dataesr/scientific-paragraphs-categorization huggingface dataset:
Weighting and Selecting Annotations Using the linker ranking from the previous step, the annotations are voted, and selected for final output or rejected based on the vote. We used two voting schemes. The first one relies on each annotation's confidence score, weighted by the annotator's rank and precision on the ranking datasets from 3. 2. The rationale is that a high-confidence annotation for a low-ranked annotator can be better than a low-confidence annotation for a higherranked annotator. The definition is in Figure  1 : For each annotation (m, e) in the results, m is its mention, 9 e is the entity paired with m, and Ω m is the set of annotations in the results whose mentions overlap 10 with m. If the size of Ω m is 1, the scaled confidence 11 o scf of Ω m 's unique annotation ο must reach threshold t uniq in order for ο to be accepted.
for each set Ω m of overlapping annotations: for L ∊ Ω m : The entity for the subset L which obtains the highest vote among Ω m 's subsets is selected if its vote is higher than P max , i. e. the maximum precision in the ranking dataset (0. 568, see Section 3. 2). After selecting the winning entity, we still need to select a mention for it. The mention is selected at random among the mentions of the annotations in the winning subset L. This implementation of mention selection is meant as a baseline that can be refined in the future. Two initial factors to consider in mention selection would be mention length and the annotators having chosen each mention. vote(L) = ∑ (N -( ro ant -α )) • Po ant o ∈ L N if max L ∊ Ω m (vote(L) ) > P max : select argmax L ∊ Ω m (vote(L)).
Introduction Coevolving positions in the amino acid sequences of proteins are studied most often in terms of contact sites between or within protein molecules. Coevolution is considered also in terms of epistasis when functionally interdependent sites are involved  [1, 2]. Further, distant sites could be bound by allosteric tracts  [3, 4]  and/or electrostatic interactions. The availability of large databases of homologous sequences and of methods refined for the detection of direct interactions (direct coupling analysis  [5, 6] ) are prerequisites for an increasingly reliable statistical analysis of coevolution. A sizable collection of sequences is available from the genome of the highly variable HIV (http://www. hiv. lanl. gov/). Despite of a high rate of mutation the envelop proteinretains a dense glycosylation covering most of the exposed surface of the spike trimer.
[10]. The authors use a mutual information measure of coevolution with a level of significance determined by a bootstrap procedure, which is not sufficient to offset the entropy dependence and does not remove the chain effects. Consequently, the results are highly restricted and fail to demonstrate the obvious coevolution couplings for instance of adjacent and contacting residues. Most studies of the structural aspects of Env gp120 to date have focused on clade B (  [11] [12] [13] [14] [15] [16]  just to name a few). Utilizing this information, we studied the network of coevolving primary structure positions in Clade B gp120 based on a set of sequences from the database maintained at the Los Alamos National Laboratory (LANL) using mean field direct coupling analysis (mfDCA)  [17]. The results were mapped onto the common residues involved in the structure 2B4C, which is also based on a Clade B isolate and features the constant core with the V3 loop in receptor and X5 antibody bound conformation.
Sequences and models To reduce the phylogenetic and sequence bias artefacts, a multiple sequence alignment was used that: 1) was restricted to one clade (B), 2) to one sequence per patient and 3) to sequences with less than 80% homology to any other. Ensuring a relatively homogenous evolutionary distance between the sequences avoids the phylogenetic artefact caused by deep trees with few main branches. This MSA (n = 984) is documented in S1 Dataset. In addition, positions were retained if they were less than 99% conserved and contained less than 20% gaps-this MSA is also part of S1 and S2 Datasets. The study was based on the clade B 2B4C crystal structure, which presents also the V3 loop but has a truncated V1/V2 loop and the N terminal 53 amino acids  [13]. The final alignment contained 742 sequences and 327 positions with 64 sequons and 94 sequon related positions (SRP: P1 -N or P3 -S/T), of which respectively 40 and 61 are represented in 2B4C.
The MSA was performed on the LANL server. The non-random occurrence of sequons was determined based on the hypothesis of random co-occurrence of N and S or T and the respective marginal frequencies in the MSA yielding 16 instance for this set of sequences. Thus, only those sequons were considered, which reoccurred 17 or more times at a particular position. Molecular graphics were generated using the UCSF Chimera package. Chimera is developed by the Resource for Biocomputing, Visualization, and Informatics at the University of California, San Francisco (supported by NIGMS P41-GM103311)  [19]. The method of mfDCA is described in detail elsewhere  [5, 6, 17]  and the algorithm in Matlab implementation is available at http://dca. upmc. fr/DCA/DCA. html. The essential property of this algorithm is that by using mean field approximation rather than belief propagation it provides a faster algorithm for eliminating the chain covariance effects and detects only the direct interaction between two positions in the sequence based on the observable covariances.
Both methods can be viewed as "inference engines" acting on the statistical information encoded in large Bayesian networks  [20]. The mfDCA results are found to outperform those generated by simple covariance analysis as well as approximate Bayesian analysis  [17]. The mfDCA algorithm was applied to the Clade B MSA without change. The baseline mfDCA values were determined as the maximal mfDCA value for each position from 100 sequence alignments derived from the original MSA after scrambling separately each column. This preserves the marginal frequencies but destroys the inter position correlations (the script is in S2 File).
Graph visualization The set of relations was further analyzed as an undirected weighted graph and visualized using Gephi 0. 8. 2 software (www. gephi. org) [21]. For the graph analysis, the weight of the edges was calculated as: w i;j ¼ ÀlogD i;j ; where D i,j is the mfDCA value of the significant couplings. Since 0<D<1, the lower weight corresponded to higher mfDCA value, which was necessary for the correct application of most of the graph analysis algorithms. The layout was generated by applying first a circular layout based on amino acid positions followed by ForceAtlas 2 algorithm (https://gephi. org/docs/ toolkit/org/gephi/layout/plugin/forceAtlas/ForceAtlasLayout. html) with the following parameters: Dissuade Hubs, Prevent Overlap, Edge Weight Influence = 1. 0, Scaling = 30, Gravity = 0.
Betweenness centrality and all shortest paths The betweenness centrality was calculated by the Ulrik Brandes algorithm as implemented in the Gephi suit  [22]  as well as by the David Gleich Matlab_BGL package based on the Boost graph Library (https://www. cs. purdue. edu/homes/dgleich/packages/matlab_bgl/) both algorithms giving the same result. The shortest paths were found using the Dijkstra algorithm as implemented in the GraphTheory Matlab package.
Mapping the potential N-glycosylation sites Relating position entropy to frequency of sequon related asparagine grouped the potential Nglycosylation sites in 3 groups:-frequent (13 N and 10 S/T positions), rare (20 N and 14 S/T positions) and highly variable (31 N and 6 S/T positions) (Fig  4A ). Some N positions coincide with S/T positions of an adjacent sequon so S/T positions are fewer. This classification omits the highly conserved positions N88 and N262, which were filtered initially. Since all the sequons represent only potential glycosylation sites from here on we shall omit the word potential but it will be implied all through this report. The complete list of the analyzed sequon positions is given in S1 Dataset. The variable positions are characteristic of the variable loops V1/ V2, V4 and V5.
Several attempts were made to describe co-evolutionary patterns of gp120 in the recent years. Early on Korber et al. [30]  studied the covariance of mutations in the V3 loop of the envelop protein of HIV type 1. A group of connected positions including S306, H308, A316, F 317, G321 and E322 was identified. A good agreement was found between this data and the mfDCA network, which showed a highly connected clique containing these and adjacent V3 residues. Korber at al. did not correct for the entropy and chain effects but instead calculated statistical significance only by a bootstrap procedure. It is possible that the clique type of connectivity allowed for an equivalence between the two methods. Wei et al. analyzed separately B and C clade sequences and found considerable differences in the C terminal part, which evolves much faster in clade C  [10].
RNA extraction and microarrays Cell lysis and RNA extraction were performed in Trizol (Invitrogen Life Technologies, Cergy Pontoise, France). RNA quality was checked with an Agilent bioanalyzer [RNA integrity number (RIN) >9]. RNA profi ling was performed using a high-density oligonucleotide array covering the whole human genome (Genechip human genome U133 Plus 2. 0; Affymetrix, Santa Clara, CA). Sample processing and array hybridization was performed according to the manufacturer's protocols. Expression values and absent/present/marginal calls were calculated using the GCOS v1. 4 software (Affymetrix). Absolute expression transcript levels were normalized for each chip by globally scaling all probe sets to a target signal intensity of 500. chemokines, run aggressive enzymatic attacks, and activate lymphocytes of innate and adaptive responses.
Oil Red O and Hoechst DNA staining Cells were fi xed with 4% formaldehyde for 15 min at room temperature and subsequently stained with a solution of 0. 4% Oil Red O dissolved in isopropanol (Sigma-Aldrich) for 20 min and gently shaken at room temperature. After three washes in water, DNA was stained with 10 g/ml of Hoechst 33342 (Sigma-Aldrich) for 30 min at room temperature. Pictures were analyzed using a Leica DMiRB microscope equipped with ×40/0. 30 NA or ×40/0. 55 NA objective lenses (Leica) a Leica DC300F camera and the Leica FW400 software.
Bodipy-FL-C16 capture Cells  (10 5  ) were resuspended in 100 µl PBS with or without 0. 5 µg/ml of Bodipy-FL-C16 (Invitrogen) and incubated at 37°C or at 4°C for 10 min. Cells were washed fi ve times by centrifugation at 450 g for 5 min in ice-cold PBS containing 0. 2% BSA. Fluorescence was measured by fl ow cytometry on a LSRII and analyzed using the FlowJo software. The intracellular Bodipy-FL-C16 fl uorescence was estimated from the shift in the mean fl uorescence intensity between 37°C and 4°C.
Analysis of microarray data Data were fi ltered on the detection call so that probe sets with an absent call among all samples were excluded from the analysis. Statistical analyses were performed on 33,253 probe sets with linear models for microarray data (LIMMA) package  ( 21 )  in R/Bioconductor. LIMMA uses moderated t -statistics, which provides for greater power at small sample sizes. Probe sets with a Benjamini-Hochberg-corrected P value р 0. 01 and a fold change у 2 or р 0. 5 in DC-17 versus DC were considered as differentially expressed. The regulated gene ontology (GO) biological pathways were identifi ed using DAVID (Database for Annotations, Visualization and Integrated Discovery)  ( 22 ). The data set is available from the Gene Expression Omnibus database (GSE53163).
Based on prior studies demonstrating that Socs3 negatively regulates IL-17A expression in T cells  ( 39 ) , Socs3 Ϫ / Ϫ Ldlr Ϫ / Ϫ chimeric mice were generated and had reduced atherogenesis  ( 40 ). Anti-IL-17A antibody treatment or IL-17A defi ciency increased plaque formation in those mice, suggesting that IL-17A may be antiatherogenic when the Apoe gene is functional  ( 41, 42 ). Assuming that IL-17Adependent foamy DCs are physiologically relevant, our in vitro data provide knowledge to solve the apparent discrepancies on the role of IL-17A in atherosclerosis mouse Monocytes (Mo), monocyte-derived macrophages (MP), and monocyte-derived DCs before (DC) and after (DC-17) 6 days of treatment with IL-17A. Expression of the indicated markers was analyzed on Mo, MP, DC, and DC-17 by fl ow cytometry.
The ADA, the American Heart Association, and many other national and international organizations, including French guidelines at the time of data collection, consider statins to be the drugs of choice for lipidbased cardiovascular risk reduction in diabetic patients with additional risk factors when not contraindicated  [5]. It is not known how these guidelines are applied in primary care. This study was therefore designed to describe the prescribing habits of family physicians in terms of their choice between statins and fibrates when initiating lipid-lowering drug primary prevention in diabetic patients with high cardiovascular risk, by using a nationwide database. The incidence of cardiovascular events and death associated with these drugs up to 30 months after initiation of treatment was also compared.
Study design and data source Detailed methods are provided in S1 Text. Briefly, we conducted a historical cohort study based on nationwide data from the French National Health Insurance Information System (SNIIRAM), which contains individualized, anonymous, and comprehensive data on health spending reimbursements and demographic data  [6]. Information on 100% reimbursed severe and costly chronic diseases including diabetes and hypertension, is available in the SNIIRAM  [7]. These data can be linked to the French Hospital Discharge database (PMSI)  [8]. This database provides detailed medical information on all admissions in public and private hospitals, including discharge diagnosis ICD-10 codes and medical procedures performed during the stay. The authors were not involved in the initial data collection.
In France, only confidentiality approval from the Commission Nationale de l'Informatique et des Libertés (CNIL) [French data protection authority] is required for non-interventional observational studies; ethical approval is not mandatory (Law No. 2004-800 on bioethics, Aug. 6, 2004). CNIL approval for our data source had been obtained previously (CNIL AT/CPZ/ SVT/JB/DP/CR05222O  (Jun. 14, 2005) ; DP/CR071761 (Aug. 28, 2007) ). Informed consent was not required, as patients' data were anonymized and de-identified prior to analysis. The national health administrative database can be accessed upon authorization delivered by the CNIL, 8, rue Vivienne, CS 30223, 75083 Paris cedex 02 (http://www. cnil. fr/les-themes/sante/ fiche-pratique/article/communication-des-donnees-de-sante/). A description of the process, in English, is available at http://www.
Study population Eligible patients were registered in the French national health insurance general scheme, who initiated fibrate or statin monotherapy (2 consecutive reimbursements) prescribed by a general practitioner between 1 st July 2008 and 31 st December 2009, with T2D and hypertension (defined by at least 3 reimbursements of oral antidiabetic/antihypertensive drugs over one year during the 30 months prior to study entry) at the date of first reimbursement of a fibrate or statin, corresponding to the date of study inclusion (Fig  1 ). This 30-month period was the longest period available in our database. Patients had to be over the age of 50 (men) and 60 (women), these gender-specific thresholds being considered in the recommendations and guidelines provided by The French National Health Authority (HAS, Haute Autorité de Santé) as defining a cardiovascular risk factor.
Moreover, the reimbursement rate for serum creatine kinase assay during the year preceding first use of the index lipid-lowering drug was less than 10% for the two drugs. This low rate does not suggest that muscle adverse effects were a special concern or that fibrate users in this study were statinintolerant. Fibrates may also be preferred due to the presence of hypertriglyceridemia, a common feature of diabetes. This possibility cannot be excluded, as the French administrative database does not include laboratory test results. Another consideration is the potential fear of aggravating diabetes with the initiation of statins  [16]. However, this notion is quite recent. Moreover, guidelines clearly indicate that statins should be first-line treatment in high-risk diabetic patients and a trial of fenofibrate in diabetic patients failed to demonstrate any benefit on coronary outcomes  [3].
Limitations First, the present study is a retrospective observational analysis and not all possible confounders can be accounted for. This study was based on several independently collected, French nationwide medical administrative databases, resulting in a decreased risk of selection biases. These databases are considered to be comprehensive, with annual quality controls of coding. However, during acute care or long-term hospitalization, as with long-stay institutions, current medications are included in hospital costs and individual medications cannot be identified. We may therefore have unintentionally neglected older populations in whom lipid-lowering drug therapy was initiated in long-stay hospitals or institutions, but this bias is not expected to have a major impact on the generalizability of our conclusions.
Due to legal restrictions concerning access to the databases, pre-inclusion use of lipid-lowering drugs could not be excluded for periods of more than 30 months. There is therefore a possibility that patients who failed to respond to previous statin therapy could have been included. A small proportion of the patients included were treated with clopidogrel; this treatment can be considered to be a marker of an undocumented cardiovascular event, but it is not expected to change the guidelines concerning the use of a statin rather than a fibrate. Sensitivity analyses including a specific approach based on propensity scores was conducted and reached similar conclusions, although we admit that the data included in the propensity score were the same as those entered in the Cox analysis, and that residual confounding remains a potential limitation.
Statistical analysis was conducted according to an intention-totreat approach, which means that a patient who initiated treatment with a fibrate and who was then switched to a statin, remained in the fibrate group for the analysis. However, the intentionto-treat approach cannot be expected to have induced the association between the fibrate covariate and clinical outcome, as this approach is conservative and would attenuate rather than accentuate any associations. Moreover, the same results were obtained in a sensitivity analysis in which data for switchers were censored after a 6-month follow-up. The main limitation concerns from the lack of behavioral data, like smoking habits, and of laboratory test results in the databases. These variables may participate to residual confounding. However, the guidelines emphasize the benefit associated with the use of statins in high-risk patients, regardless of baseline LDL-cholesterol, and the study population was undoubtedly at high risk.
Follow-up did not exceed 30 months, a limitation related to recent French regulations concerning confidentiality of health insurance databases. However, this relatively short follow-up was sufficient to demonstrate an increased risk associated with the use of fibrates. The same limitation applies to the observation period prior to the study. Although unlikely, we cannot exclude the possibility that some patients may have been exposed to a fibrate or a statin before this 30-month period. According to the study design, only patients with an initial prescription for fibrates or statins prescribed by a general practitioner were included. This theoretically limits the generalizability of our conclusions. However, most patients with type 2 diabetes are managed in the primary care setting in France, especially in terms of cardiovascular primary prevention.
Chromosome conformation may play a role in gene regulation A hierarchical clustering of the 5,185 expressed proteincoding gene primary transcripts was performed based on their expression profiles in the 15 conditions. Genes were aggregated into 55 distinct clusters according to their expression profiles. Based on the median value of intergenic distances of 30 kb, Choulet et al. [33]  estimated that 73% of genes were organized in small islands or 'insulae'. Using the same criteria, 3,465 out of the 5,185 expressed genes (67%) were found to be organized in 1,199 insulae, comprising 2. 9 genes on average. Out of these 3,465 genes, 1,218 (35. 2%) belong to the same expression cluster as their direct neighbor, defining 718 co-expressed gene pairs. This proportion is higher than the previously reported value of 11%  [29]  most probably because of the higher resolution achieved with a reference sequence compared to a partial gene dataset.
Read alignment and expression analysis Illumina reads were mapped on the chromosome 3B scaffolds using Tophat2 v2. 0. 8  [93, 94]  and bowtie2  [95]  with the default parameters except: 0 mismatch, 0 splice-mismatch. PCR duplicates were removed with Samtools  [96]  rmdup option and an annotation-guided read alignment was performed with Cufflinks v2. 1. 1  [93, 97]  to reconstruct transcripts and estimate transcript abundance in units of fragments per kb of exon per million mapped reads (FPKM)  [98]. Regions with FPKM values higher than zero were considered as expressed. TriAnnotpredicted regions were distinguished from unannotated regions (novel transcribed regions, NTRs) using the -g option. NTRs were reconstructed and ORFs were detected using transcripts_to_best_scoring_ORFs. pl (Trinity)  [99]  and blasted against the Magnoliophyta database (BLASTX, e-value 10e-5).
Based on the FPKM scale defined in by Hansey and collaborators  [79]  expressed genes can be divided in three classes: genes with a FPKM value below 5 are low expressed, genes with a FPKM value greater or equal to 5 and less than or equal to 200 are medium expressed, and genes with a FPKM value greater than 200 are high expressed (semi-quantitative organization). Sequences and annotations of the reference pseudomolecule and unassigned scaffolds have been deposited in ENA (project PRJEB4376) under accession numbers HG670306 and CBUC010000001 to CBUC010001450, respectively. Segmentation/change-point analysis Segmentation analyses were performed using the R package changepoint v1. 0. 6  [100]  with Binary Segmentation method and BIC penalty on the mean change. The different features that were subjected to this analysis were: recombination rate, transposable element density, predicted gene density, number of condition in which a gene is expressed.
Acknowledgements The authors would like to thank  Hélène Rimbert  for assistance in bioinformatics analysis. They also thank the  International Wheat Genome Sequencing Consortium (IWGSC)  for pre-publication access to the chromosome-based draft sequence of the wheat genome. This work was supported by grants from the  French National Research Agency  ( ANR-09-GENM-025 3BSEQ ) and  France Agrimer. LP was funded by a grant from  Région Auvergne.
Methods This analysis was performed using data from the BREATHE study, the methodology of which has been described in detail elsewhere. 13 Briefly, this study was a cross-sectional epidemiological survey of COPD in a random sample of the general population in eleven countries: Algeria, Egypt, Jordan, Lebanon, Morocco, Pakistan, Saudi Arabia, Syria, Tunisia, Turkey, and UAE conducted between June 2010 and December 2011. The present analysis concerned the data relating to COPD and BMI.