dataesr/scientific-paragraphs-categorization huggingface dataset:
2. 1 Ecological variables. Our previous study of BTV-8 spread in France indicated that the velocity of BT spread could be influenced by environmental factors  [23]. Thus, to measure the effect of vaccination on the velocity of BTV-1 spread, we needed to consider the variables that may influence the velocity of BT spread and consequently, tested the same covariates as in the BTV-8 study  [23]. These covariates are related to host availability and immunity, vector abundance and activity, and vector-host contact. Hence, sixteen covariates defining five thematic groups of related variables were tested (Table  1 ). Host availability, vaccination, elevation and landscape-related variables were obtained at the municipality level. Meteorological-related variables were obtained on an 868 km square grid through the SAFRAN database supplied by Meteo-France  [31].
S1 ). Vaccination began later in other areas. The inactivated vaccines ZULVACH1 Bovis and ZULVACH1 Ovis were used for cattle and small ruminants, respectively. After the second vaccine dose, time to full protection is 15 days in cattle and 24 days in small ruminants. Vaccine efficacy was assumed to be 100%. Expenses for livestock vaccination were covered by the French Ministry of Agriculture and data on BTV-1 vaccination were provided by FranceAgriMer, which is the organisation that paid the veterinarians who performed vaccination. Vaccine coverage in a municipality was calculated as the proportion of small ruminants and cattle immunized at the date of the first BTV-1 clinical case in the municipality, i. e. , the ratio of the number of small ruminants and cattle that reached full protection at the date of the first BTV-1 clinical case, to the sum of the number of small ruminants reported on January 2008 and the number of cattle over 2 months old reported on September 2008.
80: the covariates were not highly correlated and could be included simultaneously in a model  [33]. Moreover, to determine whether the covariates should be considered as continuous or categorical, we examined the linearity of the association between each continuous covariate and the response variable (see Material S3). We finally obtained 4 continuous and 12 categorical candidate variables (Table  1 ). Only plausible two-way interactions were considered, i. e. , the interaction between temperature and rainfall at equivalent temporal lags, and the interaction between small ruminant density and dairy or beef cattle densities. Overall, 16 candidate covariates along with 4 plausible biological interactions between candidate variables were tested. The dataset was split randomly into ''training'' and ''testing'' subsets (75% and 25% of the data, respectively).
We initially fitted a linear regression model to the training dataset using ordinary least squares (OLS). However, spatial autocorrelation in the residuals indicated that the assumption of independent errors was violated. We consequently extended the model to account for residual spatial structure by using a residuals autocovariate model (RAC)  [34] , which included, in addition to the environmental covariates, an autocovariate calculated from the residuals of the OLS fitted model (see Material S4). Statistical analyses were performed using the R v2. 13. 1 software  [35]. Linear models were compared using the package MuMIn  [36]  and RAC models were fitted using the packages raster  [37]  and geoR  [38]. We selected the best model by using backward model selection based on AICc  [23]. As recommended by Burnham and Anderson  [39] , we considered that two nested models differing by less than 2 AICc points received identical support from the data.
In such a situation, the model with fewer parameters was preferred. Once the best model was identified, we characterized its performance by using two statistics: the coefficient of determination and the Root Mean Squared Error (RMSE). The coefficient of determination, i. e. , the squared Pearson correlation r between predicted and observed values  [40, 41]  is a measure of the overall goodness of fit. We also calculated the Root Mean Squared Error (RMSE)  [42]  of values fitted to the training dataset since it is a good measure of prediction accuracy, lower values of RMSE indicating a better fit. Moreover, to evaluate the predictive power of the model we used the municipalities of the testing dataset. As for the training dataset, we calculated the squared Pearson correlation and the RMSE. Finally, we used likelihood ratio tests for nested models  [43, 44]  to assess the relative importance of environmental variables in the RAC model: D~{2 1 red {1 full ð Þ where D is the log-likelihood ratio test statistic, and l red and l full are the log-likelihoods of the reduced and full models, respectively.
2, 95% Confidence Interval (CI): 20. 4320. 93) and a bell-shaped distribution. No spatial structure was detected in these residuals. The difference between the fitted and observed date of first clinical case was less than 16 days for 1,337 municipalities (84%) and environmental covariates were available for 1,314 of these municipalities (82%). For this sub-dataset of 1,314 municipalities the minimum and maximum velocities were identical to those of the full dataset, and the mean and median values of the velocity of BTV-1 spread were 5. 72 and 2. 74 km/day, respectively. The estimated velocities at these 1,314 municipalities were subsequently included in the analysis of the effect of vaccination (see section 3. 2). Velocity vectors of the 1,314 municipalities are presented in Figure  2 : from the initial introduction zone (indicated by a red arrow on the map), the virus spread rapidly from west to east along the Pyrenees Mountains, then, from this initial incursion, the virus spread sideways to the south and north.
This OLS model performed poorly in predicting the velocity of BTV-1 spread from environmental covariates (squared Pearson's r = 0. 27, RMSE = 7. 33 km/day) in the training dataset and spatial autocorrelation at short distance was detected in the residuals (Fig. S2A ). We thus fitted a RAC model to account for spatial autocorrelation. The RAC model contained the environmental covariates from the above OLS model plus an autocovariate that represented spatial autocorrelation in the residuals of the OLS model at a neighborhood size of 3. 6 km. The fit of the RAC model was satisfactory (squared Pearson's r = 0. 81, RMSE = 3. 69 km/day). In contrast to the OLS model, analysis of the residuals showed no spatial autocorrelation (Fig. S2 ). Parameter estimates of the RAC model are presented in Table  2.
The RAC model was tested on the 328 municipality testing dataset and predictive performance was good (squared Pearson's r = 0. 86, RMSE = 3. 14 km/day). Estimated coefficients and p-values of environmental covariates are reported in Table  2. The intercept indicates an average velocity of BTV-1 spread of approximately 3. 5 km/day (Table  2 ). As expected, vaccination was negatively associated with velocity of BTV-1 spread, which was, on average, 1. 7 km/day lower in municipalities with immunized animals at the date of first clinical case, than in municipalities with no immunized animals. Meteorological variables, landscape factors and host availability were also correlated to velocity of BTV-1 spread. The contribution of covariates to model fit was assessed via D-values of each covariate (Fig.
Acknowledgments We are grateful to  P. Hertsens  from  FranceAgriMer (vaccination data ),  C. Lacz  from the  FRGDS Midi-Pyrenees ,  T. Rouanet  from  ARSOE de Soual  and  S. Bacchin-Vinet  from the  Chambre d'agriculture de Midi-Pyre  ´nees (small ruminant's count),  J. B. Perrin  from the  French Ministry of Agriculture  (cattle count),  D. Chavernac  from  Cirad (BT cases database ),  P. Bontour  from the  Direction Departementale de la Cohesion Sociale et de la Protection des Populations (DDCSPP)   09 ,  A. Montagne  from  DDCSPP 31 ,  N. Fradin  from  DDCSPP 64 ,  C. Pau  and  P. Saura  from  DDCSPP 65 ,  A. M. Micheletto  from  DDCSPP 66 , and  C. Carrerra  from  DDCSPP 81 , as well as MeteoFrance (climatic data). We also thank two anonymous referees for their valuable comments.
This study was funded by  EU  grant  FP7-261504  EDENext and is catalogued by the EDENext Steering Committee as EDENext122 (http://www. edenext. eu). The contents of this publication are the sole responsibility of the authors and don't necessarily reflect the views of the  European Commission. HG and RL are partially funded by the  Direction Generale de l'Alimentation (DGAL)  of the  French Ministry of Agriculture. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Study design This monocentric study compares the PH Vittel criteria (Table  1 ) with 2 scores calculated at the end of the clinical assessment: the Injury Severity Score (ISS) and the Trauma Injury Severity Score (TRISS). Polytrauma was defined as an ISS > 16. The goal of the study was to evaluate the performance of Vittel criteria to select polytrauma patients during the pre-hospital stage and evaluate any additional benefit with the use of the specific criterion "PH resuscitation". The data was prospectively collected. The protocol was approved by the Institutional Review Board.
Statistical analysis A statistical analysis evaluated the performance of the Vittel criteria in selecting patients with an ISS > 16 (Stata version 9 software, Stata Corporation). A descriptive analysis with the comparison between the subgroups was made with ANOVA. The correlation between the variables utilized the Pearson coefficient. Linear regression, univariate and multivariate analysis were used to measure the link between Vittel criteria and the ISS and TRISS. The significance level of the study was Ⅲ.
ABO alleles registered in the Blood Group Antigen Gene Mutation Database exceed 250, and ABO has become one of the most studied human genetic loci for its polymorphism  9. ABO genes exist not only in humans but also in many other vertebrate species although ABH antigen expression patterns may be different. In addition to A and B transferases, there are additional enzymes transferring a GalNAc/galactose by a1,3-glycosidic linkage: a1,3-galactosyltransferase and isogloboside 3 synthase (both of galactose specificity), and Forssman glycolipid synthase (GalNAc specificity). These enzymes catalyze the last synthetic steps of a1,3galactosyl epitope (Gala1-. 3Gal 1-. 4GlcNAc -), isogloboside 3 (Gala1-. 3Gal 1-. 4Glc 1-Ceramide), and Forssman glycolipid antigen (GalNAca1-. 3GalNAc 1-. 3Gala1-. 4Gal 1-.
As in many other areas of genetic studies, functional assays are of critical importance. In the present work, we analyzed many homologous genes and sequences that had been identified in various species through genome sequencing efforts. In addition to the sequences, we also utilized additional data and information available: gene structure to determine whether a gene is partial or complete; chromosomal organization to deduce duplication(s), deletion(s), inversion(s), and translocation(s) that have occurred; and information on A/B transferases and A/B oligosaccharides to obtain clues on functionality. Data were interpreted with caution because of the incompleteness of genome sequence databases, wrong annotations, and differences among individuals within a species, and errors in genome assemblies.
Results Gene duplications and changes in substrate specificity of the encoded glycosyltransferases created ABO family of genes in animals. All the a1,3-Gal(NAc)T genes in genome databases that were analyzed are listed in Fig. 1. Species were aligned based on their evolutionary relationship (human at top and lamprey at bottom)  25. A phylogenetic tree was constructed for the 104 protein sequences that are likely to encode functional a1,3-Gal(NAc)Ts, and is shown in Fig. 2. GBGT1, A3GALT2, GGTA1, and GLT6D1 genes formed separate clusters, whereas both A and B genes were clustered into a single ABO gene cluster. Except that many nonfunctional genes are omitted, these results obtained from amino acid sequence analysis coincided well with the nucleotide sequence-based Ensembl gene tree ENSGT00400000022032 and a previous report  15.
Our in vitro mutagenesis study  30  and the determination of the threedimensional structures of A/B transferases by others  31  confirmed the critical roles of amino acids at codons 266 and 268. In this study we prepared a library of 40 amino acid substitution constructs of human A transferase, which contained any one of potential 20 amino acid residues at codon 266 in combination with either glycine of A transferase or alanine of B transferase at codon 268. Furthermore, we also prepared additional constructs at codons 263-268 that contained deduced amino acids present in annotated ABO and related a1,3-Gal(NAc)T genes in the genome databases but were not represented in the library. DNA from those constructs was transfected to HeLa cells expressing cell-surface H substances, and the expression of A/B antigens was examined immunologically, using antibodies against blood group A/B antigens, respectively.
A code table was generated that correlates amino acid sequence motifs and A/B specificity of the enzymes encoded by the various constructs (Table  2 ). The activity is shown semi-quantitatively in a 4-fold expo-Figure  1  | Species-dependent distribution of FUT1/FUT2/SEC1 a1,2-fucosyltransferase genes and ABO/GBGT1/A3GALT2/GGTA1/GLT6D1 a1,3-Gal(NAc) transferase genes. This table shows the distribution of a1,2-FT genes and a1,3-Gal(NAc)T genes in a variety of organisms. Ensembl gene identifiers are listed only with the meaningful digits, excluding 0 s on the left from their IDs. Genes were categorized into groups based on Ensembl gene trees, chromosomal locations, and our own analyses, and they are aligned in different columns and shown highlighted in different colors. Amino acid sequences corresponding to the codons 266-268 of human A/B transferases are also shown.
The symbol ''---'' indicates the absence of sequence motif, and ''N/A'' means not annotated in databases. A single column of ''Pseudo/Ancient'' was used to list two types of annotated gene sequences: The ABO retropseudogene sequences that were originally derived from an intronless cDNA are highlighted in tan color (Pseudo) and the sequences that formed a cluster next to the ABO gene in the phylogenetic analysis are highlighted in yellow (Ancient). The gene sequences that formed a cluster outside of the ABO/ GBGT1 genes are highlighted in orange, and they are shown separately in the ''ABO/GBGT1 Ancient'' column. The annotated genes may or may not be functional, the latter of which may also be called as O genes or pseudogenes. Note that genome sequences were not complete for many species, and therefore, errors may exist.
The amino acid sequences corresponding to codons 69-354 of the human A transferase were examined. 1,000 bootstrap replications were computed. Branches leading to ABO, GBGT1, A3GALT2, GGTA1, and GLT6D1 genes are colored in yellow, grey, green, purple, and blue, respectively. The bootstrap frequencies are shown on the branching points. Fishes, amphibians, reptiles, and birds are marked with closed circles in red, purple, green, and dark blue whereas mammals are unmarked. The species code names correspond to the names shown in the ''Ensembl Database'' column in Fig. 1. For instance, PTR for chimpanzee (Pan troglodytes) is obtainable by removing ENS and G from the database name (ENSPTRG). specificity of the annotated ABO genes and critically evaluated several hypotheses on the evolution of the ABO genes.
These results suggest that functional differentiation between A and B gene sequences appeared early in evolution, possibly just after the ABO gene emergence in amphibians. As shown in Table  3 , horse A and B gene sequences are closely located in tandem on the same chromosome. Therefore, if horse genome assembly is correct, those sequences may not be unigenic alleles. Microbat A and B gene sequences have not yet been mapped on chromosomes, however, at least one A and one B gene sequences of the three present in the genome were aligned side-by-side within a single contig (ENSMLUG00000029891 with LGG and ENS-MLUG00000026173 with MGA in Scaffold GL431842: 18,186-26,341). Accordingly, they are not allelic, either. The rat genome in the Ensembl database lists 4 ABO gene sequences: 1 A (AGG) and 3 Bs (MGA).
The surrounding chromosomal organization in Table  3  shows that those sequences are not alleles. Rat A and B gene sequences located tandemly in a cis-manner contrast to mouse gene (GGA) encoding a transferase with dual specificity (cis-AB enzyme)  34. However, heterogeneity seems to exist among different strains of rats. The Ensembl genome is from the BN/SsNHsdMCW strain. In addition to this strain, GenBank database also houses the genome sequence from another strain, the BN/Sprague-Dawley strain (Rn_Celera). 1 A (AGG) and 2 B (MGA) gene sequences, rather than 1 A and 3 B, were mapped for this strain. In another strain, Wistar, 3 A and 1 B gene sequences were cloned although they have not been mapped  33. Different cloning results were obtained from inbred GOT-W strain  35  and the BDIX strain  36  , further complicating the understanding of rat ABO genes.
Amino acid sequences corresponding to the codons 266-268 of human A/B transferases are also shown in parentheses. Genes in the same species are bracketed. When potential A and B gene sequences are both present in a single species, the bracket was colored in red. Horse genes and ferret genes in 2 separate clusters are bracketed in blue and purple, respectively. Other species are bracketed in dark blue. (b): A phylogenetic tree of originally intronless ABO retropseudogene products. The entire protein sequences of processed retropseudogenes were analyzed. Branches leading to different amino acid sequences at the important positions are coded in different colors. (c): ABO gene evolution in bacteria. EMBL-EBI InterPro database listed 57 bacterial proteins within the GT6 family. 56 proteins/peptides, excluding 1 short one, were aligned to construct a phylogenetic tree.
Because the ABO gene inheritance in primates was still controversial  46  , we re-visited the topic for further evaluation, with additional experimental data on sugar specificity and activity of A/B transferases summarized in the code table. Genome sequences in databases do not cover ABO polymorphism. Human reference and non-reference genes (both with LGG motif) in Ensemble database represent O and A alleles, respectively. The chimpanzee, gorilla, and macaque genes with LGG, MGA, and MGA, respectively, represent A, B, and B alleles from those species. In all the primate species the chromosomal region containing ABO gene is similar to the consensus with minor differences (Table  3 ). The current EMBL-EBI InterPro database hosts non-overlapping 65 ABO protein/peptide sequences, including several proteins with MGG, MGS, or LGA motif.
Analyzing 19 bacterial genes, horizontal gene transfer between eukaryotes and prokaryotes and among bacteria was proposed to explain the absence of ABO genes in many species of invertebrates, plants, and fungi  50. Because recent microorganism genome sequencings have identified additional bacterial ABO genes, we analyzed 56 bacterial proteins in EMBL-EBI InterPro database, and constructed phylogenetic trees of bacterial ABO genes. A tree is shown in Fig. 3c. In contrast to vertebrate ABO genes, all the bacterial A genes with GalNAc specificity segregated from the B or AB genes with galactose or GalNAc/galactose specificity, respectively. Another important finding is that the bacterial ABO genes have a different variation in the amino acid sequence motif from the animal genes. AGG and CGG motifs were found in the A gene sequences, MGS and QGC in the B gene sequences, and MGG, QGG, and TGA were in the AB gene sequences.
When functional A/B transferases are expressed by DNA transfection, H substances are converted to A/B antigens. We have used this system at various occasions to examine the specificity and activity of A/B transferase variants  30, 57, 58. DNA transfection experiments were performed using 96-well plates as previously described  59. Lipofectamine 2000 reagent was used, following the manufacturer's instructions. DNA from the FUT2 expression construct prepared in pSG-5 and DNA from the pEGFP-N1 vector (GenBank Accession #U55762) were co-transfected: the former to increase the acceptor substrate availability and the latter to calculate the transfection efficiency for activity adjustment. Two days after DNA transfection, GFP-positive cells were counted. The next day, cells were fixed with paraformaldehyde and washed with PBS.
After drying, cells were treated first with either anti-A or anti-B monoclonal antibodies, second with biotinylated anti-mouse IgM, then with Avidin/Biotinylated Peroxidase Complex (ABC), followed by color development using DAB substrate. Stained cells were counted microscopically, and A/B specificity and activity were determined after adjusting the transfection efficiency using GFP-positive cell counts. Because of variable detachment of cells from dish substratum during fixation and immunostaining procedures, data were presented in a semi-quantitative manner. Databases, sequence alignment, and construction of phylogenetic trees. Nucleotide and amino acid sequences, exon-intron organizations, and chromosomal locations of a1,2-FT genes (FUT1/FUT2/SEC1) and a1,3-Gal(NAc)T genes (ABO/GBGT1/ A3GALT2/GGTA1/GLT6D1) were retrieved from Ensembl (www.
ensembl. org/index. html) and GenBank (www. ncbi. nlm. nih. gov/genbank/) genome sequence databases. Protein/peptide sequences of the ABO genes were retrieved from the EMBL-EBI InterPro database (www. ebi. ac. uk/interpro/). Ensembl genome sequence database (release 73) listed 89 annotated a1,2-FT genes with 66 speciation nodes and 15 duplications in the ENSGT00390000001450 gene tree and 255 annotated a1,3-Gal(NAc)T genes with 185 speciation nodes and 65 duplications in the ENSGT00400000022032 gene tree. The phylogenetic tree in Fig. 2  was constructed by the neighbor-joining method  60. JTT model  61  was used for estimating number of amino acid substitutions and 1,000 bootstrap replications were computed by using MEGA5  62. The phylogenetic trees in Fig. 3  were constructed by Maximum Likelihood method, using the same software.
Acknowledgments This work was supported by the  Instituto de Salud Carlos III  (grant number  PI11/00454 ) from the  Spanish Government  and the fund from  Institut de Medicina Predictiva i Personalitzada del Cancer (IMPPC)  to FY. We thank  Mrs. Masako Mizuguchi  for phylogenetic construction of Fig. 2 and  Ms. Patricia Barrero  for technical assistance.
disease for which expensive treatments are now used. There is an urgent need for an accurate and standardized MR imaging methodology among centers to better characterize and follow intrapatient changes longitudinally in personalized medicine and to facilitate analysis of large standardized datasets, which could help define predictors of disease evolution and long-term effects of therapies. Several attempts to improve and standardize MR imaging protocols have been published,  [4] [5] [6]  and several national cohorts are being developed (MAGNetic resonance Imaging in Multiple Sclerosis centers in Europe,  7  L'Observatoire Francais de la Sclerose en Plaques in France  8  ), all sharing the objective of creating a central library documented by using high-quality homoge-neous MR imaging examinations with demographic and clinical evaluations.