after 48 h incubation at 28 • C. Significant differences of the CFU counts were analyzed by Tukey's LSD test at (p ≤ 0. 05) using SAS software. Total community DNA was extracted from the rhizosphere pellets (500 g) with the FastDNA spin kit for soil (MP Biomedicals, Heidelberg, Germany). The GENECLEAN SPIN Kit (MP Biomedicals, Heidelberg, Germany) was applied to purify the extracted DNA according to the manufacturer's instructions. DNA samples were diluted 1:10 by 10 mM Tris HCl pH 8. 0 and stored at -20 • C for further analysis.
, 2003) , with a confidence threshold of 80%. Information regarding the sequence counts for each sample is provided in the Supplementary Table  S2 , and rarefaction curves are presented in Supplementary Figure  S2. Communitylevel analysis was performed with a cluster dendrogram using the unweighted pair group method with arithmetic mean (UPGMA, Euclidean distance). Significant changes in the relative abundance of dominant taxa were identified with an ANOVA under a generalized linear model, followed by Tukey's honest significance detection test (p < 0. 05). Sequences were submitted for deposition at the public repository Sequence Read Archive (SRA 2  ) with the accession number PRJNA574588 3. PCR-Southern Blot Hybridization-Based Detection of R. solanacearum Specific fliC Gene PCR amplification with primers targeting Rs-fliC gene was performed according to  Schönfeld et al.
FUNDING This work was funded by the  BIOFECTOR  project  312117. TE was granted a  German Egyptian Research Long-Term Scholarship (GERLS)  offered by the  Ministry of Higher Education of the Arab Republic of Egypt  (MoHE) and by  Deutscher Akademischer Austauschdienst (DAAD). SJ was funded by the  University of Bourgogne Franche-Comté  via the  ISITE-BFC International Junior Fellowship award  ( AAP3 :  RA19028. AEC. IS ).
ml -1 for control, 59,589 ± 42,886 pg. ml -1 for HYP) (data not shown). In order to validate the effectiveness of our IFN priming, we measured three cell surface markers known to be expressed at low level by MSC and stimulated by IFN. The cytometry performed on a pool of our cells showed a substantial increase in the percentage of cells expressing HLA-DR (0. 59 and 88. 56% for Cont and IFN, respectively), CD54 (13. 56 and 99. 47%), and B7-H1 (1. 91 and 98. 55%) (data not shown).
4 software from ThermoScientific, by comparing the results with a human protein database and a control database containing scrambled sequences. Proteins identified by at least two unique peptides were further analyzed for functional enrichment using the Funrich analysis software tool 1 and the human Funrich database. Nano tracking analysis (NTA) was used to determine the EV size distribution and concentration using a Nanosight NS300 with a 488 nm laser. Samples were diluted to reach an appropriate concentration (1 × 10 8 and 1 × 10 9 particles. ml -  ) with PBS. The samples were injected with an automatic syringe pump. Data acquisition and analysis were performed using the NTA Analytical Software (version 3. 4). For each sample, five movies of 60 s were recorded. All others settings were in automatic mode.
Control of MSC Priming About 1. 10 5 MSCs were incubated in PBS + 2% HSA, and 0. 5% polyvalent human immunoglobulins (LFB) for 20 min at 4 • C; then incubated with antibodies at a saturating concentration for 20 min at 4 • C: MSC CD90, HLA-ABC, HLA-DR, B7-H1, and CD54 (all from Beckman Coulter). Then, MSCs were washed with PBS and immediately acquired using Navios cytometer (Beckman Coulter). Data were analyzed on Kaluza software (Beckman Coulter). Concentration of VEGF was determined using a sandwich-enzyme linked immunosorbent assay technique (R&D system) according to the manufacturer's recommendations. VEGF was determined in MSC supernatant of naive and HYP-primed cells.
The results are not shown here but are available in a public database (GEO database, # GSE156919). Then, we measured a selection of miRNA in each individual sample of the three groups. These miRNAs were selected based on their detectability and or their description in MSC-EV in the literature. They were measured on each individual sample using custom-designed miRCURY LNA TM Universal RT microRNA PCR, Pick-&-Mix, Ready-to-use Panel (Exiqon). All miRNAs were analyzed using geNorm version 3. 4  (Vandesompele et al. , 2002)  to identify suitable internal references. The normalization was performed with five miRNAs, namely, hsa-let-7a-5p, hsa-miR-21-5p, 23a-3p, 23b-3p, and 24-3p. The final quantification was performed as the geometric mean of the quantification with the selected reference miRNA.
EV Characterization The TEM analysis showed typical round-shaped pictures in EV preparations (Figure  1A ). To validate our EV isolation protocol, we performed a proteomic analysis of the control MSC-EV preparation. The mass spectrometry analysis identified 185 proteins with at least two unique peptides. The results were analyzed with Funrich database  (Pathan et al. , 2015)  and we found that 83. 4% of them were annotated as "exososomal" (Figure  1B ) including transmembrane (for example, HLA-A, ITA3, or ITB1) and cytosolic proteins (such as FLOT1, CAV1, ANXA 1, 2, 4, and 5). Moreover, cytofluorimetric analyses of EV showed the presence of several antigens typically expressed by MSCs, CD73, CD90, and CD105, and of classical "exosomal" markers, the tetraspanins CD9, CD63, and CD81 (Figure  1C ).
Validation of the Priming Conditions To validate the efficacy of our hypoxic priming, we measured VEGF protein by ELISA in MSC supernatant and found an increase in response to HYP (15,144 ± 3119 pg. ml -1 for control, 59,589 ± 42,886 pg. ml -1 for HYP) (data not shown). In order to validate the effectiveness of our IFN priming, we measured three cell surface markers expressed at low level by MSC and stimulated by IFN. The cytometry performed on a pool of our cells showed a substantial increase in the percentage of cells expressing HLA-DR (0. 59 and 88. 56% for Cont and IFN, respectively), CD54 (13. 56 and 99. 47%), and B7-H1 (1. 91 and 98. 55%) (data not shown).
EV Secretion Profile The NTA method was used to study EV concentration and size. A typical size/concentration profile is shown (Figure  1D ). The EV concentrations in the final preparation were slightly different. We found a significant global effect when comparing the three groups; however, no difference between control and HYP or control and IFN priming was found in the multiple comparison test (Figure  1E ). The NTA showed that priming did not alter EV size distribution as evaluated by the mode, D10, D50, and D90 (data not shown). miRNA Profiling in Pools of EV Eighty-one miRNAs were detected in at least one of the pools (Control, IFN, or HYP); only 46 of them were detected in each sample. Forty-one miRNAs were quantified since five reference miRNAs were necessary to reach Genorm requirements for the normalization (hsa-let-7a-5p, hsa-miR-21-5p, hsa-miR-23a-3p, hsa-miR-23b-3p, and hsa-miR-24-3p).
Yet, taken individually, five miRNAs were significantly upregulated in IFN-primed MSC EV and one miRNA was downregulated in HYP MSC EV. The bioinformatics analysis first consisted in identifying the experimentally validated targets of selected miRNAs in miRBase and then analyzing the targets in a gene enrichment database (Panther Classification System). This approach was chosen because specific miRNA enrichment databases are very much annotated in the field of cancer, which was not relevant to our study. We identified 106 target genes; many were involved in pathways relevant to tissue repair including "p53, " "cell cycle, " "TGF-beta signaling, " "angiogenesis, " or "PDGF signaling. " Some pathways were also relevant to inflammation and immunomodulation such as "interleukin signaling, " "inflammation mediated by chemokine and cytokine signaling, " or "Toll receptor signaling.
Methods and findings A population-based prospective cohort using the French national health data system (SNIIRAM), identified 69,911 adults living within five well-defined geographical areas, who were new users of antiplatelet drugs in 2013-2015 and who had not received any antithrombotics in 2012. Among them, 63,600 started a monotherapy and 6,311 a dual regimen. Clinical data for all adults referred for bleeding was collected from all emergency departments within these areas, and medically validated. Databases were linked using common key variables. The main outcome measure was time to major bleeding (GI, ICH and other bleedings). Secondary outcomes were death, and event-free survival (EFS). Hazard ratios (HR) were derived from adjusted Cox proportional hazard models. We used Inverse Propensity of Treatment Weighting as a stratified sensitivity analysis according to the antiplatelet monotherapy indication: primary prevention without cardiovascular (CV) risk factors, with CV risk factors, and secondary prevention.
Study design and participants The study design has previously been reported  [18]. Briefly, a prospective population-based cohort study was set up linking the French Health Insurance Database (SNIIRAM) to data from all emergency departments located within five well-defined areas around five large The SNIIRAM anonymously and comprehensively links the universal healthcare reimbursement database (DCIR) to the French hospital discharge database (PMSI). The DCIR contains anonymous individual data on all reimbursements for health expenditure, including drugs. This database does not provide any direct information on the medical indication for each reimbursement. The PMSI provides hospital discharge diagnoses (ICD-10 code) as well as details on medical acts. Thus, all adult subjects (> 18 years) living in the five above-mentioned areas, affiliated to the French universal Health Insurance System, and with at least one reimbursement for an antiplatelet drug (aspirin, clopidogrel, prasugrel, ticagrelor) in 2013-2015 were identified.
PLOS ONE From emergency departments, clinical data for all adult subjects living in the five abovementioned areas and referred between January 1, 2013 and December 31, 2015 for bleeding while receiving an antiplatelet drug was prospectively collected, focusing on the type of bleeding. Their demographics were collected (month and year of birth, gender) as well as their date of hospital admission. In each emergency department, the medical referent validated the final inclusion of all records of severe bleeding detected. The SNIIRAM and clinical databases were linked using common key variables (date of birth (month, year), gender, date of hospital entry and discharge, type of antiplatelet drug, and care facility involved). Only "new users" defined as having had neither an antiplatelet drug delivery nor any other antithrombotic drug delivery in 2012 were analysed.
There was a slight alteration with respect to the International Society on Thrombosis and Haemostasis (ISTH) classification of major bleeding events, because in our dataset no information was available on haemoglobin levels  [20]. Major bleeding events were further classified into three classes: intracranial haemorrhage (ICH), GI bleeding and other bleeding events. For each type of bleeding event, censoring was based on death or any other type of major bleeding event or end of study follow-up, whichever came first. Major-bleeding-event-free survival was defined as time to major bleeding or death or end of study follow-up, whichever came first.
The indication for antiplatelet prescription was derived from the main discharge diagnosis and/or medical acts performed in the 30 days before the first observed issue of antiplatelet therapy (see S2 Table in S1 File). Three groups of patients according to antiplatelet monotherapy indications were defined: 1) patients with antiplatelet drug for secondary prevention (coronary disease, carotid artery disease, peripheral artery disease, stroke, valvular heart disease, miscellaneous diseases), 2) patients with antiplatelet drugs for primary prevention with identified cardiovascular (CV) risk factors (arterial hypertension, diabetes, renal disorders, lipid-lowering drugs), and 3) patients with antiplatelet drugs for primary prevention without any identified CV risk factors (no factors identified by the SNIIRAM database).
Principal findings Using an administrative healthcare database linked to prospectively collected clinical data from emergency departments, our population-based cohort study showed low incidence rates of major bleeding and low mortality rates among new antiplatelet drug users. A 2-to 3-fold increased risk of gastrointestinal bleeding and other major bleeding was observed in dual regimens compared to monotherapy, with a better safety profile for low-dose ASA (� 100 mg) among monotherapies. There were no significant differences across dual regimens. We observed very few events in patients prescribed with dual regimens, keeping in mind only major bleeding were accounted for; given these low incidences we had a very low power to detect any difference.
Strengths and weaknesses This large, comprehensive study is original for its ability to directly compare different antiplatelet drugs, including the different doses and regimens, encompassing all indications, to explore important, common safety outcomes. Patients exposed to anticoagulants combined with antiplatelet therapy were not included in this analysis. Analysing major bleeding minimizes the bias that affects the external validity of studies focusing on hospital data only, where patients diagnosed and managed in primary care are not included. An important point is that this study retrieved and linked data from a prospective multi-centre clinical study and from a public healthcare system that covers all residents within the defined area. As a result, the dataset provided a complete picture of all hospitalizations and prescriptions dispensed, minimizing selection bias.
The systematic medical validation of all bleeding limited the overestimation of incidence rates of major bleeding  [23]. Exposure in our study was based on reimbursement claims data. We studied drug exposure on the basis of pharmacy dispensation but we had no information on the patients' actual intake. The lack of information on patient adherence could have led to incorrect estimations of exposure, but the clinical validation of major bleeding made it possible to check that patients were still receiving antiplatelet drugs at the time of bleeding. Causes of death were unfortunately not available. The design and linkage to Health Insurance database allowed to state the study was exhaustive within five well-defined areas around five large French cities. But translating the result to French population is more hazardous.
Data Access Small RNA libraries were SRX966734 for An. gambiae ovaries  [21] , available at the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA, https://www. ncbi. nlm. nih. gov/sra); GSM830467 for Ae. aegypti adults  [24] ; GSM1318059 for fetal mouse testes  [25] ; and GSM822760 and GSM822762 for adult mouse testes  [26] , these datasets being available at NCBI Gene Expression Omnibus datasets (GEO DataSets, https://www. ncbi. nlm. nih. gov/gds).
Mapping Small RNA Reads Reads were mapped against AgamP4. 2 and AaegL3, genome assemblies for An. gambiae and Ae. aegypti respectively, allowing zero mismatch, using sRNAPipe  [27]. Small RNAs of 24-29 nt length were considered as putative piRNAs. They were mapped against transcripts or TEs using scripts and pipelines based on Burrows-Wheeler Aligner (BWA)  [28] , Bowtie2  [29]  or NucBase  [30]. RPM (reads per million) for each sequence were calculated as the number of reads per million genome-mapped reads allowing no mismatch. Multi-mapping reads were randomly assigned to the mapping sequences. Transcript-mapping reads were identified by alignment to protein-coding transcripts from genome assemblies AgamP4. 2 (An. gambiae) and AaegL3. 2 (Ae. aegypti), available at VectorBase  [31] , and to lncRNAs  [32].