dataesr/scientific-paragraphs-categorization huggingface dataset:
As the TIL448 complete genome sequence was not available, the tryptic peptides were identified by a mass matching approach against a database including all Lactococcus protein sequences and the sequences deduced from partial DNA sequences of the TIL448 plasmids. Two surface proteins, encoded by plasmids in TIL448, were identified as candidate adhesins, the first one displaying pilin characteristics and the second one containing two mucus-binding domains. Inactivation of the pilin gene abolished adhesion to Caco-2 cells whereas inactivation of the mucus-binding protein gene had no effect on adhesion. The pilin gene is located inside a cluster of four genes encoding two other pilinlike proteins and one class-C sortase. Synthesis of pili was confirmed by immunoblotting detection of high mo-lecular weight forms of pilins associated to the cell wall as well as by electron and atomic force microscopy observations.
5 ml of 2% paraformaldehyde prepared in DPBS, washed three times with DPBS, and mounted onto a glass microscope slide with DABCO-PBS mounting medium (Fluka). Fluorescent bacteria were observed and images captured with an epifluorescence microscope (Olympus BX51, FITC filter). Ten random fields per coverslip were analyzed. Images were analyzed with the software UTHSCSA ImageTool (version 3. 00, http://ddsdx. uthscsa. edu/dig/ download. html) as previously described  (29). Microbial adhesion was estimated as the percentage of surface covered by bacteria. Adhesion Quantification by Counting Colony-Forming Units (cfus)-After the DPBS washes, Caco-2 layers were disrupted by addition of 1 ml of deionized sterile ice-cold water in each well and repeated pipetting. Serial dilutions of the suspension in PBS were plated on M17Glc agar with a spiral plater (Spiral System Inc.
The obtained tryptic peptides were purified by HPLC using a C18 column (Aquapore reverse phase RP300, 2. 1 ϫ 30 mm, 7 m, Applied Biosystem), and recovered by isocratic elution with a solution of 72/28/0. 1% (H 2 O/ACN/formic acid). They were dried using speedvacuum and then solubilized in 25 l of loading buffer: 2% ACN, 0. 08% TFA in H 2 O for LC coupled to tandem MS (LC-MS/MS) analysis. For comparative analysis, two independent biological replicates were prepared for each strain and each growth phase. Protein Identification by LC-MS/MS and Databases Searching-Tryptic peptides were analyzed by LC-MS/MS with a nanoLC Ultra system (Ultimate 3000, Dionex) connected to a LTQ-Orbitrap Discovery mass spectrometer (Thermo Fisher Scientific) located on the proteomic platform PAPPSO (INRA, Micalis, France, http://pappso.
Only the doubly and triply charged ions were subjected to the CID fragmentation step. The m/z of the fragmented precursor was excluded to the analysis during 90 s with a tolerance of 10 ppm. The raw files produced under Xcalibur were first converted in mzXML files with ReADW (http://sashimi. sourceforge. net) and in a second step, protein identification was performed with X!tandem software (X!tandem Cyclone 2011. 12. 01. 1; http://www. thegpm. org) against a Lactococcus protein database (NCBI, 54381 proteins downloaded on June, 13 th , 2012) and the six-frame translation ORFs deduced from the TIL1229 plasmid sequences obtained in this study (1854 translated protein sequences), associated to a classical proteomic contaminant database. The X!Tandem search parameters were trypsin specificity with two missed cleavages and variable oxidation states of Met.
The semi-tryptic peptide detection was included by activating the option in the data refine mode. The mass tolerance was fixed to 10 ppm for precursor ions and 0. 5 Da for fragment ions. The final search results were filtered using a multiple threshold filter applied at the protein level and consisting in the following criteria: protein log (E-value) ϭ -3 identified with a minimum of two different peptides sequences, detected with a peptide E-value lower than 0. 03. The False Discovery Rate was estimated for all samples by using a reverse database between the X!Tandem analysis to 0. 04 and 0% at the peptide and protein levels respectively. Results from X!TandemPipeline 3. 3. 0 analysis (http://pappso. inra. fr/bioinfo/xtandempipeline/) of MS/MS data are available in (supplemental Table  S4 ).
The mass-matching approach was completed by a de novo approach only for the unmatched spectra that were not used by X!tandem. The unmatched spectra were automatically translated into amino acid sequences by Pepnovo software (version 3. 1). All sequences with a Pepnovo score higher than 80 were compared by fasts36 (version 36. 2. 6) against a Lactobacillales Uniref90 database (UNIREF, 266,612 proteins) in an iterative process with the matrix MDM20. The sequences corresponding to a validated protein with an E-value lower than 0. 05 were eliminated before a next step of analysis of FASTS36. The de novo pipeline used was developed on the PAPPSO platform by Benoit Valot (http://pappso. inra. fr/bioinfo/ denovopipeline/). The detailed information on all the peptides and proteins identified in all liquid chromatography-tandem mass spectrometry (LC-MS/MS) runs were deposited online using PROTICdb database (30) at the following URL: http://moulon.
inra. fr/protic/surftil448. The putative localization of the experimentally detected proteins was predicted with the LocateP database corresponding to the four Lactococcus strains IL1403, MG1363, KF147 and SK11 (http://www. cmbi. ru. nl/locatep-db/cgi-bin/locatepdb. py). Construction of L. lactis TIL448 Mutant Derivatives-An 813-bp internal fragment of yhgE2 gene was amplified by PCR from TIL448 total DNA with primers 5Ј-AAACTGCAGCAGGTAGTGCAAATGATGG-3Ј (PstI site underlined) and 5Ј-ATATGCGGCCGCTTAAATAGCGATAC-CGAATACAGC-3Ј (NotI site underlined). The resulting fragment was cloned into the PstI and NotI restriction sites of pGhost9 plasmid vector, a thermosensitive plasmid in L. lactis  (31). The recombinant plasmid was produced in E. coli TG1repAϩ and used to transform competent L. lactis TIL448 grown at 28 °C.
Grids were examined with a Zeiss EM902 electron microscope operated at 80 kV (Carl Zeiss -France), and images were acquired with a charge-coupled device camera (Megaview III) and analyzed with ITEM Software (Eloïse, France) on the MIMA2 Platform, INRA, Jouy-en-Josas, France (www6. jouy. inra. fr/mima2). Atomic Force Microscopy (AFM)-L. lactis cells were grown to exponential phase (OD 600 of 0. 6 -0. 8) in M17Glc medium at 37 °C. Bacterial cells were harvested by low speed centrifugation (3000 ϫ g for 2 min, 4 °C) to avoid damage of the pili. Each pellet was washed twice in acetate buffer (150 mM sodium acetate, pH 4. 75) and was finally resuspended in 2 ml acetate buffer. AFM contact mode images were obtained in air at room temperature using a Nanoscope V Multimode AFM and MLCT cantilevers (Veeco Metrology Group, Santa Barbara, CA).
The tryptic peptides were then identified by a mass-matching approach against a database including all protein sequences derived from Lactococcus sequences and from the sequence data that we obtained from TIL448 plasmid partial sequencing. Also, de novo peptide sequencing followed by homology-based protein identification was performed using a home-developed de novo pipeline, to identify more distantly related proteins against a Lactobacillales protein database. A total of 81 proteins could be identified in TIL448 by mass matching (Table  II ), including 32 proteins predicted to be located at the bacterial surface by LocateP, consisting of two LPXTG-proteins, 13 lipoproteins, 13 proteins with an N-terminal transmembrane anchor, and four secreted proteins. The other identified proteins include mainly ribosomal proteins (28 sequences) and other intracellular predicted proteins most of which known as moon-lighting proteins  (32).
lactis YhgE protein identified recently as a pilin in L. lactis IL1403  (33). The second protein exhibited high sequence similarity with putative MUB-proteins (34) of Leuconostoc citreum KM20 and Lactobacillus fermentum. It contains two MucBP domains (PF06458) (positions 716 -817 and 971-1066) followed by a LPXTG motif for peptidoglycan anchoring at the C-terminal end, a N-terminal signal peptide followed by 14 Ser,Thr-rich repeated motifs of 11 amino-acids (with the following consensus sequence SSA(V,T)NA(D,E)(S,T)T-(S,G)A); also two completely identical 85-amino acid repeated sequences preceding the MucBP domains (positions 599 -683 and 880 -964) are present (supplemental Fig. S2 ). The two last proteins were identified as a peptide transport system (OppAlike) and a nisin-resistance protein respectively, but were detected by a lower number of peptides (Table  II ).
In addition, the comparative proteomic analysis that we performed on the adhesive L. lactis strain TIL448 and the non-adhesive derivative TIL1230 allowed us targeting directly proteins that are synthesized, surface-located and putative adhesins. This proteomic-based approach allowed bypassing a more fastidious and time-consuming one that would have consisted in complete sequencing of the large and not abundant plasmids of L. lactis TIL448 followed by systematic inactivation of all the genes predicted to encode surface proteins and characterization of the adhesive properties of the constructed mutants. The "shaving" approach combined with MS/MS analysis proved to be very efficient in identifying surface-exposed proteins in the adhesive L. lactis TIL448 strain. Since the whole TIL448 genomic sequence was not available to identify proteins from MS/MS data, we used a mass matching approach against a database including all protein sequences derived from Lactococcus nucleotide sequences and from the sequence data that we obtained from plasmid sequencing in this study.
4D  and Fig. 5F ). In parallel, we tested a de novo approach that can be used as a complementary one to the mass matching approach for bacterial species with nonsequenced genomes. In this way, we could increase the number of peptides detected for certain proteins, such as for Usp45, a known abundant extracellular protein  (41). Also, a few other extracellular proteins not identified by mass matching (such as YufC and XynD) were detected. Nevertheless, the plasmid-encoded proteins, YhgE2 pilin and MUB-protein, were too divergent at the amino acid sequence level, from the proteins of the same families encoded in the complete genome sequences of other L. lactis strains (only 28% sequence similarity between YhgE2 and YhgE), to be identified either by mass matching on Lactococcus sequence databases or by the de novo approach.
Acknowledgments-We thank  Veronique Monnet  and  Mireille Yvon  ( INRA, Micalis, France ) for their constant support and helpful discussions. We thank  Jean-Christophe Piard  and  Virginie Oxaran  ( INRA, Micalis, France ) for helpful discussions, Stephane Chaillou ( INRA, Micalis, France ) for precious advice for plasmid extraction and sequencing and  Francis Repoila  ( INRA, Micalis, France ) for his expert advice for RT-PCR experiments. We are indebted to  Catherine Sapin  ( Saint-Antoine Hospital, France ) for help with epithelial cell cultures. We thank  Alain Dufour  ( Universitede Quimper, France ) for the gift of plasmid pES03. We warmly thank  O. Langella  ( PAPPSO, INRA, France ) for making proteomic data accessible in the Protic database.
This initial genome-scan led to evidence of selection for loci involved in aesthetic and performance characteristics. However, many regions left uninvestigated may also harbor important information regarding polymorphisms involved in the determination of traits of significance in these breeds. Linkage disequilibrium generally breaks down within 400 kb in the horse genome  [17]. Therefore, 500 kb windows were chosen for the calculation of the d i statistic to allow for the capture of linkage blocks as well as for the inclusion of the minimum number of SNPs (4) deemed necessary to eliminate stochastic variation and calculate a robust statistic. While formal tests for extended haplotype homozygosity (EHH)  [32]  were not performed, haplotype phasing of the entire SNP dataset across regions of interest was utilized to narrow and prioritize loci for follow-up work.
Size Size, including both height and mass, is a highly-studied phenotype. Loci involved in the determination of size have been identified in the dog  [4, 6, 9, [63] [64] [65] , cattle  [66] [67] [68]  and humans  [69] [70] [71] , among other species. In horses, a majority of variation in skeletal measurements in can be explained by one principal component  [72]  and four loci have been identified that account for a large proportion of variance in size across breeds  [73]. In addition, two significant quantitative trait loci for size have been identified in the Franches-Montagnes  [74]. Although all are known for their size and strength, each draft horse population has its own, unique history. While the British Isles native Clydesdale and Shire, and mainland European Belgian and Percheron, are all considered heavy draft horses, several breeds with smaller stature but still bred for substance and strength (light draft) are included in the dataset.
Samples and Genotyping 744 horses representing 33 breeds were collected through the Equine Genetic Diversity Consortium either as hair root samples or previously collected genotypes. For hair roots, DNA was isolated using a modification of the Puregene (Qiagen) protocol for DNA purification from tissue. Modifications include the addition of 750 ml of isopropanol rather than 300, increasing the precipitation spin time to15 m and doing so at 4uC, and washing the pellet twice. Approximately 1 mg of DNA was used for SNP genotyping using the Illumina SNP50 Beadchip according to the manufacturer's protocol. All genotype calls were extracted from the raw intensity data using GenomeStudio (Illumina) with the minimum gencall (GC) score threshold of 0. 15. Horses were chosen to be unrelated at, or more recent to, the grandparent level based upon pedigree information.
Phasing The entire SNP dataset was pruned for minor allele frequency of 0. 001 and genotyping rate of greater than 95%. The data from all such SNPs within genomic regions of interested identified by the d i statistic, including those eliminated from d i calculations, were phased using fastPHASE 1. 2  [88]. Parameters were set to consider 25 to 45 clusters (-Kl25 -Ku45 -Ki5) and include breeds denoted as subpopulations. Conserved haplotypes were then identified within/among the breeds showing significant d i values and the frequency of the identified haplotypes calculated within and across all breeds. The haplotypes were then examined for candidate genes that may contribute to desired phenotypes of the breed(s) of interest using the annotated equine reference sequence.
DNA from 389 horses (Quarter Horses and Paints) available from the Equine Neuromuscular Diagnostic Laboratory was genotyped for the presence/absence of the SINE insertion using primer pair MSTN_13  [20]. Gluteal muscle biopsies from 79 healthy Quarter Horses (genotyped as part of the 389 horses above) were randomly chosen for muscle fiber type analyses and also for the intron 1 SNP (g. 66493737C. T)  [20]. A subset of the samples was genotyped for the promoter SNP (g. 66495715T/C)  [21]  using primer pair MSTN14a (Table  S4 ). Of the 389 horses above, SNP array data was available from 132 as part of this study, or for another study in the laboratory. 63 horses with SNP array data were also genotyped for the intron 1 SNP. Genotypes from these horses were then used to evaluate the association between the extended haplotype and the SINE, the haplotype and intron 1 SNP, and SINE and SNP.
Muscle fiber type analysis. 10 mm thick sections were cut from frozen gluteal muscle tissue, preincubated at pH 4. 6, and stained for myosin adenosine triphosphatase (ATPase). Muscle fiber type compositions were determined by counting the number of Type 1, 2A, and 2B fibers for a minimum of 250 fibers per biopsy and calculating a percentage composition. Maximum skeletal muscle fiber diameters were determined in 25 fibers of each type using the I solution Lite software program (IMT Technology). A MANOVA was performed to determine significance of genotype or allele effects of the MSTN SINE and/or intron 1 SNP and age on muscle fiber proportions assuming an additive mode of inheritance and including sex and age at biopsy as covariates. Directionality of the effect of the SINE and intron 1 SNP was then investigated using multiple linear regression in R (http://www.
Availability of Data All SNP genotype data is available upon request (www. animalgenome. org/repository/pub/UMN2012. 1130/) for the purpose of reconstructing the analyses. The only exception is the data collected from the Tennessee Walking Horse, which, under agreement from the granting agency (to the University of Minnesota from the Foundation for the Advancement of the Tennessee Walking Show Horse (FAST) and the Tennessee Walking Horse Foundation (TWHF)), is only available under a Material Transfer Agreement (MTA) between interested individuals and the University of Minnesota.
GFR Measurement Exogenous plasma creatinine clearance test was performed. 22, 23 lasma creatinine concentration was measured as described above in fasted cats before and 5, 30 minutes, 1, 2, 3, 5, and 8 hours after administration of an intravenous bolus of a sterile solution of exogenous creatinine at a nominal dose of 20 mg/kg. Creatinine solution (80 mg/mL) was prepared the day before testing by dissolving anhydrous creatinine l in distilled water. The solution was sterilized by filtration through a 0. 2-lm filter. Exact individual dose was determined from syringe weight. Plasma data for creatinine concentration were subjected to noncompartmental analysis by a software program. m The area under the curve was determined using the trapezoidal rule with extrapolation to infinity. Clearance (ie, GFR) was calculated by dividing the amount of exogenous creatinine administered by the area under the curve.
evidenced, statistical analysis was performed on log transformed data and results are expressed as geometric mean and 95% confidence interval. Otherwise, results obtained from native data were used and are expressed as mean AE standard deviation. Compound symmetry, ie, conditional independence in repeated measures analysis, was assumed. A statistical power analysis was performed for 2 primary variables of interest: GFR and systolic blood pressure. Based on 10 cats by group, the statistical analysis was found to be powerful enough to reliably detect a 20% change in these variables. Indeed, using standard deviations of 0. 3 mL/min/kg and 15 mmHg and an effect size of 0. 4 mL/min/ kg and 20 mmHg for GFR and SBP, respectively, statistical power was found to be 85% for both variables. Effect of dietary salt intake on tested variables was primarily assessed through the diet by period interaction term of the model.
Acknowledgments The study was supported by  Royal Canin SAS ,  Centre de Recherches, Aimargues, France. The authors are grateful to  Samuel Ninet , Th er ese Fr egier, and  Philippe Bleiss  (Oniris),  Thomas Daste  and  Am elie Dutech  ( National Veterinary School of Toulouse ) for their technical assistance during the animal phase,  Claude Germain  ( National Veterinary School of Toulouse ),  Helen Woodcock  and  Liam Sawbridge  ( Royal Veterinary College ) for performing assays, and  Jo€ elle Ribaut  ( National Veterinary School of Toulouse ) for administrative and logistical support.
Case A 20-year-old man, native of France, was diagnosed in August 2008 with a B-cell acute lymphoblastic leukemia carrying the t  [4, 11]  translocation and blasts negative for CD20 and CD10. The patient was treated according to the GRAALL 2005 protocol NCT00327678 (Group for Research in Adult Acute Lymphoblastic Leukemia). Complete remission was achieved in October 2008, but the scheduled allogenic stem cell transplantation (HSCT) could not be performed because no compatible donor had been identified. Intensification therapy was started, and the good condition of the patient allowed him back to work part-time in May 2009, and full-time in September 2009. On December 2009, a subsequent medullar relapse was diagnosed along with a H1N1 influenza pneumonia. The patient was treated with L-asparaginase encapsulated within erythrocytes (GRASPA s ), according to the GRASPALL-protocol 2005-01  [6].
ITS1, ITS4, NS3, NS4, EF1F, EF1R were used individually as primer to sequence both strands of each PCR product with ABIPrism Dye Terminator Cycle Sequencing Ready Reaction v1. 1 Kit (Applied Biosystems) according to the manufacturer's recommendations. The nucleotide sequences of ITS (GenBank accession number JX997932), and of parts of the 18S rDNA gene (GenBank accession number JX997933) and EF1a gene (GenBank accession number JX997934) were compared with those of the databases of the National Center for Biotechnology Information website (http:// www. ncbi. nlm. nih. gov) using the Basic Local Alignment Search Tool (BLAST, http://blast. ncbi. nlm. nih. gov/Blast. cgi). Sequence identity (Evalue 0) was found with N. vasinfecta. Antifungal susceptibility testing was performed by E-test (BioMerieux) on RPMI medium and revealed multiresistance.
Bangladeshi AIV sequences Our study focuses on a dataset of AIV H9 HA segment sequences sampled between 2003-2019. The dataset includes 82 newly generated H9N2 HA sequences and H9 HA sequences for which only the HA segment was generated, but that are assumed henceforth to be from H9N2 infected birds (justification of this assumption is provided in Results and Discussion) (study sources in Table  1 , accessions provided in Table  S1 ). The dataset also includes 216 previously published sequences from both the GISAID  (Shu & McCauley 2017)  epiFLU database (www. gisaid. org) (n = 211, Table  S2 ) and from  Ripa et al. (2021)  (n = 5)  (Ripa et al. 2021). Newly generated sequences were sampled through observational studies and routine surveillance in Dhaka and Chattogram from 2016 to 2018 (details in Table  1 ), one of which has been previously described  (Kim et al.
2018 ). Whilst we focus on HA here, sequences from other segments were generated for a subset of our H9N2 samples. NA gene sequences from  Ripa et al. , (2021)   (Ripa et al. 2021)  were combined with NA sequences from GISAID  (Shu & McCauley 2017 ) epiFLU database (H9N2; n = 200) corresponding to those viruses for which HA was available (Table  S2 ), and used for a subset of analyses. Associated information on species, location (either market-or farm-level) and sampling date was available for all newly generated sequences (Table  1 ). The type of chicken (either broiler, deshi, or sunali) was also available for 70 newly reported H9N2 virus genome sequences generated through a cross-sectional study of Dhaka and Chattogram's LBMs during February-March 2016 (henceforth, the "cross-sectional H9N2 dataset")  (Kim et al.
2018 ) (Table  1 ). For sequences accessed from public databases, we extracted available corresponding location metadata from the Influenza Research Database (IRD)  (Squires et al. 2012)  animal surveillance database (www. fludb. org) (Table  S3 ). We also obtained unpublished LBM characteristics for 184 of the publicly available sequences in the H9N2 HA dataset from Professor Richard Webby (St. Jude Research Center of Excellence for Influenza Research and Surveillance) (Accession numbers in Table  S4 ). In addition to the H9N2 data described above, H5NX sequences were generated via next-generation sequencing through two of the three surveillance studies in Table  1. HA sequences (n = 29) and available corresponding NA gene segment sequences (n = 15) (Table  1 ) were combined into datasets with previously published H5NX sequences from GISAID epiFLU (HA; n = 175, NA; n = 172) (Table  S2 ) and  Ripa et al.