dataesr/scientific-paragraphs-categorization huggingface dataset:
III. DISCUSSION Clonal families are the building blocks of memory repertoire shaped by VDJ recombination and subsequent somatic hypermutations and selection. Repertoire sequencing datasets enable new approaches to understand these processes. They allow us to model the different sources of diversity and measure the selection pressures involved. To take full advantage of this opportunity we need to reliably identify independent lineages. Here, we introduced a general framework for studying the methods for partitioning high-throughput sequencing of BCR repertoire datasets into clonal families. We have identified the main factors that influence the difficulty of this inference task: low clonality levels and short recombination junctions. We quantified the clonality level using the definition of pairwise prevalence ρ and introduced a method to estimate it a priori, without knowing the partition.
The need to estimate the false-positive rate is at the same time the main possible limitation of all of these approaches. In this work we took advantage of a soNNia model based on a neural network, and benefited from its expressivity to quantify the purifying selection that modifies the VDJ recombination statistics. We found the performance of this model satisfactory when applied to healthy memory repertoires, in agreement with previous findings  [13, 19]. However, purifying selection is expected to be more pronounced in datasets of disease-specific cohorts and a default soNNia model may overestimate the diversity  [26]  and lead to underestimation of the fallout rate. The inference framework introduced here could still be applied with more sophisticated models of selection, and take advantage of higher levels of clonality that characterize many disease-specific datasets  [10, 14].
A. Data preprocessing and alignment We focus the analysis high-throughput RNA sequencing data of IgH-coding genes  [1]. The sequences were barcoded with unique molecular identifiers (UMI) to correct for the PCR amplification bias. We aligned raw sequences using presto of the Immcantation pipeline  [28]  with tools allowing for correcting errors in UMIs and deal with insufficient UMI diversity. Reads were filtered for quality and paired using default presto parameters. We selected only sequences aligned with the IgG primer and therefore the lineage analysis is limited to the IgG subset of the repertoire. Pre-processed data was then aligned to V, D and J templates from IMGT  [29]  database using IgBlast  [30]. Pairs of sequences stemming from the same VDJ recombination are expected to have the same CDR3 length l and align to the same V and J remplates.
The package is coded in C++ with a Python interface and is available independently. The time performance of this method for high-sensitivity and high-specificity partitions is studied as a part of the method benchmark analysis. We take advantage of the speed of a prefix treebased clustering and perform single-linkage clustering with an adaptive threshold. For any dataset, we define two CDR3-based partitions: high-sensitivity and highprecision clustering. To ensure high sensitivity s * , the threshold n of clustering should grow linearly with the CDR3 length l, ŝ(t) = n≤t P 1 (n) ≥ s * , (15) where we assume the Poisson or geometric distribution of positives. We find effectively μ 4%, so that the threshold for high-sensitivity clustering reads t sens = 10%l +1 for s 95% and t sens = 15%l + 1 for s 99% (where.
E. Synthetic data generation To generate synthetic data we make use of the lineages identified in the high-sensitivity and high-precision regime of CDR3-based inference (Fig. 3F ), we denote the set of these lineages by L. We assume that to good approximation the mutational process and the selection forces that shaped the mutational landscape in these lineages do not depend on the CDR3 length. To test the performance of different inference methods across CDR3 lengths, we build synthetic datasets of fixed length. In the first step, we choose the number of families N. We then draw N independent family sizes from the family size distribution of the form observed in healthy datasets p(z) = z -α Z α , (19) where Z α = z≥1 z -α = ζ(α, 1 ). In the next step, we assign a naive progenitor to each lineage by sampling from the P post distribution, selecting sequences with a prescribed length l (Fig.
1 < 2 <FIG. 3. 123 FIG. 3. Full inference method with mutational information. (A) For a pair of sequences, n1, n2 denote the numbers of mutations along the templated region (V and J), and n0 is the number of shared mutations. For related sequences, n0 corresponds to mutations on the initial branch of the tree, and is expected to be larger than for unrelated sequences, where n0 corresponds to coincidental mutations. (B) Positive and negative pairs are called mutated if both sequences have mutations n1, n2 > 0. Among positive pairs in the synthetic datasets, more than 99% are mutated. (C, D) Distributions of the rescaled variables x and y (4), for pairs of synthetic sequences belonging to the same lineage (positive pairs) and sequences belonging to different lineages (negative pairs). The separatrix x -y = t marks a high-precision (99%) threshold choice.
(E) To limit the number of pairwise comparisons we make use of high-precision and high-sensitivity CDR3-based partitions. High precision corresponds to the choice t = t *. High sensitivity corresponds to a coarser partition where t is set to achieve 90% sensitivity. When the two partitions disagree, mutational information can be used to break the coarse, high-sensitivity partition into smaller clonal families. (F,G) Mutations-based methods achieve high sensitivity across all CDR3 lengths l in the synthetic dataset (G), extending the range of applicability with respect to the CDR3-based method (F).
Gene expression Total RNA from cell lysates was extracted using the NucleoSpin RNA II kit (Macherey-Nagel, Germany) according to the manufacturer's instructions, including a rDNAse step for the elimination of contaminant DNA. RNA quality and concentration were determined using a Nano-Drop (Thermo Scientific, USA). Total RNA (0. 5 μg per reaction) was reverse transcribed using the iScript cDNA synthesis kit (Bio-Rad, USA). Quantitative real-time PCR (qPCR) was performed on a CFX96 machine (Bio-Rad, USA), the reaction mixture consisting of iQ SYBR Green Supermix (Bio-Rad, USA), cDNA, primers (250 nM, Eurogentec, Belgium) and nuclease-free water (Sigma-Aldrich, UK) in a total reaction volume of 20 μL. qPCR data were analysed using the CFX Manager software 3. 1 (Bio-Rad, USA). Gene expression for each target gene was normalised to gene expression levels of chicken glyceraldehyde 3-phosphate dehydrogenase (GAPDH) and β-2-microglobulin (β2M).
Cell viability HD11 viability following different stimuli was assessed using the fluorescent DNA intercalator 7-aminoactinomycin D (7-AAD, BD Biosciences, USA). 7-AAD assay allows identifying populations representing live, apoptotic, and late apoptotic/dead cells. Briefly, following stimulation or transfection, supernatants were discarded, and the cells were harvested and washed in PBS. Cells were stained according to the manufacturer's protocol and the viability was analysed by flow cytometry (BD FACS Calibur). Data were expressed as the percentage of 7AAD positive cells over total acquired events (50,000 cells).
, 2001). These data indicate that TLR21 can potently activate a transcriptional IFN-I and chemokine response in chicken macrophages. Next, we tested the response of HD11 cells to several nucleic acid species in parallel and assessed the transcription of four genes, IFNB, CCL4, IL1B and the interferon-stimulated gene ISG12. 2 (encoding IFI6). ODN induced all four genes to a higher level of expression than intracellular DNA stimulation or poly(I:C) transfection, apart from ISG12. 2 that was induced to the greatest level by intracellular DNA, sensed by the cGAS/STING pathway (Fig. 2B ). Indeed, we have previously shown that, consistent with mammalian cGAS mechanism, stimulation of HD11 cells with DNA species or 2′3′-cGAMP resulted in robust IFN-I transcription, dependent on the cGAS/STING pathway  (Oliveira et al.
Funding This research was funded by the  CASI  project (supported by  BioST federation of Université de La Réunion). G. L. , D. E. S and A. P. R. have PhD degree scholarship from  Réunion University (Ecole doctorale STS)  funded by  DIRED/2021-0161 ,  DIRED/2021-1115  and  DIRED/2021-1124  from  Région Réunion , respectively. We want to acknowledge the  Dr. Philippe Desprès  for his thoughtful advices.
Activation of the Interferon regulatory factors (IRF) pathway was monitored by measuring Lucia luciferase activity in A549 Dual cells. It was evaluated using QUANTI-Luc substrate according to manufacturer's recommendations. Briefly, 100 µL of QUANTI-Luc substrate was added to 20 µL of cell culture supernatant and IRF-induced luciferase levels were 2. 10. Measurement of the IFN-β Pathway activation quantified by luminescence measurement using a Luminoskan™ microplate luminometer (ThermoFisher, Waltham, MA, USA). 2. 11. Transcription factors prediction Prediction of potential binding sites for transcription factors in the promoter region of antiviral effectors was achieved using PROMO tool from ALGGEN group, which based on TRANSFAC 8. 3 [32,33]. Briefly, a sequence of at least 1000 bp upstream of the 1 st exon of each of the following genes was recovered from the Ensembl database [34]: viperin (ENSG00000134321), OAS1 (ENSG00000089127), ISG12 (ENSG00000165949), ISG15 (ENSG00000187608) and ISG54 1:200 Mouse anti-IFN-β AB_2122765 (Biolegend) 1:200 Rabbit anti-STAT2 sc-22816 (Santa Cruz) 1:200 Donkey anti-mouse Alexa 488 ab150105 (abcam) 1:750 Donkey anti-rabbit Alexa 488 ab150073 (abcam) 1:750 (ENSG00000119922).
Antibiotic stewardship program During the course of the pandemic, a very low rate of co-infection was reported in various studies  [9]. We analyzed the cohort of clinically ill COVID-19 patients in our ICU, and the data were consistent with those reported in different studies. Additionally, we observed a significant empirical antibiotic consumption in these patients. We then elaborated an antibiotic stewardship document with some recommendations in the treatment of COVID-19 patients and these recommendations were presented in a clinical session. The first clinical session was on February 2021, at the end of the 2nd pandemic wave. The document of antibiotic stewardship recommendations was based in three main key points: First it was recommended not to start empirical antibiotic therapy unless the patient was suspected to have a bacterial coinfection based in clinical judge and inflammatory parameters, mainly procalcitonin.
Lineage identification We sent positive samples to Eurofins Genomics Company for Sanger sequencing. We then blasted sequences against the MalAvi database for the lineage identification  (Bensch et al. 2009 ). Due to the high quality of the sequencing, we robustly identified single and multiple infections of Plasmodium sp. and Haemoproteus sp. By contrast, we could only identify five equally most likely lineages for Leucocytozoon sp. , the quality of sequencing being lower.
), the other urban exclusive lineages occurring too rarely to robustly conclude on their habitat-specificity. When investigating the previous occurrences of these 3 specific lineages (i. e. AFR065, DELURB4 and YWT4) in the MalAvi database, we found that they were relatively rarely encountered, at least in great tits. AFR065 was reported only twice, once in the Miombo scrub robin (Cercotrichas barbata, Muscicapidae) and once in the western greenbul (Andropadus tephrolaemus, Pycnonotidae) in Malawi and never on the European continent nor in the great tits  (Lutz et al. 2015). As mentioned before, the individual infected by AFR065 was captured in the Zoo du Lunaret (most natural urban site). At the time of the sampling for this study, the zoo hosted 65 African birds from 14 different species.
While malaria infection status of these captive birds held in the zoo are low (<5%, unpublished data), we can easily hypothesise that they were the initial carriers of AFR065 that was then transferred to a great tit via the contaminated vector. This result raises concern regarding local wildlife epidemiology when introducing or keeping exotic wildlife captive in contact with for native species. Regarding DELURB4, we found no previous occurrence of this lineage in great tits in the MalAvi database, even if this lineage was previously shown to be the second most common lineage present in the vector C. pipiens in the area  (Zélé et al. 2014 ) and numerously recorded in the close sister species the Blue tit Cyanistes caeruleus  (Ferrer et al. 2012)  and in other bird families (e. g. Passeridae, Turdidae and Muscicapidae) in several European countries (Spain, Italy, Bulgaria, Russia according to the MalAvi database).
Similarly, YWT4 is a rare lineage with only 7 occurrences in the whole MalAvi database, mainly in the Western yellow wagtail (Motacilla flava), but was found 25 times in the studied urban great tits, and once in a forest bird. Reasons why these lineages were more common in urban areas than in forest habitat remain to be explored. A possible explanation could be the difference in bird community compositions between habitats, leading to contact with different bird species, each with their own body of specific Haemosporidian parasite lineages. Testing this hypothesis would require a thorough scan of Haemosporidian infections in multiple species from both urban and forest habitats in replicated cities.
Conclusion While we found no striking difference in malaria prevalence between urban and forest great tits, urbanization was associated with earlier infections in nestlings. In addition, Plasmodium/Haemoproteus sp. prevalence tended to be higher in the more urbanized parts of the city. Taken together these results suggest that urbanization may lead to a parasitic burden for urban dwelling species. Interestingly, although sites displayed no major differences in Haemosporidian lineage community composition, the forest habitat showed the lowest diversity in Haemosporidian lineages and some lineages, that turned out to rarely occur in malaria databases, were preferentially occurring in urban areas This suggests that urbanization could play a role in the emergence and spread of previously rare disease strains.
Funding This work was funded by the  Agence Nationale de la Recherche  (grant " EVOMALWILD ",  ANR-17-CE35-0012 ) and long-term support from the  OSU-OREME (Observatoire des Sciences de l'Univers -Observatoire de REcherche Montpellierain de l'Environnement). B. R. was supported by the  Betty Moore Foundation  (grant  GBMF9881 ).
Haemosporidian lineages (in multiple species: Carbó-Ramírez et al. 2017 ;  in the House Sparrow: Jiménez-Peñuela et al. 2021). In our case, the Zoo du Lunaret of Montpellier consists of a 80-ha natural area where a large diversity of both native and exotic plant and bird species coexist. Interestingly, the only occurrence of Haemoproteus sp. AFR065 lineage was in this zoo. According to the MalAvi database (Bensch et al. 2009) , this lineage was found previously only on the African continent, in two bird genus in Malawi (Cercotrichas and Andropadus, Lutz et al. 2015). Hence, the presence of such lineages in this particular area of the city is most probably linked to the presence of captive African birds in the zoo (see next section for details on these birds). Surprisingly however, our forest site of La Rouvière, 20 km away from the city of Montpellier, showed the lowest level of Haemosporidian lineage diversity, which contrasts with previous results found showing opposite trends (e.
The sequences were analyzed and aligned using Genome Lab and MEGA 6 software to construct the phylogenetic tree by the Neighbor-joining (500 bootstraps, calculation with the 2 parameters Kimura method). The V3 sequences for the 2 HIV-1/N and HIV-1/P strains were extracted from sequences previously published in the Genbank (JN572926, AJ006022 and GU111555 respectively).
ACKNOWLEDGEMENTS The  TROPI -CO project was supported by the  Rouen University Hospital  and the region  of Rouen Normandy , and  Santé Publique France. The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication. We thank the  IAME laboratory from Bichat Hospital and Université Paris Cité , for providing the drug. We thank  Gatien Durand  and  Romain Legros  for their contribution to the project.
FUNDING This work was funded by the  French Centre National de la Recherche Scientifique , the  Laboratory of Excellence Medalis  ( ANR-10-LABX-0034 ),  EquipEx program I2MC  ( ANR-11-EQPX-022 ),  Strasbourg University, Fondation Arthritis Courtin, ANR ERAPerMed BATMAN  ( ANR-18-PERM-0001 ),  ANR   AUTOMATE  ( ANR-20-CE15-0018-01 ) and Strasbourg's  Interdisciplinary Thematic Institute (ITI) for Precision Medicine, TRANSPLANTEX NG , as part of the  ITI 2021-2028 program  of the  University of Strasbourg ,  CNRS  and  INSERM , funded by  IdEx Unistra  ( ANR-10-IDEX-0002 ) and  SFRI-STRAT'US  ( ANR-20-SFRI-0012 ). Florent Arbogast and  Delphine Bouis  were recipients of pre-doctoral fellowships from the  Ministère de la Recherche et de l'Enseignement Supérieur. Benjamin Voisin  was supported by  Marie Slodowska-Curie Individual Fellowship  ( H2020-MSCA-IF-2019 896095  VirIVITES).
Acknowledgements The authors wish to thank all blood donors. The study was supported by the  Deutsche Forschungsgemeinschaft (DFG)  within the  Collaborative Research Center CRC124 FungiNet "Pathogenic fungi and their human host: Networks of interaction ,"  DFG  project number  210879364  (project A2 to UT, HE and JL, C3 to OKu, and INF to SS and GP). We thank  Jean-Paul Latgé ,  Institute of Molecular Biology and Biotechnology (IMBBFORTH), University of Crete, Heraklion, Greece , for his great support and advice in the preparation of this manuscript.
CIMC pHIV-1/OM. The pattern of the HIV-1/OM recombinant virus involved RBF206 from the first bases of 5'LTR to the unique but conserved AvrII restriction site, in the vpr gene, and 89. 6 from the AvrII site to the last bases of 3'LTR (Fig. 1 ). The breakpoint in Vpr was localized at 5661-5667, relative to the reference form HIV-1/M HxB2 (GenBank accession number K03455). The CIMC pHIV-1/OM, synthesized by Genecust Society, corresponded to the HIV-1/OM full-length sequence inserted into a pET-28b(+) vector and was 15 358 bp in length (Fig. 3 ).
ACKNOWLEDGMENTS We wish to thank the staff of the  laboratory of Virology of Rouen University Hospital  (especially  Fanny Lermechain ) and the members of the DYNAMICURE research team for the cloning experiments, especially  Gaetan Riou , from  Inserm UMR1234 -PANTHER Laboratory , for his help in flow cytometry experiments. We are grateful to  Nikki Sabourin-Gibbs ,  Rouen University Hospital , for her help in editing the manuscript and to  Denys Brand , from  Tours University , for his rigorous proofreading.
KCs, identified by their classical marker VSIG4, distributed very differently between conditions in the tSNE projection (Fig. 1B ). To further analyze the impact of short-term HC diet feeding on KCs, RNA sequencing was performed on KCs isolated from mice fed a chow or a HC diet for 4 days. This revealed marked changes in gene expression upon HC diet (Fig. 1C ). KEGG pathway analysis on genes up-regulated in the HC-fed condition showed terms associated with lysosomes and cholesterol metabolism (Fig. 1D ). Highlighted pathways were also suggestive of intense metabolic activities (metabolism of xenobiotics, arginine biosynthesis, drug metabolism, ribosome). Interrogation of the GSEA Molecular Signatures Database (MSigDB) confirmed such activities (Xenobiotic, Mtorc1 signaling, Glycolysis) and also revealed the induction of genes involved in cell cycling (G2m checkpoint, Mitotic spindle) (Fig.
Massive cellular accumulation of cholesterol occurs in Kupffer cells following induction of hypercholesterolemia We next aimed to further characterize the cellular changes occurring in EmKCs shortly after the induction of hypercholesterolemia (4 days). As reported above, genes associated with cholesterol metabolism were enriched in KCs isolated from hypercholesteremic animals (Fig  1D). Thus, we wondered if genes involved in cholesterol biosynthesis were regulated in KCs after the induction of hypercholesteremia. We performed Gene Set Enrichment Analysis (GSEA) using a gene dataset that include all the major genes involved in cholesterol synthesis. The analysis revealed a clear downregulation of this pathway in the HC-fed condition (Fig  2A). Such expression profile is usually observed in cholesterol-loaded cells, including foamy macrophages  24.
Transcription factor enrichment analysis (CHEA) revealed that many of the down-regulated genes (FC ≥ 1. 3) were putative target genes of RXR, LXR and PPARa (based on the use of the ChIP-seq liver mouse dataset GSE35262 39 ) (Fig. 6M ), all nuclear receptors known for their pivotal roles in the transcriptional control of lipid metabolism. Liver lipidomic analysis confirmed disturbed cholesterol homeostasis (Fig. 6N ). Indeed, DT-treated mice exhibited elevated content of cholesterol biosynthesis intermediates (squalene, lanosterol, lathosterol and desmosterol) (Fig. 6N ). Liver free cholesterol and cholesteryl-esters were also increased in DT-treated animals as compared to bDT-treated controls (Fig. 6N ). Altogether, this shows that transcriptional control of cholesterol metabolism is rewired in the liver of mice exhibiting decreased EmKCs numbers.
Blood, cell-sorted and tissue lipid analyses Blood samples were collected with heparin-coated capillaries by retro-orbital bleeding in EDTA-containing tubes under isoflurane anesthesia (2% isoflurane/0. 2 L O2/min). Plasma samples were stored frozen at -80°C. Plasma total and free cholesterol levels were determined using commercial kits (Diasys). Quantification of cholesterol and cholesteryl ester species in sorted cells or liver tissue was performed by LC-ESI/MS/MS using a Prominence UFLC and a QTrap 4000 mass spectrometer (ICANalytics core facility of the institute of Cardiometabolism and Nutrition (IHU-ICAN, ANR-10-IAHU-05). Briefly, cell pellets or liver tissues resuspended in methanol 70% and homogenized were supplemented with internal standards: CE(18:1)_d7 and cholesterol_d7. Lipids were extracted according to a modified Bligh and Dyer method in methanol/CHCl3 (2:1) and HCl 0.
Acknowledgements We thank ILL (Proposal number  9-13-924 ) and ISIS (https://doi. org/10. 5286/ISIS. E. RB2210096 ) for access to neutron beam time and solid-liquid interface cells. The research was funded by the  Swedish Research Council  (Grant numbers  2021-05498 ; MM, LC),  Independent Research Fund Denmark  (Grant number  9040-00020B ; MM and EPO), as well as the  LEO Foundation Center for Cutaneous Drug Delivery  (Grant number  15007 ; MA and MM).
23, 24 Based on these studies, a clinical study invalidating CISH in CD8 + tumor infiltrating lymphocytes (TILs) via Crispr-CAS9 approach prior to adaptive cell transfer is ongoing (NCT04426669). Thus, a new concept of cancer immunotherapies to target intracellular inhibiting proteins is emerging. Here we investigated the targeting of intracellular TCR-signaling inhibiting proteins DOK1 and DOK2 to improve CD8 + T cell activation and cytotoxicity against tumors. 6] [27] [28]  DOK1 and DOK2 expression increase upon T cell maturation. 29 0] [31]  DOK1 and DOK2 proteins are implicated in negative regulation of TCR signaling as their deficiency improve TCR-mediated cytokine production and proliferation in T-cell lines and in mouse CD4 + T lymphocytes. 29, 30 Upon preprint (which was not certified by peer review) is the author/funder.