dataesr/scientific-paragraphs-categorization huggingface dataset:
Analyses As the analyses were exploratory, no predefined hypotheses were tested and no adjustment for multiplicity was applied; betweengroup differences and changes over time were described using 95% CIs. 32 Persistence data for ustekinumab and TNFi are presented as Kaplan-Meier (KM) curves and compared using Cox regression analysis, including propensity score (PS) to adjust for baseline imbalanced covariates; this included sex, bDMARD line, body surface area (BSA), enthesitis, PsA axial symptoms, PsA category and PsAID-12 score. To investigate their interaction with the PS-adjusted treatment effect, the Cox model was expanded with several factors, among which were concomitant methotrexate (MTX) use and skin involvement. HRs, with 95% CI, are presented. Observed effectiveness outcomes (MDA including VLDA/ VLDA and cDAPSA LDA including remission/remission) were summarised at each assessment timepoint by proportion of.
Patient disposition In total, 991 participants were enrolled between December 2015 and June 2018 at 92 sites in Belgium, France, Greece, Italy, the Netherlands, the Russian Federation, Spain and the UK. Of 991 patients, 57 were not eligible and were excluded from the study. Therefore, 934 patients were included in the safety analysis (ustekinumab n=459; TNFi n=475); of these, 14 (1. 5%) terminated study participation due to the COVID-19 pandemic. Of 934 patients, 895 (ustekinumab n=439; TNFi n=456) had baseline and follow-up effectiveness data up to 3 years and were included in the overall effectiveness analysis set; 219 (49. 9%) ustekinumab-treated and 218 (47. 8%) TNFi-treated patients were included in the remainer analysis (figure  1 ).
Nevertheless, given the differences between these populations, direct comparisons between ustekinumab and TNFi treatments should be interpreted with caution. Several previous studies demonstrated superior persistence for ustekinumab in patients with PsA. For example, a retrospective Swedish registry study of 3918 patients with PsA for a maximum of 10. 6 years demonstrated favourable treatment persistence with ustekinumab versus adalimumab across treatment lines. 35 hile we cannot directly compare retrospective analyses of national registries or claims databases to a prospective observational study such as PsABio, the subgroup analyses in PsABio are in line with the above-mentioned study results. In the PsABio study, 51% of patients stopped/switched their initial treatment at 3 years, with similar mean persistence for ustekinumab and TNFi.
Participants We evaluated three mRNA booster vaccines in participants who received their two-dose primary series as part of the mRNA-1273 Phase 1 dose-ranging trial (NCT04283461, DMID 20-0003) between March and June 2020. 3, 4, 9, 11, 14  The phase 1 trial participants were recruited into three age-group strata (18-55 years, 56-70 years, and ≥71 years), and received a primary series of two mRNA-1273 vaccinations 28 days apart at doses of 25, 50, 100, or 250 mcg (Figure  1 ). The monovalent prototype 100 mcg mRNA-1273 booster vaccine was evaluated in a substudy of the phase 1 trial and included any participant (any primary series dose) who chose to participate. The two variant-containing booster vaccines were evaluated in a new Phase 1 study (NCT04785144, DMID 21-0002) available to 20-0003 participants in the 50, 100, or 250 mcg dose groups who chose to leave the DMID 20-0003 phase 1 study and join the new trial.
Following booster vaccination, a robust anamnestic response to similar titers was observed in all three groups to 614D S-2P at Day 15 [monovalent prototype 62,272 AUC (95% CI 59,973, 64,659); monovalent variant 61,373 (95% CI 58,622, 64,254); bivalent 62,025 (95% CI 59,468, 64,691)] (Figure  3 , Supplementary Table  S9 ). To provide context, samples from 30 Phase 2 mRNA-1273 study (P201, NCT04405076)  5, 15  participants who had received 100 mcg mRNA-1273 primary series followed by 50 mcg mRNA-1273 boost approximately 6 months later, were also tested, with similar results on Day 15 after the third dose (61,650 (95% CI 59,609, 63,762)). Pre-boost IgG binding levels to the Beta variant S-2P antigen were approximately 60% lower than against 614D. However, in all groups, the third dose of mRNA vaccine induced similar anamnestic responses against B.
Trial Designs and Participants Additional details of the design, conduct, oversight, analyses, and results of the trials can be found in the protocols, statistical analysis plans, and Supplement. The 20-0003 substudy (NCT04283461) and the 21-0002 (NCT04785144) trial protocols were reviewed and approved by the Advarra institutional review board. Both protocols permitted interim analyses to inform vaccination strategies and public health. This report includes ndings through 28 days after the third mRNA vaccination. The booster vaccination evaluations were conducted at the Kaiser Permanente Washington Health Research Institute in Seattle, the Emory University School of Medicine in Atlanta, and the VRC at National Institutes of Health in Bethesda. Participants were healthy adults who must have received two doses of mRNA-1273 in the Phase 1 study; other eligibility criteria are included in the protocols (Supplement).
All third doses of mRNA vaccine were administered between March and April 2021 and recipients will be followed for safety, reactogenicity, and immunogenicity for twelve months after the third dose of mRNA. Immune responses observed in these monovalent prototype, monovalent variant, and bivalent groups were compared with two other groups that had received an initial two-dose 100 mcg mRNA-1273 primary series: peak neutralization responses after a 100 mcg primary series in 33 participants in the Phase 1 trial (peak pseudoneutralizing antibody titers were also evaluated in those that received a 25 or 50 mcg primary series); and sera from a Phase 2 randomized placebo-controlled trial sponsored by Moderna, protocol P201(NCT04405076)  5, 15  who received a third dose of 50 mcg mRNA-1273 six to eight months after completion of their two-dose 100 mcg mRNA-1273 primary series.
Characterization of the SARS-CoV-2 RNA interactome in human cells To characterize the host factors that interact with the SARS-CoV-2 genome during infection, we performed a ChIRP-MS (Figure  1A ). Briefly, we challenged 293T cells stably expressing the human angiotensin-converting enzyme 2 (ACE2) receptor (293T-ACE2) with a primary clinical SARS-CoV-2 220/95 strain (EPI_ISL_469284) isolated by our laboratory in March 2020  (Onodi et al. , 2021). Forty-eight hours later, SARS-CoV-2-infected and -uninfected cells were treated with formaldehyde to crosslink RNA with RNA-binding proteins (RBPs) to preserve ribonucleoprotein (RNP) complexes. To specifically capture SARS-CoV-2 RNA, we designed 129 biotinylated antisense probes (Table  S1 ) complementary to the full-length viral RNA, and subsequently used streptavidin beads to pull down the RNPs.
We also added TRIM28, a protein for which no RNA-binding activity was reported, which likely was co-purified with vRNA in our ChIRP-MS through protein-mediated interaction. We confirmed that for the 5 proteins tested, there was a significant enrichment of vRNA relative to the negative controls (Figures  1F  and S2A ), whereas there was no vRNA enrichment in the TRIM28 sample, strongly pointing to the existence of specific interaction. These results were also confirmed in A549-ACE2 stably expressing the different proteins (Figures  S2B  and S2C ). Altogether, these observations demonstrate that our ChIRP approach can identify proteins that associate with vRNA. Next, we compared our RNA interactome with recently published datasets obtained by either RNA antisense purification coupled with MS (RAP-MS) or ChIRP-MS approaches in different SARS-CoV-2-infected cell lines  (Flynn et al.
, 2006). Chaperone proteins (HSP90AB1, HSPA2, CCT2, and CCT8) were also significantly enriched in our study. It is likely that they are indirectly associated with the vRNA either by contributing to nascent viral protein co-translational folding  (Cabrita et al. , 2016)  or by interacting with viral NS proteins, as shown for dengue virus NS1  (Hafirassou et al. , 2017)  or hepatitis C virus NS5B or influenza PB2 viral polymerases  (Fislovaet al. , 2010; Inoue et al. , 2011). Characteristic RBPs involved in RNP granules such as paraspeckles (RBM14, NONO, MATR3, SFPQ) and stress granules (SGs) (G3BP1, G3BP2, TIA1, CAPRIN1, ATXN2L)  (Nakagawa et al. , 2018; Yang et al. , 2020)  were among the highest scoring candidates. Many paraspeckles-interacting proteins were also highly represented in our ChIRP-MS dataset (DAZAP1, EWSR1, FAM98A, FUS, RBMX, UBAP2L, as well as hnRNPA1, A1L2, H1, H3, K, R, UL1)  (Naganuma et al.
All readouts were normalized to the siNT-transfected cells. Transfected cells were also monitored for cell viability, and the siRNA with cytotoxic effects (below 75% of cell viability in control) were removed from the analysis (7%, 9/138). As expected, siRNA-mediated depletion of either CTSL or ATP6V1B2 resulted in a strong decrease in infection in both assays (Figures  3B  and 3C ). qRT-PCR experiments revealed that 45 siRNAs reduced viral particle release by at least 50%, whereas 4 siRNAs increased it by 200% (Figure  3B ). Flow cytometry studies showed that 21 siRNAs decreased the percentage of infected cells by more than 50%, while 12 enhanced it by 150% (Figure  3C ). By intersecting the data from both assays, we identified 25 proteins that affected viral infection by acting either as host dependency factors (HDFs) (19/25) or host restriction factors (HRFs) (6/25) (Figure  3D ).
This contrasts with the data recently published by  Flynn et al. (2021)  showing that the majority of SARS-CoV-2 RBPs identified in their study has an antiviral function. It is likely that RNP complexes are dynamically regulated and that some RBPs could function as pro-or antiviral host factors at different stages of the viral life cycle. We observed a high correlation coefficient (r = 0. 742) between our qRT-PCR and flow cytometry datasets indicating that most of the identified proteins are required for genome replication (Figure  3D ), and only very few act at a late step (assembly/particle egress) of the SARS-CoV-2 life cycle (Figure  3D , green circles). Interestingly, several HDFs such as ILF3, HNRNPU, HNRNPK, FAM120A, and QKI were predicted to bind the 5 0 -or 3 0 -UTR of SARS-CoV-2 RNA  (Sun et al.
We then looked at the DrugBank, ChEMBL, DGIdb (Drug-Gene Interaction Database), and PanDrugs databases and identified 274 small molecules targeting 30 vRNA-binding proteins. Among them, we selected camptothecin (XRCC5), cerulenin (FASN), dabigatran (HNRNPC), geldanamycin (HSP90AB1), phenethyl isothiocyanate (HNRNPK), sunitinib malate (EWSR1), and artemisinin (an antimalarial interacting with multiple RBPs), which were predicted to interact with HDF having a log2 (titer ratio) % 0. 5 in our siRNA screen. To test their effect on infection, A549-ACE2 cells were incubated with each compound at a concentration of 10 and 1 mM and then challenged with SARS-CoV-2. We used equivalent amounts of DMSO as negative control and similar concentrations of remdesivir, an inhibitor SARS-CoV-2 replication  (Wang et al.
, 2020) , as positive control. We monitored both the release of progeny viruses in the supernatant and cell viability 24 h post-infection. Of all of the compounds tested, we observed a significant inhibitory effect for phenethyl isothiocyanate (40% inhibition) and sunitinib malate (80% inhibition) at a concentration of 1 mM without toxicity (Figure  3E ). These data suggest that the host factors identified in our ChIRP-MS study could represent promising antiviral drug targets. HNRPNA2B1, ILF3, QKI, and SFPQ mediate SARS-CoV-2 replication Among the HDF identified, we were particularly interested in ILF3 and QKI (for which limited information on viral infection are available), as well as HNRNPA2B1 and SFPQ, which are likely able to associate with SARS-CoV-2 vRNA (Figures  1F  and S2C ). Consistent with our screen, siRNA-mediated depletion of HNRPNA2B1, ILF3, QKI, or SFPQ (Figure  4A , left panel) significantly reduced the percentage of infected cells and progeny viruses release (Figure  4A , center and right panels).
Cell populations were sorted based on GFP expression with a BD FACSAria II (Becton Dickinson) with FACSDiva 6. 1. 2 software (Becton Dickinson). d KEY RESOURCES Flow cytometry analysis of ACE2 cell surface expression Cells were detached with 2. 5 mM EDTA in PBS and incubated with anti-human ACE2 mAb (5 mg/mL) in 100 mL of PBS with 0. 02% NaN 3 and 5% FBS for 1 h at 4 C. Following the primary staining, cells were washed and stained with incubated with the Alexa 647-conjugated goat anti-mouse IgG (Jackson ImmunoResearch) for 30 min at 4 C. Acquisition was performed on an Attune NxT Flow Cytometer (Thermo Fisher Scientific) and analysis was done by using FlowJo software (Tree Star). Comprehensive identification of RNA binding proteins by mass spectrometry ChIRP-M/S was performed as previously described by Ooi and colleagues  (Ooi et al.
Identification of known interactors of coronaviruses in the ChIRP dataset A recently published meta-analysis by Perrin-Cocon et al. was used as a reference for known interactions between coronavirus and host proteins  (Perrin-Cocon et al. , 2020). In this report, the literature was manually curated to assemble a dataset of 1,311 coronavirus-host interactions encompassing 1,140 distinct cellular proteins. Host proteins in the ChIRP dataset overlapping with those present in this reference interactome were considered as previously reported or « known » interactors of coronaviruses. They were displayed together with the interacting-coronavirus proteins as an interaction network using Cytoscape  (Shannon et al. , 2003). siRNA screen assay An arrayed ON-TARGETplus SMARTpool siRNA library targeting 138 of the 146 RNA-interacting proteins significantly enriched in our ChIRP-M/S was purchased from Horizon Discovery.
Drug treatment and SARS-CoV-2 infection Using DGIdb, DrugBank, ChEMBL, and PanDrugs databases, we identified 274 compounds targeting 30 RBPs. Compounds were first filtered to select molecules described either as an inhibitor or with the highest interaction score. Finally, we selected the compounds targeting RBPs with a log2 (titer ratio) % 0. 5 in our siRNA screen. Cells grown in 24-well plates were treated with the indicated compound concentrations for two hours prior infection and compounds were maintained throughout the course of infection. Cells treated with equivalent concentration of DMSO were used as control. The cells were challenged with SARS-CoV-2 at a MOI of 0. 05 for 3 h, then washed once with PBS and incubated with fresh media. 24 h postinfection, cells and 200 mL of supernatants were collected for N protein staining and viral RNA quantification, as described in ''Viral infection quantification assays''.
Viral infection quantification assays For infection quantification by flow cytometry analysis, 24 h post-infection cells were trypsinized and fixed with 2% (v/v) paraformaldehyde (PFA) diluted in PBS for 15 min at room temperature. Cells were incubated for 45 min at 4 C with 1 mg/mL of the anti-N mAb diluted in permeabilization flow cytometry buffer (PBS supplemented with 5% FBS, 0. 5% (w/v) saponin, 0. 1% sodium azide). After washing, cells were incubated with 1 mg/mL of Alexa Fluor 647-conjugated goat anti-mouse IgG diluted in permeabilization flow cytometry buffer for 30 min at 4 C. Acquisition was performed on an Attune NxT Flow Cytometer (Thermo Fisher Scientific) and analysis was done by using FlowJo software (Tree Star). To assess infectious viral particle release during infection by RT-qPCR, viruses were first inactivated by incubating the supernatants v/v with 1% Triton X-100 (Sigma) in PBS for 30 min under agitation at RT.
Then we adjusted the normalized RIP fraction Ct value for the normalized WT Ct value (DDCt = DCt [normalized RIP]-DCt [normalized HSPB1 negative control]). Finally, we performed a linear conversion of the DDCt (2^[-DDCt]) to calculate the fold change over the HSPB1 protein binding to vRNA. Gene editing and trans-complementation experiments sgRNA targeting QKI were designed using the CRISPOR software (http://crispor. org). Sequences for all the sgRNAs are listed in the key resources table. The sgRNAs were cloned into the plasmid lentiCRISPR v2 (Addgene) according to the recommendations of members of the Zhang laboratory. A549-ACE2 gene-edited cells were generated as previously described  (Meertens et al. , 2019). Gene-edited cells were transduced with the FLAG-GFP and FLAG-QKI cDNA cloned in the lentiviral vector pLVX-EF1alpha-IRES-Puro.
Statistical analyses Graphical representation and statistical analyses were performed using Prism7 software (GraphPad Software). Unless otherwise stated, results are shown as means +/À standard deviation (SD) from at least 2 independent experiments in duplicates. Differences were tested for statistical significance using One-way or two-way ANOVA with multiple comparisons post-test. Protein functional enrichment was performed in Cytoscape (Version. 3. 8. 2). Gene Ontology (GO) Biological process were enriched with the ClueGO  (Bindea et al. , 2009)  extension (Version. 2. 5. 7) using a two-sided hypergeometric test with Bonferroni correction. Adjusted p-values < 0. 5 were considered as significant. p-values and percentage of represented genes per GO terms were computed to select the most enriched functional families.
This was illustrated with ggplot2 package (Version. 3. 3. 2) in R Studio interface (Version. 1. 2. 1335). Most representative terms were represented in networks using the Cytoscape's Genemania extension (Version. 3. 5. 2). Comparison of functional enrichment between our datasets and previous studies was performed in Metascape  (Zhou et al. , 2019b). GO Biological process with p-value < 0. 01, enrichment score >1. 5 and overlap = 4 were selected.
ACKNOWLEDGMENTS This work was supported by the  French government 's  Investissement d'Avenir program ,  Laboratoire d'Excellence ''Integrative Biology of Emerging Infectious Diseases' ' (grant no. ANR-10-LABX-62-IBEID ), the  Fondation pour la Recherche Medicale  (grant no. FRM-EQU202003010193 ), the  Agence Nationale de la Recherche  ( ANR/FRM  Flash  COVID  project  IDISCOVR  and  ANR-20-CO11-0004  project  FISHBP ), and  University Paris Cite(Plan de Soutien  Covid-19:  RACPL20FIR01-COVID-SOUL ). The authors thank  Alessia Zamborlini  for critical reading of the manuscript. L. M. and A. A. dedicate this work to the memory of  Professor Jean-Louis Virelizier  ( United'Immunologie Virale, Institut Pasteur, Paris ) and  Professor Renaud Mahieux  ( Ecole Normale Superieure, Lyon, France ), who left us during the SARS-CoV-2 epidemic.
METHOD DETAILS Virus preparation and titration SARS-CoV-2 strain 220_95 (EPI_ISL_469284) was isolated from nasopharyngeal swab specimens collected at Service de Virologie (Hospital Saint Louis, Paris)  (Onodi et al. , 2021). Virus was propagated on Vero E6 in DMEM-2% (DMEM supplemented with 2% FBS, 1% P/S, 1% GlutaMAX, and 25 mM Hepes). Viruses were passaged three times before being used for experiments. For the last passage, viruses were purified through a 20% sucrose cushion by ultracentrifugation at 80,000 3 g for 2 h at 4 C. Pellets were resuspended in TNE1X pH7. 4 (Tris 50 mM, NaCl 100mM, EDTA 0. 5 mM), aliquoted and stored at À80 C. Viruses titer was determined by plaque assays in Vero E6 cells and expressed as PFU/mL. Cells were incubated for one hour with 10-fold serial dilution of viral stocks.
Methods: We collected data on domestic dog registration and deworming and stray dog sheltering in 74 counties/ districts in the TAR from 2017 to 2019. Fecal samples from domestic dogs were collected from randomly selected towns to determine Echinococcus infection in dogs using coproantigen ELISA. We analyzed the data to compare the canine rate of infection between 2016 and 2019. The data analysis was performed by SPSS statistical to compare dog infection rate in 2016 and 2019 by chi-square test, and ArcGIS was used for mapping. Results: From 2017 to 2019, 84 stray dog shelters were built in TAR, and accumulatively 446,660 stray or infected dogs were arrested, sheltered, or disposed of. The number of domestic dogs went downward, with an increased registration management rate of 78. 4% (2017), 88.
Data collection and analysis Data on dog registration, management and deworming, and stray dog accommodation were collected through retrospective surveys and field study. The results of the 2016 TAR echinococcosis prevalence survey were used as a baseline data for dog infection rate. The dog infection rate in 2019 was based on data from the Central Government's Transfer Payment Project for Echinococcosis Control. The collected data were firstly systematized and checked before being entered and analyzed using SPSS 20. 0 (IBM, Armonk, USA). A chi-square test was used to compare the dog infection rate in two cross-sections. Geographic information maps were mapped using Arc-GIS version 10. 1 (ESRI, Redlands, USA).
These results were confirmed subsequently and the interplay between PS and M1, in which M1 interacts mostly with PS-enriched domains within lipid bilayers and stabilizes these PS domains during M1 self-assembly, was described in detail  [69]. Finally, thanks to RICS, SPR and circular dichroism spectroscopy (see Lexicon), a subsequent investigation of the precise mechanism of the interaction between IAV M1 protein and the PS-enriched bilayer was published by Höfer et al. in 2019  [70]. A specific conformational change was found to occur upon the M1's binding to the negatively charged PS. From the structures in the protein data bank (PDB) and simulations, N-terminal domains of M1 was shown to be involved in membrane binding, stabilizing C-terminal domain to favor self-assembly. SLBs are standard models for lipid diffusion measurements.
ACKNOWLEDGEMENTS The authors gratefully acknowledge the  Cell Biology Unit, UMPI ; the joint research unit between the  Institut Pasteur de Montevideo  and the  Instituto Nacional de Investigación Agropecuaria (INIA) , the  Advanced Bioimaging Unit  at the  Institut Pasteur Montevideo  for their support & assistance in the present work. We would like to especially thank  M. Sc. Marcela Diaz ,  Tabare de los Campos  and  M. Sc. Paula Céspedes. We thank the  TEM Unit at the School of Sciences, Universidad de la República. We are especially grateful to  Dr. Gabriela Casanova ,  Dr. Gaby Martínez  and  M. Sc. Magela Rodao  for their diligent assistance in acquisition and processing of images. We also thank the  TEM units of the Center of Microscopy at the Universidade Federal de Minas Gerais, Belo Horizonte , and the  Centro Nacional de Biologia Estrutural e Bioimagem, Rio de Janeiro, Brazil.
Pan-Parapox virus Forward CGAGCTTTAAATAGTGGAAACACAGC ORF 032  (Friederichs et al. , 2014)  Reverse GCACCATCATCCTGTACTTCCTC screened to remove short and duplicate sequences  (Altschul et al. , 1997). The final data set for phylogenetic analyses comprised 15 sequences for B2L, including three pseudocowpox sequences from this study, one pseudocowpox virus from cattle, one from reindeer, two from humans, four orf viruses, and four bovine popular stomatitis viruses. The final data set for phylogenetic analyses of ORF 032 comprised 24 sequences including seven pseudocowpox virus sequences from this study, one pseudocowpox virus from cattle, one from reindeer, three from humans, eight orf virus, and four bovine popular stomatitis viruses. Phylogenetic analyses were inferred using the maximum likelihood estimation method implemented in Mega X  (Kumar et al.