dataesr/scientific-paragraphs-categorization huggingface dataset:
Trials completed and ongoing All trials presented here are completed, have locked their databases and shared their final data for the meta-analysis. Table  2  shows the date of last follow-up for each trial. The course of each trial is represented in Figure  4  on page 14, in a subplot indicating the period of recruitment and follow-up in each trial. Figure  3  shows that three more trials are concluded and in process for their data to be added to this living systematic review. One has been in preparation for the data transfer agreement for 2,5 years, one cannot share IPD but is preparing aggregate data, and one is awaiting their own trial publication before joining the meta-analysis.
COVID-19 hospitalisations For events of COVID-19 hospitalisations only the NL, DK, BR and SA trials contribute events. However, for NL, DK and BR it is not possible to obtain a useful trial-specific confidence interval due to limited data; the estimation procedure did not converge (so we have no maximum likelihood estimate) and the intervals for the HR range from 0 to infinity. For SA, the maximum likelihood estimator in the Cox model stratified by hospital was 2. 11 with (0. 17-26. 73) as its anytime-valid 95%-confidence interval. Because we have no estimate per trial, we cannot inverse-variance weigh these estimates to produce a meta-analysis estimate, as described in the Methods section and performed for COVID-19 infections. We can however, opt for a one-stage non-stratified approach and combine all data together in one dataset and analyse it stratified by trial (but not stratified by hospital).
A challenge when analysing data of ongoing trials is that datasets are subject to retrospective changes due to misclassifications and delayed registration of events. Considering misclassifications, we used objective outcome definitions to reduce this risk. Delayed registration cannot be avoided. Both misclassification and delayed registration could be argued to be conservative or result in unbiased relative effects if not associated with the intervention, but they may somewhat increase the type-I error rate. Despite these limitations, we are convinced that a live metaanalysis in an emergency setting with over 20 trials ongoing in parallel offers important potential benefits for society. Putative false-positive findings from one of these trials might have resulted in discontinuation of some of the other trials if they observed a trend in the same direction in their own data.
Code used for the analysis The event times are considered in calendar time such that all participants within the same hospital at a given date are at risk of any events observed, regardless of their own time since randomisation (in R processed using the Surv() function from the survival package with type = "counting"). Late entries are left-truncated and participants that are lost to follow-up or vaccinated with a COVID-19 specific vaccine are right-censored. Data was analysed for e-values using the R functions designSafeLogrank() and safeLogrankTest() from the R package safestats, maximum-likelihood estimators for the HR were obtained using coxph() from the R package survival, and anytime-valid confidence sequences were obtained using inverse-variance weighted z-scores for log(HR) using computeConfidenceIntervalZ() from the R package safestats  (Turner, Ly, Pérez-Ortiz, ter Schure, & and Grünwald, 2022).
Image Capture for Immunohistochemistry All images (1,024 x 1,024 pixels) for figure preparation were acquired using a confocal microscope (Zeiss, LSM 700, objective 40X) with Zen software (Carl Zeiss, Oberkochen, Germany). Images shown in the figures were pseudo-coloured using LSM Image Browser software (Carl Zeiss, Thornwood, NY), and Photoshop (Adobe Systems, San Jose, CA) was used on the resulting tiff files only to adjust for brightness and contrast.
Statistical Analysis Statistical analyses were performed with GraphPad Prism5 software (GraphPad Software, San Diego, CA). Data were compared using a non-parametric Kruskal-Wallis test followed by a Dunn's post-test. A one-way ANOVA followed by a Bonferroni post-test was used to compare the size of the neurospheres after GCV treatment. A two-way ANOVA was used to compare body weights and food intake, and to compare the number of entries and the time spent in each area of the elevated plus maze. A Wilcoxon test was used to compare the sexual preference and the attractiveness of males. Differences were considered statistically significant for a p-value < 0. 05. Data presented in the histograms are mean values ± standard error of the mean (S. E. M. ).
ACKNOWLEDGMENTS The authors thank the PAO experimental unit No. 1297  ( EU0028 ;  INRAE Val de Loire ) for animal care, Anne-Lyse Lainéand the members of the hormonal assay platform, Nouzilly, France, for conducting testosterone and cortisol assays and the  PIC platform INRAE-Val de Loire UMR PRC. The authors wish to thank  Dr Alexandre Surget ,  Dr Matthieu Keller ,  Dr Julie Le Merrer  and  Dr Jeŕome Becker  for technical and scientific advice and for their help with behavioral testing and  Professor Michael Sofroniew  for kindly donating the Tk antibody.
In particular, non-ribosomal peptide synthetase (NRPS) genes involved in the biosynthesis of lipopeptides are considered to be an indicator for the prediction of the biological activities or functions of certain bacteria  [20, 21]. NRPS operons often consist of regularly arranged modules, where one module is responsible for the adenylation, condensation, and thiolation of one amino acid, leading to an extension of peptide chains. Due to the modular structure of NRPS, homology analysis of predicted NRPS genes identified thanks to bioinformatic tools can help to predict peptide sequences  [22]. A database dedicated to non-ribosomal peptides, named NORINE  [23] , was developed to help to identify such peptides and could therefore be used to assess the potential of endophytic bacteria to produce lipopeptides.
Bacterial and Fungal Strains A collection of 31 endophytic bacterial strains previously isolated from vetiver roots was used  [24]. These strains were selected for their growth inhibition activity against F. graminearum in in vitro dual cultures and characterized taxonomically (Table  1 ). They were stored in a 15% glycerol solution at -80 • C. The 16S rDNA sequences of the 31 strains were deposited in GenBank, and the accession numbers are shown in Table  1. The phytopathogenic fungal strains used in this study were F. graminearum, F. oxysporum, and F. culmorum. The F. graminearum strain was kindly provided by IFBM (Institut Français de la Brasserie et de la Malterie), while the other 2 strains were purchased from BCCM/MUCL: F. oxysporum f. sp. radicis-lycopersici Jarvis & Shoemaker (MUCL 039790) and F.
Lipopeptide Detection with MALDI-TOF For lipopeptide detection in the supernatants, MALDI-TOF mass spectrometry analyses were performed on an Autoflex Speed TM (Bruker Daltonics, Billerica, MA, USA). The molecular mass measurements were performed in the range of 700 to 3500 m/z and in automatic reflectron mode using FlexControl TM 3. 4 software. The equipment parameters were as follows: voltage values of ion sources #1 and #2 set as 19. 00 and 16. 50 keV, respectively; voltage values of reflectrons #1 and #2 set as 21. 00 and 9. 50 keV, respectively; lens tension 8. 00 keV; pulsed extraction 120 ns; laser intensity between 60 and 70%; smartbeam parameters set to ultra and sample rate; and digitizer settings set to 4. 00 GS/s. The MS signals were acquired by summing 10,000 laser shots per spectrum.
h-1, a nebulizer gas flow of 6. 5 bar, and source and desolvatation temperatures of 120 and 500 • C, respectively. The mass spectrometer was previously calibrated using a sodium formate solution and measurements were performed in sensitivity, positive, and data-dependent modes using the proprietary MassLynx software (version 4. 1, Waters). A maximum of 5 precursor ions with an intensity threshold of 1000 were selected for the fragmentation (MSMS) by collision-induced dissociation (CID) with specified voltages ranging from 10 to 15 V and from 20 to 100 V for the lower-and higher-molecular-mass ions, respectively. Mass data were collected in the measurement range of 200 to 2000 m/z for MS and of 10 to 2000 m/z for MSMS using lock mass correction with 556. 632 m/z, corresponding to simply charged leucine enkephalin.
Author Contributions: Conceptualization, Y. M. , S. S. -D. and F. C. ; methodology, S. S. -D. and F. C. ; validation, E. H. , S. S. -D. , A. H. and F. C. ; investigation, Y. M. , E. H. , M. D. , B. D. and T. D. ; writing-original draft preparation, Y. M. ; writing-review and editing, S. S. -D. , F. C. , A. H. and E. H. ; visualization, Y. M. ; supervision, S. S. -D. and F. C. ; project administration, S. S. -D. and F. C. ; funding acquisition, A. H and F. C. All authors have read and agreed to the published version of the manuscript. Funding: This research was supported by the "Impact Biomolecules" project (ANR-15-IDEX-04-LUE Lorraine Université d'Excellence) and by the Bio4Solutions Chaire. This research also received funding from the ALIBIOTECH program, administered by the Hauts-de-France Region.
Acknowledgments The authors thank  Tania Bray ,  Jan Hempstead ,  Heather Mayne ,  Joanne Mulder-Brambleby , and  Irene Wilson  for their supporting contributions, and all patients and families affected by MCDs, who shared their needs and concerns for development of this project. Authors involved in study conception and design were  P. Valent ,  S. V. Jennings ,  C. C. Finnerty ,  J. S. Hobart ,  M. Martín-Martínez ,  K. A. Sinclair ,  V. M. Slee ,  J. Agopian ,  C. Akin ,  I. Álvarez-Twose ,  P. Bonadonna ,  A. A. Bowman ,  K. Brockow ,  H. Bumbea ,  C. de Haro ,  J. S. Fok ,  K. Hartmann ,  N. Hegmann ,  O. Hermine ,  M. Kalisiak ,  C. H. Katelaris ,  J. Kurz ,  P. Marcis ,  D. Mayne ,  D. Mendoza ,  A. Moussy ,  G. Mudretzkyj ,  N. Nidelea Vaia ,  M. Niedoszytko ,  H. Oude Elberink ,  A.
The immunogenicity analyses, including the equivalence and non-inferiority testing, used the per protocol (PP) population (participants with no protocol violation that could have interfered with the evaluation criteria, and analyzed according to the vaccine received). Data from the full analysis set (FAS) (those who received at least one vaccination, and analyzed according to the randomization) supported the evaluation done using the PP population. The safety evaluation used the safety analysis set (SafAS) (participants who received at least one vaccination). Statistical analyses were done under the responsibility of Sanofi Pasteur's statistical group using SAS software, Version 9. 4 (SAS Institute, Cary, NC, USA).
Acknowledgements The authors would like to acknowledge all study staff for their contributions to the study conduct and all study participants and their parents/legal guardians. Additionally, the authors thank  Julie Leclercq  for assistance in the statistical analyses,  Sanofi Pasteur's Global Clinical Immunology (GCI) laboratory (Swiftwater, PA, USA)  for serological testing,  Dr Veena G Kamath  and  Dr Dinesh M Nayak  (co-investigators at  Kasturba Medical College, Manipal ), and  Dr Emmanuel Vidor  ( Sanofi Pasteur ) for his valuable input into the development of this article. The authors would also like to thank  Emilia Jordanov  for her contribution in the study. Dr Andrew Lane  (Lane Medical Writing) provided professional medical writing assistance in the preparation and development of the manuscript in accordance with the European Medical Writers Association guidelines and Good Publication Practice and was funded by  Sanofi.
Endpoints and data analysis There was no formal and homogenous sample size calculation per country since this study was exploratory, and we expected to find important variation across countries in disease profile and level of utilization of care facilities. The target size for the whole NIDIAG cohort of persistent fever was however set at 2000 participants, with at least 300 inclusions per country and a period of enrolment in each country of at least one year (to capture important seasonal variations). We first described the frequency of the diagnoses established during the NIDIAG study, with a focus on the priority ubiquitous infections, observed in at least three countries. If a participant was diagnosed with more than one priority condition, only confirmed diagnoses were retained for the analysis.
General population characteristics and outcome Of 1939 enrolled participants, 1922 (99. 1%) had sufficient diagnostic data for analysis, including 667 (34. 7%) in Sudan, 300 (15. 6%) in DRC, 577 (30. 0%) in Nepal, and 378 (19. 7%) in Cambodia. Baseline characteristics, pre-inclusion pathway, and clinical outcomes of study participants (n = 1922) are presented in Table  1  for the whole cohort and per country. The median age of the overall study population was 35 years (range: 5-99 years), but younger in DRC (median: 19 years) and older in Cambodia (median: 47 years). The male-to-female ratio was 0. 94, with only minor differences between countries. The median duration of fever was 14 days (interquartile range [IQR]: 9-28 days) and similar in all sites. A large proportion of the patients with fever also had respiratory (1325, 69%), digestive (1145, 60%), or genitourinary symptoms (710, 37%).
Funding This work is part of the  NIDIAG European research network (Collaborative Project ), supported by the  European Union 's  Seventh Framework Programme  for research, technological development, and demonstration under grant agreement no. 260260. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The corresponding author had full access to all the data in the study and had final responsibility for the decision to submit the article for publication.
Background: Mycoplasma (M. ) bovis is a major etiological agent of bovine respiratory disease, which is the most economically costly disease of cattle worldwide. Cattle disease surveillance on M. bovis is increasingly using gene-based techniques, such as multilocus sequence typing (MLST), or genome-based techniques such as core genome MLST that both require only partial genomic data. However, accurate up-to-date surveillance also demands complete, circular genomes that can be used as reference to track the evolution of the different lineages. Yet, in France, two of the main subtypes currently circulating still have no representing genome in public databases. Here, to address this gap, we provide and compare three new complete M. bovis genomes obtained from recent clinical isolates that represent major subtypes circulating in France and Europe.
The type strain of the species, M. bovis PG45 T , was isolated in 1961 in the USA from the milk of a cow with mastitis, and a laboratory clone was not fully sequenced until 2011, i. e. 50 years later  [5]. Fortunately, more recent strains have been sequenced since, and 48 complete genomes are available today in the NCBI database  [3]. If we i) focus only on strains from the animal species Bos taurus (n = 24), i. e. excluding those from bison, ii) remove ('duplicate' genomes corresponding to in vitro passages of a same strain, and iii) add two further genomes available but not retrieved by the NCBI browser, we end up with 24 complete genomes, of which only one is from France (Additional file 1), which is a surprising outcome given that France has a long history of M. bovis infections  [6] [7] [8] [9] [10] [11] [12].
All three genomes showed the low G + C content (~ 29%) and other genomic features typical of M. bovis, such as two sets of rRNA (23S, 16S and 5S) and 35 tRNA loci (Table  1 ). The total number of predicted CDS varied from 884 for strain L15762 to 925 for strain F9160 and 1,025 for strain L15527. The three genomes were highly similar with an ANI calculated using PG45 T as a reference varying between 98. 0% for L15527 to 99. 6% for the closest strain F9160 (Table  1 ). The genome size of strains L15762 and F9160 was coherent with other completelysequenced M. bovis isolates available in databases, in a range of [0. 948516-1. 165290 Mb] (Additional file 1), but isolate L15527 surprisingly had a bigger genome of 1. 187771 Mb.
Three µg of size-selected pool was liganded to an AMII adapter, then purified with L fragment buffer. Sequencing was performed using SQK-LSK109 sequencing reagents and GridION × 5 (GridION release 20. 10. 06). The Guppy version 5. 0. 11 base caller was used in super accuracy mode to generate the FASTQ files, which included a quality score Q for each base of each read that is correlated to error rates but slightly differs from the Phred score  [25]. FASTQ files with a score > Q7 were demultiplexed using a barcode detection score of 72 and a midadapter detection score of 60.
e. a minimum read length of 1,000 bp and target bases was selected to retain 500 Mb  [18, 23]. Annotation was done using the Prokka 1. 14. 6 pipeline  [56]. Assembly statistics were computed using QUAST 5. 0. 2  [57]  with M. bovis PG45 T genome (GenBank accession number NC_014760. 1) as reference. To evaluate the completeness of the reconstructed genome, assemblies were run through  Busco 4. 1. 4 [58]  with the following settings: -m geno -auto-lineage-prok and the mycoplasmatales_odb10 lineage database (174 genes).
In silico analyses for detection of IS and ICE The presence of IS was searched using the BLASTn tool in the ISFinder database  [21, 39]. For ICE detection, BLASTn searches were run against each genome to search for CDS sequences corresponding to the core ICE backbone as defined by Tardy et al. plus CDS3, 14, 16 and 19  [30]. In detail, CDS1 (GenBank locus tag MBOVPG45_0213) and CDS22 (MBOVPG45_0183) were used to search for ICEB PG45 -2 and CDS3 (MBOVPG45_0495), CDS5 (MBOVPG45_0494), CDS14 (MBOVPG45_0487), CDS16 (MBOVPG45_0484), CDS17 (MBOVPG45_0483), CDS19 (MBOVPG45_0481) and CDS 22 (MBOVPG45_0479) were used to search for vICEB PG45 -1.
Acknowledgements We thank  Christophe Boury  from the PGTB platform for his precious insight and help with the ONT data. We thank the  IFB Core Cluster and Community  for allowing us to perform the analyses of genome assembly. We thank  Antoine Drapeau  for letting us test different assembly protocols on his computer server and for insightful discussions on the outputs. We also thank  Maxime Bruto  for his help with ANI analysis and critical reading of the manuscript.
Genome comparison The complete or draft genome sequences (whole-genome shotgun allowed gap set to five genes). In order to analyse the gene content of the T. maritimum type strain's O-AGC, similarity searches were performed with each encoding proteins: (i) using BLAST-P against the Swiss-Prot database (release 2022_01) and (ii) using HHpred with default parameters in the PDB_mmCIF70 database (release 12 October 2021). HHpred is a sensitive protein homology detection, function and structure prediction based on HMM-HMM comparison  (Zimmermann et al. , 2018). For phylogenetic reconstruction, comparison of the gene content between strains was done by pairwise proteome similarity search using BLAST-P Bidirectional Best Hit and the MicroScope default parameters (i. e. >80% protein identity, >80% coverage).
A set of 2034 groups of core genome proteins was retained and multiple alignments on individual groups were performed using MUSCLE using an inhouse R script. The resulting alignments were concatenated using an inhouse script and tree phylogenetic reconstruction was inferred by approximatelymaximum-likelihood using Fastree v2. 1. 10 with default parameters  (Price et al. , 2010). The tree was visualized using FigTree v1. 1. 4 and rooted using midpoint.
Conventional serotyping assay Conventional serotyping was performed using both slide agglutination and dot blot assay on 22 T. maritimum strains, whose genomes were previously sequenced  (Bridel et al. , 2020). These strains were retrieved from various geographic locations and host fish species. They display a significant diversity as they encompass the four serotypes previously described (Table  1 ). Indeed, strains were originally selected to maximize the genomic diversity and therefore expected to display such a serotypic heterogeneity. Each strain reacted strongly with a unique serum, except strain NCIMB 2154 T that was successively This is likely the consequence of typical drawbacks arising from conventional serotyping protocols. Nevertheless, the resulting data were used as a cornerstone for comparing serotypes with strains' genomic organization.
Development of an mPCR serotyping scheme Based on these observations and on the grouping of strains according to the Type they belong to, we noticed that the presence of distinct genes coding transmembrane proteins was the best marker able to discriminate the Types and displaying obvious correlations with the results of conventional serotyping. Indeed, all strains belonging to Type 1 and Type 2 have a gene (MARIT_2530 in strain NCIMB 2154 T and orthologs) that is absent in strains belonging to Type 3 and Type 4. This gene encodes a protein with predicted 11 transmembrane segments but with very low BLAST-P similarities with proteins having any known function. However, using HHpred to detect remote homologies, eight out of the 10 best hits (probability ranging from 94. 84% to 99. 94% that the database match is a true positive) belong to O-antigen ligases and O-antigen polymerases family proteins.
Screening a collection of T. maritimum isolates using mPCR In addition to the 40 strains mentioned in Table  1 , we used the proposed mPCR serotyping scheme to screen a collection of 124 T. maritimum isolates retrieved from a wide variety of geographic areas and host fish species during the last 50 years. Most of these isolates have been previously typed by various methods including MLST  (Habib et al. , 2014)  and MALDI-TOF MS  (Bridel et al. , 2020). All amplifications were successful and the results are show in Table  S2. Strikingly, and taking into account the whole dataset (i. e. the 40 WGS-types strains and the 124 mPCR-types isolates), the isolates are unevenly distributed among the Types: isolates belonging to Types 1-0, 2-1 and 3-1 are widely predominant, whereas isolates belonging to Types 1-1, 2-0, F I G U R E 3 Distribution of the isolates according to their Types.
ACKNOWLEDGEMENTS The authors are very grateful to  Maelenn Le Roy  (IFREMER) and  Benjamin Fradet  ( INRAe ) for skillful technical assistance, to  Alicia Estévez Toranzo  ( USC ) and  Tatiana Rochat  ( INRAe ) for helpful discussions and critical reading of the manuscript, to the many individuals listed in Table S2 for kindly providing bacterial strains and to  Zoé Rouy  from the  MicroScope Platform  for her kind help with genome data management. This work has benefited from the facilities and expertise of the high-throughput sequencing facility of I2BC. We also wish to thank the  INRAE MIGALE bioinformatics platform , the LABGeM and the  National Infrastructure 'France Génomique'  for providing computational resources.
e. orthologous gene sets were computed using BLAST-P Bidirectional Best Hit or displaying at least 30% identity on 80% of the shortest sequence and a genomic co-localization with a Different serotypes have been reported for the type strain NCIMB 2154T. bStrain NBRC 15946 is not the type strain according toPérez-Pascual et al. (2017). c NCBI genome accession number or genome available in PubMLST (https://pubmlst. org/bigsdb?db=pubmlst_tenacibaculum_isolates&page=query). Isolate id is given in parentheses.