dataesr/scientific-paragraphs-categorization huggingface dataset:
RESULTS A total of 3113 patients with IE admitted to 156 hospitals in 40 countries were included in the EURO-ENDO registry (3 patients were excluded from the initial population), of whom 267 (8. 6%) had recurrent IE and 2839 (91. 4%) a first episode of IE. Overall, 214 recurrent IE patients (79. 3%) were from ESC-affiliated countries and 53 patients (20. 6%) were from outside Europe (non-ESC countries); among these, reinfections and relapses were observed in 212 (79. 4%) and 55 (20. 6%) patients, respectively (Supplemental Table  1 ). Demographic, clinical, echocardiographic, and microbiological data of the study population are reported in Table  1.
Reinfection vs relapse (Table 1) Among patients with episodes of IE recurrence, 79. 4% (n=212) were reinfection and 20. 6% (n=55) relapse. No differences in anamnestic data were recorded, except for an increased rate of valvular intervention in patients with reinfection (71. 7% vs 58. 2%; P= 0. 054). Patients with relapses had a similar incidence of heart failure but higher BNP values than patients with reinfection.
ACKNOWLEDGEMENTS EORP  Oversight Committee ,  Registry Executive  and  Steering Committees. The Data collection was conducted by the EORP department of the ESC:  Emanuela Fiorucci , as Project Officer;  Viviane Missiamenou ,  Florian Larras , and  Rachid Mir Hassaine , as Data Managers. Statistical analyses were performed by  Cécile Laroche  of the  EURObservational Research Programme ,  European Society of Cardiology, France. Overall activities were coordinated and supervised by  Doctor Aldo P. Maggioni  (EORP Scientific Coordinator). Special thanks to the  EACVI (European Association of CardioVascular Imaging) , to the  ESC Working Group on Valvular Heart Disease  and to the  AEPEI (Association pour l'Etude et la Prévention de l'Endocardite Infectieuse)  for their support.
Data Analysis The selected CCS reads from the sequencing step were analysed with a dedicated analysis pipeline available in the Sequana project  [25] , available on https://github. com/sequana/laa. The first step consisted in mapping the CCS reads on the archetype CY genomic sequence (Genbank: AB038249. 1), which is based on the alignment program called minimap2  [26]. Then, consensus genomes were obtained for each barcode and variant calling performed using those consensus genomes. JCV genotyping was performed by phylogenetic analysis of whole genome consensus sequences (NCCR excluded). Previously published JCV genomic sequences (n=113) from all known genotypes were obtained from the GenBank database and used as reference sequences for comparisons  [27] [28] [29] [30] [31] [32] [33] [34].
The phylogenetic analysis was decomposed into a multiple alignment with mafft followed by tree construction using RAxML. A standard phylogeny was repeated 100 times from which the best tree was selected. A bootstrap analysis was included, using 100 runs. Finally, iTOL (Tree of Life) web service was used for plotting (https://itol. embl. de/). From the variant calling analysis, whole genome single mutations were filtered to keep single nucleotide variation (SNV) with a minimum depth of 10 and a minimum strand ratio of 0. 2. No filtering was applied on the frequency of the SNVs so as to investigate low-frequency variation for each sample using the Freebayes variant calling software  [35]. Missense mutations were analysed with regard to all samples of previous studies and NCBI database. Each NCCR sequence was aligned on the archetype CY NCCR (GenBank: AB038249.
Acknowledgements European Network on ME/CFS (Euromene) http:// www. eurom ene. eu/. Austria: Francisco WESTERMEIER, Monika RIEDERER; Belgium: Els TOBBACK, Mira MEEUS; Bulgaria: Evelina SHIKOVA-LEKOVA; Denmark:  Henrik NIELSEN ,  Ivan BRANDSLUND ; Finland: Olli POLO; France:  François Jérôme AUTHIER ,  Jean-Dominique DE KORWIN ;  Germany: Carmen SCHEIBENBOGEN ,  Thomas HARRER ,  Bhupesh PRUSTY ,  Patricia GRABOWSKI ,  Helma FREITAG ; Greece: Giorgos SAKKAS; Ireland: Dominic TREPEL, John CULLINAN; Italy: Lorenzo LORUSSO, Enrica CAPELLI; Latvia:  Uldis BERKIS ,  Modra MUROVSKA ,  Zaiga NORA-KRUKLE ,  Santa RASA , Angelika KRUMINA; Netherlands: Fernando ESTEVEZ LOPEZ, Ruud VERMEULEN; Norway:  Elin B STRAND ,  Anne Marit MENHSHOEL ,  Ingrid Bergliot HELLAND ; Poland: Pawel ZALEWSKI; Portugal: Nuno SEPULVEDA; Romania:  Carmen Adella SIRBU ,  Magdalena EFRIM-BUDISTEANU ; Serbia: Slobodan SEKU-LIC, Maia VUKADINOVIC; Slovenia:  Uros MARUSIC ,  Rado PISOT ; Spain:  Jesus CASTRO-MARRERO ,  Jose ALEGRE-MARTIN ,  Julia BLANCO ,  Elisa OLTRA ,  Jordi MIRO ;  Sweden: Jonas BERQUIST ,  Jonas BLOMBERG ;  United Kingdom :  Eliana LACERDA ,  Luis NACUL ,  Derek PHEBY ,  Jonathan EDWARDS ,  Xia WANG.
This result, together with the nature of the task, suggests that comprehension did not play a major role in the experimental effects. Analysis of brain lesions was carried out for LA-and LA+ by means of the MRIcron software (https://www. nitrc. org/projects/mricron; Rorden & Brett, 2007; 2011). The MRI/CT scans available for all the patients were mapped by drawing on the standard T1-weighted MRI template (ICBM152) of the Montreal Neurological Institute (MNI) coordinate system, approximately oriented to match the Talairach space  (Talairach & Tournoux, 1988). The standard template (size: 181x 217x181 mm, voxel resolution: 1 mm 2 ) was rotated on the three planes in order to match each patient's MRI/CT scan orientation as closely as possible. Then, two experienced clinicians (who were blind as to which patients the scan belonged to) traced any lesion manually on the axial slices of the rotated template, while another one checked all the drawings in a double-blind procedure.
EEG recording and analysis EEG data were acquired by means of tin electrodes embedded in a fabric cup (Electro-Cap International, Inc. ), according to the 10-10 system, from 60 scalp sites  (Spinelli et al. , 2018). The electrode on the right earlobe served as online reference, while the ground electrode was placed on AFz. A bipolar electro-oculogram was recorded from two electrodes placed on the lateral end of the bicanthal plane. The signal was recorded by a Neuroscan SynAmpsRT (Compumedics, ltd) at 1000 Hz, and filtered with a hardware band-pass of 0. 05-200 Hz. All impedances were kept below 5 KΩ. EEG traces were processed using the FieldTrip toolbox  (Oostenveld et al. , 2011; release: 20170607)  in Matlab R2016a (The MathWorks, Inc. ). For each subject, continuous EEG signals were filtered offline with a 0.
Context. Recent spectroscopic explorations of large Galactic stellar samples stars have revealed the existence of red giants with [α/Fe] ratios that are anomalously high, given their relatively young ages. Aims. We revisit the GALAH DR3 survey to look for both dwarf and giant stars with extreme [α/Fe] ratios, that is, the upper 1% in the [α/Fe]-[Fe/H] plane over the range in [Fe/H] between -1. 1 and +0. 4 dex. We refer to these outliers as "exαfe" stars. Methods. We used the GALAH DR3 data along with their value-added catalog to trace the properties (chemical abundances, masses, ages, and kinematics) of the exαfe stars. We applied strict criteria to the quality of the determination of the stellar parameters, abundances, and age determinations to select our sample of single stars. We investigated the effects of secular stellar evolution and the magnitude limitations of the GALAH survey to understand the mass and metallicity distributions of the sample stars.
Ages, masses, and corresponding uncertainties In this work, we consider the ages and masses provided in GALAH VAC that were obtained with the Bayesian stellar parameter estimation code BSTEP  (Sharma et al. 2018 ) using PARSEC+COLIBRI isochrones from  Marigo et al. (2017). However, to better handle the uncertainties on these two quantities, we independently computed the ages and masses of the dwarf sample with the SPInS tool  (Lebreton & Reese 2020)  which relies on pre-computed stellar models (we used the solarscaled BaSTI evolutionary tracks from  Pietrinferni et al. 2004 Pietrinferni et al. , 2006) )  and MCMC approach. The input observables used for the stars are T eff , luminosity L, log g, and [M/H] (we computed [M/H] from [Fe/H] and [α/Fe] using the formula from  Salaris & Cassisi 2005).
Importance of Li for exαFe dwarfs In Fig. 5 , we display the Li abundance (when available) vs. T eff of the exαFe and [α/Fe]-normal dwarf stars (top and bottom panels, respectively) of the main and additional samples (left and right panels, respectively). The GALAH data are color-coded as a function of age. We note the similarities between the exαFe and the [α/Fe]-normal stars. First, the highest Li abundance is similar in both cases, with A(Li) ∼ 3. 5, and it is found in the hottest (i. e. , more massive) and youngest (y-exαFe and [α/Fe]-normal) stars. Second, the Li abundance decreases with increasing stellar age and decreasing effective temperature, with the latter being a proxy for the mass. This well-known behavior has long been observed in field and open cluster dwarfs (e. g. ,  Zappala 1972; Sestito & Randich 2005).
Acknowledgements. This work was supported by the  Swiss National Science Foundation  (Project  200020-192039 PI C. C. ). We extensively used  NASA 's Astrophysics Data System Bibliographic Services and TOPCAT (Taylor 2005). We are grateful to  A. De Cia ,  N. Lagarde ,  V. Hill , and  E. Fernández Alvar  for enlightening discussions. We are thankful to the anonymous referee for the important comments.
Data collection Clinical data were collected at admission and during hospitalization, together with a previous history of heart disease, cardiovascular risk factors, and comorbidities. Transthoracic echocardiography (TTE) was performed in all cases and data obtained were collected (left and right ventricle diastolic and systolic function, size and localization of the VSD). Biological monitoring included blood gas and arterial lactate, prothrombin ratio, NT-pro-BNP, aspartate aminotransferase, alanine aminotransferase, total bilirubin and creatinine levels, and estimated glomerular filtration rate. The EuroSCORE II was calculated for all patients.
To investigate whether this protracted humoral anti-PA103 response was protective on its own, we collected sera from animals that were either protected from a secondary infection or not and uninfected/mAb treated controls mice. Sera were decomplemented and administered intraperitoneally to naive mice (Figure  5A ) before and after PA103 infection. Animals, which were either not subjected to serum transfer (data not shown) or treated with control sera, developed severe pneumonia and died within few days. In contrast, mice, which received serum from immune-(LD100-mAb166) animals survived better to PA103 infection as compared to those who received serum from non-protected-(LD0-mAb166) animals (Figures  5B  and 5C ). This result suggests that the humoral anti-PA103 response developed in animals resistant to secondary infection contributes to the protective anti-bacterial response.
Statistical analysis Statistical evaluation of differences between the experimental groups was determined by using one-way analysis of variance (ANOVA) followed by a Newman-Keuls post-test (which allows comparison of all pairs of groups). Log-rank test was used for survival analysis. Student's t-test was used for comparison between two groups and paired t-test was used when comparing the same individual before and after challenge. All tests were performed with GraphPad Prism, Version 6 for Windows (GraphPad Software Inc. , San Diego, CA, USA; www. graphpad. com). All data are presented as mean +/-standard error of the mean (SEM). A p value <0. 05 was considered significant. (A) B6 mice were treated with 100µg or 50µg of mAb166 and infected as described in Figure  1A. (B) Survival was monitored over the entire period.
aeruginosa strain PA103 (3×10 5 cfu / primary infection) and 1 hour later were treated or not with 100 µg of mAb166 via the pulmonary (airway) route. Surviving animals were challenged, 30 days later (secondary infection) by the orotracheal instillation of 40 µL of P. aeruginosa strain PA103 (3×10 5 cfu) without additional treatment. (D) Survival was monitored over the entire period. The results correspond to 6 pooled, independent experiments (n=36-72 mice per group), **: p<0. 01 with a log-rank test. (E) The bacterial load (cfu) in the broncho-alveolar lavage (BAL)and the lungs was measured 24 hours after the primary infection or after the secondary infection. The data are quoted as the mean values ± SEM. The results correspond to 4 pooled, independent experiments (n=5-15 mice per group), *: p<0.
B) Survival was monitored over the entire period. The results correspond to 3 pooled, independent experiments (n=10-36 mice per group), **: p<0. 01; ***: p<0. 001 with a log-rank test comparing with respective untreated groups. (C) Total anti-PA103 (white bars), anti-CLJ1 (black bars) or anti-PA14 (gray bars) IgG in serum was determined by ELISA at D+7 after secondary infection. The data are quoted as the mean values ± SEM. The results correspond to 3 pooled, independent experiments (n=5-10 mice per group). Supplementary Figure1: Kinetics of free and total mAb166 in the serum and the airways after PA103 infection.
Acknowledgements This work was supported by a public grant overseen by the  French National Research Agency (ANR)  as part of the  "Investissements d'Avenir" program  ( LabEx MAbImprove ,  ANR-10-LABX-53-01 ). AP is funded by a fellowship from  ANR-10-LABX-53-01. Additional fundings were provided by  Region Centre-Val-de-Loire  ( Novantinh Program ) and  C-VALO  ( Infinhitim Program ).
( B) Survival was monitored over the entire period. The results correspond to 3 pooled, independent experiments (n=10-36 mice per group), **: p<0. 01; ***: p<0. 001 with a log-rank test comparing with respective untreated groups. (C) Total anti-PA103 (white bars), anti-CLJ1 (black bars) or anti-PA14 (gray bars) IgG in serum was determined by ELISA at D+7 after secondary infection. The data are quoted as the mean values ± SEM. The results correspond to 3 pooled, independent experiments (n=5-10 mice per group). Supplementary Figure1: Kinetics of free and total mAb166 in the serum and the airways after PA103 infection.
Preparation of cryo-EM grids and data collection Purified RABV-G/RVA122 complexes at a concentration of ~200 g/ml were mixed 3:1 with 0. 12 mM (0. 03 mM final concentration) lauryl maltose neopentyl glycol (LMNG; Anatrace) and immediately frozen on 1. 2-/1. 3-m C-flat grids [Electron Microscopy Sciences (EMS)] using an FEI vitrobot Mark IV (Thermo Fisher Scientific) in 85% humidity and 4°C with a 10-s blot time. A total of 1969 micrographs were collected on a 200-keV Talos Arctica with a K2 direct electron detector (Gatan) at the Pacific Northwest Cryo-EM Center (PNCC) with pixel size of 1. 15 Å/pixel and a total dose of 26. 7 e -/Å 2. A second cryo-EM dataset of 6305 micrographs was collected with purified RABV-G/RVA122 complexes (~200 g/ml) mixed 3:1 with 0. 36 mM (0. 09 mM final concentration) LMNG and frozen on 2-/1-m C-flat grids in 85% humidity and 4°C with a 10-s blot time.
Cryo-EM data processing and model building The dataset containing RVA122/RABV-G complexes with 0. 09 mM LMNG (table  S1 ) was used for high-resolution reconstruction and model building. Recorded movies were motion-corrected and doseweighed using either cryoSPARC's own algorithm or RELION's MotionCorr2 implementation. Contrast transfer function (CTF) parameters were determined either with cryoSPARC's Patch CTF program or in RELION using CTFFIND4  (36). Particles were picked using the TOPAZ neural network picker  (37)  and processed in cryoSPARC  (38). Two-dimensional (2D) classification and 3D hetero-refinement were used to screen for particles bound to cellular membrane or micelle densities. Symmetryexpanded particles were used in a local refinement job to produce the first high-resolution map.
Fourier shell correlation curves were generated using RELION, the local resolution histogram using cryo-SPARC, and correlation coefficient graphs using Phenix. Lower-resolution cryo-EM maps of RABV-G/RVA122 complexes not bound to micelles or cellular membranes were prepared from the dataset containing complexes with 0. 03 mM LMNG. Particles were picked with TOPAZ, as above, reconstructed into an initial model in cryoSPARC with C3 symmetry, and then sorted via 3D variability analysis focusing on the fusion loops to identify particles with fusion loops in different conformations. Groups of similar particles were reconstructed with a homogeneous refinement job and C1 symmetry.
25 to 80 nM were incubated with biosensors for 300 s to measure association, followed by a 300-s incubation in kinetics buffer to measure disassociation. For measurements of RABV-G binding affinity, biosensors were incubated with unbiotinylated RABV-G ectodomain at concentrations ranging from 3. 75 to 960 nM, followed by a 300-s incubation in kinetics buffer. For measurements at pH 5. 5, all steps were performed in 0. 1 M citric acid/trisodium citrate buffer (pH 5. 5) with 0. 1% BSA and 0. 02% CHAPS. Experiments were performed in duplicate (technical replicates), and a sensor run without analyte was used as a reference. Affinity rate constants were calculated by subtracting the reference and then applying global fitting using the Octet Data Analysis HT software version 11 (ForteBio) and a 1:1 fitting model.
coli DNA polymerase I (NEB), 1 l (5 U) of E. coli ribonuclease H (NEB), and 43 l of nuclease-free water. Last, dsDNA was purified using AMPure XP (Beckman Coulter) at a ratio of 1. 8, as recommended by the manufacturer, and eluted in 20 l of nuclease-free water. The dsDNA libraries were constructed using the TruSeq DNA PCR-Free libraries prep kit (Illumina, San Diego, USA) and sequenced on Illumina NextSeq 2000 platform. The data obtained were analyzed using the Galaxy@Pasteur software  (47) : The sequences are first assembled de novo, without any reference sequence, to obtain "contigs," and then they are aligned on a reference sequence, making it possible to extract the nucleotide differences present in at least 2% of the cases (fig. S8 ).
Statistical analyses All statistical analyses were performed using GraphPad Prism version 9. 0. 0. In vivo neutralization was graphed as a cumulative Kaplan-Meier survival curve, and comparisons between groups were performed using a log-rank (Mantel-Cox) test. In vitro neutralization curves were generated by fitting data points using a variable slope and a four-parameter regression curve (best-fit method), and IC 50 values for P0 and P7 virus were compared via the unpaired t test. ELISA and flow cytometry data were analyzed using an ordinary, one-way ANOVA. Numbers of replicates per experiment are indicated in the figure legends. Experiments were represented as means ± SEM or SD, as indicated in the figure legends. P < 0. 05 was considered to be statistically significant. *P < 0. 05, **P < 0.
Acknowledgments: We thank  S. Schendel  for manuscript editing and  L. Kergoat  ( Lyssavirus Epidemiology and Neuropathology Unit, Institut Pasteur, Paris, France ) for technical assistance with virus and mouse experiments. Part of this work was performed at the  UtechS Photonic BioImaging (PBI)  platform supported by  Institut Pasteur  and by  Région Ile-de-France  (program DIM1Health). We also thank  G. M. Haustant  and  L. Lemée  ( Biomics Platform ,  C2RT ,  Institut Pasteur, Paris, France ), supported by  France Génomique  ( ANR-10-INBS-09 ), and IBISA for Illumina sequencing. Funding: This work was supported by  National Institutes of Health (NIH)  grants  5T32AI07244-36  (H. M. C. ) and  5F32AI147531-03  (H. M. C. ) and by  Swiss National Science Foundation Early Postdoc Mobility  Fellowship P2EZP3_195680 (D.
5 ) (Supplementary Tables  5  and 6 ). The haplotype, similar to the flow cytometry estimate, was anchored into pseudochromosomes using the physical map generated with high-throughput chromatin conformation capture (Hi-C) technology (144× coverage). Eventually, a reference genome of 15 pseudochromosomes (470 Mb; Fig. 1b , Extended Data Fig. 1  and Supplementary Table  7 ) was obtained with 96. 2% completeness in conserved single-copy protein-coding sequences (BUSCO v. 3 and the eudicotyledons_odb10 database). For annotation, mRNA sequencing (RNA-seq) data were aligned to the reference genome, and 31,896 putative protein-coding gene models were predicted with estimated completeness of 94. 8% (also using BUSCO; Fig. 1c  and Supplementary Tables  8 9 10 11 12 ). These results attest to the high accuracy and completeness of our lychee genome assembly.
Both K a and K s were low (<0. 05) for most alleles, indicating strong identity between allelic genes (Supplementary Fig. 12 ). However, DEAs had significantly lower K a /K s than equivalently expressed alleles (EEAs) (t-test, P value = 7. 8 × 10 -6 ), indicating that DEAs were under greater purifying selection pressure (Fig. 4c ). About 5. 7% (1,824 out of 31,896) of allelic genes evidently experienced purifying selection (K a /K s <0. 1), while 3. 7% (1,186 out of 31,896) of allelic pairs showed possible positive selection (K a /K s >1) (Supplementary Table  28 ). Compared with EEAs, the promoters, introns and 3′ and 5′ untranslated regions (3′ UTR, 5′ UTR) of DEAs had much higher SNP densities, suggesting that their differential expression may Estimates of the relationship level were obtained using KING software  29  and reflect the level of shared heterozygous or homozygous haplotype blocks.
Phased reads were assembled de novo using Canu (v. 1. 6)  33. Contigs were linked with the help of reference genome sequences using RaGOO (v. 1. 1)  44 software. Finally, 15 pairs of homologous pseudochromosomes were obtained. Afterwards, Illumina population resequencing reads from different lychee accessions were aligned to the 15 pseudochromosome pairs, with those dominated by reads from the YNW/EEMC/GXW cultivar group assigned to the HY haplotype, with the remaining haplotype being termed HH. Genome annotation. Gene model annotation. Gene models were annotated using the MAKER  45  genome annotation pipeline (v. 2. 31. 8), which integrates both ab initio gene predictions generated by AUGUSTUS  46  (v. 3. 3. 2) and SNAP  47 (v. 2013-11-29)  and homology evidence including plant protein sequences in the SwissProt database  48  (release 2018_12) as well as a de novo transcriptome assembly generated from lychee RNA-seq data using Trinity 49 (v.
2. 8. 3). For improved results, we ran the MAKER pipeline iteratively (three times in total) as recommended  45. The gene models were further refined using PASA  50 (v. 2. 3. 3). For the gene models from the two haplotypes, those models corresponding to the longest transcripts in the reference were converted to their two haplotypic sequences using GMAP (v. 2017-11-15)  51  with parameter 'n = 2'. Haplotypic gene models were considered redundant if the overlap between two gene models was over 60%, and these were subsequently removed from the final gene model list. Completeness of gene annotation. BUSCO 52 (v. 3. 0. 1) was used for evaluation of annotation completeness with the 'eudicotyledons_odb10' database. LTR annotation. LTRs were predicted using LTR_FINDER  53  (v. 1. 07) with parameters '-D 15000 -d 1000 -L 7000 -l 100 -p 20 -C -M 0.
9' and with LTRharvest 54 (v. 1. 5. 10) using parameters '-similar 90 -vic 10 -seed 20 -seqids yes -minlenltr 100 -maxlenltr 7000 -mintsd 4 -maxtsd 6'. Results from the above LTR annotation steps were integrated using LTR_retriever 55 (v. 2. 6), and LAI 56 was also evaluated. Evolutionary analyses. Gene family identification. Genome assemblies and GFF3 files for 12 species, including D. longan  57  , X. sorbifolium  58  , C. sinensis  59  , Arabidopsis thaliana  60  , Carica papaya  61  , Fragaria vesca  62  , Malus domestica  63  , Cucumis sativus  64  , Medicago sativa  65  , Vitis vinifera  6  , Solanum lycopersicum  66  and Acer yangbiense  67  , were downloaded from public databases (Supplementary Table  34 ). Protein-coding sequences from 13 species were exacted using TBtools  68  , and only the longest transcripts were retained.