dataesr/scientific-paragraphs-categorization huggingface dataset:
Statistics Statistical significance was assessed using Prism 7 software (GraphPad, La Jolla, CA). Two-or 3-way analysis of variance (Bonferroni post hoc analysis) was applied for multiple-and 3-group comparison, respectively. A 2-tailed Student t test was performed for 2-group comparison of parametric data. P #. 05 was considered significant. All data are presented as mean 6 standard deviation (SD).
Acknowledgments The authors thank  Jerry Ware  ( University of Arkansas ),  Dougald M. Monroe III  ( University of North Carolina at Chapel Hill ),  Brian Petrich  ( Emory University ), and  Pamela B. Conley  ( Portola Pharmaceuticals Inc. ) for providing mice deficient in extracellular GPIba, VWF, talin1, and  P2Y12 , respectively. The authors also thank  Delphine Borgel  (INSERM,  UMR-S1176 ,  Universit é Paris-Sud, Universit é Paris-Saclay, Le Kremlin-Bic être, France and Assistance Publique-H ôpitaux de Paris, Laboratoire d'H ématologie, H ôpital Universitaire Necker-Enfants Malades ) and  Jenny Goudemand  ( D épartement d'H ématologie et de Transfusion, Centre Hospitalier Universitaire de Lille, Universit é Lille 2, EA 2693, Facult é de Médecine, Lille, France , and  Institut Pasteur de Lille ,  European Genomic Institute for Diabetes, INSERM UMR 1011, Universit é Lille 2, Lille, France ) for valuable help with enrolling patients and providing clinical laboratory information.
9, 10 In daily life conditions, IEs can be more simply detected as a decrease in airway pressure (Paw) with a simultaneous drop in expiratory flow during expiration, followed in some cases by inspiratory flow initiation that fails to trigger the ventilator or, if the expiration has ended, by an inspiratory flow increase that does not trigger the ventilator. 11 This noninvasive method can be easily used with the data provided by ventilators' software. However, whether it is sufficiently sensitive in patients with impaired inspiratory muscle function due to neuromuscular disease is unclear. The aim of this study was to assess the performance of noninvasive IE detection based on pressure and flow signals, using Pes monitoring as the reference standard.
Statistical analysis The statistical analysis was conducted using SPSS 15. 0 Command Syntax Reference 2006 (SPSS, Chicago, Illinois, USA). Continuous variables were described as mean + SD and range and dichotomous or categorical variables as percentages. Pes measurement was the reference standard for diagnosing IE. A true-positive result was an IE detected using the noninvasive method and confirmed by the invasive method (Figure  2 ), a true-negative result was cycling of all breaths by the ventilator (Figure  2 ), a falsepositive result was an IE detected using the noninvasive method but not confirmed by the invasive method, and a false-negative result was an IE detected by the invasive method but missed by the noninvasive method. Standard formulas were used to calculate sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV).
Funding The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was supported by a grant from the  French Ministry of Health (PHRC). Figure 6. Delayed triggering of the ventilator simulating ineffective efforts. The dashed line indicates zero flow. The solid vertical line and black arrow mark the beginning of an inspiratory effort, indicating delayed triggering of the ventilator. Pdi: transdiaphragmatic pressure; Pes: esophageal pressure; Paw: airway pressure.
Pigmentation genes and their functional classification Vertebrate pigmentation genes (PGs) are defined here as genes that are involved in the differentiation of a neural-crest derived pigment cell in at least one vertebrate species. This strict definition excludes in particular pigment cells present in the retinal pigmented epithelium, an anterior neural plate derivative  (Ramón Martínez-Morales et al. 2004). According to this definition, one PG can be implicated in pigment cell differentiation in one species but not in others. To establish the PG dataset used in this study (Figure  1 ; Table  S1 ), we first retrieved genes annotated under the Gene Ontology (GO) term "pigmentation" (GO: 0043473) in vertebrates (taxon identifier: 7742) (http://www. geneontology. org/, last accessed on March 08 th , 2017).
We manually verified the correspondence of automatic GO annotations with our definition of a pigmentation gene and, when necessary, excluded some genes from the list. For instance, sod2 was not kept in our dataset because its deficiency causes red blood cell damage  (Friedman et al. 2004). As such, it does not fit the definition above. In addition, all genes previously described in two former papers on vertebrate pigmentation were included  (Hoekstra 2006; Braasch et al. 2009a). PGs from these different sources were sometimes redundant (Figure  1 ). Finally, we conducted a review of the literature to include PGs from more recent studies (Figure  1 ; Table  S1 ). Based on previous work, Figure  1  Origin of pigmentation genes studied in this work. Most PGs were either retrieved using the Gene Ontology term "pigmentation" (GO: 0043473) parsed for vertebrates (taxon id: 7742) or were previously cited in two studies  (Hoekstra 2006; Braasch et al.
To encompass the broad diversity of vertebrates we additionally included the genome of a chondrichthyan (cartilaginous fish), the elephant shark Callorhinchus milii. At the time of analysis, data from the lamprey genome were too incomplete to be included in the study. Sequences from five non-vertebrate deuterostomes that diverged from the vertebrate lineage before the 1R/2R WGDs were used as outgroups in the molecular phylogenies: the two urochordates Ciona intestinalis and C. savignyi, the cephalochordate Branchiostoma floridae (amphioxus) and the more distantly related ambulacrarians Strongylocentrus purpuratus (echinoderm) and Saccoglossus kowalevskii (hemichordate). For each species, protein sequences of the longest isoform were retrieved from Ensembl v86 (www. ensembl. org; Oct. 2016) and NCBI (https://www.
ncbi. nlm. nih. gov/, last accessed March 08 th , 2017). When an Ensembl sequence was missing from the Ensembl annotation pipeline, we manually tested on the genome assembly (using Ensembl BLASTn method with the closest ortholog as query) whether this was due to gene loss or annotation skews. In the latter case, we used the FGENESH+ program of the Softberry suite (http://www. softberry. com/) to extract the gene sequence and predict the protein sequence. Sequence alignments were performed using Clustal Omega v1. 2. 1 (Sievers and Higgins 2014) with default parameters and were individually manually curated for each PGCF  (Blouin et al. 2009). Each alignment was then analyzed using the software prottest3 v. 3. 4. 2  (Darriba et al. 2011 ) and the evolutionary model for tree-building was selected based on the Bayesian information criterion  (Luo et al.
2010). Tree building was conducted with the best fitting model using the Maximum Likelihood method implemented in PhyML v3. 1  (Guindon et al. 2010)  with SH-aLRT support  (Le and Gascuel 2008; Anisimova et al. 2011). The best-fitting model for each alignment is available (Table  S2 ). In order to assess if a duplication event was likely to be due to Ts3R and not to a small-scale duplication (SSD), and to identify large paralogons supporting Ts3R evidence, we conducted for each gene a synteny analysis using the Genomicus web browser (v86; http:// genomicus. biologie. ens. fr/genomicus-86. 01/cgi-bin/search. pl) (Louis et al. 2015). Finally, as genes can be described in different organisms with different names, we used the unified nomenclature system for humans provided by the HGNC Database  (Gray et al.
Pathway enrichment analysis and protein-protein interaction networks For each gene (PGs and their corresponding vertebrate 1R/2R-ohnologs, if any), we retrieved the UniProt ID of the human ortholog in the UniProtKB/Swiss-Prot database (www. uniprot. org/, The UniProt Consortium 2015, last accessed March 08 th , 2017). Gene IDs were used to test for enrichment in Gene Ontology (GO) terms with g: Profiler (http://biit. cs. ut. ee/gprofiler/)  (Reimand et al. 2016 ) using default parameters and the human genome as background. The significance threshold for enrichment was set at 0. 05 (corrected p-value for multiple testing with Benjamini-Hochberg FDR) and the "Hierarchical filtering" was set at "Best per parent group" to obtain only hierarchically highest GO terms. The number of interactions for each protein was obtained from the manually curated "Binary interactions" tab in UniProt.
Vertebrate pigmentation genes and pigmentation gene-containing families We analyzed Gene Ontology databases and the existing literature to obtain a list of 198 vertebrate PGs that correspond to 181 PGCFs (the number of genes here is estimated after 1R/2R but before Ts3R; see Methods for details). Seventeen PGCFs contained two PGs, sometimes with different pigmentary functions (see Table  S3 ). In contrast, most families (164/181) possessed only one PG, with its "non-PG" 1R/2R-ohnolog(s) (if any) having to the best of our knowledge no function described to date in the development of neural crest derived-pigment cells (either experimental evidence or absence of data). The evolutionary history of nine gene families (asip, foxd3, gja5, krt2a, rab8a, slc2a11, ugt1a8, xdh and zic2) was too ambiguous to be included in our study because of the presence of many independent segmental duplication events and low phylogenetic resolution (this was previously reported for the asip gene family  (Cal et al.
2017b) ; data not shown). We also excluded the bcl2l11, defb103a and krtap21-1 families because these genes are either tetrapod-specific (bcl2l11) or eutherianspecific (defb103a, krtap21-1). The final analyzed dataset therefore consisted of 184 PGs and 144 non-PG paralogs for a total of 328 total genes within 169 PGCFs. After phylogenetic and genomic analyses of 27 deuterostomes species (including 22 vertebrates), orthology and paralogy relationships were established for all the 328 genes. A schematic representation of the occurrence of all genes with copy numbers (corresponding to a total of 9,112 sequences) is provided for each studied species (see Figure  S4A-J  and an example case Figure  S5 ). Retention rates of pigmentation genes after the fishspecific WGDs (Ts3R and Ss4R) are higher than genome average We first observed that the global retention rate (RR) of PGs after Ts3R was 34.
2% (= 63/184) (Figure  3 ; Table  1 ). Interestingly, this rate was significantly higher than the range of values reported for the whole genome, i. e. , 4-18% depending on the datasets used  (Jaillon et al. 2004; Woods et al. 2005; Brunet et al. 2006; Howe et al. 2013; Inoue et al. 2015 ) (P = 1. 8 • 10 28 , chi2 test). Of note, values published in earlier studies were recalculated if needed before comparison to be consistent with our calculation method. This indicated that PGs have been globally more frequently retained as duplicates than other genes after the Ts3R WGD. After the salmon-specific Ss4R WGD, the RR was 75. 2% for PGs (182/242; Figure  3 ; Table  1 ). Again, this value was higher than the value reported for the whole genome (48-55%, P = 4. 3 • 10 210 , respectively, chi2 test)  (Berthelot et al.
2014; Bright et al. 2017). Hence, we hypothesized that genes in families with high RRs would have more "central" molecular functions (e. g. , transcription factors or intracellular signaling actors such as protein kinases) than PGs in families with low retention rates. Accordingly, enrichment analyses in Gene Ontology terms on genes in multigenic PGCFs showed that the most significant "Molecular Function" term was "transcription regulatory region DNA binding" (Table  S4A ). In contrast, PGs in monogenic PGCFs were mostly enriched in metabolic enzymes (Table  S4B ). In addition, we estimated the number of interaction partners for each pigmentation protein using the UniProtKB/Swiss-Prot database (selfinteractions being excluded). We showed that products of genes in multigenic PGCFs held more interactions on average than PGs in monogenic PGCFs (n = 5.
DISCUSSION In this study, we first showed that pigmentation genes were on average more retained than the genome average after both teleost-specific Ts3R and Ss4R WGDs, but not after the 1R/2R WGDs. Non-pigmentary post-1R/2R ohnologs of pigmentation genes are also more retained than the rest of the genome after WGDs in teleosts, suggesting that the function in pigmentation is not the only factor determining gene retention. After the Retention rates for pigmentation genes from monogenic and multigenic families after successive WGDs in vertebrates. Green and orange boxes (respectively black and white) represent number of genes that are whether retained or not at the considered WGD for PGs (respectively non-PGs paralogs in multigenic PGCFs). Total numbers of genes per dataset are indicated. For 1R/2R, the bar does not represent retention rates but the 77 monogenic PGCFs vs.
informatics. jax. org/allele) as well as in the Zebrafish Information network databases (last accessed February 9 th , 2018), two of the most comprehensive mutant databases in vertebrates. Most presumed "non-pigmentary" post-1R/2R paralogs of PGs had indeed no "pigmentation" mutant described, confirming the robustness of the dichotomization "pigmentation"/"non-pigmentation" used here (data not shown). The lack of functional evidence can nevertheless either reflect a "real" absence of effect on pigmentation, or an artifactual lack of evidence due to a small number of studies. A putative ancestral pigmentation gene repertoire in jawed vertebrates Mammals only have one pigment cell type (melanocytes), while birds, lepidosaurians and amphibians have four to five. As already suggested by others, early gnathostomes (jawed vertebrates) were likely to possess most of these pigment cell types  (Lapedriza et al.
The numerical simulations performed with MULTICOR-3D software on an operating ball bearing shown that the lubrication regime at the rolling element-raceway contact can be easily monitored and quantitatively identified. To assess the efficiency of the discrete modelling, a parametric study is carried out in order to exhibit how the operating conditions affect the lubrication regimes and the fluid film spread in the loaded zone. The adequacy between the choice of lubricant and the bearing tribofinition is sought to optimize the component lifetime.
Moreover, the increasing developments related to tribological studies have considerably enhanced our understanding of the mechanisms of lubrication that take place in highly loaded non-conformal contacts, in the case of rolling bearings, gears and cams  [12, 13] , as well as for the identification of the fluid film thickness  [14, 15]  and the characterization of the friction behaviour  [16, 17]. Wear and fatigue damage behaviour in bearings is hard to describe theoretically and numerically. Indeed, both wear and fatigue mechanisms are quite complex and essentially dependent on operating conditions, lubricant quality associated with a good mounting and a suitable bearing design. To overcome these limitations, a numerical twin of bearings, based on DEM using MULTICOR-2D software, has been developed to enable users to access outputs relative to damage initiation and to improve coupling models for monitoring  [18, 19].
In this paper, a 3D DEM model is enriched with the phenomenological contribution of lubrication, in order to develop a monitoring tool based on an electrical measurement  [21]. In this sense, the lubricant consideration must remain sufficiently adapted to the scale of the apparent contact, where the competition between the metal-metal contact with asperities (resistive) and the contact through the fluid (capacitive) plays an essential role in electromechanical coupling. To achieve this proposal, from a mechanical standpoint, a three dimensional dynamic model for ball bearings based on MULTICOR-3D software is developed. The aim is to create a lubrication model by using a discrete formulation. The proposed model implements a major part of the functionalities according to the state of the art, such as the slice model, the mutual influences of neighbouring elements with clearance, elastic contact models, lubricant film estimation, damping forces, centrifugal forces, etc.
The simulated radial ball bearing of 6208 series is designed fully and accurately in accordance with its geometrical conformity. Moreover, a mechanical formulation, based on contact stiffness for elliptic areas and viscous damping effects is developed. With the assumption of piezo-viscous-elastic fluid behaviour, an EHL model is implemented in the numerical software allowing the determination of the viscous damping due to the fluid film. Numerical simulations are carried out with MULTICOR-3D software to validate the proposed discrete model of radial ball bearing and are presented and discussed in Appendix A. The third section treats the qualitative prediction of the lubrication regimes in an operating radial ball bearing. To exhibit the relevance of the DEM approach, several operating conditions are considered.
Generally, the minimum thickness of the fluid film is of the order of the roughness; nevertheless, in the case of optimal conditions at high speed and adequate viscosity, the fluid film exceeds the size of the surface asperities so that a fluid film thickness of several micrometers can be reached, 3 to 10 × σ a  [47, 48]. In this section, numerical simulations carried out with MULTICOR-3D software will be discussed. The lubrication regimes of a radial ball bearing under operating conditions are investigated by taking into account both imposed mechanical loading and fixed kinematic conditions. Sensitivity analyses are performed on the main driven parameters, namely the radial load F r , the diametral clearance P d and the angular speed ω of the inner ring, which more or less may affect the lubrication regime.
Conclusions and Perspectives Through this study we wanted to highlight the relevance of the DEM approach in describing the dynamic behaviour of multicontact systems such as rolling bearings. Under a quasi-static radial load, the proposed discrete description of a radial ball bearing, using a contact stiffness model based on elliptic integrals, achieves very similar radial deflection and normal load distributions in comparison to analytic formulation  [45]. The implementation of the discrete model in the MULTICOR-3D software allowed us to investigate the lubrication regimes from a qualitative point of view under operating conditions. Moreover, in the context of the EHL study, the DEM has proven to be a useful numerical tool since it enables continuous prediction of the lubrication regimes and dynamic management of the contact interface.
For a radial ball bearing with zero clearance under radial load F r , Stribeck  [11]  determined that: Q max = F r Z J r (ε) (A3) with Z the number of rolling elements (Z = 9) and J r the radial integral. For example, for a radial ball bearing with zero clearance (P d = 0, ε = 0. 5) the radial integral J r is of 0. 2288  [45]. To validate the discrete model of a radial ball bearing, numerical simulations are performed with MULTICOR-3D software under quasistatic loading. Figure  A1a ,b exhibit the radial deflection δ ψ and the normal load Q ψ plotted with respect to azimuth angle ψ of rolling element. Three types of clearance are considered, ε = 0. 685, ε = 0. 5 and ε = 0. 4 which corresponds to three configurations with negative clearance (P d = -12. 6 µm), zero clearance (P d = 0) and positive clearance (P d = 12.
Background Many tools have been developed for the standardized collection of cancer family history (fh). However, it remains unclear which tools have the potential to help health professionals overcome traditional barriers to collecting such histories. In this review, we describe the characteristics, validation process, and performance of existing tools and appraise the extent to which those tools can support health professionals in identifying and managing at-risk individuals. Methods Studies were identified through searches of the medline, embase, and Cochrane central databases from October 2015 to September 2016. Articles were included if they described a cancer fh collection tool, its use, and its validation process.
Despite its essential role in cancer-risk prevention, fh is not systematically or adequately collected in clinical settings  9, 10. Hence, at-risk individuals remain unidentified  11, 12. Furthermore, when fh is collected, followed-up recommendations are not always provided  13, 14. Thus, at-risk individuals might not be referred to the appropriate resources  9, 15  or might be falsely reassured  16. Barriers to collecting fh in clinical settings include poor reimbursement, provider's lack of time and expertise, lack of guidelines and adequate tools, and limited functionality of electronic health information systems to capture and interpret fh data  17. The use of adapted fh collection tools could potentially alleviate some of those barriers and assist providers in collecting and interpreting fh.
METHODS Data Sources and Inclusion Criteria We searched the medline, embase, and Cochrane central databases using combinations of the words "family history," "taking," "collection," "assessment," "cancer risk," "tools," "cancer," "questionnaire," "instrument," and "validation. " We applied the PubMed function "similar articles" to articles meeting our inclusion criteria and searched the lists thus generated by PubMed. We also manually searched bibliographic references of retrieved articles and systematic reviews. No time limit was applied to the search. The final literature search took place on 1 September 2016. To be included in the analysis, articles had to meet these inclusion criteria: publication in English or French, description of a tool used to collect cancer fh in adults, primary focus on the collection of fh, and evaluation of the potential benefits and psychological impacts of a fh collection tool.
Data Extraction and Analysis A descriptive approach was used to summarize the features and validation process of the retained tools. The tools were described based on characteristics previously reported in three systematic reviews  [18] [19] [20]  , but user experience was also included in our analysis. An Excel database (Microsoft Corporation, Redmond, WA, U. S. A. ) containing 51 variables was created to describe study and tool characteristics, including tool name, first author name, year of publication, country, and setting in which the tool was tested or used. Properties and attributes of the tools were grouped to build the framework used to conduct our analyses and to present results. Components of that framework included diseases or cancers targeted, tool format, and the tool's capacity to produce pedigrees, perform risk assessment and stratification, deliver recommendations.
However, updates to the fh are possible in only 3 of them (MeTree, Hughes Risk App, Cancer in the Family)  42, 86, 89. Only 2 (Health Heritage, Me-Tree)  11, 42  were evaluated for fh accuracy and completeness, and risk-assessment accuracy or compliance with proposed genetics referral guidelines. Moreover, only 3 were deemed easy to use (Health Heritage, CancerGene Connect, Cancer in the Family)  11, 89, 91. More importantly, none are embedded into an ehr system. Hickey et al. 100  and Feero et al. 101  made a case for integrating, into ehrs, a common fh core dataset that would allow for the standardized collection and exchange of fh throughout health information systems, ensuring a continuum of patient care. Although none of these 6 proposed tools are "ideal" cancer fh questionnaires, they can still help health care providers to identify at-risk individuals and families.