dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgments We thank:  Laetitia Barbier  ( Department of Pathology, Dijon University Hospital, F-21000 Dijon, France ) for her help in analyzing temporal artery biopsies;  Sabine Berthier ,  Barbara Nicolas ,  Vanessa Leguy  and  Jérôme Razanamahery  ( Department of Internal Medicine and Clinical Immunology, Dijon University Hospital, F-21000 Dijon, France ) for their help in recruiting patients. We thank  Amandine Bataille  ( Cel-limaP, Plateforme d'imagerie cellulaire, UMR1231, Inserm; Université de Bourgogne, AgroSup; Dijon, France ),  Elodie Noirot  and  Christine Arnould  ( DImaCell -UMR Agroécologie, Université de Bourgogne, Dijon, France ) for their help in performing the experiments. We thank  Anabelle Legrand  and  Serge Monier  ( Plateforme de Cytométrie, Institut Fédératif de Recherche 100, Université de Bourgogne ).
Beta-lactam degradation by beta-lactamases is the most common mechanism of beta-lactam resistance in Gram-negative bacteria. Beta-lactamase encoding genes can be transferred between closely-related bacteria, but spontaneous inter-phylum transfers (between distantly related bacteria) has never been reported. Here, we describe an extended-spectrum beta-lactamase (ESBL)-encoding gene  shared between the Peudomonadota and Bacteroidota phyla. An Escherichia coli strain was isolated from a patient in Münster (Germany). Its genome was sequenced (Illumina and Nanopore). The ESBL encoding gene was cloned and the corresponding enzyme was characterised. Distribution of the gene among bacteria was studied with BLASTN using RefSeq Genomes databases. Frequency of its closest homolog in the Global Microbial Gene Catalog (GMGC) was also analysed.
However, ARGs from commensal anaerobic bacteria strongly differ from those found in Enterobacterales, stressing that if ARG transfers from anaerobic bacteria to Enterobacterales actually occurred, they would be particularly rare or would not persist so it would go unseen from the scientific community  (8). Hence, inter-phylum transfers of ARGs seem to be exceptional to observe outside laboratory conditions. In a recent work, we searched for ARGs in 70k E. coli genomes from the Enterobase using ARG databases including ARGs from intestinal strict anaerobic bacteria  (9, 10). We could identify four ARGs presumably originating from non-Pseudomonadota, including a beta-lactamase encoding gene also found in bacteria from the Bacteroidota phylum and that we propose to characterize in the present work.
Phenotypic characterization Analyzing 70,301 E. coli genomes available from the Enterobase, one was identified as possessing a betalactamase -encoding gene which was only found in the ResFinderFG and Mustard databases  (6, 10, 11). The strain of interest was an E. coli strain belonging to the A phylogroup, sequence type (ST) 744/2 according to the Warwick University/Pasteur Institut schemes, respectively, serotype Onovel132:H10, fimH allele 54. It was isolated in 2015 from a wound infection in a patient hospitalized at the University Hospital of Münster, Germany  (12). Of note, subcultures in LB medium yielded two distinct morphotypes. The first type corresponded to white and regular shaped colonies while the second was represented by greyish and less regular colonies (Figure  1 ). Both morphotypes were maintained in subsequent cultures.
Distribution of the blaMUN-1 gene We searched for blaMUN-1 using RefSeq Genomes databases from NCBI (>70% nucleic acid identity, 80% coverage) and BLASTN  (14). A total of 125 hits were obtained, with the blaMUN-1 gene being found in 28 species with 100% nucleic acid identity and coverage (Supplementary Table  4 ). Most of the species were from the Bacteroidota phylum and more precisely from the Bacteroidales order. A unique hit was obtained in the Pseudomonadota phylum with Sutterella wadsworthensis. Among all the hits, we could not determine whether the sequence holding the blaMUN-1 gene was chromosomal or plasmidic, one exception being a Bacteroides uniformis genome (AP019724. 1 and AP019725. 1) bearing two copies of the 7. 6 kb genomic island (containing the the blaMUN-1 gene), one being on a plasmid surrounded by sequences annotated as IS256 family transposase and site-specific integrase.
Of note, two sequences on this plasmid were annotated as phage protein. Few species displayed variation in the sequence of the blaMUN-1 gene. Hits without 100% identity were obtained in Bacteroides salyersiae, Bacteroides xylanisolvens, Parabacteroides distasonis, P. stercorea and Phocaeicola vulgatus (97. 0-99. 9% nucleic acid identity). Additionally, Barnesiella propionica was shown to bear a gene with 71. 9% nucleic acid identity and 96% coverage to blaMUN-1 gene. As in our E. coli strain of interest, the gene was occasionally found in several copies (maximum of 6 copies/genome in B. uniformis). Of note, blaMUN-1 was not found in all genomes available from a given species in any species (Supplementary Table  4 ). Additionally, MGnify and the global microbial gene catalog (GMGC) databases were used to analyze the distribution of the blaMUN-1 gene  (15, 16).
Bioinformatic analyses In our previous work  (9) , ARGs were searched in 70,301 E. coli genomes available from the Enterobase 10 using Diamond and the following ARG databases: AMRFinder (2019-04-29 version), Mustard (2017-09-30 version) and ResFinderFG (2016-11-01 version)  (6, 11, 25, 26). A hit was considered as a potential ARG if the nucleic acid identity × coverage ≥ 0. 64. All redundancies between the hits obtained in ≥2 databases were removed. The ARG families were picked according to the Mustard website (mgps. eu/Mustard). Among all hits, we identified a putative beta-lactamase encoding gene sharing 100% nucleic acid identity with a beta-lactamase-encoding gene from ResFinderFG (beta_lactamase|KU546399. 1|feces|AMX, 100% identity , 93. 9% cover) and Mustard (MC3. MG60. AS1. GP1. C4251.
19. 0). Serotype and virulence genes were characterized using the ABRicate (1. 0. 0) software and the ecoh and a home-made database respectively. The fimH allele was determined using FimTyper (v1. 1). ARGs were identified using the Diamond software (v2. 1. 8) and the ResFinder database (v4. 0)  (28). PlasmidFinder was used to characterize plasmid incompatibility groups. Contigs were annotated using Bakta (v1. 8. 2)  (29, 30).
Distribution of the blaMUN-1 gene The distribution of blaMUN-1 and potential variants was assessed using BLASTN (>70% identity, 80% coverage) online with RefSeq Genomes database from NCBI (as of August 24 th 2023)  (14). In each genome homologs of blaMUN-1 were found, its genetic environment was described using Bakta (v1. 8. 2) annotation and Clinker  (31). One RefSeq genome containing the blaMUN-1 gene of each species was randomly chosen and a copy of its 16S rRNA encoding gene was retrieved. If no 16S rRNA encoding gene were available in any RefSeq genome from a species containing the blaMUN-1 gene, the 16S rRNA encoding gene was taken from another RefSeq genome of the species. The 16S rRNA encoding genes were used for alignment with MAFFT (v7. 407)  (32). To assess the phylogenetic distance of each species bearing the blaMUN-1 gene, a phylogenetic tree was made using IQ-TREE (v1.
Comparison of MUN-1 to known beta-lactamases The blaMUN-1 gene was translated into protein and aligned with other beta-lactamases retrieved from the ResFinder (v4. 0) database using MAFFT (v7. 407). To assess the phylogenetic distance between each beta-lactamases, another phylogenetic tree was made using IQ-TREE (v1. 6. 9, with ultrafast bootstrap and general time reversible model).
During tooth development, transcripts were localized from the dental lamina at E12. 5 (Figure  1A , 1C), to the cap stage at E14. 5 (Figure  1B , 1D), to the bell stage at E16. 5 (Figure  1E , 1F), and at postnatal PN1 (Figure  1G ) in both the ectodermal and ectomesenchymal compartments. Rogdi displayed differential enrichment in both ameloblasts and odontoblasts. At PN5 (Figure  1H ), a strong signal was observed in ameloblasts only, likely correlating with a critical role of Rogdi in amelogenesis. According to the dataset consulted in https://kleintools. hms. harvard. edu/tools/springViewer_1_6_dev. html? datasets/Sharir_et_al_2019/control_epithelial 16 Rogdi transcripts are enriched in the incisor epithelium, speci cally in the preameloblast and ameloblast classes. Cycling cells and non-ameloblast epithelial cells also have expression, but at lower levels.
Data analysis of single-cell sequencing of the central system Single-cell transcriptomics of twenty-four cell populations in ve regions of the central nervous system produced by  15  were analyzed for Rogdi expression. Reads were grouped into low (50 RPKM to 500 RPKM), moderate (500 RPMK to 2000 RPKM), or high expression (> 2000 RPKM). Data analysis of single-cell sequencing of the incisor Rogdi expression in incisor epithelium was analyzed in https://kleintools. hms. harvard. edu/tools/springViewer_1_6_dev. html? datasets/Sharir_et_al_2019/control_epithelial. This tool identi es distinct cell types by single-cell transcriptomic analysis and delineates their spatial organization in the incisor epithelium. SPRING representation of the incisor epithelium dataset described in 16 presents 15 spectral clusters, grouped into 3 main classes: cycling cells, pre-ameloblasts and ameloblasts, and non-ameloblast epithelial cells.
Acknowledgments This work was supported by grants from the  French Ministry of Health (National Program for Clinical Research ,  PHRC 2008 N°4266   Amelogenesis imperfecta ), the  University Hospital of Strasbourg  (HUS,  API ,  2009-2012 , ' Development of the oral cavity: from gene to clinical phenotype in Human' ), the  European Regional Development Fund (ERDF)  of the  European Union  in the framework of the  INTERREG IV and V Upper Rhine program   RARENET  ( 2016-2019 ),  Agence Nationale de la Recherche , " programme Investissements d'Avenir"  ( ANR-10-INBS-07 PHENOMIN ),  Recherche Filière TETECOU   2021 , and  AFM Téléthon  ( 23933 ). This work of the  Interdisciplinary Thematic Institute IMCBio , as part of the  ITI 2021-2028 program  of the  University of Strasbourg ,  CNRS  and  Inserm , was supported by  IdEx Unistra  ( ANR-10-IDEX-0002 ), and by  SFRI-STRAT ' US  project ( ANR 20-SFRI-0012 ) and  EUR IMCBio  ( ANR-17-EURE-0023 ) under the framework of the  French Investments for the Future Program.
Sequencing and phylogenetic analysis of RVFV All positive samples after the full-length RVFV S segment PCR amplification following the protocol defined in  [34]  were sequenced. The phylogenetic analyses were done after multiple alignments of the obtained sequences, along with GenBank reference sequences using ClustalW (v1. 8. 1 in BioEdit v. 7. 0. 9. 0. software). Indeed, before phylogenetic analysis, datasets and multiple sequence alignments were thoroughly checked to eliminate misalignments and ensure the correct framing of the coding sequences. Maximum likelihood (ML) methods were used for tree construction using full-length sequences of the S segment (1690 nucleotides). Sequence evolution was modeled using the general time reversible (GTR) + Gamma model, as determined using Model Test  [35].
Main The ATP binding protein F (ABC-F) family, belonging to the ABC superfamily  8  , constitutes a group of proteins where all the members studied to date are involved in ribosomerelated functions  6, 7, [9] [10] [11] [12] [9] [10] [11] [12] [13] [14] [15] [16] [17] [18] [19] [20] [21]. They are widespread in bacteria and eukaryotes and in general, paralogues are present in the same organism, such as E. coli which has four ABC-F proteins: EttA, Uup, YheS and YbiT  6, 13, [21] [22] [23]. ABC-F proteins are composed of two ABC domains in tandem connected together by a linker region that contains the P-site tRNA Interaction Motif (PtIM)  6, 14, 21, 23, 24  , a signature motif of the family defined by the Pfam database  25  as ABC_tran_Xtn (PF12848). Each ABC-domain carries consensus Walker A and B motifs and in the presence of ATP the two domains come together, binding two ATP molecules to shape an ATP-bound closed conformation  21, 23, 26.
1% (v/v) formic acid in acetonitrile) in 70 min and 20 to 37% solvent B in 20 min). Data acquisition was performed in positive and data-dependent modes. Full scan MS spectra (mass range m/z 400-1800) were acquired in profile mode with a resolution of 70,000 (at m/z 200) and MS/MS spectra were acquired in centroid mode at a resolution of 17,500 (at m/z 200). Data processing for label-free quantification -Raw data were processed with the MaxQuant software package (http://www. maxquant. org, version 1. 5. 6. 5)  105. Protein identifications and target decoy searches were performed using the Andromeda search engine and the SwissProt database restricted to the E. coli K-12 taxonomy (release: 15/11/2018; 4477 entries) in combination with the Maxquant contaminants database (number of contaminants: 245).
org/perseus, version 1. 6. 0. 7) on LFQ intensities. Proteins belonging to contaminants and decoy databases were filtered. For each biological replicate, the median intensity of the two injected replicates was determined and proteins having quantitative data for all the biological replicates were considered for statistical analysis using a Benjamini-Hochberg test. Principal component analysis of the S15 proteomic result showed an outlier sample for one of the ∆ettA biological triplicate, therefore, it was excluded and the analysis was carried on biological duplicate for the three strains.
𝑓 = 𝐴 -𝐵 Where A is the FluoN of the strain WT, ∆ettA or CettA and B the FluoNcontrol. The resulting standard deviation of the FluoNC was calculated using the equation: 𝜎 > = ?𝜎 @ A + 𝜎 C A -2𝜎 @C Where 𝜎A and 𝜎B are the standard deviations of the variables A and B and 𝜎AB the covariance. Finally, the standard deviation of the ratio (𝜎r) is: 𝜎 D = 𝐹𝑙𝑢𝑜𝑁𝐶 KL 𝜎 > For the fluorescence reporters for mgtL or mgtA the normalization was done on the WT strain in the 2 mM Mg 2+ culture condition. Protein sequence motif analyses -Presence and position of the proteins containing the motif E/D X{0,1} E/D within the first 50 aa of the N-terminal part of the sequence were determined in the E. coli proteome using the Ecocyc database 108 and mapped to the proteomic quantification (S15) data (with the EttA targets presented in this study previously excluded).
ACKNOWLEDGEMENTS FO, TO and GB were supported by funds from the  CNRS  ( UMR8261 ),  Université Paris Cité , the  LABEX program  ( DYNAMO ANR-11-LABX-0011 ), and two  ANR  grants ( EZOtrad/ANR-14-ACHN-0027  and  ABC-F_AB/ANR-18-CE35-0010 ). FO received a fellowship from the  Edmond de Rothschild Foundation. This work was also supported by the  EQUIPEX CACSICE  ( ANR-11-EQPX-0008 ), through funding of the  Proteomic Platform of IBPC. We express our great gratitude to  Pr. Hirotada Mori  for his gifts of the  Keio  collection and the YFP fusion strains collection. We thank  Alexandre Pozza  for its help with  SEC-MALS.
DATA AVAILABILITY RNA-sequencing data are available through the EBI ArrayExpress database (https://www. ebi. ac. uk/biostudies/arrayexpress/studies) under accession code: E-MTAB-13458. Proteomic data are available through the massIVE Repository (https://massive. ucsd. edu/ProteoSAFe/static/massive. jsp) under accession code: MSV000093143.
Specifically, the branching ratio was calculated as: ߪ ൌ ෑ ି1 ୀ1 ቆ ሺ 1ሻ ሺ ሻ ቇ 1 ି1 where σ is the branching parameter of the i-th avalanche in the dataset, Nbin is the total number of bins in the i-th avalanche, nevents j -is the total number of events in the j-th bin. After that we averaged the results over all avalanches as follow: ߪ ൌ ෑ ൌ1 ሺ ሻ 1 Critical processes are represented by σ = 1, that was present at bin length = 3. However, we repeated our analysis varying time bins from 1 to 5 and obtained similar results. Each avalanche had an avalanche pattern defined as the set of all ROIs that were above the threshold.
Acknowledgements This publication is based upon work from  COST  Action  18105  ( Riskbased Meat Inspection and Integrated Meat Safety Assurance ; www. ri bmins. com), supported by  COST (European Cooperation in Science and Technology ; www. cost. eu). Participation of  Madalena Vieira-Pinto  was supported by projects  UIDP/00772/2020  and  LA/P/0059/2020 , funded by the  Portuguese Foundation for Science and Technology (FCT).
From September 27 th to October 22 nd , 2021, 96 were successfully recontacted and invited to complete a 5-minute questionnaire (phase 2) on linkage to confirmatory testing and care. Among those, 89 accepted to participate in phase 2 and 78 fully completed phase 2 questionnaire. The interviews were conducted in either French, English, Bambara, or Wolof. On-the-fly translation into other local languages was also available. Compensation of XOF 2 000 (≈3. 40 USD) in the form of telephone credit was given to participants who completed the phase 2 questionnaire. Unlike in phase 1, it was not a financial incentive as participants were informed about it only at the end of the interview. Interviews were not audio-recorded. Questionnaires' responses were captured on a computer and stored in a database managed by PAC-CI, an Ivorian research institute with expertise in clinical research.
We also describe (i) for those who did not link to confirmatory testing, the main reported reason; and (ii) for those who did link to confirmatory testing, the type of facility attended for confirmation and the time between HIVST and confirmatory testing. A dedicated anonymised dataset and the corresponding R script are available on Zenodo (https://doi. org/10. 5281/zenodo. 8329454) to allow replication of the analysis. All analyses have been performed using R version 4. 3. 1  [39]. All the descriptive tables were generated using the tbl_summary() function from the gtsummary package  [40]. Confidence intervals (95% confidence interval, 95%CI) were computed using Wilson's method with Yate's continuity correction (prop. test() function). The full research protocol was written in French (https://hal.
Acknowledgements We wish to acknowledge the commitment and determination of all the ATLAS program teams, which made this research possible. We would also like to thank the interviewers for their professionalism in collecting this sensitive data. Finally, we are grateful to the participants who were kind enough to give us some of their time by agreeing to take part in the survey. MCB and RS acknowledge funding from the  MRC Centre for Global Infectious Disease Analysis  (reference  MR/R015600/1 ), jointly funded by the  UK Medical Research Council (MRC)  and the  UK Foreign, Commonwealth & Development Office (FCDO) , under the  MRC/FCDO  Concordat agreement and is also part of the EDCTP2 programme supported by the  European Union. For the purpose of open access, the author has applied a Creative Commons Attribution (CC BY) license to any Author Accepted Manuscript version arising.
Background: Pharmacovigilance studies indicate clozapine history is marked by adverse drug reactions (ADRs). Objective: In a 2021 article, the United Kingdom (UK) had >90 % of European clozapine-related fatal outcomes in VigiBase, the World Health Organization's pharmacovigilance database. Two possibly opposing hypotheses could explain this disparity: 1) fewer reported fatal outcomes in other Western European countries mainly reflect underreporting to VigiBase, and 2) the higher number of UK reports reflects higher real relative mortality. Methods: VigiBase reports from clozapine's introduction to December 31, 2022, were studied for ADRs and the top 10 causes of fatal outcomes. The UK was compared with 11 other top reporting Western countries (Germany, Denmark, France, Finland, Ireland, Italy, Netherlands, Norway, Spain, Sweden and Switzerland).
, 2009)  and infections in general  (Mace et al. , 2022). Based only on physician reports to VigiBase,  Montastruc et al. (2021)  proposed clozapine as the fourth most frequently reported drug associated with fatal ADRs worldwide and the most lethal in Europeans and non-geriatric adults. The careful review of the UK data led to three shocking findings for the UK pharmacovigilance system (Supplementary Box S5): 1) a high annual fatal outcome count in UK clozapine-treated patients  (Handley et al. , 2022 ; UK Medicines and Healthcare Products Regulatory Agency, 2023), 2) UK reporting that accounted for more than half the fatal outcomes worldwide  (De Las Cuevas et al. , 2024) , and 3) UK reporting that accounted for >90 % of European fatal outcomes  (de Leon, 2022b). Two possibly opposing hypotheses could explain the apparent discrepancy in reports of fatal outcomes in clozapine-treated patients in the UK versus other Western European countries: 1) fewer reported fatal outcomes in other Western European countries mainly reflects underreporting by their drug agencies to VigiBase, and 2) the higher number of UK reports reflects higher real relative mortality.
VigiBase search VigiBase is the World Health Organization (WHO) global pharmacovigilance database of reported potential ADRs of medicinal products. This study utilized VigiBase for an observational, retrospective analysis conducted on January 15, 2023. Supplementary Box S6  (Bachmann et al. , 2017; Whiskey et al. , 2021; de Leon, 2022b ) provides further details.
Underreporting in Denmark Table  1  indicates that VigiBase received only 45 fatal outcomes from Danish clozapine outcomes with "cardiac arrest" as the top cause of fatal outcomes and "death" as second. Based on our estimations (Supplementary Table  S4 ), there is huge underreporting of fatal outcomes; instead of 45, from the UK data 469 fatal outcomes would be expected. Supplementary Table  S4  also suggests that Denmark reports more all drug-related ADRs than the UK (ratio = 1. 2), but underreports clozapine-related ADRs in general, since in Denmark clozapine ADR reports account for 0. 2 % of all drugs vs 3. 5 % in the UK. In spite of pioneering reports on myocarditis and the recent lack of fatal outcomes found in the Danish registry, there is great need to improve the clozapine pharmacovigilance reports sent from Denmark to VigiBase.
Underreporting in Finland VigiBase received only 43 fatal outcomes from Finland (Table  1 ), but the major top causes of fatal outcomes were similar to the UK. Based on our estimations (Supplementary Table  S4 ), there is huge underreporting of fatal outcomes, instead of 43 from the UK data 1415 fatal outcomes would be expected. Supplementary Table S4 also suggests not only underreporting of clozapine-related fatal outcomes, but of all drugrelated ADRs since, after correcting for population size, Finland reported a little more than half the UK number of clozapine-related fatal outcomes (ratio = 0. 58). In spite of pioneering reports on agranulocytosis and clozapine intoxication during pneumonia, there is great need to improve the clozapine pharmacovigilance reports sent from Finland to VigiBase.
Underreporting in the UK Compared with the other 11 countries, the UK overreports but we are convinced that there is some level of underreporting and not all clozapine-related ADRs and their associated fatal outcomes are reported to the UK pharmacovigilance agency. This agency is called the Medicines and Healthcare products Regulatory Agency (MHRA) and submits its data to VigiBase. The MHRA provides a webpage with updated general summaries of clozapine reports including fatal outcomes. The limited data provided by the MHRA webpage does not provide any data on relevant confounding variables such as psychiatric diagnosis, and comedications included in individual reports (Yellow Cards) are incomplete or absent. The MHRA webpage prioritizes only one reported ADR associated with each fatal outcome.