dataesr/scientific-paragraphs-categorization huggingface dataset:
The structure of RidL 2-281 was solved at 1. 9-Å resolution. The electron densities allowed for building a model comprising a Values in parentheses are for the last resolution shell residues 7-274. The structure features a "foot-like" fold, consisting primarily of interacting bundles of α-helices connected by loops of various lengths (Fig. 1a , Supplementary Fig. 1  and Supplementary movie 1). A search for related structures or structural motifs using the Dali server  42  did not reveal any closely related structure deposited in the protein data bank (the nearest structural neighbor with a low Z-score of 4. 8 and a high RMSD of 4. 4 was PDB entry 1J1J, a human translin protein involved in RNA/DNA binding). The surface representation of B-factors indicates an increasing flexibility from the heel to the toes of the foot (Fig.
pneumophila infection than Rab7. Given that TBC1D5 appears to play a role for the release of the retromer from Rab7 at later steps in retrograde trafficking  25  , RidL might also target later steps in the process. However, the exact role of the retromer interactor TBC1D5 for L. pneumophila infection requires further studies. The data show mean and 95% confidence intervals of one representative experiment out of three independent biological replicates (***P < 0. 001; two-way ANOVA with Bonferroni post hoc test). c D. discoideum DH1 stably producing GFP-TBC1D5 was infected (MOI 20, 2 h) with DsRed-producing L. pneumophila JR32 or ΔridL harboring pCR77 (vector), ΔridL/pIF007 (RidL) or ΔridL/pKB201 (RidL-Δβ-hairpin). Intact LCVs were purified, immuno-stained for calnexin, and analyzed by fluorescence microscopy.
At the indicated time points, the infected amoebae were detached from the surface and fixed with 4% PFA for 30 min at 4 °C. With an imaging flow cytometer (ImageStreamX MkII, Amnis), 10,000 events were acquired, and after color compensation, analysis was carried out using the IDEAS 6. 2 software (Amnis) as described  9, 10, 53  , by first selecting in-focus single cells that were positive for GFP, and then gating cells having internalized L. pneumophila using the IDEAS internalization wizard. The cells containing more than one bacterium were subsequently eliminated using the feature [Spot Count_Spot(M04 or M05, Lpn, Bright, 8. 5, 1, 0)_4]. The included cells were finally analyzed for co-localization between mPlum or DsRed and GFP (IFC co-localization score), using the co-localization wizard in IDEAS, which computes the log transformed Pearson's correlation coefficient of the localized bright spots with a radius of 3 pixels or less in two images, thus providing an IFC co-localization score for each cell.
The mean score for the sample is reported. The IFC data were analyzed by regular two-way ANOVA followed by Bonferroni post hoc tests, comparing each sample to the corresponding wild-type. For IFC of isolated LCVs, D. discoideum DH1 dually expressing GFP-TBC1D5 (pFL1304) and AmtA-mCherry were seeded in T25 cell culture flasks and infected (MOI 50) with L. pneumophila JR32 or ΔicmT producing mPlum (pAW14). At the indicated time points, the amoebae were detached from the surface, washed, homogenized using a ball homogenizer, and fixed in suspension as described above. With an imaging flow cytometer (ImageStreamX MkII, Amnis), 20,000 mPlumand AmtA-positive events were acquired, and after color compensation, analysis was carried out using the IDEAS 6. 2 software (Amnis). First, in-focus events were gated using the feature [Gradient RMS_M05_Lpn].
Eluates were collected and beads were washed four times with lysis buffer before resuspending in loading buffer. 20% of total eluate or bead suspension, respectively, were analyzed by SDS-PAGE and Western blot as described above. The membrane was cut according to the expected target sizes and different pieces were individually immuno-stained for GFP or RidL as described above, or for Vps35 (1:1000, Abcam: ab10099) or Vps26 (1:1000, Abcam: ab23892). The bands were quantified using the ImageQuant QL software relative to the value for beads with mock elution. Molecular cloning. Plasmids and oligonucleotides are listed in Supplementary Tables  1  and 2 , respectively. DNA manipulations were performed according to standard protocols, and plasmids were isolated using kits from Qiagen (EndoFree Plasmid Maxi Kit, 12362) for transfection grade plasmids or from Macherey-Nagel.
Protein concentration was determined by OD 280 using a NanoDrop 2000 photospectrometer and calculated based on theoretical extinction coefficients (www. expasy. ch/tools/ protparam. html). Crystals of RidL 2-281 Se-Met were obtained by the vapor diffusion method in sitting drops at 20 °C against a reservoir containing 20% (w/v) polyethylene glycol (PEG) 8000, 100 mM TRIS/HCl pH 8. 5 and 200 mM MgCl 2. Analogously, crystals of RidL 10-258 -Δβ-hairpin were obtained against a reservoir containing 25% (w/v) PEG 1500. The protein to reservoir volume ratio was 1:1. The crystals were cryoprotected in mother liquor supplemented with 20% glycerol and flash-frozen in liquid nitrogen. Structure determination. The diffraction data of the crystals were collected at the beamline X06DA of the Swiss Light Source (SLS, Villigen, Switzerland) equipped with a PILATUS detector (Dectris) and processed using XDS  56.
In an inverted setup, biotinylated RidL 2-1167 -Avi was immobilized (1000 RU) and Vps29 was used as an analyte (50-1. 35 μM). Injection time was 150 sec. Responses at equilibrium were plotted against Vps29 concentration. The equilibrium constant K D was determined by non-linear regression using an equilibrium binding equation equivalent to the Michaelis-Menten equation in which R eq denotes the SPR response at equilibrium, R max denotes the maximal SPR response and [Vps29] is the Vps29 concentration: R eq = R max [Vps29]/(K D + [Vps29]). Docking studies. Information-driven docking was performed using the HAD-DOCK2. 2 webserver (http://milou. science. uu. nl/services/HADDOCK2. 2/)  62, 63. The RidL 2-281 structure (PDB: 5OH5) and the Vps29 structure (PDB: 5GTU, with the peptide TBC1D5-Ins1 removed) were used for docking.
The amino acids Met -3 to His 0 of the Vps29 structure (PDB: 5GTU), which must be cloning artifacts, were removed, since they are located in close proximity to the anticipated binding region. We defined Ile 170 of RidL and Leu 2 , Leu 25 , Leu 152 and Tyr 165 of Vps29 as active residues and ran the docking with default settings using the "Easy interface"  59. In the two best scored solutions (HADDOCK score of -65. 9 and -56. 6, respectively), the RidL β-hairpin is only partially accommodated by the hydrophobic groove of Vps29, and Ile170 of RidL was not contacting Leu152 of Vps29, while other surface regions of RidL, which were not being part of the β-hairpin, interacted strongly with the surface of Vps29. The third best solution (HADDOCK score -55. 6), on the other hand, featured a contact between Ile 170 of RidL and Leu 152 of Vps29, and RidL with Vps29 exclusively via the β-hairpin.
Acknowledgements We acknowledge  Beat Blattmann  and  Céline Stutz-Ducommun  of the  Protein Crystallization Center UZH  for performing the crystallization screening, and the staff of the  SLS  beamlines  X06SA  and  X06DA  for their support during X-ray data collection. STxB-Cy3 was obtained from  Ludger Johannes  ( Curie Institute, Paris ). Confocal laser scanning microscopy and imaging flow cytometry was performed using equipment of the  Center of Microscopy and Image Analysis  or the  Flow Cytometry Facility, University of Zurich (UZH). SPR measurements were carried out at the  Functional Genomics Center Zurich (FGCZ). Work in the group of H. H. was supported by the  UZH , the  Swiss National Science Foundation  (SNF;  31003A_153200 ), the  German Bundesministerium für Bildung und Forschung (BMBF ;  031A410A ;  Infect-ERA  project  EUGENPATH ), the  Novartis Foundation for Medical-Biological Research , and the OPO foundation.
eu) that allows users to effectively search the document base. An ontology defines a set of concepts and the relations between them. The VALERIE ontology is built by experts in the agricultural and forestry domain and contains 6169 concepts (21 st October 2016). The document base is the collection of documents in which the system searches. The VALERIE document base includes scientific and practical documents derived from various sources, written in any of a number of languages. All documents contained in the document base are annotated using the ontology: each term (a word or a short phrase) in the document that matches a concept in the VALERIE-ontology is linked to that concept. Annotation is an automated process that takes place whenever a document is added to the document base. The document base contains 4278 documents (October 2016).
As a result, there are increasing demands on farmers to produce more with less, with more often explicitly including public goods and services, and they have to meet these demands in an environment where there is an increasing disconnection between research and farming. The main aim of the European project VALERIE (2014-2017; http://www. valerie. eu) is to improve the accessibility to and availability of new knowledge for innovation in agriculture and forestry produced by European and national research, and to facilitate its integration into farming and forestry practice. More specifically, we are developing a digital assistant expert in the field of agriculture and forestry (ask-Valerie. eu) that could help farmers and foresters to find information on innovation. In particular, the digital expert will allow users to articulate queries, find all relevant results (documents/fragments of documents, projects, people, equipment, software), and rank them.
Ontology An ontology defines a set of representational primitives (concepts) and the relations between these primitives  (Gruber, 2009). The VALERIE domain consists of the above-mentioned six themes within the agronomy and forestry sectors. The VALERIE domain ontology is defined in the SKOS-format and consists of concepts (terms) from these themes and this domain. Each concept may have synonyms (skos:altLabel) in multiple languages. The concepts have been interrelated in two ways. First, a hierarchical organisation has been added to the terms, using an is a kind of relation (skos:narrower; http://www. w3. org/TR/skos-reference/). Concepts may have more than one parent. Second, the relation (skos:related) has been added to allow for other, more generic connections between concepts. The VALERIE domain ontology has been created using the ROC+ method as described in  Willems et al.
Types of documents belonging to VALERIE's document base The ask-Valerie. eu document base is the collection of documents in which ask-Valerie. eu searches. From this base, searches by ask-Valerie. eu will return one or more documents, one or more text fragments, or a combination of these. It is important to underline that ask-Valerie. eu does not store copies of the documents. Documents are regarded as part of the ask-Valerie. eu document base once they have been annotated. Annotation results in a stored index (set of terms that refer to concepts in the ontology). The original documents remain in their original repositories. VALERIE's document base includes both scientific and practical documents derived from various sources, and in multiple languages (Italian, English, French, Finnish, Spanish, and Dutch).
Ontology The creation of an ontology is an iterative process, which will be developed with at least four versions of the VALERIE domain ontology foreseen during the four year project. Currently, version 7 of the VALERIE ontology is available online as Linked Open Data at http://www. foodvoc. org (consulted on 21 st October 2016), the next version of the VALERIE ontology is under construction. The latest version of the ontology consists of 6169 concepts, 30,515 synonyms and translations, 6194 terms connected via a skos:narrower relation and 3090 terms connected via a skos:related relation. All concepts in the ontology are translated into French, Italian, Finnish, Spanish, Polish and Dutch, and frequently synonyms in these languages have been added. Thus ask-Valerie. eu is a multi-lingual platform, where each user can search for answers in their own languages, and find answers in preselected languages.
In each cycle, new features of ask-Valerie. eu are implemented and tested by the case study partners. From these sessions, existing functionality is evaluated, requests for changes and for new features are gathered and prioritised. Then, a new cycle starts. Completion of four cycles in the last two years has led to a clear improvement in the interface, search functionality, language integration, quality of search results and user interaction; thereby enhancing the accessibility of ask-Valerie. eu for the target audience. In addition, we envisage that the content and facilities of the platform could be improved in the future through an iterative process of interaction between the users and hosts of ask-Valerie. eu Although other agriculture and forestry-oriented search engines exist, we are not aware of search engines in the agriculture and forestry domains similar to VALERIE.
For example, the EPPO Global database (http://gd. eppo. int; consulted on 21 st October 2016) provides comprehensive coverage of organisms in agriculture. The future maintenance of ask. Valerie. eu will be able to draw upon these methodologies, but will need an organisation or institute to oversee the process. Within the current VALERIE project, we allow users to provide ontology terms and ask dedicated expert groups to integrate these new terms into the existing ontology. When this is done on a regular basis, the amount of time needed is limited. When new concepts are added to the ontology, all documents in the document base need to be scanned for the new concepts. This is an automated process and like all automated processes, must be monitored and adjusted when incorrect behaviour is detected.
FP7 European projects. The European Union Open Data Portal (https://open-data. europa. eu/en/data/) indicates that 48,860 projects were funded under FP5, FP6 and FP7 calls, in all disciplines. There are about 1500 projects related to agriculture, food, and forestry. We have accessed the CORDIS database to provide access to documents produced by those projects, possibly using also the OpenAire (http://www. openaire. eu) public repository. Other repositories exist outside the EU; in particular, most universities from the US have an extension service delivering practical fact sheets dealing with crop management techniques (e. g. Iowa State University, https://store. extension. iastate. edu/; University of Missouri, http://extension. missouri. edu, consulted on 21 st October 2016). Substantial effort will be devoted to find documents in non-English languages.
Morphometric analysis of Iba1 stained microglia. 3 images of each half of the arcuate nucleus from each of 3 different slices/mouse and 2 images of LH, DMH, VMDMH and VMH from each of three different slices/mouse were taken. The size of the fields analysed was 173 μm × 218 μm. 5 mice per group were analysed. Morphological analyses was performed in a double blind manner. ImageJ software was used to measure immunoreactivity through a threshold method and the number of positive pixels and the extension of area of interest were used to determine the fractional area covered by the specific signal. Quantification of AgRP positive puncta. 3 images of each half of the arcuate and paraventricular nucleus from each of 3 different slices/mouse were taken. The size of the fields analysed was 173 μm × 218 μm.
5 mice per group were analysed. The number of AgRP positive synaptic puncta was quantified by sharpening the contour with the software Axiovision 4. 6. 3 and then using the plugin Puncta Analyzer (written by Bary Wark, available upon request, c. eroglu@cellbio. duke. edu) under the ImageJ analysis software platform. Quantification of POMC positive puncta. 2 images of each half of the arcuate from each of 4 different slices/ mouse were taken. 3 mice per group were analysed. ImageJ software was used to quantify the number of POMC positive synaptic puncta. Cell culture. The N9 microglia cells were developed by immortalizing mouse primary microglia cells with the v-myc or v-mil oncogenes of the avian retrovirus MH2  82. This cell line displays several phenotypic traits of primary microglia mouse cells  75.
Statistical analysis. Statistical Analyses-Data are represented as mean ± S. E. M and statistical significance was verified using GraphPad Prism 5 ® software (GraphPad Software, San Diego, CA). Statistical significance was assessed by two-tailed unpaired t test for comparisons between two groups, one-way or two-way ANOVA followed by Bonferroni or Newman-Keuls post hoc tests were used for comparisons of multiple groups.
Acknowledgements We are grateful to  Prof. Carola Eva  for the help provided with the quantification of POMC expression. This work was supported by a grant from the  European Community  ( ERC-Advanced Grant Ways   322977 ), by  Cariplo Foundation  (Grant  2013-0786 ) and by the  Seventh Framework Programme  ( FP7/2007-2013)  under grant agreement no. 278 850  ( INMiND ).
Methods Data were extracted from two previous crosssectional studies. The first one was the French validation study of the GOHAI conducted in 2000-2001 among a sample of 255 adults in the "Puy de Dome" department (France)  [4]. Disadvantaged adults were over-represented in this sample and their age varied from 18 to 45 years. The sample included low-income earners benefiting from extended public health coverage. The second study was the validation study of the GOHAI conducted in 2015 in a PWS sample  [6]. Data were collected within a multicentre cross-sectional descriptive study (BUCCODOR). A cluster sampling method was used to recruit 108 PWS aged 21-75 years in the "Côte d'Or" department (France). Schizophrenia was defined according to the standard classification of mental disorders (DSM-V).
For both studies, data were collected using personal interviews and dental examinations. Details of the methodology used for sampling and data collection have been described in previous publications  [4, 23]. This study has been approved by the ethics The sample size for Rasch analysis should be at least equal to the number of questions multiplied by the number of answer categories  [24]. Given that a 5-point Likert scale was used, the minimal number of participants needed was 60. Nevertheless, a sample of at least 200 individuals is generally used  [25]. The sample size (n = 363) obtained with the data from the two studies was thus considered sufficient. For the Rasch analysis, item scores were ordered so that low values represented the worst level of OHrQOl and that high values represented satisfactory OHrQOl.
For example, the answers to question 3 ("How often were you able to swallow comfortably?") was coded from 0 (never) to 4 (always), while those to question 4 (« How often have your teeth or dentures prevented you from speaking the way you wanted?") were coded from 0 (always) to 4 (never). The Partial Credit Model (PCM) was applied to examine the GOHAI  [24]. Ad-hoc tests of fit of the PCM were realized using RUMM 2030 software. We used the chi squared statistics of RUMM to test the fit of the PCM to the dataset. The criteria of infit and outfit meansquare (MnSq) were set at 0. 6 to 1. 4. The fit of items outside this range was considered poor  [26]. Items were characterized by using difficulty parameters δ with the unit of logit (a standardized score with mean as 0 and SD as 1 for unit of the latent variable) and were calculated for each item  [27].
Results Overall associations between SNPs in mRNA splicing-related genes and lung cancer risk in the TRICL Consortium. Overall, 11,966 SNPs in 206 mRNA splicing-related genes in six GWAS datasets were selected from the TRICL Consortium (an imputated dataset that included 5,472,374 common SNPs), and their associations with lung cancer risk are shown in the Manhattan plot (Fig. 1 ). The sample size for each study had been listed in Table  1. After FDR correction (P FDR corrected ≤ 0. 05), the 12 SNPs in three genes remained statistically significant (Fig. 1 ). The most significant SNP for each gene was: rs75100087 in PRPF6 (P = 6. 83E-06); rs115420460 in DHX16 (P = 3. 93E-09) and rs114312980 in LSM2 (P = 2. 19E-07). Their basic information and associations with lung cancer risk are listed in Table  2.
6 + means positive association, andmeans negative association. associated with expression levels of PRPF6 in both additive and dominant models (Supplementary Figure  5  and Supplementary Table  2 ). We also queried the GTEx database (http://www. gtexportal. org/) and found that SNP rs8126213 was significantly correlated with mRNA expression levels of PRPF6 in normal lung tissues (P = 1. 50 × 10 -5 ), which was consistent with the results in the lymphoblastoid cell lines. Similar results were found for other five SNPs (Supplementary Figure  6 ). Replication of PRPF6 SNP (rs8126213) in another two lung-cancer GWASs. We then selected one of these six PRPF6 SNPs (rs8126213) and investigated its association with lung cancer risk in two additional lung-cancer GWASs of Caucasian origin, Harvard Lung Cancer Study (984 cases and 970 controls) and Icelandic Lung Cancer Study (deCODE from the ILCCO) (1,319 cases and 26,380 controls).
In the present study, we systematically evaluated the associations between 11,966 genetic variants in 206 mRNA splicing-related genes and lung cancer risk using the data from eight published GWAS datasets. To the best of our knowledge, this is the first and largest study focusing on exploring associations between SNPs from mRNA splicing-related genes and risk of lung cancer. Overall, our study identified six SNPs within mRNA splicing-related gene PRPF6 that might play an important role in the development of lung cancer. Furthermore, all of these six SNPs were found to be associated with PRPF6 mRNA expression in both lymphoblastoid cell lines and normal lung tissues of European descendent. Therefore, we proposed that these six SNPs were associated with abnormal expression of PRPF6 and thus modified individual's susceptibility to lung cancer.
Study populations. In the present study, we used the data from eight lung-cancer GWASs with a total of 14,463 lung cancer cases and 44,188 health controls. As shown in Table  1 , the analysis included six GWAS datasets from the TRICL consortium (12,160 lung cancer cases and 16,838 controls of European ancestry) and another two datasets of lung cancer GWASs: the Caucasian origin-Harvard Lung Cancer Study (984 cases and 970 controls) and the Icelandic Lung Cancer Study (deCODE from the ILCCO) (1,319 cases and 26,380 controls). As described previously  16  , the TRICL six lung-cancer GWASs include the MD Anderson Cancer Center (MDACC) GWAS, the Institute of Cancer Research (ICR) GWAS, the National Cancer Institute (NCI) GWAS, the International Agency for Research on Cancer (IARC) GWAS, Lunenfeld-Tanenbaum Research Institute study (Toronto) GWAS and the German Lung Cancer Study (GLC) GWAS.
GWAS genotyping, imputation and quality controls. GWASs included in the current study were performed by the following platforms: Illumina HumanHap 317, 317 + 240 S, 370 Duo, 550, 610 or 1 M arrays. Genotype imputation was conducted based on linkage disequilibrium (LD) information from the 1000 Genomes Project (phase I integrated release 3, March 2012) by IMPUTE2, MaCH or minimac software  16. Imputed SNPs with information score < 0. 40 by IMPUTE2 or r 2 < 0. 30 by MaCH were excluded from further analysis. In addition, standard quality control on samples by excluding individuals with low call rate (< 90%) and extremely high or low heterozygosity (P < 1. 0 × 10 -4 ), as well as those estimated to be of non-European ancestry (using the HapMap phase II CEU, JPT/CHB and YRI populations as reference) were conducted among all of the studies.