dataesr/scientific-paragraphs-categorization huggingface dataset:
Comparison of early and late env sequences. The env consensus sequences of the viral quasispecies infecting each patient at the early and late stage of infection were determined by NGS analyses. We compared the 8 sequences to the most closely related env sequences available in GenBank. Phylogenetic analysis confirmed that the env sequences from the 4 selected patients grouped into the same cluster (bootstrap value of 100%) (Fig. 1 ). As expected, based on the genetic distances, early env sequences were closer to the hypothesized most recent common ancestor of the cluster than the late env sequences, confirming substantial viral evolution overtime in each patient (Fig. 1 ). Furthermore, the Shannon entropy measures of NGS-generated sequences, representing the overall genetic diversity within each viral quasispecies, were higher in late than early samples, except for patient 3 who received an antiretroviral treatment four months before late sampling (Fig.
Infection levels were determined 48 h later by measuring luciferase activity (RLU). (a, c, e, g) Results are expressed as percent inhibition of infection of early (dashed lines) and chronic (solid lines) viruses as a function of plasma concentrations. The late plasma sample of patient 3 was not tested due to its contamination by antiretroviral drugs. The data shown are mean results obtained from two independent experiments performed in triplicate. The statistical significance of differences between early and chronic neutralization curves was evaluated using a two-way ANOVA test. (b, d, f, h) Histograms represent the neutralizing titers (ID 50 values derived from neutralization curves) of late plasma samples against early (dashed bars) and chronic (solid bars) viruses. Graphs were generated using GraphPad Prism, version 6.
This observation is associated with an increase of the envelope glycoprotein level into the chronic viruses compared to early viruses. These results suggested that the decrease of functionality of Env regarding the use of CD4 might have been compensated or even reversed by two possible non-mutually exclusive   (a, b ) Neutralization sensitivity of early and late Env-pseudotyped viruses to bNabs targeting the V3 loop. Each virus stock was diluted to 400 TCID 50 /mL and incubated for 1 h at 37 °C with serial dilutions of bNAbs PGT121 or 10-1074 before infecting TZM-bl cells. Infection levels were determined 48 h later by measuring luciferase activity (RLU). Results are expressed as percent inhibition of infection as a function of PGT121 (panel a) or 10-1074 (panel b) concentrations. The data shown are mean results obtained from two independent experiments performed in triplicate.
Among available Env sequences present in databases, the best way to address this question was to compare the Env sequences of transmitter and recipient pairs, focusing on transmission events that occurred during the chronic phase of infection of transmitters. So, we compared Env of recipients with acute infection with Env of chronically infected transmitters in five previously characterized transmission pairs of the Swiss Cohort (T1-R1, T2-R2, T3-R3, T4-R4 and T5-R5 pairs, described in the paper of Oberle et al  78  ) and did not observe identical mutations in any of the pairs. Thus, the common evolutionary pattern of Env observed in the different hosts seems to be specific to the infecting strain. This suggests that under the selective pressure of NAbs, the capacity of Env to adapt to changing environments may be restricted by functional constraints that limit its evolutionary landscape.
similarity of the pol gene (genetic distance < 0. 015 substitution/site) and phylogenetic analyses (bootstrap of the cluster 100%)  80. Although we can assume that the viruses belong to a same transmission chain based on molecular evidences, we do not have epidemiological data suggesting that there are direct links such as donor/receiver pairs within them. The estimated date of infection was defined as the date of symptom onset minus 15 days for patients with symptomatic primary infection, or, for asymptomatic patients, the date of the incomplete western blot (presence of antibodies to gp160 and P24) minus 1 month or the midpoint between a negative and a positive ELISA result  79. Early plasma samples were collected less than 4 months post-infection. Late plasma samples were collected 18 to 24 months after the first sampling of each patient.
Sequence analysis. To analyze the env diversity of the viral population in each sample, paired-end sequencing was performed on a MiSeq platform (Illumina), as previously described  88. 1 ng of DNA per sample was necessary to build the sequencing library according to the Nextera XT DNA sample preparation kit (Illumina, San Diego, USA). Illumina sequencer output files matching 151 base-pair sequencing reads were processed using the "Biomina Galaxy platform"  89  after verifying read quality (FastQC algorithm). De novo assembly was performed using the Trinity program and reads were mapped with "Burrows-Wheeler Aligner" (BWA). Finally, nucleotide analyses were done using the Mpileup program. The Shannon entropy was defined as the mean nucleotide diversity at each position of the entire population, excluding gaps.
All sequences have been submitted to Gen-Bank and assigned accession numbers SRX6979911 to SRX6979918. NGS Consensus Nucleotide sequences were aligned using CLUSTALW and manually edited. Potential N-linked glycosylation sites (PNGS) were identified using the N-Glycosite tool at the HIV LANL database website (https ://www. hiv. lanl. gov) and amino acid positions were identified by the use of standard HXB2 numbering. An env maximum likelihood tree was computed with RAxML using a GTRGAMMA model of nucleotide substitutions with 1000 bootstrap replicates. For each sequence, we conducted a BLAST search to identify the most closely related sequences available in the HIV database (https ://www. hiv. lanl. gov/). After excluding duplicate sequences, these sequences were downloaded and included in the phylogenetic analysis.
Acknowledgements This work was supported by the  Agence Nationale de Recherche sur le SIDA et les hépatites (ANRS, Paris, France). Maxime Beretta  was supported by doctoral fellowships from  INSERM , the  Région Centre and Sidaction (France). We thank the patients and clinicians who participated in the  ANRS PRIMO CO6  cohorts. The following reagents were obtained through the  NIH AIDS Research and Reference Reagent Program, Division of AIDS, NIAID ,  NIH : pNL4. 3. LUC. R-E-from N. Landau; TZM-bl cells from  J. C. Kappes ,  X. Wu , and  Tranzyme Inc. ; Maraviroc (Cat # 11580 ); sCD4 from Progenics;  U373-MAGI-CXCR4  and  U373-MAGI-CCR5  cells from  Dr Michael Emerman ; anti-HIV-1 gp120 Monoclonal ( PG9 , and  PGT145 ) from IAVI; anti-HIV-1 gp120 Monoclonal ( 10-1074  and  3BNC117 ) from  Dr.
Genotyping for Antiretroviral Resistance Mutations Genotyping for antiretroviral resistance mutations was performed in the virology laboratory at the George Pompidou European Hospital in Paris, using plasma aliquots conserved at -80 • C. Genotyping was performed using the technique from the resistance group of the French National Agency for AIDS Research [www. hivfrenchresistance. org]. Each sequence of interest was registered in GenBank. The viral subtype was deduced from sequences within the pol gene in FASTA format using the freely accessible genotyping software developed by the National Center for Biotechnology Information. Following gene sequencing of protease and reverse transcriptase, comparisons between amino acids in the sequences generated from patients and the reference sequences were made using the interpretation algorithms of resistance of the National Agency of AIDS Research and viral hepatitis of the ANRS 2013 (Agence Nationale de Recherche sur le Sida; 75,013, Paris, France) [http://www.
Statistical Analyses Data were entered into an Excel table and analyzed using SPSS. 18 and Epi Info. 06. fr (ENSP-Epiconcept-InUS, 2001). A Chi-squared test was used to compare frequencies and the Fisher t-test was used to compare means with a 5% standard deviation. A measure of the association between variables was examined using odds ratios with 95% confidence intervals. To verify whether HSV-2 infection could constitute a risk factor associated with virological failure in patients infected with HIV in Central Africa, we made the following null hypothesis: there is no significant (p-value > 0. 05) difference in virological (plasma HIV-RNA load, ARV resistance mutations and level of circulating genetic diversity) and immunological (CD4+ T cell count) parameters between HSV-2 seropositive and HSV-2 seronegative individuals.
Acknowledgments: We thank the managers and all staff of the laboratories that participate in this study. We thank  Litto Labo of Douala, Microbiology Laboratory of the Faculty of Health Sciences of Libreville , the  National Reference Center for Sexually Transmitted Diseases and AIDS in Bangui , and the  National General Hospital of Reference  in N'Djamena for their contribution to the collection of samples. We also thank the  Microbiology laboratory of Georges Pompidou European Hospital  for the analysis of the samples.
We conducted subgroup analyses by regimen: (1) NNRTIs (nevirapine [NVP] and/or EFV) + 2 NRTIs (32 studies), (2) EFV + 2 NRTIs (subset of 8 studies), or (3) EFV/XTC/TDF (subset of 6 studies); by population (children; adults); and by definition of the exposure (PDR; NNRTI PDR with or without NRTI PDR). Table  1  describes the characteristics of studies included in the subgroup analysis. To increase comparability of the findings, authors of studies assessing impact of PDR in patients receiving NNRTIs were invited to reanalyze their dataset using our study definition of resistance, and focusing to subpopulations receiving EFV + 2 NRTIs and, where available, EFV/XTC/TDF.
Statistical heterogeneity was assessed using the χ 2 test for homogeneity with a level of significance α =. 10 and the I 2 statistic to quantify inconsistency. Publication bias was assessed using a funnel plot for outcomes with 10 or more studies. We analyzed the data using Stata/IC 16. 0 for Windows and WINPEPI, and present the results as effect measures and 95% confidence intervals (CIs). Additional information on data analysis is shown in Supplementary Appendix 1.
SUBGROUP ANALYSIS We performed subgroup analysis to assess the impact of PDR among populations receiving EFV-based ART  [8, 13, 17, 22, 23, 25, 27, 40]  and in populations receiving EFV/TDF/XTC (Table  1  Authors of studies including patients receiving multiple nucleoside reverse transcriptase inhibitor backbone were contacted and provided data of patients on EFV/XTC/TDF using standardized definition of resistance, as described in the Methods. b The VL cutoff value used for the EFV/XTC/TDF subanalysis is >1000 copies/mL for all studies (including Avila-Rios et al) except  Derache et al. c  Authors provided data for this analysis on the impact of nonnucleoside reverse transcriptase inhibitor (NNRTI) PDR among people on EFV-based ART using standardized definitions described in the Methods. d Authors provided data for this analysis on the impact of NNRTI PDR among people on EFV/XTC/TDF using standardized definitions described in the Methods.
DISCUSSION Thirty-two studies comprising 30 unique datasets and >30 000 participants were included in this analysis documenting that PDR, and NNRTI PDR in particular, defined as the presence of 1 or more mutations conferring resistance to NNRTIs (irrespective of whether or not NNRTI-associated resistance mutations were paired with NRTI-associated mutations), predisposes to VF, selection of additional drug resistance mutations, and treatment discontinuation or switch. People with PDR were 3 times more likely to experience VF, and the clinical impact was even larger in patients with NNRTI PDR. Similar results were observed both in adults and in children. In most study settings, PDR is largely driven by resistance to the NNRTI drug class, which likely explains the strong clinical impact of PDR, even when it is loosely defined as any resistance mutations detected at time of ART initiation.
Our results should be interpreted in light of the following limitations. First, data were drawn mostly from regression estimates, with composition of the regression models (factors controlled for) varying across studies; in some instances, unadjusted estimates were used. Second, concerns about selection bias, comparability of cases and controls, and attrition limit the certainty of the overall body of evidence. It is, however, unlikely that these sources of bias have led to profound under-or overestimation of the effect of PDR on treatment outcomes. Many of these sources of uncertainty are inherent to studies of PDR, as PDR is not amenable to randomization, given that there is an ethical imperative to act upon knowledge of PDR. In all of the included studies, HIV-DR testing was performed retrospectively on stored samples.
Third, the exclusion of data from studies using next-generation sequencing technology with limits of detection <20% or from studies using point mutation  assays may have led to the exclusion of potentially informative studies; however, this approach was adopted to reflect generalizable interpretation of resistance data. Fourth, given that studies did not report outcomes separately for individuals with NNRTI mutations only vs NRTI and NNRTI mutations, or whether such mutations, when detected, were on the same genome, we were unable to assess the impact of single vs dual class resistance or of mutation linkage. However, while it is unlikely that this had a large impact on our results because very few new ART initiators have both NRTI and NNRTI HIV-DR mutations, the possibility that single-class NNRTI PDR is not predictive of virological failure of treatment with EFV/XTC/ TDF should be investigated in future studies.
Fifth, as raw sequence data were unavailable to us for reanalysis, we are unable to comment on the possible impact of specific mutations, polymorphisms, or HIV subtype on study outcomes. Sixth, very few studies reported the outcome of death; thus, mortality outcome in this analysis should be regarded with caution. Last, in the subanalysis restricted to studies with people receiving EFV/XTC/TDF, EFV was dosed at 600 mg daily in all studies except 1, in which the dose was 400 mg daily  [22]. We are unable to assess whether the clinical impact of NNRTI PDR is worse in people using EFV 400 mg vs 600 mg daily. The strength of this systematic review lies in the exhaustiveness of the search and the diverse geographic locations in which the studies were conducted, suggesting a wide generalizability.
To maximize data comparability of the EFV and EFV/XTC/ TDF subgroup analysis, we contacted study authors, who reanalyzed their data using common definition of resistance. In conclusion, this systematic review and meta-analysis provides evidence of poorer treatment outcomes-that is, higher risk of VF, acquisition of new resistance mutation, or ART switch or discontinuation-in both adults and children with PDR (either PDR or NNRTI PDR) initiating NNRTI-containing regimens. This conclusion holds true in people receiving EFV/ XTC/TDF. Our findings are significant due to documented high levels of NNRTI PDR and the lack of PDR testing in many LMICs, particularly in situations where a substantially large proportion of the population has limited access to or poor tolerability of currently recommended DTG-based first-line ART.
6, 150 mM NaCl, 1 mM EDTA, 0. 1 mg/mL BSA and 8% DMSO. The reaction was stopped by the addition of 1 volume of formamide loading buffer (96% formamide, 20 mM Tris/HCl pH 8. 0 and 2 mM Na 2 EDTA), heated at 80 • C for 2 min and then analyzed by 20% Urea-PAGE, as previously described  [45]. After electrophoresis, the gels were exposed for autoradiography, revealed using Typhoon imager and quantified with ImageQuant software. Under these conditions, only 50% of the substrate is converted to the cleavage product (limiting enzyme concentration conditions). For an initial evaluation of the inhibitory effect, 40 µM of 2TX/TXn was used. The thio-compound was added to the reaction mixture before the final addition of the enzyme (competition condition). For the best identified inhibitors, a dose-response curve was generated and IC50 A determined (Figure  1  and Table  1 ).
The DNA binding activity was measured using EMSA  [37]. Briefly, 0. 1 nM of the 5 -labeled 14-mer [THF:C] (see above) was incubated with the enzyme at 4 • C for 30 min in 25 mM HEPES/NaOH (pH 7. 5), 150 mM NaCl, 5% glycerol, 0. 1 mg/mL BSA and 8% DMSO. The incubation mixture was then loaded onto a native 10% polyacrylamide gel (Acryl/Bis 19/1) and electrophoresed at 25 V/cm for 90 min at 4 • C. After electrophoresis, the gels were dried and exposed overnight for autoradiography using a Typhoon imager and quantified with ImageQuant software. To evaluate the inhibitor effect of 2TX/TXn on the DNA binding activity of each Fpg/Nei enzyme, we first determined the experimental conditions required to bind 50% of the DNA probes without an inhibitor in the presence of 8% DMSO (limiting enzyme concentration).
Molecular Dynamic Simulation and Docking Four 3D structures were used as receptors for ligand docking: (i) the 3D model of free Fpg from L. lactis (LlFpg) obtained by removing DNA duplex from the X-ray structure of the enzyme bound to THF-containing 14-mer DNA duplex, (ii) the X-ray structure of LlFpg/DNA-THF complex (PDBidcode: 1PM5), (iii) the X-ray structure of free hNeil1 (PDBidcode: 1TDH) for which missing residues were reconstructed using the Prime module from Schrödinger (Schrödinger, LLC, New York, NY, 2017) (https://www. schrodinger. com/) and (iv) the X-ray structure of hNeil1 bound to THF-DNA (PDBidcode: 5ITT). The four systems were placed in a rectangular box with explicit TIP3P water molecules with a 10 Å buffer. To ensure the neutrality of the systems, counter ions were added.
org/). For the two systems containing a THF (tetrahydrofuran), the geometry and charge distribution of the THF residue were computed using Gaussian 03 program (https://gaussian. com/) and fitted with the RESP program  [48]  for compatibility with Cornell et al. 's force field  [49]  adapted to Parm98 parameters. For each system, a Hierarchical Ascending Clustering (HAC) method by average linkage distance calculation was used to classify system conformations in clusters based on a 2D RMSD map (each configuration of a trajectory was compared to all the others). We extracted one structure, called centroid, for each cluster. A centroid is representative of the system flexibility within a single cluster. The thirty collected centroids were then used for docking studies. Reduced and disulfide forms of 2TX were sketched within the Sybyl suite and their 3D structures calculated with Concord and their energy minimized.
For the disulfide dimer of 2TX, several conformational search techniques (Random search, GA search and Confort with the default parameters set in Sybyl package) were used to have a representative set of conformers. To obtain an exhaustive (as possible) set of cyclic conformers for docking with TX19 Ox1,Ox2 , we used several methods such as Random search, Grid search and simulated annealing, as implemented in the Sybyl package (Certara, NJ, USA), all with default parameters. To prepare the docking with Surflex-Dock 2. 706 Surflex Manual: Docking and Similarity Version 2. 7 (May 2012) by BioPharmics LLC (Santa Fe, CA, USA), a protomol was generated for each protein structure (centroids) in automatic mode with default parameters from the Sybyl interface. Protomols can be seen as an 'imprinting' an interaction cavity of a protein.
Crystallization and X-Ray Structure Determination LlFpg/DNA complexes (70-160 µM) were prepared by mixing in a 1. 5 molar excess the 14-mer [THF:C] DNA duplex with LlFpg and crystallized at room temperature in the presence of 0. 5% DMSO and with (for TX19) or absence of TCEP using a previously described method  [18, 22, 23]. Crystals with 2TX, TX13, TX15, TX19, TX19 (+TCEP), TX20 or TX27 were obtained by soaking crystals of LlFpg/DNA complex in 2TX (TXn)-saturated mother liquor. Soaked crystals were then flash cooled in liquid nitrogen. X-ray diffraction data sets were collected at 100 K at beamline PROXIMA-1 and PROXIMA-2 (SOLEIL, Paris) or ID30A-3/MASSIF-3 (ESRF, Grenoble). All data were processed using the XDS package  [50]  and the CCP4 program SCALA  [51]. The 3D structures were solved by molecular replacement using the crystal structure of the wild type LlFpg protein bound to 14-mer [THF:C] (PDB ID code 1PM5,  [35] ) as previously described  [18].
Acknowledgments: We are very grateful for the help provided by  Quoc-Tuan Do and Philippe Bernard from Greenpharma (AS, 3 Allée du Titane, 45000 Orléans ) (https://www. greenpharma. com/)for their help in docking experiments with disulfide cyclophanes. We thank  Samia Aci-Sèche  ( Institut de Chimie Organique  et analytique,  UMR7311 ,  CNRS-Université d'Orléans)  for her help in parameterizing THF-containing DNA required for the preparation of the 3D structure of the LlFpg/DNA and hNeil1/DNA complexes before molecular dynamic simulations. We thank the staff of the  ESRF (Grenoble, France)  and  SOLEIL (Saclay, France)  synchrotron facilities for their help in X-ray diffraction data collection. We are grateful to  Loïc Habert  for her excellent experimental assistance in the synthesis of thiopurines.
Library Generation/Protein Identification, Data Processing and Relative Quantitation A spectral library of all the detectable peptides in the samples and relative quantitation was performed according to Estrada-Peña  [46] , with the exception of spectra identification which was performed by searching against a compiled database containing all sequences from Ixodidae and Babesia taxonomies and rabbit (Oryctolagus cuniculus) proteome (135,071, 19,087 and 21,178 Uniprot entries, respectively, in September, 2017) with the following parameters: iodoacetamide cysteine alkylation, trypsin digestion, identification focus on biological modification, and thorough ID as search effort. The MS raw proteomics data have been deposited at the PeptideAtlas repository (http://www. peptideatlas. org/) with the dataset identifier PASS01362.
Gene Ontology Gene ontology was obtained using Blast2GO software (version 3. 0. 11, available at http://www. blast2go. org) [47, 48]. Homology to the protein identification (UniprotID) was searched by blast against Arthropoda (nr subset) [arthropoda, taxa:6656] from 30. 01. 2017 as well as a mapping and annotation steps to assign functional terms at level 3. GO terms were also assigned manually based on UniProt-associated databases. GO frequency and protein regulation charts were constructed for each condition using the Microsoft Office 2016 Excel tool. To elucidate about the GO and the differentially representation of proteins in response to infection, feeding, or both, chord diagrams were generated using the GOplot R package in RStudio (Version 1. 1. 453) [49].
In Silico Analysis of Proteins, Selection of Targets and Recombinant Protein, and Peptide Production Proteins commonly represented in the four conditions were further characterized using the software STRING 10. 5 (Search Tool for the Retrieval of Interacting Genes/Proteins available at http://string-db. org) in order to identify known/novel protein-protein interactions in the Ixodes scapularis database. Briefly, the program generates the network images based on a spring model. The selection of targets for further analysis was based on three main criteria:  (1)  Proteins present in all the datasets from proteomics; (2) proteins that may have a pivotal role in tick-parasite interplay; and (3) proteins that may be potential protective antigens resulting in a vaccine candidate. The amino acid sequences of L7M1X7 and L7MAU7 were analyzed in silico in order to predict the protein localization (CELLO v.