dataesr/scientific-paragraphs-categorization huggingface dataset:
g-h The relative amounts of cell-associated genomic and antigenomic viral RNA were determined by RT-qPCR analysis at 12 and 24 hpi. Amounts of viral RNA were expressed as genome equivalents (Geq) or antigenome equivalents (AGeq) per microgram of total cellular RNA. Statistical analysis: Two-way ANOVA with post hoc Sidak's test (n. s. not significant; *p < 0. 05; ****p < 0. 0001). Experiments were performed once in triplicate (N = 1, n = 3) or three times in triplicate (N = 3, n = 3) and are represented as means ± SD. Dashed lines indicate the limit of detection. compared to YF-FNV, both at 12 and 24 hpi (Fig. 3f ). These data suggest that for FNV background, genetic diversity promotes neuroinvasiveness. FNV-N2 replicated in endothelial cells with a similar efficiency than YF-FNV, both producing around 2 × 10 5 copies of genomic viral RNA and 6 × 10 3 copies of minus strand RNA, per μg of total RNA at 24 hpi (Fig.
RNA extraction and RT-qPCR analysis Total RNAs were extracted from cell lysates using the NucleoSpin RNA plus kit (Macherey-Nagel, #740984). Total cDNA synthesis was performed with an equal amount of purified RNA (0. 25 μg) using the SuperScript III reverse transcriptase (Invitrogen, #18080044). Random primers (Roche, #110347310 01) were used for the detection of positive-sense RNA and an NS5-specific primer (YF-NS5-AntiG 5′-GGCGGTGAGTGAGACGAC-3′) was used for the quantification of the viral negative-strand (or antigenome). Quantitative real-time PCR was performed on a real-time PCR system (QuantStudio 6 Flex, Applied Biosystems) with SYBR Green PCR Master Mix (Thermofisher Scientific, #4367659). Data were analyzed with the ΔΔCT method, with all samples normalized to GAPDH. Primers used in this study were: GAPDH (GGTCGGAGT CAACGGATTTG and ACTCCACGACGTACTCAGCG) and YF-NS5 (ATGGCAGGA GGATTGTGGTG and GTTGTGCGTCCTTGTGGAAC).
Sequence analyses and comparison of diversity of viral subpopulations The analysis was performed using the CLC Genomics Workbench software version 8. 5 (CLC bio-Qiagen, #832022). The analytical pipeline consists in quality control of the run, trimming of low-quality reads, reads assembly on the target reference genome of YF-FNV or YFV-17D (respectively, Genbank MG51218. 1 and MG051217. 1) and low frequency variant calling. All algorithms are proprietary of CLC Genomics Workbench and are described in the user manual (chapters 25 to 29). As expected for short viral genomes, a high sequencing depth was obtained. The parameters used at each step were selected to maximize stringency (Supplementary Note 1). The complete set of NGS data has been filed to the NCBI SRA database under the PRJNA675082 accession number.
ACKNOWLEDGEMENTS We thank  Anaelle Da Costa de Matos  for sharing her expertize on mBBB. We are indebted to  Nathalie Pardigon  for the gift of the original YF-FNV vaccine strain. We thank  Jérémy Pontvianne ,  Yves Girerd-Chambaz , and  Maryline Bouteille  for their expertize in sequencing and variant analysis. We acknowledge  Anne-Gaëlle Darmont ,  Florence Boudet , and  Bachra Rokbi  for critical reading of the manuscript and their helpful comments. We thank  Lucie Danet  and  Sarah Lesage  for their assistance in virological assays. We thank the  Association Nationale de la Recherche et de la Technologie  ( CIFRE 2017/0314 ),  Sanofi-Pasteur and Institut Pasteur  for funding.
Material and Methods 2. 1. Patients 2. 1. 1. HEGP Cohort 80 patients with histologically proven gastric or esogastric junction adenocarcinoma treated in the Gastro-intestinal Oncology unit of Georges Pompidou European Hospital (Pr. J. Taieb) were included from January 2016 to July 2020. The study was approved by the local ethics committee (Comité de Protection des Personnes d'Ile-de-France 04/09/2014). Oral and written information was provided, and each patient signed a written consent prior to enrolment. For each patient, a blood sample was collected before or throughout planned treatment. Clinical and pathological data were obtained from medical records. Patients' characteristics at the time of blood collection are presented in Table  1. Patients with autoimmune diseases or receiving targeted therapies or monoclonal antibodies (such as trastuzumab and ramucirumab) were excluded.
Peripheral Blood Mononuclear cells (PBMCs) were isolated from peripheral blood on Ficoll-Hypaque gradients, Treg staining was performed on fresh PBMCs and analyzed by flow cytometry (see the corresponding paragraph). The assessment of circulating immune cells was planned in the initial design of the study. The final analysis presented hereby included 64 patients for whom data on circulating Treg were available both on day 1 and day 28. Specific informed consent was required for each patient. The trial was registered with the US and French health registries (NCT01443065, EudraCT No. 2009-012797-12). The study protocol has been approved by a French national ethics committee.
1); CD1c (clone: L161); CD4 (clone: OKT4) (all purchased at Biolegend, USA); Ki-67 (clone: MOPC-21) purchased at BD Pharmingen (Franklin Lakes, NJ, USA); cMet APC (clone: 95106) purchased at R&D Systems (Minneapolis, MN, USA). Intracellular staining was performed using Foxp3/transcription factor staining buffer set (ThermoFisher Scientific) according to manufacturer's recommendations. Cell viability was assessed using the LIVE/DEAD fixable dead stain kit (Thermo Fisher Scientific). Samples were run through a LSRII flow cytometer or Fortessa ×20 (BD Biosciences, Franklin Lakes, NJ, USA) using DIVA ® software (BD Biosciences, Franklin Lakes, NJ, USA). Analysis were performed using FlowJo ® software (Flow Jo, Ashland, OR, USA). Dead cells and doublet cells were excluded from the analysis. Isotype controls and fluorescence minus one controls were used as negative controls.
Statistical Analyses Results are presented as mean and Standard Error of the Mean (SEM). All statistical analyses were performed with GraphPad Prism ® software (GraphPad Software, San Diego, CA, USA). Comparisons were performed with Wilcoxon, Mann Whitney, or Kruskal Wallis test, as appropriate. Overall survival (OS) was defined as the time from randomization to death by any cause. OS was estimated by the Kaplan-Meier method. Univariate analysis was performed using a proportional hazard model to estimate the hazard ratio. Comparisons were performed using the log-rank test. A p-value < 0. 05 was considered statistically significant. All statistical tests were two-sided.
Considering our results, Treg drop could be attributable to c-Met/HGF and/or VEGF/VEGFR inhibition in this context. Associations of cabozantinib with different immunotherapies are being evaluated in different clinical trials especially in GC patients (NCT04164979, NCT03539822). Recently, an association of cabozantinib with nivolumab has been reported to enhance OS and PFS in advanced renal cancer patients  [45]  and has been approved as first-line treatment in advanced renal cancer patients  [46].
Acknowledgments: We thank The  William Stamps Farish Fund  and  Novartis  for support to M. K. and  R. M. G. During  the writing of this article, J. Z. K. was supported by "Kościuszko" grant #  508/2017/DA  from the  Polish Ministry of National Defense. Some of the images used to make figures were from the  Servier Medical ART: SMART , smart. servier. com.
, 2019). Overall, 88. 8% of isolates were MenB, 4. 7% were MenY, 1. 6% were MenA, 1. 6% were MenC, and 1. 6% were MenW  (Brik et al. , 2019). Findings from an analysis of the level of expression of fHbp by enzyme-linked immunosorbent assay suggested that 92. 4% of MenB isolates were expected to be killed by anti-fHbp antibodies  (Brik et al. , 2019). One obstacle to obtaining a clear representation of IMD in North Africa is identifying national and comprehensive databases clearly attributing disease to N. meningitidis. Moreover, a standardized and common case definition across countries, essential for making reliable comparisons across countries and for improving diagnosis, is lacking. Current surveillance systems often rely on clinical reporting that defines cases based on meningitis rather than IMD.
meningitidis. Therefore, implementing molecular diagnostic techniques, coupled with properly trained laboratory personnel, should greatly improve the accuracy of available datasets, allowing development of effective health strategies to prevent IMD in North Africa. From the limited available data, N. meningitidis appears to be one of the most common causes of bacterial meningitis across North Africa. It was identified as the second or third most frequent cause of bacterial meningitis cases in Tunisia, following S. pneumoniae and H. influenzae  (Saguer et al. , 2016; Sfaihi et al. , 2014). Studies from Egypt identified N. meningitidis as the most common pathogen causing meningitis and had the highest CFR compared with other pathogens  (Mobarak, 2012; Farag et al. , 2005). Importantly, MenB was the most frequent serogroup among IMD isolates in North Africa, yet considerable genetic heterogeneity exists across the region.
Kaplan-Meier method was used to estimate the distribution of TTFT and OS. Comparisons among patient subgroups were performed with the Log-rank test. The concordance statistic (C-index) was calculated to assess the accuracy of CBA and GM for predicting TTFT and OS. Multivariate analysis using Cox proportional hazards regression model was used to assess the maintenance of the independent prognostic impact on TTFT and OS. Statistical analyses were performed using SPSS v. 23 software (SPSS Inc, Chicago, IL, USA) and R v3. 5. 2. Pvalues <0. 05 were considered statistically significant.
Discussion In recent years, there has been a rising interest in identifying CLL patients with CK since they may pursue a more aggressive clinical course and respond less well to treatment. 2, 4, 28 Large cooperative studies within the ERIC have demonstrated that five abnormalities is the optimal cut-off which better predicts an impaired outcome by both CBA and GM. 5, 25 However, data comparing the risk stratification based on genomic complexity by both methods in the same patients are scarce. Indeed, a small cohort of 122 patients from Leeksma et al study was analyzed by GM and CBA, but the proportion of CK cases was very low, as expected in an unselected CLL population. To the best of our knowledge, the present study is the largest report conducted to date in which a cohort of CLL patients enriched in CK cases has been simultaneously analyzed by CBA and GM, comparing the usefulness of both methods in their prognostic stratification.
TABLES were assessed on DNA from whole PB (n=113; 33%), PB mononuclear cells (n=63; 19%), PB CD19+ purified cells (n=110; 32%) or from BM samples (n=54; 16%). Only DNA that fulfilled quality controls required was amplified, labelled and hybridized to different genomic microarray platforms according to the manufacturer's protocols. Obtained data were visually revised and copy number variants found as benign polymorphisms in the Database of Genomic Variants (http://dgv. tcag. ca/dgv/app/home) were excluded. For defining genome coordinates, annotations of genome version GRCh37/hg19 were used. Chromothripsis-like and chromothripsis patterns were defined by the presence of ≥7 and ≥10 oscillating switches, respectively, between two or three copy number states on an individual chromosome. 7, 8, 15 though the objectives of the study did not consider the analysis of copy-number neutral loss of heterozygosity (CN-LOH), in those cases in which the microarray platform included single nucleotide polymorphisms (SNP) probes, a global screening for CN-LOH was performed.
IGHV mutational analysis IGHV mutational status was analyzed in 307 (90. 3%) patients following established international guidelines. 17 Sequences were examined and interpreted using the IMGT database and the IMGT/V-QUEST tool. Clonotypic IGHV gene sequences with <98% germline identity were defined as mutated (M-IGHV) whereas those with ≥98% identity were classified as unmutated (U-IGHV).
Acknowledgements The authors would like to thank  Idoya Ancín ,  Andrea Campeny ,  María Dolores García-Malo ,  Alberto Valiente ,  Marco Moro ,  Gonzalo Blanco ,  Ferran Nadeu  and  Julio Delgado  for their contribution to the study providing patients samples and data and the  MARGenomics Platform from Institut Hospital del Mar d'Investigacions Mèdiques (Barcelona)  for performing part of the genomic microarrays. This work was partly supported by grants from  Generalitat de Catalunya  ( 17SGR437 ),  Gilead Sciences Fellowship  ( GLD17/00282 ),  Ministerio de Educación, Cultura y Deporte of Spain  ( FPU17/00361 ),  Fundación Española de Hematología y Hemoterapia  ( FEHH-Janssen ),  Instituto de Salud Carlos III/FEDER  ( PT17/0015/0011 ) and the " Xarxa de Bancs  de tumors" sponsored by  Pla Director d'Oncologia de Catalunya (XBTC).
Acknowledgements We are grateful to all collaborators that over the years contributed to work discussed in this manuscript. Some of the work mentioned in this article has been supported by a  Jeunes Chercheuses/Jeunes Chercheurs  grant from the  Agence National de la Recherche  ( ANR-16-CE15-0012-01 ) and a subvention by the  French Society of Allergology (SFA). FJ is an employee of  CNRS (Centre national de la recherche scientifique ).
A total of 535/575 (93%) of the spectra obtained were of good enough quality to be used for our analyses. Our home-made MALDI-TOF MS arthropod database was upgraded with spectra obtained from between one and five randomly selected specimens per species. For these reference specimens, molecular identification of the ticks was also made using 16S, 12S rDNA genes and the Cox1 mtDNA gene sequencing. The remaining good quality spectra were then queried against the upgraded MALDI-TOF MS database, showing that 100% were in agreement with the morphological identification, with logarithmic score values (LSVs) between 1. 813 and 2. 51. The consistency between our morphological, molecular and MALDI-TOF MS identification confirms the capability and precision of MALDI-TOF MS for tick identification.
To collect ticks from pigs, the slaughterhouse was visited (48 visits) between 6 and 9 a. m. , and visible ticks were carefully removed manually. Ticks collected from the same animal were stored in an Eppendorf vial (1. 5 ml) in 70% ethanol with a host unique identifier code. In addition, data about the host such as weight, date, origin, sex, and ectoparasite type were noted in a field book and reported on digital data sheets. Approximately 20 tick specimens were sent to prof. Horak's team at the University of Pretoria (South Africa) for morphological identification. In the DRC, the identifications made by prof. Horak's team were extrapolated to the remaining specimens, depending on whether they were collected from the same host, in order to identify them at the species level. The ticks were transferred from IRSNB (Brussels, Belgium) to the University Hospital Institute Méditerranée infection of Marseille (Marseille, France) for analysis.
In Marseille, the morphological identification of each specimen entered in the MALDI-TOF MS database was checked using a Leica EZ4 binocular microscope (Zeiss Axio Zoom. V16, Zeiss, Marly le Roi, France) and appropriate identification keys  (Apanaskevich et al. 2013; Elbl and Anastos 1966a; Matthysse and Murray 1987; Walker et al. 2000). Ticks which could not be identified using morphology nor MALDI-TOF MS by the entomological team in Marseille, including two Rhipicephalus ticks, were sent to prof. Lorenza Beati, curator of the National Tick Collection, Institute for Coastal Plain Science, Georgia Southern University, USA, for identification.
To control matrix quality, sample loading, and performance of the MALDI-TOF mass spectrometer, the matrix solution alone was used as negative control and a protein extract from laboratory-reared Amblyomma variegatum legs was used as positive control. The MALDI-TOF MS spectra obtained from the tick legs were evaluated by analysing the average spectra obtained from the four spectra of each sample tested using Flex analysis 3. 3, MALDI-Biotyper v. 3. 0. and ClinPro-tools 2. 2 software. In order to verify and select MS spectra of excellent quality (i. e. , peak intensity > 3000 arbitrary units, without smoothing and right baseline subtraction), the average spectra (main spectrum profile, MSP) obtained from the four spectra of each sample were visualised using flexAnalysis v. 3. 4 software (  Nebbak et al.
Database upgrading and blind tests The spectra obtained from the legs of one to five specimens per tick species identified morphologically and molecularly were added to our laboratory's reference spectra database, after controlling their quality, reproducibility and specificity. To create a database, MSPs reference spectra were created by combining the results of different spectra from same specimen of each species using the automated function of MALDI-Biotyper v. 3. 0 software (Bruker Daltonics). MSPs were created based on an unbiased algorithm using peak position, intensity and frequency data. Our entire database is currently not open access, although we are working to make it accessible to all researchers. However, it is available as part of collaborations with other researchers. In this context, the spectra files are available on request and transferable to any Bruker MALDI-TOF MS device.
The reference spectra created in this study are provided in Supplementary Data 1. All good quality spectra were then blind tested against the reference spectra database. The identification level was determined using the logarithmic score values (LSVs) assigned by the MALDI-Biotyper v. 3. 0 software (Bruker Daltonics)  (Yssouf et al. 2013). This value, ranging from 0 to 3, assesses the similarity between a tested spectrum and the reference spectra by comparing the position of the peaks and their intensity. The results of tick identification were considered reliable and relevant when the LSV was greater than or equal to 1. 8  (Nebbak et al. 2017. A minimum difference of 0. 2 between the best species match score and the second species match score was considered as an additional criterion for the validation of our identification  (Kumsa et al.
Molecular identification of ticks The half-ticks were incubated individually at 56 °C overnight in 180 μl of G2 lysis buffer (Qiagen, Hilden, Germany) and 20 μl of proteinase K (Qiagen), followed by extraction using the EZ1 DNA tissue kit (Qiagen) according to the manufacturer's recommendations. The 15 tick specimens whose spectra were entered in our database as well as 43 ticks with LSVs > 1. 8 and five specimens with LSVs < 1. 8 randomly selected were subjected to standard PCR, followed by sequencing using the 16s, 12s rDNA genes and the mDNA Cox1 gene  (Boyer et al. 2019; Diarra et al. 2017). The forward and reverse reads of the targeted mtDNA sequences were assembled and analysed using ChromasPro v. 1. 34 software (Technelysium, Tewantin, Australia) and submitted for analysis to the NCBI BLAST website (http:// blast.
ncbi. nlm. nih. gov). The different mtDNA gene sequences were aligned with BioEdit, and phylogenetic trees were inferred using TOPALi v. 2. 5 software (Biomathematics and Statistics Scotland, Edinburgh, UK)  (Laroche et al. 2017b ). The model Maximum Likelihood (ML) phylogenetic tree proposed default in TOPALi v. 2. 5 software was used for the construction of phylogenetic trees. Node numbers are percentages of the bootstrap values obtained by repeating 1 3 100 iterations of the analysis to generate a majority consensus tree (only those with a value equal to or greater than 80 were retained).
MALDI-TOF MS identification All 575 ticks were subjected to MALDI-TOF MS analysis. Of these, 535/575 (93%) had good-quality spectra (Fig. 2A ), including 517/530 (97. 5%) ticks collected between September 2015 and September 2016, and 18/45 (40%) of those collected in 2010. Good quality spectra obtained from the legs of 15 ticks  (5 Rh. complanatus, 4  Rh. congolensis, 3 I. cumulatimpunctatus, 2 A. exornatum and 1 A. compressum) were added to our reference database MALDI-TOF MS (Table  1 ). A comparative analysis of MS spectra for intra-species reproducibility and inter-species specificity was performed. The visualisation of two MS spectra per tick species showed perfect intra-species reproducibility and inter-species specificity (Fig. 2A ). Similarly, the dendrogram made with the MS spectra of between one and five specimens per morphologically-identified tick species showed that specimens of the same species grouped on the same branch, confirming intra-species reproducibility and inter-species specificity (Fig.
2B ). A comparison of MS spectra from male and female specimens was performed only for Rh. complanatus and Rh. congolensis species for which both sexes were available. The PCA and cluster analysis shows that there was no difference between the MS spectra of males and females (Fig. 3A , B and Supplementary Fig. 1 ). The remaining 520 good quality spectra of ticks were queried against our upgraded database. This blind test showed that 434/439 (98. 9%) Rh. complanatus, 56/56 Rh. congolensis, 9/9 I. cumulatimpunctatus, 5/5 A. compressum and 12/12 of exornatum were correctly identified by MALDI-TOF MS, with LSVs between 1. 813 and 2. 51 (Table  1 ). Thus, 99% (515/520) of the ticks which were blind tested presented a concordance with the morphological identification and were considered correctly identified.
The morphology of the five ticks which were initially morphologically identified as Rh. complanatus that were not correctly identified by MALDI-TOF MS (LSV < 1. 8) MALDI-TOF MS were rechecked, using the remaining part of the body. This revealed that one tick was in fact Hae. muhsamae and that four identical specimens belonged to another Rhipicephalus sp. , which could not be definitively identified to the species level. The spectra of these five specimens did not match any of the ticks in our MALDI-TOF MS database and had LSVs ranging from 1. 00 to 1. 327. The spectrum of Hae. muhsamae was added to the MALDI-TOF MS database. The spectrum of one Rhipicephalus sp. was also temporarily added to the database as a potential reference spectrum for the remaining Rhipicephalus sp. The blind test showed that the three other unidentified Rhipicephalus sp.
indeed matched with the spectrum of the Rhipicehalus sp. introduced in the database, with LSVs ranging from 2. 05 to 2. 22. The mean differences between the first species match scores and the second species match scores were 0. 66 ± 0. 11, 0. 62 ± 0. 10, 0. 63 ± 0. 18, 0. 86 ± 0. 15 and 0. 85 ± 0. 10 for Rh. complanatus, congolensis, I. cumulatimpunctatus, A. exornatum and A. compressum, respectively (Table  1 ). We had 100% agreement between our morphological identification and MALDI-TOF MS for the specimens tested.
Molecular identification of ticks Fifty-seven ticks, including 25 Rh. complanatus, 14 Rh. congolensis, 5 I. cumulatimpunctatus, 4 A. exornatum, 3 A. compressum, 2 Hae. muhsamae and 4 Rhipicephalus sp. , were subjected to standard PCR and sequenced using the 16s, 12s rDNA gene and the Cox1     sequence identities ranged from 85. 3 to 96. 6%, 85. 6 to 96. 8% and 86. 7 to 90. 6%, respectively, for genes 16s, 12s rDNA and Cox1 mtDNA, with the known species available on GenBank. This DNA-based approach did not allow us to identify the Rhipicephalus sp. ticks that had not been morphologically identified down to the species level. The percentage of sequence identity of these ticks was 92. 2, 93. 5 and 87. 4% with the sequences of Rh. sanguineus (KT382455), Rh. pusillus (AF150022) and Rh. sanguineus (KU364312), respectively, for genes 16s, 12s rDNA and Cox1 mtDNA (Table  2 ).