dataesr/scientific-paragraphs-categorization huggingface dataset:
While the observed clinical activity of IPH4102 and its impact on QOL in SS patients is very promising, this study was not powered to provide definite conclusions on these fronts and thus these findings require further confirmation. In addition, we could not draw conclusions on the dose-response relationship as intra-patient dose-escalation took place in the majority of patients in the dose-escalation part of the study. In conclusion, this study provides preliminary encouraging evidence showing that IPH4102 could emerge as a very promising treatment option in patients with relapsed/refractory SS. Based on these results, the FDA has granted on January 17, 2019 Fast Track designation for IPH4101 in managing these patients. A phase 2 study (TELLOMAK, clinicaltrials. gov: NCT03902184) is currently underway to confirm the clinical activity in SS and evaluate the potential of IPH4102 in other T-cell malignancies that express KIR3DL2.
For phylogenetic analyses a MAFFT-alignment was generated. A distance matrix based on concatenated SNPs was calculated and plotted as dendrogram using Unweighted Pair Group Method with Arithmetic mean (UPGMA) for visualization. Results. Aligning of about 200. 000 nucleotides of 8 virus isolates associated with the pet rat outbreak revealed complete identity of six genomes, the remainder two genomes differed in as little as 3 SNPs. When comparing this dataset with four already published CPXV genomes also associated with the pet rat outbreak, again a maximum difference of 3 SNPs was found. The outbreak which lasted from 2008 till 2011 was indeed caused by a single strain which has maintained an extremely high level of clonality over 4 years. Aligning genomic sequences from four cases of feline cowpox revealed 3 identical sequences and one sequence which differed in 65 nucleotides.
A pathognomonic feature of isolates assigned to the species CPXV is the induction of hemorrhagic pocks on the chorioallantoic membrane and the formation of intracytoplasmatic A-type inclusion bodies  (Fenner, 1990). However, conducting these assays is laborious and time consuming. Therefore, attempts had been made to correlate the phenotype with the genotype of OPV species either by generation of Restriction Fragment Length Polymorphism data or by sequencing single genes, such as the hemagglutinin (HA) gene  (Ropp et al. , 1995). Both genome-based methods successfully confirmed the current species concept originally based on phenotypic characteristics. Sequencing of the HA gene had become the method of choice to assign a given OPV isolate to a species of the genus Orthopoxvirus and numerous HA sequences from various cases are available in GenBank  (Ninove et al.
, 2018). With the introduction of benchtop sequencers, enabling even small routine diagnostic laboratories to perform whole genome sequencing, sequencing of only a part of the microorganisms' genome is not a riddle anymore. Determination of drug resistances or virulence genes can be performed easily based on the same sequence dataset, as well as identification and in-silico typing and clonal assignment of the investigated strains. In this study Next Generation Sequencing (NGS) was used to re-analyze the pet rat and the feline cowpox outbreak. We determined the genomes of further strains and lesion materials and conclude that the pet rat-associated outbreak which lasted from 2008 till 2011 had been indeed caused by a unique CPXV strain. In addition, we determined genomic sequences of the 2015 Hannover outbreak in cats and conclude that hospital acquired cowpox infections had occurred in three out of four hospitalized cats.
Bioinformatics Sequences encoding the entire open reading frame (ORF) of the hemagglutinin gene of ''Old World'' OPVs were downloaded from NCBI nucleotide archive. The respective strains (n = 462) and their accession numbers are listed (Table  S1 ). For sequence clustering a Unweighted Pair Group Method with Arithmetic mean (UPGMA)-analysis was performed using software Bionumerics and visualized as Minimum-Spanning-tree (MST).
Sequence analysis The sequenced paired-end reads were mapped against chromosomes of Catus felis (RefSeq NC_018723-NC_018741) or Chlorocebus sabaeus (RefSeq NC_023642-NC_023672) in order to discard sequence reads of eukaryotic background DNA. Remaining reads were assembled de-novo with SPAdes v3. 9  (Bankevich et al. , 2012). Hence, resulting contigs were aligned against CPXV reference strain Brighton Red (RefSeq NC_003663. 2) using blastn  (Camacho et al. , 2009)  to determine their order. Afterwards, an in-house developed Python script was used to concatenate sequences into one single scaffold by resolving overlaps or creating gaps filled with Ns of a length estimated from the mapping. BWA  (Li, 2013)  was subsequently used to map the raw reads to the chromosomal contigs. Finally, Pilon  (Walker et al.
, 2014)  was applied to undo mis-assemblies, polish the sequence by correcting SNPs and small InDels, as well as to close gaps in order to obtain one continuous chromosome based on almost the complete whole genome sequence. The Genome Annotation Transfer Utility (GATU  (Tcherepanov, Ehlers & Upton, 2006) ) was used for annotation of genomes. The criteria for annotation included 90% nt similarity with CPXV strain Brighton Red. After the transfer of annotation, assigned open reading frames of all genomes were visually inspected and corrected manually, if needed. All generated genomes were deposited into NCBI GenBank as a BioProject PRJNA369073. For phylogenetic analyses, a MAFFT-alignment  (Katoh & Standley, 2013)  of all sequenced and downloaded reference virus genomes (Tables  1  and 2 ) was generated using the FFT-NS-2 algorithm and inspected and manually corrected using MEGA 6.
0, if needed. Using an in-house python script, only those positions present in all datasets were used for further calculations. Furthermore, for determining of SNP-calling, only those SNPS were used, of which within a surrounding area of 10 nucleotides no further SNPs were observed in the used dataset, and no gap in the alignment for at least one sequence was observed. A Maximum Parsimony distance matrix using the accelerated transformation (ACCTRAN) was calculated and plotted as dendrogram using R (packages Phangorn and Phytools). Bootstrap values were calculated with 1,000 replicates.
Hemagglutinin-based phylogenetic relationships of Orthopoxviruses We reconstructed the phylogeny of Old World OPVs by using sequences covering the entire ORF of the HA gene since the number of HA sequences by far exceeded those of other genes. As of June 2018, a total of 462 sequences were retrieved from Genbank and aligned. Details about the species, the year and location of isolation, the host and the length of the ORFs are given in Table  S1. A total of 152 unique sequences were identified and identical sequences were assigned common group numbers. Bayesian inference showed a consensus Minimum-Spanning-Tree (Fig. 1 ). Circle sizes are relative to the number of identical sequences and branch lengths are relative to the number of nucleotide changes. In general, all sequences of strains and isolates belonging to the species MPXV (n = 112 sequences), VARV (n = 87), CMLV (n = 39) and ECTV (n = 11) cluster closely together with little variation.
Comparison with sequences derived from GenBank In a next step, we compared our dataset with five sequences already deposited in GenBank from other pet rat-associated CPXVs  (Dabrowski et al. , 2013). A maximum difference of up to eight nucleotides was initially observed between the isolates ''HumAac09'' and ''Rat Biederstein''. These sequences had been generated  (Dabrowski et al. , 2013)  by using the Roche 454 technology which is known to produce sequencing errors especially in homopolymer regions  (Quail et al. , 2012). Visual inspection and comparison of the alignment confirmed that most differences could be attributed to homopolymer regions. As no raw reads are publically available, a re-calculation with actually available error-correction algorithms could not be performed. By ignoring those positions, strains HumKre08 and RatKre08 from a rat and its owner (Case #1) were identical to the six sequences determined here as well as with strain HumAac09 (Case #3) from a different rat owner.
The associated rat isolate ''RatAac09'' however, differed in two nucleotides as compared to the human isolate. The genetic difference of strain ''RatGer09'' (Case # 2) was determined to be of two nucleotides. By comparing this pet rat associated-dataset with sequences already published at NCBI, the closest next neighbor was determined to be strain HumGra07 (KC813510), which originates from a case of human cowpox in Graz, Austria, 2007, and differed in a total of 51 SNPs (Fig. 3 ).
Comparison with sequences derived from GenBank In order to find a possible relationship to previously reported cases of cowpox, sequences generated here were compared to genomes with identical HA sequences. A total of 201. 073 nucleotide positions could be used for evaluation. Strain ''CPXV S2216/04'' which was isolated from a cat in 2004 in the same region, differed in 96 SNPs and strains CPXV ''K779 UK2000'' and ''CPXV 75/1'' differed in 108 nucleotides.
, 2017; Franke et al. , 2017). Creating and updating reliable databases of orthopoxvirus genomes would even allow a better understanding of genetic diversity and clonality. In combination with new sequencing technologies, this knowledge might help to be prepared for future orthopoxvirus outbreaks of MPXV or CPXV. This has already been successfully applied during the recent Ebola outbreak in West Africa: Sequences were generated on site  (Arias et al. , 2016; Quick et al. , 2016) , linked to clinical cases and enabled outbreak reconnaissance and containment of the outbreak.
Lower panels are higher magnification (8000Â) images of area shown in blue box in the corresponding upper panels (1500Â). (c) Percentage of degranulated mast cells in synovial tissues obtained from individuals with osteoarthritis (n = 5) and non-osteoarthritis (n = 5). Intact and degranulated mast cells were counted by an examiner blinded to sample group assignment. Data are mean ± s. d. **p<0. 01 by Student's ttest, and are representative of three independent experiments using independent sample sets. DOI: https://doi. org/10. 7554/eLife. 39905. 002 The following figure supplements are available for figure  1 : Wild-type + PBS Kit W-sh/W-sh + PBS Kit W-sh/W-sh + BMCMCs Mcl-1 fl/fl mast cell deficiency is known to be incompletely penetrant with the presence of residual mast cells observed in certain organs and mice  (Lilla et al.
Acknowledgements These studies were supported by:  VA RR&D Merit Review Awards I01BX002345 ,  I01RX000934 ,  I01RX000588  and  I01RX002689  to WHR. Studies at the  Cell Science Imaging Facility at Stanford  were supported in part by  ARRA  Award Number  1S10RR026780-01  from the  National Center for Research Resources (NCRR). Studies were supported by  NIH/NIAMS  grant  R01AR067145  and  NIH/ NIAID  grant  R01AI132494  to SJG. The authors would like to thank  Mariola Leiberbasch  and  Phillip Starkl  for their technical assistance,  John Perrino  at the  Cell Science Imaging Facility at Stanford  for technical guidance and performance of the electron microscopy studies.
e HIV and syphilis status was determined retrospectively on stored samples using the VIKIA HIV 1/2 test (Biomérieux, France) and the RPR-Nosticon II (Biomérieux, France) and TPHA (Biorad, France) tests, respectively. ese analyses aimed to exclude individuals with interfering parameters for CSF analysis. Children under 12 years were also excluded to avoid complications in obtaining lumbar puncture samples and also possible difficulties in interpretation  [41, 42]. For our analysis of neopterin and CXCL-13, we selected 83 patients for whom we had maximum of neopterin and CXCL-13 CSF concentrations data. When the concentration data were missing and we had CSF samples available in the biobank, we determined the neopterin and CXCL-13 concentration in the CSF via ELISA. e ELISA kits for the dosage of neopterin and CXCL-13 used are the same throughout the study  [42].
Parasitological examination of CSF was done using the modified single centrifugation technique. is optimized parasitological confirmation method permits sensitivity of parasite detection similar to that of molecular testing  [42, 43]. All plasma, buffy coat, and CSF samples that remained after the diagnostic procedures were aliquoted and stored in liquid nitrogen before being transported to Limoges on dry ice and then stored at -80 °C. Patient medical data were anonymized. Samples were further selected for neopterin and CXCL-13 determination at diagnosis  [42].
Test Procedures. Commercially available ELISA assays were used to measure CSF levels of neopterin (Brahms, ermo Fisher Scientific, Germany) and CXCL-13 (R&D Systems, UK, and RayBiotech, GA, USA) as performed previously by Tiberti et al. [36, 37]. All assays were performed according to the manufacturer's instructions and the interassay variability was evaluated using quality controls (coefficient of variation (CV) < 20%). A limit of detection corresponding to the mean concentration measured for the lowest standard less than 2 standard deviations was calculated for each assay. All data were obtained using the same ELISA assays than previous authors and data were compared to those obtained by Tiberti et al. [36, 37].
Quantification and statistical analysis Statistical analyses were performed using GraphPad Prism 7 (GraphPad Software). Data were presented as means ±SD or ± SEM and differences were considered statistically significant when P < 0. 05. More in details, for experiments where there are only two groups a T test was applied, for experiments including more groups and/or more time points an ANOVA multivariate analysis was performed accompanied by a post-hoc modification test as described in Figure  legends.
Results The VEGFC/VEGFR3 pathway is upregulated in CRC and positively correlates with LV and macrophage density To investigate the involvement of the VEGFC/VEGFR3 pathway in CRC onset, we took advantage of the Gene Expression Across Normal and Tumor tissue (GENT) database (http://medicalgenome. kribb. re. kr/GENT/search/search. php). Gene expression profiles of more than 200 non-metastatic CRC patients were analyzed for the expression of both VEGFC and VEGFR3 as a function of the tumor stage. As shown in Fig. 1A  and B , both VEGFC and VEGFR3 were up-regulated in mucosal extracts of CRC patients, when compared to healthy control tissues, while the other lymphangiogenic growth factor VEGFD showed levels comparable to healthy colon tissue (Supplementary Fig. S1A ). This was confirmed at the protein level on tumoral and healthy mucosal biopsies (Fig.
S1C ) and both LV (Supplementary Fig. S1D ) and TAM density (Supplementary Fig. S1E ) was significantly increased in the colon of tumor-bearing mice. Notably, we confirmed not only the presence of VEGFR3 on murine CRC-associated LVs and TAMs (Supplementary Fig. S1F-H ), but also its upregulation by FACS in both murine LECs (Supplementary Fig. S1I ) and TAMs (Supplementary Fig. S1J ). Since VEGFR3 could also be expressed by blood vessels during tumor angiogenesis we analyzed by FACS the expression of VEGFR3 on CD31+Pdpn-cells. Blood endothelial cells (BECs) were found negative for VEGFR3 both in human (Supplementary Fig. S1K ) and mouse tissues (Supplementary Fig. S1L ). Collectively, these data demonstrate that the VEGFC/VEGFR3 pathway is upregulated in both human and murine non-metastatic CRC and that this positively correlates with active lymphangiogenesis and TAM abundance.
Acknowledgments We thank  Ron Haskell  ( ViraQuest Inc. ) for his expert technical assistance with adenovirus preparation. Dr. Bronislaw Pytowski  ( Eli Lilly ) provided the VEGFR3 blocking Ab mF431C1. Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Author Manuscript Published OnlineFirst on June 25, 2019; DOI:  10. 1158/0008-5472. CAN-18-3657 on August 1, 2019. © 2019  American Association for Cancer Research. cancerres. aacrjournals. orgDownloaded from Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Author Manuscript Published OnlineFirst on June 25, 2019; DOI:  10. 1158/0008-5472. CAN-18-3657 on August 1, 2019. © 2019  American Association for Cancer Research. cancerres. aacrjournals.
OLGA is powered by an efficient dynamic programming method to exactly sum over generative events and obtain net probabilities of amino acid sequences and motifs. We validate our algorithm by comparing its results and performance to Monte-Carlo sampling estimates. We present results using publicly available data for both TCR α (TRA, Pogorelyy et al. [28] ) and β (TRB, Robins et al. [33] ) chains and BCR heavy chains (IGH, DeWitt et al. [3]  of humans), and TRB of mice  [35]. We applied OLGA to a TCR database that catalogs the different CDR3 amino acid sequences responding to a variety of different epitopes associated with disease  [37]. We computed the generation probability of particular CDR3 amino acid sequences, as well as the net generation probability of all the TCR that respond to a particular epitope.
B. Dynamic programming computation of the generation probability of amino acid sequences We now give an overview of how OLGA computes Eq. 2 without performing the sum explicitly, using dynamic programming. Fig. S1 -S2 give a graphical overview of the method, and details of the method implementation can be found in SI Secs. I and II and in the code manual. Given the genomic nucleotide sequences of the possible gene templates, together with a specific model of the type described in Eq. A1, the algorithm computes the net probability of generating a recombined gene with a given CDR3 amino acid sequence under a given set of V and J gene choices. Each recombination event implies an annotation of the CDR3 sequence, assigning a different origin to each nucleotide (V, N1, D, N2, or J, where N1 and N2 are the VD and DJ insertion segments, respectively) that parses the sequence into 5 contiguous segments (see schematic in Fig.
In practice, to determine the generation probability of a typical sequence (which can be as low 10 -20 , see Fig. 3  and below), one needs to generate very large datasets, and thus the generation probability of many sequences cannot be calculated by the MC method. Alternatively, one could list all possible nucleotide sequences that translate to a particular amino acid CDR3 and sum the generation probabilities of each nucleotide sequence, using the IGoR algorithm  [25]. Each amino acid sequence in the mouse validation sample is, on average, coded for by 1. 84 billion nucleotide sequences (and much more for human TRB). Since IGoR computes generation probabilities of nucleotide sequences at the rate of ∼ 60 seqs/CPU/sec, it would take ∼ 8500 CPU hrs to compute the generation probability of a single amino acid sequence.
While all these datasets are based on DNA RepSeq, we checked that the generation probability distribution was robust to the choice of protocol by computing the TRB distribution for independent datasets generated by RNA RepSeq  [38, 44, 47]  (Figs. S6 and S7, and SI Sec. V). The generation models used here and elsewhere in this paper were taken from Marcou et al. [25] , except for the human TRB model which was relearned using IGoR from one individual in Emerson et al. [9]  as a check. Going from recombination events to nucleotide sequences to amino acid sequences leads to substantial shifts in the distribution, and corresponding drops in entropies, as the distribution is progressively coarse-grained. Higher generation probability of a given receptor sequence leads to higher chance of finding it in any given individual.
E. Generation probability of specific TCR We can use OLGA to assess the total fraction of the generated repertoire that is specific to any given epitope, simply by summing the generation probabilities of all TRB sequences known to bind specifically to that epitope: P func gen (epitope) = a | epitope P aa gen (a), (7) where "a | epitope" means that the amino acid sequence a recognizes the epitope. Many experiments, based e. g. on multimer sorting assays  [2, 14]  or T-cell culture assays, have established lists of epitope-specific TCR sequences for a number of disease-related epitopes. We used the VDJdb database  [37] , which aggregates such experiments, to compute P func gen of all TRB known to be reactive against several epitopes. In Fig. 4  we show results for 4 epitopes associated with Hepatitis C, and 5 epitopes associated with Influenza A.
F. Model accurately predicts the frequencies of sequences and of groups of specific sequences To compare OLGA's predictions with sequence occurrence frequencies in real data, we used the aggregated TRB repertoire of 658 human subjects described in Emerson et al. [9]  as a test resource. More specifi- cally, we measured the frequencies in this large dataset of the specific CDR3 sequences contained in the VDJdb database  [37] , and compared them to the values assigned by OLGA. When measuring frequencies we discarded read count information, recording only the presence or absence of nucleotide sequences in each individual in order to eliminate effects of clonal expansion and PCR amplification bias, averaging over the 648 individuals in the Emerson et al. [9]  dataset to get reliable estimates of frequencies.
Each sequence in the VDJdb database is displayed as a dot in Fig. 6 , and the resulting distribution shows a strong correspondence between mean frequency in the large data set and the predicted P aa gen of that sequence. We then measured the fraction of CDR3s in the aggregated repertoire that is specific to epitopes associated with 6 viruses (using lists of specific sequences in VD-Jdb), and compared it to OLGA's prediction, P func gen. The agreement was again excellent (triangles in Fig. 6 ). Again we observe that most epitope-specific sequence groups have large enough frequencies to be found in any individual. Thus, the model can be used to predict the size of repertoire subsets specific to any epitope, as long as specificity data are available for this epitope.
OLGA can be used to compute baseline receptor frequencies and to identify outlying sequences in repertoire sequencing datasets. In Elhanati et al. [8]  we used it to shed light on the question of public repertoirescomposed of sequences shared by many individualsand predict quantitatively its origin by convergent recombination  [23, 24, 41]. Deviations from the baseline expectancy have been used to identify disease-associated TCR from cohorts of patients  [9, 10, 12, 34, 48] , and to identify clusters of reactive TCRs from tetramer experiments  [14]  and vaccination studies  [30]. Such estimates could be made faster and more reliable by OLGA, especially for rare sequences, and without the need for a negative control cohort  [29]. In the future, OLGA could be useful in vaccine and therapy design by focusing atten-tion on clonotypes that are likely to be present in every individual.
We applied OLGA to an experimental database of TCR responding to a variety of disease-associated epitopes. These selected TCR do not differ in their generation probabilities from those of random TCR found in the blood of healthy donors. However, some viral epitopes bind a much larger fraction of the repertoire than others. This observation has potentially important consequences for vaccine design. Since vaccine epitopes stimulate TCR in a pre-existing repertoire, epitopes targeting receptor sequences that are more likely to be generated will have a higher success rate in a wider range of individuals. OLGA can be used to identify such epitopes by computing their specific repertoire fractions, P func gen. While our examples are restricted to TCR, OLGA can also handle BCR and could be used to compute the generation probabilities of BCR precursors of highly reactive or broadly neutralizing antibodies, and thus guide vaccine design in that case as well.