dataesr/scientific-paragraphs-categorization huggingface dataset:
Discussion A large set of complementary methods can capture the impact of lesions on distant regions and expose the subsequent consequences on patients' neuropsychological performance. Several of these methods are built directly into our freely available software package BCBtoolkit. This package can be used to measure the pathophysiological mechanisms that cause cognitive deficits and to assess the relationship between these mechanisms and their consequential effects. Here, we evaluated the risk of disconnection of classically defined white matter tracts and tested their relationship with category fluency performance. We then used a tractography-based approach to reveal regions that were structurally disconnected by the lesion and to assess their relationship with category fluency performance as compared to controls and other patients.
Additionally, these approaches require a much larger database of patients than the current study. Future research that uses large lesion databases will be required to explore the effect of multivariate statistical analysis on disconnectome maps. Multivariate approaches also elegantly demonstrated that false positives can be driven by the vascular architecture  [7]. This is an important limitation concerning any voxel and vascular lesion symptom mapping. Here, the group of patients explored had stroke and surgical lesions. Although we cannot exclude the participation of the vascular architecture in the present findings, the heterogeneity of the lesions included in our analyses may have limited this factor. Additionally, the statistical interaction between vascular architecture and the disconnectome map results remain to be explored in large databases of lesions.
Conclusion Overall, using BCBtoolkit, researchers and clinicians can measure distant effects of brain lesions and associate these effects with neuropsychological outcomes. However, our methods require the manual delineation of lesion masks, automatization remaining a big challenge, especially on T1 images  [105]. Taken together, these neuroimaging measures help discern the natural history of events that occur in the brain after a lesion, as well as assist in the localization of functions. These methods, gathered in the BCBtoolkit, are freely available as supplementary software  [1, 107].
Acknowledgments We thank  Lauren Sakuma ,  Roberto Toro ,  Jean Daunizeau ,  Emmanuel Mandonnet ,  Beatrice Garcin ,  Stephanie J. Forkel , and the  BCBlab and Brainhack  for useful discussions. We also thank  Mozilla spaces  for their support, the participants of this study as well as  Prof. Claude Adam ,  Dr. Carole Azuar ,  Dr. Marie-Laure Br  échemier,  Dr. Dorian Chauvet ,  Dr. Fr  éd éric Clarencon,  Dr. Vincent Degos ,  Prof. Sophie Dupont ,  Prof. Damien Galanaud ,  Dr. B éatrice Garcin ,  Dr. Florence Laigle ,  Dr. Marc-Antoine Labeyrie ,  Dr. Anne Leger ,  Prof. Vincent Navarro ,  Prof. Pascale Pradat-Diehl , and  Prof. Michel Wager  for their help in recruiting the patients. The research leading to these results was funded by the  Agence Nationale de la Recherche  (grants  ANR-09-RPDOC-004-01  and  ANR-13-JSV4-0001-01 ) and from the  Fondation pour la Recherche M édicale.
Availability of supporting data Patients' lesions registered to the reference map MNI152 are available as supplementary material via the BCBlab website  [106]  and via the GigaScience database GigaDB  [107]. However, we are not able to fully share the actual clinical sample data because sharing of the clinical raw data is not covered by the participants' consent. A copy of the consent form as signed by the participants is available via GigaDB.
In our framework, we take advantage of the fact that the horizontal plane most easily viewed by a typical human is usually the horizontal plane most used by a human. The robot has cameras positioned to provide the robot with a point of view similar to the point of view of a typical human. To recognize the furniture, the robot uses an RGB-D camera to acquire three-dimensional data from the environment. After acquiring 3D data, the robot extracts the geometrical components and creates a graph for each object in the scene. Because the robot maintains the relationships between all coordinates of its parts, the robot can transform the point cloud to a particular reference frame, which simplifies the extraction of geometric components; specifically, to the robot's footprint reference frame. From transformed point clouds of a given point of view, the robot extracts graphs corresponding to partial views for each piece of furniture in the scene.
The graphs generated are later compared with the graphs of the object's models contained in a database. The main contributions of this study are: • a graph representation adapted to detect pieces of furniture using an autonomous mobile robot; • a representation of partial views of furniture models given by sub-graphs; • a fast and linear method for geometric feature extraction (planes and poles); • metrics to compare the partial views and characteristics of geometric components; and • a process to update the environment map when furniture is repositioned.
Others works (  [5, 6] ) have followed a similar approach using features to detect other types of free-form objects. For instance, in  [5] , 3D-models were created and objects detected simultaneously by using a local surface feature. Additionally, local features in a multidimensional histogram have been combined to classify objects in range images  [6]. These studies used specific features extracted from the objects and then compared the extracted features with a previously-created database, containing the models of the objects. Furthermore, other studies have performed 3D object-detection based on pairs of points from oriented surfaces. For example, Wahl et al. [7]  proposed a four-dimensional feature invariant to translation and rotation, which captures the intrinsic geometrical relationships; whereas Drost et al.
While types of furniture can have the same graph structure, values in their components are particular for a given instance. Therefore, it is not possible to recognize with the same graph different instances of a type of furniture. In other words, a particular graph for a bed cannot be used for beds with different sizes; however, the graph structure could be the same. Additionally, to test the approach on more examples, we have tested on selected images from the dataset SUNRGB-D  [23]. Figure  17      It is important to note that to detect the geometrical components over these scenes, the point cloud from each selected scene was treated using the intrinsic and extrinsic parameters provided in the dataset. Consequently, a similar footprint reference frame is obtained such as the frame provided by the robots in this work.
This manual adjustment was necessary to simulate the translation needed to align the coordinate frame of the image with the environment, as described in Section 4. 1. (c) (d) (e) (f) (g) (h) (i) (j) (k) (l) Since the proposed approach requires a complete model for each piece of furniture, which were not provided by the dataset, it was not possible to match the graphs generated to a given piece of furniture. However, the approach has worked as expected (Figure  17 ).
illumina. com/sequencing/sequencing_software/igenome. html ). Read counting was performed using featureCounts  (Liao et al. 2014)  guided by the aforementioned Gene Model file. For TE expression profiling, reads were further trimmed to 30 nucleotides and aligned to canonical TEs using bowtie 0. 12. 7, allowing 2 mismatches and only uniquely matching reads. Sense and antisense reads were counted and merge with gene counts. Differential expression profiling was performed using edgeR  (Robinson et al. 2010; McCarthy et al. 2012). Genes with less than 5 reads on average across libraries were discarded from the analysis. Diverging from the default, we used Full Quantile between-library normalization as implemented by the EDAseq package  (Risso et al. 2011 ) and removed unwanted variation using replicate samples with the RUVs function (choosing k=2) implemented in the RUVseq package  (Risso et al.
2014). Library sequencing method (paired-end vs. single-read) was introduced together with gene-wise Full Quantile normalization offsets and gene-wise RUVs offsets as covariates in the edgeR design formula. All libraries were tested for differential gene expression against the wild type, and in addition the double-mutant was also tested against the piwi -/-mutant. Proportional Venn Diagrams in Figure  2C  and Figure  2D  were drawn using the Vennerable package ( https://github. com/js229/Vennerable ). The spearman rank correlation and corresponding P-value between log2 fold changes in TE 21 nucleotide antisense RNA (log2 fold change calculated from data underlying Figure  1C ) and sense TE transcript expression was calculated with the rcorr function in the Hmisc R package ( http://cran. r-project.
Secondary piRNA biogenesis is not detectable in adult heads Ago3 and Aubergine were detected by immunofluorescence in the optic lobe of the Drosophila central nervous system  (Perrat et al. 2013 ) and several teams sequenced small RNA molecules in head samples which had the size (24-28 nt), 3'-end 2'-O-methylation and ping-pong signature of Drosophila piRNAs  (Ghildiyal et al. 2008b; Yan et al. 2011a ; Mirkovic-Hösle and Förstemann 2014a). However, these putative piRNAs corresponded to a very minor fraction of the sequence datasets, which raises the possibility of sample contamination by gonadal tissues during RNA extraction. To address this issue, we analyzed small RNA matching TE sequences in 24 small RNA sequencing libraries prepared from adult male heads isolated by sieving after freezing  (Reinhardt et al.
In principle, the increase of TE-specific siRNAs could be maternally inherited or stably maintained from early development. We took advantage of the fact that mature Ago2-loaded siRNAs are single-stranded and that double-stranded RNAs, among which the substrates of Dicer-2, are frequently deaminated through the action of Adenosine Deaminase Acting on RNA (ADAR) enzyme, which converts adenosine (A) to inosine (I)  (Keegan et al. 2005; Palladino et al. 2000; Wu et al. 2011 ). This change manifests in a A to G mismatches in RNA sequencing datasets as compared to the DNA based reference genome. We therefore determined the frequency of all nucleotide mismatches for all FlyBase-listed TE insertions in our small RNA sequencing datasets (Figure  1G ). The amount of A to G mismatches is not elevated over other mismatches in early embryos (1.
Acknowledgements We thank  S. Chambeyron  and  Alain Pelisson  for sharing unpublished data and the  Galaxy community  for their support. This work received financial support to CA from the  Agence Nationale de la Recherche  grants  ANR-13-BSV2-0007  and  ANR-10-BLAN-1210. MdvB had a PhD fellowship from the  Ministère de la Recherche et de l'Enseignement Supérieur. The École normale supérieure genomic core facility was supported by the  France Génomique national infrastructure , funded as part of the  "Investissements d'Avenir" program  managed by the  Agence Nationale de la Recherche  (contract  ANR-10-INBS-09 ).
Background Antimicrobial resistance is a global concern that ought to be tackled by a 'One Health' approach  [1]. In the veterinary domain, this has driven the implementation of monitoring programmes of antimicrobial resistance levels and antimicrobial usage  [2] , especially in Europe  [3, 4] , where sales data are collected in nearly all Member States  [3]. In France, sales data on antimicrobial veterinary medicinal products (VMPs) have been collected yearly since 1999 by the National Veterinary Medicines Agency (Anses-ANMV). Data were first expressed as volumes (tons of active compounds), before being converted in exposure units  [4, 5]. Since 2009, attribution of VMPs sales to each animal production species is provided by manufacturers  [5]. In 2011, the French pig farmers' representative bodies, together with the French swine veterinary practitioners' associations, voluntarily implemented a consensus decision to limit prescription and usage of all third-and fourth generation cephalosporins.
Farm random sampling Previous on-farm surveys had been performed in Brittany, where over 50% of the national swine production is concentrated  [7]. From these data, 2 it was calculated that 127 randomly selected farms would provide a 15% precision level. In order for the samples to be representative of the French swine production, simple random sampling was then performed in the exhaustive national swine database of identification, BDPORC, 3 of which were excluded boar studs, farms located in Corsica and in the French overseas territories. Of those were selected farms with more than 49 sows, and farms with less than 50 sows but with more than 99 places in postweaning and/or fattening units, to exclude backyard pigs owners from the sampling frame. The working group deliberately elected to maximise the size of the sample, and an objective of 150 farms was defined for each survey.
Farm inclusion process In order to reach the pre-established target of 150 farms per studied year in 2010 and in 2013, 270 and 300 randomised farms were extracted from the national database, respectively. For each sampled farm, an explanatory letter detailing the study's principles and objectives was mailed to the corresponding production structure and treating veterinarian (as recorded in the database). Then, these professionals presented the information to the farmers, who decidedor notto participate. Participation was voluntary and was not object to any form of compensation.
The lists were required to mention the complete products' name, presentation including concentration, and quantities dispensed. For medicated feed, volume (tons), active substance(s) included in the feed and proportion (in ppm) were asked for. Finally, detailed data on the way farmers used VMPs were collected through phone interviews. Questions targeted: -The treated production stage(s): sows (including boars/gilts), suckling piglets, weaned piglets or fattening pigs. When the same VMP was administered to several production stages, the number of commercial units was dispatched according to the farmer's declaration. -The indication for the usage: the farmers were asked to mention the cause(s) of each treatment administered with the VMPs recorded (up to three indications per notified treatment were accepted).
Evolution of usage in suckling piglets Parenteral antimicrobial usage in suckling piglets was significantly reduced (-29% of nDD/animal) between 2010 and 2013 (p = 0. 05) (Table  2 ). The most drastic decrease was observed for cephalosporins (-89%). This reduction reflects the scarcity of this usage: 4% of the farms used cephalosporins in 2013, versus 18% in 2010. a National reference data from the national database BDPORC, extracted for years 2010 and 2013. Other national reference data are from the department of statistics of the French Ministry of Agriculture. There was no statistical significant difference, within each year, between the sample's criteria and those of the national reference (Chi-2 test).
On the other hand, the French ministry of Agriculture launched in June 2012 a plan to reduce by 25% veterinary antimicrobial consumption within 5 years, EcoAntibio 2017, 5 and this might also have positively influenced the enrolment of farmers in the 2013 sample. All the quantitative 2010 and 2013 data were harvested from reliable and comprehensive sources: acquired antimicrobial quantities were provided by the dispensing structure for each farm, from the list of providers that had been issued by each farmer, and yearly swine production was extracted from the farmers' accounts. The representativeness of each sample with the national swine herd population was verified against data from the two most recent agricultural censuses (2010 and 2013). Both samples being found representative, this provides robustness to the data on antimicrobial usage collected in both these instances.
Acknowledgements The authors are grateful to  Anne Chevance  and  Gérard Moulin  from  Anses-ANMV  for their support. The French Working Group 'antimicrobials in the swine industry' was composed, at the time of the 2010 and 2013 farm sample studies, of:  Philippe Le Coz , DVM and  Jean-Luc Sévin , DVM for the National Society of the  Technic Veterinary Groups (SNGTV) ,  Mélanie Liber , DVM, for the  Western France Porcine Veterinary Association (AVPO) ,  Sylvie Chouët , DVM,  Arlette Laval , DVM and  Jeanne Dupuis , DVM for the  French Branch of the International Pig Veterinary Society (AFMVP) ,  Jeff Trébaol  and  Caroline Tailleur , for the  National Swine Production Federation (FNP) ,  Yves Da Ros ,  Philippe Amar , DVM and  Valérie Bris , for the national  Agricultural Cooperative Union (Coop de France) ,  Patrick Gambade , DVM,  Estelle Morgand  and  Bruno Toussaint  for the  National Feed Industry Union (SNIA) ,  Nathalie Chatelier , DVM and  Joseph Gérard , for the  Gathering of Western France Meat Production Groups (UGPVB)  and  Roxane Rossel , DVM, for the  Aquitaine interprofessional Swine association (INPAQ).
A missense variant in the KIF1C gene is associated with progressive ataxia of Charolais cattle Genotyping of 46 suspected cases was done using the Illumina bovine 50K SNP chip (including 8 cases confirmed by histopathological analysis) (S1 Table ), followed by homozygosity mapping and haplotype analysis identified a single homozygous interval on bovine chromosome  19 (S2 Fig)  shared by 41 animals. The minimal common interval was 681 kb long (chr19: 26848700-27529700), and contained more than 40 genes as predicted in the Ensembl database. Whole-genome sequencing was performed on two affected animals (aged 31 and 36 months), and one wild type (WT) animal. Sequence analysis focused on this interval on chromosome 19. The detected polymorphisms (SNP and small indels) were then filtered in several steps.
First, affected cattle had to be homozygous for the causative variant, while the phenotypically WT cattle had to bear at least one WT allele. Second, since this mutation is supposedly specific to the Charolais breed, polymorphisms were discarded if they were already present in the dbSNP database and/or in the Illumina SNP chip. Finally, polymorphisms were filtered according to their predicted effects on transcript and/or protein, based on the hypothesis that this mutation is deleterious (Table  1 ). The only remaining putative causal SNP was a single substitution in exon 5 of KIF1C (chr19:27041449 C/T). For easier comprehension and since KIF1C gene in cattle is on the reverse strand, the substitution will be referred as KIF1C G>A in order to match with the transcription sense (Fig  1A ). The G>A substitution was further tested (Sanger sequencing) on 143 Charolais animals, including 70 of the 71 cases suspected of progressive ataxia for which DNA was available.
The KIF1C mutation results in loss of function The KIF1C gene, which is relatively conserved in mammals, encodes a microtubule-based motor protein belonging to the kinesin family  [27]  (respectively 1103 and 1105 amino acids long in human and bovine). This protein harbours an N-terminal kinesin motor domain, a central kinesin associated domain and a forkhead-associated (FHA) domain  [14]. The G>A KIF1C substitution leads to the replacement of an arginine by a glutamine (p. Arg203Gln), within the kinesin motor domain  (Fig 1B). This amino acid is highly conserved across evolution (Fig  1C ). Based on PROVEAN prediction software  [28] , this substitution is expected to be deleterious and affects the function of KIF1C (score = -3. 822). Moreover, the substitution affects the last nucleotide of exon 5, thus exon splicing is predicted to be impaired, inducing a reduction in the predicted splice score, which dropped from 7.
8 to 4. 8 when analysed with Splice Site Score Software (http://rulai. cshl. edu). The result of analysis with ESE-finder software  [29]  suggests that the mutation may also modify exonic splicing enhancer (ESE) motifs at the junction between exons 5 and 6, which would alter the affinity with several serine/arginine-rich (SR) proteins (S3 Fig). KIF1C is ubiquitously expressed in human and in mouse  [14, 27]. KIF1C mRNA expression was studied in affected and WT bovine brains, as this organ, together with lymph nodes, is known to present the main histological alterations in our model  [23]. Using primers spanning the mutation (i. e. amplifying exons 1 to 11), we showed that contrary to WT animals, affected ones could display two transcripts: a hardly detectable full-length transcript, visible in one affected case (same size as expected), and a shorter transcript (Fig  2A ).
Ethics statement All studied animals originated from diverse Charolais herds throughout France, and were normally bred by the breeders. All samples and data were obtained with the oral consent of breeders or breed organizations. Blood samples are those collected by veterinarians or by trained and licensed technicians during routine blood sampling for paternity testing, genomic selection or annual prophylaxis. All reported tissues were collected post-mortem after cattle were slaughtered for beef production at commercial slaughterhouses. No Institutional Animal Care and Use Committee (IACUC) or equivalent ethics committee(s) was required.
Whole-genome sequencing and analysis Whole-genome sequencing was performed in 2012 at the Get-PlaGe platform (http:// genomique. genotoul. fr/) on a HiSeq 2000 Illumina sequencer producing 100-bp-long pairedend reads, following the manufacturer's protocol. Three animals had their genomic DNA sequenced: two sick animals aged respectively 31 and 36 months at last examination and one healthy animal (natural death at 10 years old). Reads were quality checked and mapped on the UMD3. 1 reference genome using the BWA aln software (version 0. 5. 9-r16) [58]. The alignments were filtered with a minimum MAPQ value of 30. Reads that mapped to multiple localizations were removed. The target region identified by homozygosity mapping was selected on each produced bam file using Samtools (version 0. 1. 18) [59].
Local indel realignment and base quality recalibration were applied using GATK toolkit  [60]. Single nucleotide polymorphisms (SNPs) were predicted with samtools mpileup and bcftools, and annotated with the Ensembl Variant Effect Predictor tool  [61]. SNPs found in our studied breeds (Charolais, Limousin, Normande, Montbeliarde, Holstein, Blonde d'Aquitaine) were specified. Whole genome sequence data for the two sick animals are deposited in the European Nucleotide Archive under the study accession number: PRJEB27309.
Acknowledgments We thank  Dr. L. Bouslama  for critical reading of manuscript,  J. M. Nicol  for his involvement which facilitated identification of progressive ataxia cases in Charolais herds. We are grateful to the veterinarians and breeders who helped to recruit bovine cases, through the  French National Observatory of Bovine Abnormalities (ONAB) , assisted by  C. Grohs  and  C. Danchin-Burge. We are grateful to  O. Bouchez  and colleagues for technical support in sequencing experiments and bioinformatics analyses at the  Toulouse Midi-Pyrenees Genotoul platform. SNP genotyping was done at the  Labogena facility. We thank the  Plateformes ICM Quant and Histomic  for their contribution.