dataesr/scientific-paragraphs-categorization huggingface dataset:
2020). In particular, Gaia DR2 sources 2 and 3 in sectors 14, source 4 in sector 20, and source 8 in sector 21 all have Gband fluxes lower by 0. 5 % than that of TOI-1235 (Gaia and the TESS photometric bands are very similar). Similar results were found for the apertures of the ground-based surveys ASAS-SN and NSVS. For subarcsecond separations, we used our lucky imaging AstraLux and speckle NESSI data sets described in Sect. 2. 3 and illustrated by Fig. 3. We computed 5σ contrast curves as described by  Lillo-Box et al. (2012)  with the astrasens package 9  for AstraLux, and as reported by  Livingston et al. (2018)  for NESSI. From both data sets, we confirmed the absence of any close companion 4-6 mag fainter than TOI-1235, and derived an upper limit to the contamination of around 2 % between 0.
Joint fit To obtain precise parameters of the TOI-1235 system, we performed a joint analysis of the TESS and LCOGT photometry and CARMENES VIS and HARPS-N RV data using juliet. The model that we selected for our RV joint fit analysis was one composed of a circular Keplerian orbit for the transiting planet plus a quasi-periodic GP that we used to model the 20. 6 d signal observed in the RVs; we have discussed this in previous sections. However, we also computed models of a circular orbit, an eccentric orbit, a circular orbit plus a sinusoid, an eccentric orbit plus a sinusoid, an eccentric orbit plus a GP, and two circular orbits. The two best-fit models, judged by their log-evidences, were a two-planet model and a one-circular-planet model combined with a GP to fit the 20. 6 d signal. The star-planet tidal locking and consequent circularization of the planet orbit following the theoretical predictions of  Barnes (2017) , for instance, support both models with eccentricity fixed to zero (see also Fig.
10 +0. 38 -0. 10 , but the planet is also consistent with an Earth-like bulk composition (CRF ≈ 0. 4-0. 6). Furthermore, using Hardcore  (Suissa et al. 2018 ) and our R and M, the marginal core ratio fraction, CRF marg , is 0. 53±0. 20, similar to the Earth's true CRF value of 0. 55. Like many other transiting terrestrial and sub-Neptune planets, TOI-1235 b is on a fairly irradiated orbit and therefore may have been strongly sculpted by extreme atmospheric escape due to XUV-driven photoevaporation (e. g. ,  López   , G-,  and K -type stars with mass and radius measurement better than 30 % from the TEPCat database of well-characterized planets  (Southworth 2011) , filled red circles are planets around M dwarfs with mass and radius measurement, filled yellow circles are planets around M dwarfs with mass determinations lower than 30 % or without mass constraints at all (right panel only), and the red star is TOI-1235 b, whose radius and mass are determined with accuracies of 5 % and 10 %, respectively.
7 R ⊕ for an irradiation of 60 S ⊕ in that work). On the other hand, when we extrapolate from the sample of  Fulton & Petigura (2018) , who focused on F-, G-, and Ktype stars with precise stellar parameters and on stars that host validated Kepler exoplanets, we reach a similar conclusion. Finally, using the sample of  Hirano et al. (2018) , who focused only on low-mass stars hosting validated small planets unveiled by K2 and Kepler, we would locate TOI-1235 b in the gap, but the data in that sample (arguably more suitable for a proper comparison with the stellar properties of TOI-1235) were unable to track a proper stellar irradiation versus radius dependence of the gap. Therefore our measurements of the bulk composition of TOI-1235 b, consistent with the planet having lost its atmosphere, place a strong constraint on any interpretation regarding the radius gap for M dwarfs at the irradiation levels received by TOI-1235 b.
Conclusions We confirmed that TOI-1235 b is a transiting super-Earth planet around an M0. 5 V star, observed in sectors 14, 20, and 21 of the TESS mission. We collected CARMENES and HARPS-N spectroscopic data, from which we confirmed the planetary nature of the transit signal detected by TESS. Further support for the planetary interpretation came from our LCOGT photometric data during one transit, as well as from lucky and speckle imaging. From Article number, page 11 of 19 A&A proofs: manuscript no. TOI1235 M TESS,S21 (10 -6 ) -24. 0 +8. 0 -8. 0 σ TESS,S14 (ppm) 1. 9 +10. 5 -1. 6 σ TESS,S20 (ppm) 1. 9 +8. 2 -1. 6 σ TESS,S21 (ppm) 1. 5.
Acknowledgements. CARMENES is an instrument for the  Centro Astronómico Hispano-Alemán de Calar Alto (CAHA, Almería, Spain ). CARMENES is funded by the  German Max-Planck-Gesellschaft (MPG) , the  Spanish Consejo Superior de Investigaciones Científicas (CSIC) , the  European Union  through  FEDER/ERF FICTS-2011-02  funds, and the members of the  CARMENES Consortium (Max-Planck-Institut für Astronomie, Instituto de Astrofísica de Andalucía, Landessternwarte Königstuhl, Institut de Ciències de l'Espai, Institut für Astrophysik Göttingen ,  Universidad Complutense de Madrid ,  Thüringer Landessternwarte Tautenburg ,  Instituto de Astrofísica de Canarias ,  Hamburger Sternwarte ,  Centro de Astrobiología  and  Centro Astronómico Hispano-Alemán ), with additional contributions by the  Spanish Ministry of Economy , the  German Science Foundation  through the  Major Research Instrumentation Programme and DFG Research Unit FOR2544 "Blue Planets around Red Stars ", the  Klaus Tschira Stiftung , the states of  Baden-Württemberg  and  Niedersachsen , and by the  Junta de Andalucía.
Acknowledgements. We are grateful to  Fab-rizio Caola ,  Silvia Ferrario Ravasio ,  Basem El-Menoufi ,  Alexander Karlberg ,  Paolo Nason ,  Ludovic Scyboz ,  Rob Verheyen ,  Bryan Webber  and  Giulia Zanderighi  for helpful discussions and comments on the manuscript. We thank each other's institutions for hospitality while this work was being carried out. This work has been funded by a  Marie Sk lodowska Curie Individual  Fellowship contract number  702610 Resummation4PS  (PM), by a  Royal Society   Research Professorship  ( RP\R1\180112 ) (GPS), by the  European Research Council (ERC)  under the European Unions  Horizon 2020 research and innovation programme  (grant agreement No. 788223 , PanScales) (MD, KH, GPS, GS) and by the  Science and Technology Facilities Council (STFC)  under grants  ST/P000770/1  (FD),  ST/P000274/1  (KH) and  ST/P000800/1  (MD).
, 2001)  and the designed primer D1R-R (5'-TATGCTTAAAATTCAGCAGGT-3') which is the inverse complementary sequence of the primer DIR-F  (Scholin et al. , 1994). A mix of 1 µl of each primer, 1 µl of dNTP at 10 mM, 5 µl of 10X Advantage 2 PCR Buffer, 31 µl of sterile water and 1 µl of 50X Advantage 2 Taq polymerase (Clontech) was added in each PCR tube containing the cell pellet. The PCR was performed using a MasterGradiant thermocycler (Eppendorf) with the following conditions: one initial denaturation at 94°C for 10 min followed by 35 cycles each consisting of 1 min at 94°C, 1 min at 53°C, 1 min at 68°C and a final elongation for 10 min at 68°C. The PCR products were purified using QIAGEN MinElute PCR Purification kit according to the recommendations. After sequencing by Genewiz, sequences were treated using BioEdit software and compared to NCBI database using BLASTn tool to ensure the taxonomy of the strains.
Molecular analyses PCR amplification based assay of the strains using genus and species-specific primers confirmed the morphological analysis. The sequences obtained after PCR analysis showed a perfect alignment between the strains MCCV 054/MCCV 055 and a perfect match (100% of confidence) with Ostreopsis cf. ovata (E-value: 2e-157, accession number: MG551865. 1). Similarly, the strains MCCV 057/MCCV 058 were identified as Ostreopsis fattorussoi (level of confidence 100%, E-value: 1e-129, accession number: LT220222. 1 ;  Accoroni et al. , 2016a). These sequences were deposited in GenBank to the accession number: MT270691, MT270692, MT271779 and MT271780 for the strains MCCV 054, MCCV 055, MCCV 057 and MCCV 058 respectively.
Acknowledgements This work was supported by the  French ANR  project ( OCEAN 15: Ostreopsis Chemical Ecology and Allelopathy Network ; project  ANR-15-CE35-0002 ) and the project  COCLIME  (which is part of  ERA4CS , an  ERA-NET  initiated by  JPI Climate , and funded by  EPA (IE) ,  ANR (FR) ,  BMBF (DE) ,  UEFISCDI (RO) ,  RCN (NO)  and  FORMAS (SE) , with co-funding by the  European, Union ; Grant  6904462 ). The research leading to these results received funding from the  European Union 's J o u r n a l P r e -p r o o f  Horizon 2020 research and innovation programme  under grant agreement No  730984 ,  ASSEMBLE Plus  project. Authors are members of the  French National GdR PhycoTox. We thank the  Molecular Biology Platform  and the  Mediterranean Culture Collection of Villefranche (MCCV)  supported by  IR EMBRC-France  of the  Institut de la Mer de Villefranche (IMEV) ,  181 Chemin du Lazaret, 06230 Villefranche-sur-Mer, France  for the PCR analysis and the Ostreopsis sp.
In this medium description, the characteristic length appears in the generalized balance equation coupled with the gradient of the Micromorphic damage variable. The theory was implemented in ABAQUS ® Explicit, through a VUEL subroutine. The introduction of an additional degree of freedom implies a modification of the system of PDEs to be solved, thereby compelling the modification of the Finite Element description rather than an higher-level modification of the material module. The authors verified the developed formulation through tensile test and bending both performed using the material parameters of the DP1000 steel. The results of their analysis demonstrated an embedded mesh regularization property of the model, that was proven by varying the mesh size, whereas the global force-displacement graphs remained unchanged.
Statistical analyses. Statistical analyses were performed using either R and Rstudio software or GraphPad Prism 8 for Mac OS (GraphPad Software, Inc. ). We used only nonparametric tests. For in vivo experiments, 5 to 10 mice were used in 1 or 2 independent experiments. For all other experiments, at least 6 biological replicates in at least 2 independent experiments were used. A cutoff P value of 5% was used for all tests. *, P Ͻ 0. 05; **, P Ͻ 0. 05; ***, P Ͻ 0. 005. We are grateful to Andy Goodman and Justin Sonnenburg for providing the genetic tools used in this study and to Eric Martens for generously providing the B. thetaiotaomicron capsule mutants and mono-expressing strains. We are also very thankful to Laurie Comstock for comments on the manuscript. We thank the members of the animal facilities of INRAE-Jouy-en-Josas (Anaxem, Micalis) for their help with in vivo experiments.
This work was supported by an Institut Pasteur grant and by the French government's Investissement d'Avenir Program, Laboratoire d'Excellence "Integrative Biology of Emerging Infectious Diseases" (grant ANR-10-LABX-62-IBEID) and the Fondation pour la Recherche Médicale (grant DEQ20180339185). N. Béchon was supported by a MENESR (Ministère Français de l'Education Nationale, de l'Enseignement Supérieur et de la Recherche) fellowship. J. Mihajlovic was supported by the Pasteur Paris University International Doctoral Program and the Fondation pour la Recherche Médicale (grant FDT20160435523). N. B. , J. M. , S. V. -F. , and F. C. performed the experiments; N. B. , J. M. , C. B. , and J. -M. G. designed the experiments and analyzed the data. J. -M. G. and P. L. provided resources and funding. N.
No significant difference was observed, indicating that TB and non-TB specimens were equally diverse and there was no sample with a greater number of taxa identified (S1A Fig). When normalized Phylum abundances in the various samples were considered, no hierarchical clustering was noted according to the disease (TB or non-TB) or to the region of origin, therefore indicating high variability (Fig  1A ). Similarly, Principal Component Analysis (PCoA) did not display any segregation of the sputum samples (Fig  1B ). The study was further extended to a geographically matched dataset that included 30 HIV negative patients, 15 of which with active TB and 15 without. In each of the two groups, 8 samples came from Vietnam and 7 from South Africa (Table  2 ). As found in the previous unmatched analysis, alpha diversity was similar for the two groups at all taxonomic levels (S1B Fig).
For the same reasons, collection of the expectorate from members of the control group was performed at months 0, 2, 3, 4, 5, 6 and 7 after therapy began. To avoid sequencing batch effects, the sequencing libraries of all samples were pooled and sequenced together. Analysis of 16S rDNA Illumina reads proved that sequencing coverage was excellent for all of the samples, with more than 99. 7% of the reads mapping to the Greengenes database  [42]. S4 Fig shows the most abundant Phyla identified in the samples (Firmicutes, Bacteroidetes, Actinobacteria, Proteobacteria, Fusobacteria, TM7, Tenericutes, SR1 and Spirochaetes) and     60 ).
Microbial diversity in patients recruited in Bangladesh The last group of sputum samples was collected at the "icddr,b institute" in Bangladesh, where 11 TB patients were recruited. These were sampled at different time-points throughout therapy, together with 10 healthy donors, who were sampled only once. Demographic and clinical features of the subjects enrolled are detailed in Table  5. Technical issues (some sputa could not be collected, failure of library preparation or unsuccessful sequencing for other samples) excluded 2 healthy donors and 5 TB time-points from downstream analyses. Sequencing coverage was good in all of the remaining samples, with >99. 5% of the reads mapping to the Greengenes  [42]  dataset. S9 Fig lists the most abundant Phyla identified in the samples, which overall matched those previously noticed in the sputa collected in Italy, that is: Firmicutes, Bacteroidetes, Actinobacteria, Proteobacteria, Fusobacteria, TM7, Tenericutes, SR1 and Spirochaetes.
Accurate lung sampling would require bronchoalveolar lavage but use of this rather invasive technique is unethical in a longitudinal study such as the one presented here. This study is based on five datasets, each of which includes between 11 and 30 samples, split among TB and non-TB individuals. While these numbers fall within the order of magnitude of the sample size of previous works  [30, 31, 33] , the definition of a generic biomarker might require even bigger sample sets. A possible limitation of this investigation was that M. tuberculosis was of seemingly low abundance as evidenced by 16S rDNA sequencing although the primers used for PCR successfully amplified the correct DNA fragment from purified genomic DNA. The reason for this is unknown although a study by Sulaiman and colleagues reported the same observation, i.
Statistical analysis was obtained in R (version 3. 3. 1, https://www. r-project. org/) using standard packages (e. g. stats, base, utils) as well as limma (v. 3. 28, https://www. bioconductor. org/packages/ release/bioc/html/limma. html) for differential abundance analysis, and ggplot (v. 2. 3, https:// ggplot2. tidyverse. org/reference/). PCoA plots were obtained by applying the prcomp method (R package stats) on centered and scaled normalized abundances. Clusters were obtained from normalized and scaled abundances, running a hierarchical clustering (using the hclust method from the R package stats) based on a Pearson correlation distance. Heatmaps were plotted using the R package pheatmap (v. 1. 0). Differential abundance analyses were performed using the R package limma (v. 3. 28). Significant bacteria were selected using an absolute log2 Foldchange of 1 and an adjusted p-value (FDR) of 0.
05. The samples from Italy Bangladesh were analysed in the QIIME2 package (v. 2018. 8)  [60] , using Greengenes v13. 8 as the reference database. Greengenes 97% similarity set was used. OTUs were picked using the default parameters and the "-enable_rev_strand_match" option. Data was rarefied for even depth after reviewing the OUT table. The quality filter was set to 30 (quality-filter module) and deblur was used for denoising the reads. Sklearn (https:// scikit-learn. org/stable/) was used for the taxonomy classification. The Naive Bayes classifier was trained on the targeted 16S region of the 99_otus Greengenes dataset (extracted using the primer sequences (see above) and the feature-classifier extract-reads module).
Acknowledgments We would like to acknowledge  FIND  ( Foundation for Innovative New Diagnostics, Geneva, Switzerland ) for providing sputum samples and  Dr. Alexandre Harari  for initial discussions. The investigators at the  National Institute for Infectious Diseases "L. Spallanzani"-IRCCS, Rome, Italy , are grateful to all the patients, nurses (in particular  Sara Pantanella ,  Daniela Milordo ,  Lorella Tinari ,  Luciana Dell 'Arciprete) and physicians who helped to conduct this study.
Study Population The study population was composed of 185 patients with SCD divided into 2 subcohorts: Brazilian patients who underwent HCT from an identical sibling donor or were not submitted to HCT and patients who underwent related or unrelated HCT from an HLA-identical or -nonidentical donor in transplantation centers reporting to the European Society for Blood and Marrow Transplantation (EBMT). In Brazil, all patients were followed at the University Hospital of Ribeirão Preto and had HLA data available or DNA samples stored for performing HLA typing. One patient had 2 siblings and another patient had 1 sibling in the same cohort. Siblings were excluded from HLA allele frequency estimation. In the EBMT cohort, all patients had HLA typing available, in intermediate or high resolution.
Alleles and Haplotype Estimation For the Brazilian patients, because HLA typing was in intermediate resolution, we decodified National Marrow Donor Program (NMDP) codes using the multiple allele code (MAC) service from the NMDP (https://hml. nmdp. org/MacUI/) and estimated alleles based on previously described allele frequencies  [16, 20]. In some cases, the allele was estimated together with haplotype estimation. Hardy-Weinberg equilibrium (HWE) for loci and allele frequencies was assessed using PyPOP software  [21]. We compared allele frequencies found in our population with the African American population described in the NMDP  [16]. Haplotype estimation (HLA-A, -B and -DRB1 loci) was done using HaploStats (https://www. haplostats. org/haplostats?exe cution=e2s1). Haplostats performs haplotype estimation based on the expectationmaximization (EM) algorithm  [22].
In brief, the EM algorithm contains 2 phases: expectation (E), in which the probability of each haplotype is calculated based on the current haplotype estimates, and maximization (M), in which the results of the E phase are used to update the haplotype frequency estimates, yielding a new estimate. The E and M phases are repeated until they meet a convergence criterion  [22, 23]. The HaploStats database contains information from the NMDP registry on HLA haplotype frequency for the following ethnic groups: Caucasian, African American, Asian, Hispanic, and Native American. Based on the described haplotype frequency for each ethnic group, we defined the most likely ethnicity of each estimated haplotype as described elsewhere  [24] ; some haplotypes are described at high frequencies, defined as 1/1000 22 , in all populations and were defined as "common.
Haplotype Ethnicity and Donor Search Among the 27 Brazilian patients with 5 or more potential allelic donors, 17 patients had at least 1 common haplotype, 8 had an African American haplotype, 3 had a Caucasian haplotype, and 4 had an Amerindian haplotype. Conversely, among the 57 patients with no donors available, 37 patients had at least 1 African American haplotype, 9 had an Amerindian haplotype, 8 had a Caucasian haplotype, and only 5 had a common haplotype. In the EBMT cohort, among the 9 patients with 5 or more potential allelic donors, 3 had an African American haplotype, 3 had a Caucasian haplotype, 2 had a common haplotype, and 2 had an Amerindian haplotype. Interestingly, the 2 patients with an Amerindian haplotype had 32 and 12 potential allelic donors in the REDOME database, respectively; 1 patient had a donor in the NMDP, and none had donors in other registries.
Among the patients without a donor (n = 34), 22 carried at least 1 African American haplotype; 20 of these patients had 2 African American haplotypes. Two patients had an Amerindian haplotype. The 2 patients who carried the never-described haplotypes were also in the group with no donors. Furthermore, considering the 10 patients who underwent matched unrelated HCT, 9 had exclusively African American haplotypes; however, in all these cases, the haplotypes were frequently described in the HaploStats database.
ACKNOWLEDGMENTS This work was supported by the  Centre Scientifique de Monaco  and by the  Brazilian Coordination for the Improvement of Higher Education Personnel (CAPES). The authors thank the  Centre Scientifique de Monaco ,  CAPES , the  EBMT Pediatric Diseases Working Party , all patients and their families. The authors also thank the following centers: Austria:  St Anna Kinderspital, Vienna; Belgium: Children's University Hospital, Brussels ;  Cliniques Universitaires St. Luc, Brussels; Brazil: Hospital das Clinicas da Faculdade de Medicina de Ribeirão Preto ,  Ribeirão Preto ;  Canada: Centre Hospitalier Universitaire St Justine, Montr eal; University Hospital, Leuven; United Kingdom: St Mary's Hospital, London; Birmingham Children's Hospital, Birmingham; France: Hôpital Saint Louis, Paris; Hôpital Necker, Paris; Nouvel Hôpital Civil, Strasbourg; Hôpital Jeane de Flandre, Lille; Germany: Universitaetsklinikum Muenster, Muenster; Klinikum der Johann-Wolfgang Goethe Universitaet, Frankfurt; Italy: Clinica di Oncoematologia Pediatrica, Padova; Azienda Ospedaliero Universitaria, Bologna; Clinica Pediatrica Universit a di Milano Bicocca, Monza; Ospedale Infantile Regina Margherita, Torino ;  Centro Trapianti di Midollo Osseo, Cagliari ;  Fondazione IRCCS Policlinico San Matteo , Pavia; The Netherlands:  Leiden University Hospital, Leiden; Spain: Hospital Vall d'Hebron, Barcelona; Turkey: Acibadem University Atakent Hospital, Istanbul.
In context of double ICI treatments, so far, the results in NSCLC are disappointing. The randomized phase III Checkmate 227 (NCT02477826) trial (nivolumab-ipilimumab) demonstrated prolonged 2-year OS compared to chemotherapy alone, independent of PD-L1 expression  [17] , albeit with a comparator arm (platinum doublet chemotherapy) which is now considered inferior  [18]. On the other hand, the phase III MYSTIC (NCT02453282) and NEP-TUNE (NCT02542293) trials (both durvalumabtremelimumab) were reported negative for their primary endpoints  [19, 20]. One option to improve OS is the addition of radiotherapy to ICI, as radiation might act synergistically with ICI on the immune system  [21] [22] [23]. The added value of ICI has already been shown in stage III NSCLC, in which adjuvant durvalumab after concurrent chemoradiotherapy in patients with good PS resulted in an improved median PFS and OS, as well as an improved 3-year survival (66.
3% versus 43. 5%)  [24, 25]. In stage IV NSCLC, early signals of efficacy have been observed. Albeit negative in the intention to treat population, the PEMBRO-RT phase II trial (NCT02492568) showed that combining pembrolizumab with stereotactic ablative radiotherapy (SABR) significantly increased the OS (12 months: 55% vs 36%, 18 months: 48% vs 28%) of PD-L1-negative NSCLC patients without increasing toxicity compared to pembrolizumab alone  [26]. As the combination of radiotherapy and ICI still does not result in long-term benefit for most patients, the addition of new immunotherapy modalities to radiation should be explored. Based on personal communication, we know that L19-interleukin 2 (IL2) (darleukin; 15 MIO IU) has shown promising results in a phase I trial (NCT02086721) when combined with SABR in oligometastatic cancer patients.