dataesr/scientific-paragraphs-categorization huggingface dataset:
Quintiles of the PS were fitted in the Poisson regression model as a continuous variable. Results were consistent when we used the alternative approaches of matching, stratifying (data not shown). For all Poisson regression analyses, an intentionto-treat (ITT) approach, ignoring treatment switches as well as recurrences of clinical events of the same type, was used. All statistical analyses were performed using SAS version 9. 4 (SAS Institute, Cary, NC).
On this basis, it has been suggested by Lee and Carr that RAL should be a preferred option for patients with a preexisting risk of cardiovascular diseases, altered serum lipid levels, metabolic syndrome, or changes in body fat composition (i. e. the lipodystrophy syndrome)  [36]. Manfredi R et al. , in an analysis of a large hospital database in Italy, showed that grade 2-4 AEs attributable to RAL were neither directly observed nor reported in the selfcompleted record of possible untoward events filled in every month by patients at the time of repeat prescription, and double-checked by hospital pharmacists and physicians. In contrast, the discontinuation of some companion drugs at the time of RAL introduction and during the 12-month follow-up [especially NRTIs, some selected PIs and nonnucleoside reverse transcriptase inhibitors (NNRTIs), and enfuvirtide] had a favourable effect on the tolerability of the RAL-based regimens  [37].
In addition, no clinical or laboratory evidence of autoimmune disorders associated with exposure to RAL-containing cART regimens was found, as also reported in a recent 12month observational study  [38]. In our analysis, discontinuation was examined in the RAL cohort alone, and we found a risk of discontinuation similar to those reported in the trials. The main reason for stopping RAL appeared to be physician's choice. Although the exact reason reported by the physician under 'physician's choice' is not specified in the Euro-SIDA data collection report forms, it is conceivable that discontinuations because of toxicity induced by RAL would be filed under the reason 'toxicity', not 'physician's choice'. There was also a nonnegligible frequency of people with missing information regarding the reason for stopping, which reflects the way the date are collected, as reasons are often not known or reported in clinical patient notes.
As a consequence, although it was reassuring to see that our analyses using a range of techniques aimed at reducing bias caused by confounding, led to similar results, we are not able to exclude the possibility of confounding by indication or other bias introduced by unmeasured confounders (such as traditional lifestyle risk factors for cancer such as smoking) that can only be truly accounted for in a randomized clinical trial. In the specific case of patients who are about to receive chemotherapy, patients are typically switched to RAL to minimize pharmacokinetic interactions. Some of the residual excess risk of death seen in the RAL vs. CONC analysis might be explained by this important unmeasured source of confounding. Although the list of clinical diagnoses collected in the database follows the accepted classification of the WHO ICD, a central pathological review was not conducted.
Acknowledgment Funding: EuroSIDA was supported by the  European Union 's  Seventh Framework Programme  for research, technological development and demonstration under  Euro Coord  grant agreement no. 260694. Current support includes unrestricted grants from  Bristol-Myers Squibb ,  Gilead ,  GlaxoSmithKline LLC ,  Janssen R&D ,  Merck and Co. Inc. and  Pfizer Inc. The participation of centres from Switzerland was supported by The  Swiss National Science Foundation  (Grant  108787 ). The study is also supported by a grant (grant number  DNRF126 ) from the  Danish Na tional Research Foundation.
Population In the present study, all patients with RA (from both M-arm and S-arm) who completed the STRASS clinical trial were followed up and assessed by hospital-based or office-based rheumatologists who were completely free for therapeutic decision making. In 2015, physicians were contacted, and follow-up data were retrospectively collected from medical charts. The extended follow-up population corresponded to all patients in the STRASS population who completed the trial and continued to be followed up over the 3-year period. 14 A non-opposition form (certifying that the patients did not express any opposition with retrospective data collection from his/her medical charts) was completed by the local investigator. data collection A structured case report form was sent to all STRASS investigation centres between April and October 2015.
acknowledgements The authors thank all patients who participated in the trial and the following physicians who contributed to the data collection in their respective institution: Dr e. Dernis (Rheumatology Department, le Mans Hospital, le Mans); M. Trabelsi (Rheumatology Department, Joseph Fourrier University, Sud Hospital, grenoble); Dr O. Brocq (Rheumatology Department, Princess grace Health centre, Monaco); Dr J-M. Berthelot (Rheumatology Department, Hotel-Dieu Hospital, Nantes); Dr J-c. Balblanc (Rheumatology Department, Belfort-Montbeliard Health center, Belfort). Contributors All persons who meet authorship criteria are listed as authors, and all authors certify that they have participated sufficiently in the work to take public responsibility for the content, including participation in the concept, design, analysis, writing or revision of the manuscript.
Acknowledgments We thank  Sirius grant  ( UCB, France ) and  Montpellier Hospital  for their financial support. We thank  Edouard Tuaillon  (Lapeyronie hospital, Montpellier) and  Guillaume Cartron  ( Saint Eloi hospital, Montpellier ) for their contribution. We also thank  Montpellier RIO Imaging  ( MRI ) facility in Montpellier, especially  Myriam Boyer.
Taken together, our data show that within LNs draining the immunizing site, Tfh cells exhibit clear oligoclonal expansions of specific TRBV CDR3 lengths. The same pattern of TRBV CDR3 usage is not observed within the Tfr population that retain distributions of CDR3 lengths usage similar to Treg cells. The TCR repertoire of Tfr cells resembles that of Treg cells. The spectratyping data demonstrate that although Tfr and Tfh cell numbers increase after immunization, they present different TRBV CDR3 length usage. To further verify the different TCR usage between both populations, we sequenced the TRA of 1D2b mice, which express a fixed TCRb chain and variable TCRa chains. This 1D2b mouse line, of C57BL/6 background, was established using nuclear-transferred embryonic stem (NT-ES) cells that had been generated using peripheral CD25 high CD4 þ T cells as donor of nuclei.
2d ). Tfh cells from all three mice were able to proliferate with OVA signals but not with the control antigen bLG (Fig. 6b ). Thus, these mice, while not being able to recombine the TRB, still have a repertoire capable of specifically recognizing OVA. Five T-cell populations were sorted for TRA repertoire analysis on day 11 following OVA-IFA immunization from draining LNs of individual mice: Tfr (CD4 þ CXCR5 þ PD-1 þ Foxp3 þ ); Tfh (CD4 þ CXCR5 þ PD-1 þ Foxp3 À ); Treg (CD4 þ CXCR5 À PD-1 À Foxp3 þ ); activated CD4 þ T (Tact: CD4 þ CXCR5 À PD-1 À Foxp3 À CD44 þ ); and non-activated CD4 þ T (Tconv: CD4 þ CXCR5 À PD-1 À Foxp3 À CD44 À ) cells (Supplementary Fig. 2d ). TRA gene was then specifically amplified and sequenced on an Illumina MiSeq platform. To perform an unbiased analysis, 9,000 TCR sequences were randomly selected from each data set per sample (9,000 being the lowest number of TCR sequences identified on a sample).
Staining was performed for 1 h at room temperature  32. Enrichment of tetramer þ cells was performed using MACS cell separation system and anti-PE and anti-APC magnetic beads (Miltenyi Biotec, Catalogue#130-048-801 and 130-090-855). Samples were acquired on a BD LSR Fortessa flow cytometer. Acquisition data were analysed on FlowJo software (Tree Star). For cell sorting CD4 þ T cells for adoptive cell transfers were purified from spleen and mesenteric LNs using MACS cell separation system and anti-CD4 (L3T4) magnetic beads (Miltenyi Biotec, Catalogue#130-049-201). FACS, with monoclonal antibodies mentioned above, was performed on a BD FACSAria cell sorter. For flow cytometry analysis of cultured cells and tetramer-enriched cell samples, 10 mm latex counting beads were added to cell suspensions to obtain total cell counts (Counter Beckman).
To perform CDR3 spectratyping  26  , each obtained cDNA was divided into 23 parallel PCR reactions with a common Cb reverse primer and 23 Vb-specific forward primers (GoTaq DNA Polymerase from Promega, Catalogue#M7801, and primers from Life Technologies, Supplementary Table  2 ). Run-off reactions were done using dye-labelled Cb primer. All primer sequences can be found on Supplementary Table  2. Run-off products were run on ABI 3130XL Automatic Sequencer (Applied Biosystems) together with GeneScan 500 ROX dye Size Standard (Applied Biosystems, Catalogue#401734) and consequently separated based on their nucleotide size. Gene Mapper software (Applied Biosystems) was used to obtain nucleotide length and area of each peak. Deep sequencing. RNA from 1D2b mice sorted cell populations (1. 1 Â 10 4 -1.
0 Â 10 6 cells) was extracted using RNeasy Mini kit (Qiagen, Catalogue#74104) following the manufacturer's instructions. Full-cDNA library was prepared using Mint-2 kit (evrogen, Catalogue#SK005), which introduces 5 0 -adapters to cDNA fragments, according to the manufacturer's instructions. TRA was then specifically amplified using Pfx DNA polymerase (Invitrogen, Catalogue#11708013) and a primer pair (Life Technologies) specific for the 5 0 -adapter and the C region of TRA gene. Primers used for TRA amplification can be found on Supplementary Table  2. Sequencing library was prepared using the Nextera kit (Catalogue#FC-121-1030 and FC-131-1002), in which each sample was barcoded, and sequenced using 250 bp paired-end illumina MiSeq technology (all illumina). CDR3 data analysis. To have adequate representation of a complete TRBV repertoire, it is necessary to analyse at least 2 Â 10 5 cells.
To achieve this number of cells, it was necessary to pool draining LNs from 15 mice for each biological replicate. In our experiments, we used at least three biological replicates for each T-cell subset. To extract and analyse the data obtained for CDR3 fragment size we used ISEApeaks  33, 34. Briefly, this software quantifies the percentage of use of each CDR3 length, obtained by dividing the area of CDR3 peaks by the total area of all peaks within the profile. On C57BL/6 mice, TRBV21 and TRBV24 are pseudogenes and thus ignored on the analysis. TRBV12-2 was also discarded since it could not be detected on three of the samples. To facilitate the comparison between samples and populations, a perturbation score  27  was computed to obtain the overall differences between TRBV CDR3 spectratypes of each sample and the average profiles of Tfr samples as control group.
Acknowledgements We are grateful to  Constantin Fesel ,  Margarida Correia-Neves  and  Bruno Cerqueira-Rodrigues  for advice and reagents used in our studies. We acknowledge the  NIH Tetramer Core Facility  for providing MHC-II tetramers, and the  Gene Expression Unit at Instituto Gulbenkian de Ciencia  where the deep sequencing was performed. The research was funded by  Fundac¸a ˜o para Ciencia e Tecnologia (FCT)  grants  PTDC/SAU-IMU/120225/2010 ,  HMSP-ICT/0034/2013  and  FCT-FAPESP/19906/2014  (to L. G. ). A. R. M. and S. C. P. A. are funded by  FCT  scholarships  SFRH/BD/88030/2012  and  SFRH/BDP/81391/2011 , respectively. The work by D. K. , A. S. , E. M. -F. , W. C. and F. J. has been funded by  Assistance Publique-Hopitaux de Paris, UniversitePierre and Marie Curie (Paris VI) ,  LabEx Transimmunom  ( ANR-11-IDEX-0004-02 ) and  ERC   Advanced Grant TRiPoD  ( 322856 ).
Phylogenetic and recombination analyses Group specific PCR fragments and vpr fragments were sequenced and aligned along with a set of different HIV-1/M and HIV-1/O reference sequences from the LANL database using MEGA 5. 05 software  [32]. vpr sequences from the recombinants described by Peeters et al. [10] , Yamaguchi et al. [12] , Vessière et al. [13]  and Ngoupo et al. [14]  were also included in the alignment (GenBank access No AJ239083, AY489738, GQ351296, KM438031 and KM438032). Genotyping was performed using HIV BLAST (http://lanl. hiv. org), Genotyping Retrovirus Tool (http://www. ncbi. nlm. nih. gov/retroviruses/) and REGA HIV-1 Subtyping Tool (http://dbpartners. stanford. edu/ RegaSubtyping/). For recombination analyses, we performed: Similarity analysis, allowing localization of the recombination points, with SimPlot software  [33] ; and the Recombinant Identification Program (RIP) available on-line through the Los Alamos Database  [34].
These profiles associated with the results of vpr   [13] , and (4) KM438031 and KM438032  [14]  are represented in bold italics. The new sequences obtained here are represented in bold. The gp41 HIV-1/O sequence of YBF298 could not be used for phylogenetic analysis, because of the relatively short length of the strain. SIVcpzGAB was used as the outgroup. Phylogenetic analyses were performed using MEGA software  [32] : evolutionary distances were computed using the Kimura 2-parameter method; 1000 bootstrap replicates were performed to assess the reliability of the branching order. Bootstrap values are shown only when significant (>70) amplification indicated a vpr recombinant, associated with only one parental virus (Table  1 ). For YBF274, sequencing of the complete genome of the recombinant form, showed a mosaic pattern with gag-pol belonging to group O (subgroup H) and env belonging to group M (subtype D), with two breakpoints, in vpr and in LTR (Fig.
4  a Recombination pattern of the full-length genome of YBF274. Analysis was performed using SimPlot software with 250 nucleotide (nt) windows, 20 nt increments, and the Kimura 2-parameter method with a transition-transversion (Ts/Tv) ratio of 2. 0. Sequences representative of a strain of HIV-1/M (D. CD. 1983. ELI_patent. A07108 in red) and O (O. CM. 98. 98CMA104. AY169802 in blue) were used. The genome map was obtained using the Recombinant HIV Drawing Tool (http://www. hiv. lanl. gov/content/sequence/DRAW_CRF/recom_mapper. html). b Recombination pattern of the full-length genome of YBF282. Analysis was performed using SimPlot software with 350 nucleotide (nt) windows, 20 nt increments, and the Kimura 2-parameter method with a transition-transversion (Ts/Tv) ratio of 2. 0. Sequences representative of a strain of HIV-1/M (02_AG.
The sample collection, performed from 2006 to 2009 and not according to epidemiological methodology, may not be representative of the current situation and cannot define the prevalence or frequency of such forms. We only analyzed M + O dual seroreactivity, but reports of two cases with recombinants only  [13, 14]  and a third case here (YBF282) raise the question of the circulation of a single recombinant with a serotype profile of HIV-1/M or/O mono-infection. We searched for vpr recombinants, because we considered this gene as a potential hot-spot of recombination; indeed, three of four MO recombinant forms previously reported exhibited a vpr breakpoint. This and our data show that this region could be essential for MO recombination, compared to intra-group HIV-1/M recombination. Among the HIV-1/M CRFs, reported in the Los Alamos Database, only 12 show a recombinant breakpoint in vpr.
Only in one community was the lognormal statistically tied to another distribution (the ZSM, ΔAICc=2. 8) and that was in cervical carcinoma using a more restricted dataset (Figure  4 , Table  S3 ). However for this same community in the meta-analysis dataset the ZSM was out-performed by the lognormal and by other distributions (Figure  4 ). Except for this one tie, the ZSM was systematically outperformed by the lognormal in all our datasets. Thus, in the late stages of the natural history of the infection, viral communities are structured by non-neutral interactions between HPVs. Remarkably, the strong drop in prevalence between the first ranked HPV type and the rest (see Figures  3  and 4 ) was not captured well by any of the theoretical model distributions used. This gap was especially large in the cancer data in all anatomical locations, where HPV16 largely dominates other HPVs, particularly for head and neck cancers.
Post-vaccination data were best fitted by the same distribution as the pre-vaccination data, suggesting then that the vaccine is not changing the underlying processes that govern HPV type distributions in healthy women. While the exact kind or relative strengths of interactions between types have yet to be evaluated, there is a need to unravel the complex interactions between types (direct or indirect) in order to better evaluate the effect of the vaccines long-term. It is important to highlight that the dataset used to perform this analysis was collected over only three years after vaccine implementation, and are from samples across the USA where vaccination coverage is very heterogeneous and often very low in some areas. Thus, these conclusions should be seen as preliminary at best. To evaluate potential type replacement in the postvaccine era will require other forms of type-specific studies of non-cancer communities that are sufficiently long-term to distinguish true changes in type prevalence from natural fluctuations or noise and that can take into account sampling biases from detection methods (e.
g. , the unmasking effect; (  16 )). In order to check the validity of our results and rule out the possibility of sampling artefacts in our analyses, we checked the effect of the sample size in the selection of the best-fit model (Figure  S1 ). We found that in undersampled communities, the probability to best-fit a Power law model increases. Indeed, the lognormal distribution is believed to better-fit large datasets. Previous published studies showed that in about 500 SADs, the best fit SAD model changed depending on whether the community had been fully censored or not  [35]. These study also found that "fully censored" communities were best fit by the lognormal, while "incompletely sampled" communities were best fit by the Power Law model  [35]. We also found that the lognormal best described even the smallest datasets.
This, once again demonstrates that apparently neutral-like patterns can be generated by underlying non-neutral processes. Bacterial and viral communities have very marked differences so more studies into the roles of niche and neutral processes shaping viral communities are needed. One possible future direction would be to assess whether non-cancer communities of HPVs could be described by emergent neutrality theory  (40) (41) (42) , where patterns that appear neutral are the outcome of competition and evolutionary processes, such that species evolve to be functionally similar and thus coexist. Most of the HPVs datasets we examined appear as though they could be explained by multimodal SADs, possibly the two-mode Poisson lognormal distribution, which have been found to explain several empirical datasets  (42).
Dataset For this study the unit of analysis is the HPV at the level of type, according to the definition of the International Committee for the Taxonomy of Viruses, i. e. , when we write "different HPVs" we mean "different types of Human Papillomaviruses". For timetrends analyses, worldwide HPV type-specific prevalence values in different stages of the natural history of the cervical HPV infection (i. e. asymptomatic, low-grade squamous intraepithelial lesions (LSIL), high-grade squamous intraepithelial lesions (HSIL) and invasive cervical carcinoma (ICC)) were obtained from a meta-analysis previously published (44) (Table  S4 ). For site-specific analyses, worldwide HPV typespecific prevalence values in squamous carcinomas of different anatomical locations (i. e. cervix, anus, penis, vulva, vagina and head and neck) were obtained from the retrospective cross-sectional study by the Catalan Institute of Oncology (45-50) (Table  S5 ).
We chose to use this diversity measure because it quantifies the effective number of species in the dataset, which refers to the number of equally abundant species necessary to produce the observed value of diversity. Moreover, these effective numbers obey the replication principle, which states that if two communities with X equally abundant species are combined, then the diversity of the combined community should be twice that of the original communities  (53). Moreover, the unit of these diversity indices is the "effective number of species" (ENS) and thus values of diversity are comparable across different metrics. Hill numbers were computed using the Vegan package implemented in R (http://www. r-project. org/).
Second, the spleen is a site of immune tolerance induction and can be alerted-or affected-via apoptotic "remnants" (including apoptotic cells, or apoptotic materials, such as apoptotic bodies or microvesicles) (54) released by distant tissues during normal cell turn-over  (54). This transfer of tolerance from peripheral tissues to the spleen exists also under chronic inflammatory conditions  (54). When the functions of splenic macrophages were assessed ex vivo after i. v. infusion of apoptotic cells in the setting of arthritis models  (20) , it is possible that we measured the consequence (i. e. , the transfer of tolerance from the joint to the spleen) and not the cause of clinical improvement. Third, based on data obtained in the lungs  (57, 58) , splenic macrophages phagocyting infused apoptotic cells may release insulin-like growth factor-1 (IGF-1) and macrophage-derived microvesicle (Mφ-MVS) (57) targeting joint-infiltrating immune cells.
CONCLUSiON/CONCLUDiNG ReMARKS Apoptotic cell infusion represents an additional potential bDMARD in RA, and more particularly a cell-based bDMARD. We plan to initiate a phase I/II clinical trial (ClinicalTrials. gov Identifier: NCT02903212) to achieve LDA in patients with RA who did not respond adequately to one previous bDMARD. Concerning the potential toxicity of this approach, one may build on the experience gained by the clinical trial performed in the setting of hematopoietic cell transplantation (  16 ), but also those using extracorporeal photopheresis (ECP) in RA patients  (100, 101). Even if ECP does not necessarily generate "proper/ pure" early-stage apoptotic cells  (102) , this treatment introduces high amounts of dead cells in patients and no specific toxicity has been reported  (100, 101).
ACKNOwLeDGMeNTS This work is supported by the Agence Nationale de la Recherche (ANR) under the program "Investissements d'Avenir" with reference ANR-11-LABX-0021-LipSTIC, by the Ministère de la Santé (PHRC Interrégional-Est #PHRCI-15-037), by the Region Bourgogne Franche-Comté (support to LipSTIC LabEX 2017 and MiMedI), the Arthritis Fondation Courtin (to SP), and the Fondation pour la Recherche Médicale (DBS20131128447 to SP). The authors would like to thank Sarah Odrion for her help in editing our manuscript, the members of our laboratory for their work, as well as both reviewers for their constructive comments.
The package npbr is the first free specialized software for data edge and frontier analysis in the statistical literature. It provides a variety of functions for the best known and most innovative approaches to nonparametric boundary estimation. The selected methods are concerned with empirical, smoothed, unrestricted as well as constrained fits under both single and multiple shape constraints. They also cover data envelopment techniques as well as robust approaches to outliers. The routines included in npbr are user friendly and afford a large degree of flexibility in the estimation specifications. They provide smoothing parameter selection for the modern local linear and polynomial spline methods as well as for some promising extreme value techniques. Also, they seamlessly allow for Monte Carlo comparisons among the implemented estimation procedures.