dataesr/scientific-paragraphs-categorization huggingface dataset:
g. , those proposed by the Global Research Council; http:// www. globalresearchcouncil. org). We are aware that different nations have different constraints and regulations on the use of biological samples. Given the international nature of GIGA, we will work to ensure that national genomic legacies are protected and will consult with the pertinent governmental agencies in the countries from which samples originate. We will deposit sequence data in public databases (e. g. , GenBank), as well as deposit DNA vouchers in publically accessible repositories (e. g. Global Genome Biodiversity Network, Smithsonian). GIGA is an inclusive enterprise that invites all interested parties to join the effort of invertebrate genomics. We will attempt to capture the impact of the effort in the wider scientific and public arenas by following relevant publications and other products that result from GIGA initiatives.
Standards and Best Practices GIGA has adopted a set of standards and best practices to help ensure that genomic resources, data, and associated metadata are acquired, documented, disseminated, and stored in ways that are directly comparable among projects and laboratories. These data should be easily and equitably shared among GIGA members and the broader scientific community, and GIGA will obey appropriate laws and regulations governing the protection of natural biodiversity. Briefly, all genome projects will report on a set of parameters that will allow assessment of genome assembly, annotation, and completeness (e. g. , NG50, N50 of contigs and scaffolds, number of genes, assembled vs. estimated genome size)  (Jeffery et al. 2013). Detailed descriptions of these standards and compliant protocols will be posted on the GIGA Web site.
These will be revised periodically to facilitate the establishment and maintenance of current best practices common to many invertebrate genome and transcriptome sequencing projects and to help guide the researcher in selecting and assessing genomes for further analyses. The following recommendations summarize minimal project-wide standards designed to accommodate the large diversity of invertebrates, including extremely small and rare organisms, as well as those that live in close association with other organisms. 1. Permissions: GIGA participants must comply with treaties, laws, and regulations regarding acquisition of specimens or samples, publication of sequence data, and distribution or commercialization of data or materials derived from biological resources. Participants must acquire all necessary permits required for collection and transport of biological materials prior to the onset of the work.
Quality of RNA will be checked using RNA integrity number (RIN > 7 is preferred); however, these values have been shown to appear degraded in arthropods due to artifacts during quantification  (Schroeder et al. 2006; Winnebeck et al. 2010). 5. Taxonomic identity: The taxonomic identity of source organisms must be verified. Whenever possible, consensus should be sought from expert systematists, supportive literature, and sequence analysis of diagnostic genes (see next section). 6. Voucher specimens: As a prerequisite for inclusion as a GIGA sample, both morphological and nucleic acid voucher specimens must be preserved and deposited in public collections, and the associated accession numbers must be supplied to the GIGA database. Photographs should be taken of each specimen and cataloged along with other metadata.
The GIGA Web site lists cooperating institutions willing to house voucher specimens for GIGA projects, such as the Smithsonian Institution or the Ocean Genome Legacy (http://www. oglf. org). 7. Documentation of projects, specimens, and samples: Unique alphanumeric identification numbers (GIGA accession numbers) will be assigned to each GIGA project and to each associated specimen or sample used as a source of genome or transcriptome material for analysis. A single database with a web interface will be established to accommodate metadata for all specimens and samples. Metadata recording will also aim to coordinate and comply with previously established standards in the community, such as those recommended by Genomics Standards Consortium (http://gensc. org/; Field et al. 2011 ). 8. Sequencing Standards: Standards for sequencing are platform and taxon specific, and sensitive to the requirements of individual sequencing facilities.
For these reasons, best practices and standards will be established for individual applications. Coverage with high-quality raw sequence data is a minimal requirement to obtain reliable assemblies. An initial sequencing run and assembly will be used to estimate repeat structure and heterozygosity. These preliminary analyses will make it possible to evaluate the need for supplemental sequencing, with alternative technologies aimed at addressing specific challenges (e. g. , mate-pair sequencing to resolve contig linkage). Moreover, all raw sequence reads generated as part of a GIGA project will be submitted to the NCBI Sequence Read Archive. 9. Sequence Assembly, Annotation, and Analyses: Because assemblies vary widely in quality and completeness, each assembly should be described using a minimum set of common metrics that may include: (1) N50 (or NG50) length of scaffolds and contigs (see explanation of N50 in  Bradnam et al.
Deuterostomia is one of the major clades of bilaterian animals and includes the vertebrates (Figures  1  and 5 ). Among its nonvertebrate members, Deuterostomia comprises a wide diversity of forms ranging from microscopic to huge, familiar to bizarre, gelatinous to armor-plated, and wormlike to plant-like. Apart from Craniata (including Vertebrata), the group includes four major clades: Echinodermata, Hemichordata, Tunicata, and Cephalochordata, all exclusively marine. Echinodermata and Hemichordata form a clade known as Ambulacraria (Figure  5 ), characterized by similar dipleurula larval morphology and supported in most phylogenetic analyses. Tunicata are the closest relatives to Craniata and along with Cephalochordata form Chordata (Figures  1  and 5 ). It also has been suggested that Xenacoelomorpha are the sister group to Ambulacraria rather than being placed in a more basal position as seen in Figure  1.
2011). When available, common names are written above the branches. A collective effort to sequence thousands of invertebrate genomes will only be feasible with participation and commitment from the scientific community. The large breadth of invertebrate diversity will require taxon-specific expertise and integration of traditional biology with molecular advances, both in data generation and analysis. The GIGA team has already expanded beyond initial participants in the first GIGA planning workshop, where the cooperative spirit and ability to work in concert to establish a common platform for data sharing and analysis were demonstrated. The longrange impact of GIGA will go beyond understanding phylogenetic relationships among invertebrate taxa, leading to new avenues of research in comparative developmental biology, environmental genomics, biodiversity, and climate change research, as is routinely done in many recent ecological studies focusing on gene expression data under stress conditions  (DeSalvo et al.
Acknowledgments GIGA also greatly appreciates the help of  NSU  staff, including the  Office of Information Technology  for Web site support, and several  NSU  students,  Brittnee Barris ,  Andrea Bernhard ,  Alexandra Campbell ,  Andia Chaves Fonnegra ,  Kirk Kilfoyle ,  Jonathan Lanzas ,  Rebecca Mulheron ,  Bryce Parrish ,  Renee Potens ,  Kristian Taylor , and  Christine Testermann , for assisting with GIGA workshop I logistics. For helpful feedback and comments on early drafts, the  GIGA Community of Scientists (COS)  thank  Drs. Harris Lewin ,  Carmen Ablan ,  C. Titus Brown ,  Rob Steele , and  Scott Nichols , and the Genome10K COS, including  Warren Johnson. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the  National Science Foundation.
A literature survey and analysis was conducted to describe the epidemiology of dengue disease in Brazil reported between 2000 and 2010. The protocol was registered on PROSPERO (CRD42011001826: http://www. crd. york. ac. uk/prospero/ display_record. asp?ID = CRD42011001826). Between 31 July and 4 August 2011, the published literature was searched for epidemiological studies of dengue disease, using specific search strategies for each electronic database. A total of 714 relevant citations were identified, 51 of which fulfilled the inclusion criteria. The epidemiology of dengue disease in Brazil, in this period, was characterized by increases in the geographical spread and incidence of reported cases. The overall increase in dengue disease was accompanied by a rise in the proportion of severe cases.
In 2000 there were nearly 170 million inhabitants of Brazil, increasing to more than 190 million in 2010  [18] , the majority of whom live in the large cities of the Southeast and Northeast regions  [19]. The National System for Surveillance and Control of Diseases (SNVS) of Brazil, operates as part of the national health system (Sistema U ´nico de Saude, or SUS). All reported cases from public health services or private health providers are included in the notification database (Sistema de Informacoes de Agravos de Notificacao [SINAN]), which is openly accessible via the internet  [20]. Until 2011, the SNVS adopted the case definitions outlined in WHO guidelines  [21, 22]. In 1997, the WHO categorized symptomatic dengue disease as: undifferentiated fever, DF and, DHF  [21]. DHF was further classified into four severity grades, with grades III and IV being defined as DSS.
However, difficulties in applying the criteria for DHF  [23] , led the WHO to suggest a new classification based on levels of severity: non-severe dengue disease with or without warning signs, and severe dengue disease  [22]. During 2000-2011, both surveillance and hospitalization reporting systems in Brazil used DF and DHF; the surveillance system used an additional classification designated 'DF with complications' (DFC)  [24]. Importantly, the articles included in this literature analysis that were based on secondary data used these surveillance sources. Our objectives of this literature search and analysis were to describe the epidemiology of dengue disease (national and regional incidence [by age and sex], seroprevalence and serotype distribution and other relevant epidemiological data) in Brazil during 2000-2011, and to identify gaps in epidemiological knowledge requiring further research.
Methods A literature review group, including authors of this contribution, developed a literature survey and analysis protocol based on the preferred reporting items of systematic reviews and meta-analyses (PRISMA) guidelines  [25]. Our protocol prescribed well-defined methods to search, identify, and select relevant research, and set predetermined inclusion criteria. The protocol was registered on PROSPERO, an international database of prospectively registered systematic reviews in health and social care managed by the Centre for Reviews and Dissemination, University of York (CRD42011001826: http://www. crd. york. ac. uk/prospero/display_record. asp?ID = CRD42011001826; protocol: http://www. crd. york. ac. uk/PROSP EROFILES/1826_PROTOCOL_20130401. pdf) on 9 December 2011.
Search strategy and selection criteria Between 31 July 2011 and 4 August 2011, we searched databases of published literature (Table  1 ) for epidemiological studies of dengue disease in Brazil. Search strategies for each database were described with reference to the expanded Medical Subject Headings (MeSH) thesaurus, encompassing the terms 'dengue', 'epidemiology', and 'Brazil'. Google and Yahoo searches (limited to the first 50 results) were used to identify national and international reports and guidelines, congress abstracts, and grey literature (e. g. , Ministry of Health data, lay publications). To reduce selection bias, peer-reviewed contributions in English, Portuguese, or Spanish published between 1 January 2000 and 4 August 2011 were included; no limits by sex, age, ethnicity of study participants, or by study type were imposed.
Single-case reports and articles only reporting data prior to 1 January 2000 were excluded. Unpublished reports were included if they were identified in one of the sources listed above. Data from grey materials supplemented that from peer-reviewed literature. Publications not identified in the target databases by the search strategy (e. g. , locally published papers) and unpublished data sources meeting the inclusion criteria (e. g. , theses, Ministry of Health data) were included if recommended by members of the literature review group. Editorials and data from literature reviews of previously published peer-reviewed studies were excluded. Duplicates and articles not satisfying the inclusion criteria were removed following review of the titles and abstracts. A further selection was made based on review of the full text from the first selection of references.
Included publications were summarised using a data extraction instrument developed as a series of spreadsheets. Due to the expected heterogeneity of eligible studies in terms of selection, and number and classification of cases, a meta-analysis was not conducted. For the purposes of the analysis we defined national epidemics as those years with an incidence/ 100,000 above the 75th percentile for the period. A trend analysis was conducted on the national incidence and case number data.
Efforts to control the increasing disease incidence have been unsuccessful. This review of dengue disease epidemiology will help enhance knowledge and future disease management. Despite the high volume of research retrieved, we have identified several avenues for future research, in particular studies of regional differences, genotype evolution and age-stratified seroprevalence that will improve our knowledge of dengue disease, contribute to a more accurate estimate of global disease incidence, and also inform evidence-based policies for dengue disease prevention. Figure  1. Result of literature search and evaluation of identified studies according to the preferred reporting items of systematic reviews and meta-analyses (PRISMA). All references identified in the on-line database searches were assigned a unique identification number.
The mean ages of patients according to infecting serotype were not significantly different (p = 0. 108): DENV-1 (30?9615?9 years), DENV-2 (34?3615?0 years), and DENV-3 (30?9614?6 years). Socio-demographic factors. Several studies examined associations between the risk for dengue disease and socio-economic, Table  3. Demographic patterns of incidence of dengue disease: Regional male:female ratio and age distribution data extracted from source documents.
Conclusion on genotoxicity No genotoxicity data were available on the 17 sulphur containing hetereocyclic substances evaluated by the JECFA at its 68 th meeting. The JECFA evaluation refers to data on thiophene only, as summarised in Table  4. The JECFA concluded that in its previous evaluation of substances in this group  (JECFA, 2003) , studies on genotoxicity, as well as studies on acute toxicity and short-term toxicity were available and none raised safety concerns. In the following text from FGE. 21Rev3 (EFSA, 2012b), only the information for subgroup A-I, B-I, B-II and B-III has been presented, as the information for subgroups A-II and A-III, B-IV, B-V and B-VI was not relevant to the candidate substances in the current FGE.
010] was tested for the induction of chromosome damage and potential aneugenic effects in an in vitro micronucleus assay using duplicate human peripheral blood lymphocytes prepared from pooled blood from two healthy male volunteers. Treatments were performed both in the absence and presence of Aroclor 1254 induced rat liver S9-mix  (Watters, 2012). Cells were stimulated for 48 hours with phytohaemaglutinin to produce exponentially growing cells. A preliminary toxicity range-finding experiment was conducted with S9-mix and 3 hours treatment and without S9-mix with 3 and 24 hours treatment. Toxicity was evaluated as the effect of treatment on the Replication Index (RI). Twelve concentrations from 4. 6 to 1262 μg/mL were tested. The concentrations selected for the main experiment were based on toxicity data from this preliminary test.
CONCLUSION In Flavouring Group Evaluation 93 (FGE. 93), the EFSA considered six flavouring substances from a group of flavouring substances consisting of sulphur-containing heterocyclic substances evaluated by the JECFA at its 68 th meeting. This revision is made due to additional available genotoxicity data on 2acetyl-2-thiazoline. 010], as requested in previous version of FGE. 93. For one substance. 127], additional toxicity data was requested in FGE. 93. However, since publication of FGE. 93, the substance ] is no longer supported by Industry for use as a flavouring substance in Europe and will therefore not be considered any further. Therefore, the present revision of FGE. 93, FGE. 93Rev1, considers five flavouring substances evaluated by the JECFA. The NOAEL of 1. 8 mg/kg bw per day for 2-acetyl-2-thiazoline from a 90-day and a 52-week rat studies that examined a mixture of four flavouring substances, including.
232 Th measurement -preliminary results For the thorium measurement campaign, the 12 g sample was in the beam during 375 hours and we are able to observe many γ-transitions and especially the deexcitation of the first level at 49 keV. A lot of measurements exist in the EXFOR data base and particularly for the (n,2n) reaction which can be measured by the activation technique. Nevertheless only one (n,n' γ) reference from Dave et al. [17]  exists and for which the measurement has been performed for neutron energy up to 2 MeV. For.
184 W measurement -preliminary results Measurements on four tungsten isotopes ( 182,183,184,186 W) have been performed during 300 or 500 hours, depending on the sample. A lot of γ-transitions can be analysed and compared to TALYS-1. 2 predictions made by P. Romain (CEA). In the EXFOR data base, only few (n,xn) cross section measurements exist but nothing concerning (n,xn γ) cross sections. Fig. 5  shows three (n,n' γ) cross sections on 184 W. The cross section's shapes are well reproduced by TALYS-1. 2 but discrepancies on amplitude, sometimes large, exist and depend on the γ-transition. The situation is roughly the same for the four measured isotopes. One thing brought out by this preliminary analysis is the crucial role of branching ratio description as significant differences appear on the TALYS-1.
Conclusion With the GRAPhEME set-up we provide (n,xn γ) cross section as accurate as possible. Several analyses are still in progress and the covariance matrix determination of our data sets will also be conducted. All this work is performed with the collaboration of our theoretician and evaluator colleagues. In the near future, this kind of measurement on a more active target, 233 U, will be carried out. The knowledge of the 233 U(n,2n) cross section is indeed very important for the thorium cycle study. For this purpose, a segmented (with 36 pixels) Germanium detector will be added to the GRAPhEME set-up. At last, our collaboration will also focus its efforts on the measurement of branching ratios and of highly converted level de-excitation.
The specificities were characterized using semi-quantitative data from glycan array and analyzed by molecular docking with the Glide software. Reliable prediction of protein/oligosaccharide structures could be obtained as validated by existing crystal structures of complexes. Additionally, the crystal structure of BambL/Lewis x was determined at 1. 6 A ˚resolution, which confirms that Lewis x has to adopt a high-energy conformation so as to bind to this lectin. Free energies of binding were calculated using a procedure combining the Glide docking protocol followed by free energy rescoring with the Prime/ Molecular Mechanics Generalized Born Surface Area (MM-GBSA) method. The calculated data were in reasonable agreement with experimental free energies of binding obtained by titration microcalorimetry.
Introduction Interaction between lectins, or other carbohydrate binding proteins, and carbohydrates play important roles in many biological and pathological processes. In the last years, high throughput analysis of glycome or availability of glycan microarrays  [1, 2]  revolutionized the glycobiology field. Integrated approaches are now needed for combining data arising from investigations performed at different scales. The wealth of information obtained from glycan array experiments and available in databases has to be combined with experimental data that describe the structure and affinity of single lectin binding sites. Molecular modeling can also be performed with different levels of sophistication and represents an excellent tool for integrating and rationalizing data obtained from different methods.
Even though molecular docking calculations are routinely performed on small organic compounds, docking oligosaccharides is still a challenging task due to the constraints of ring shape (fucose preferentially adopts a 1 C 4 conformation), the occurrence of CH-p interactions between aromatic amino-acids and the C-H bonds of sugars, and the role of peculiar stereo-electronic effect such as anomeric and exoanomeric effects which are not handled in standard molecular mechanics algorithms  [21, 22]. Nevertheless, conformational analysis of histo-blood group epitopes demonstrated that these oligosaccharides can adopt a limited number of well defined conformations  [23, 24]. These are available in the BIOLIGO database (http://bioligo. cermav. cnrs. fr/) that contains threedimensional structures of bioactive oligosaccharides generated using the SWEET-II  [25]  and POLYS  [26]  builders altogether with Shape a conformational search engine based on a genetic algorithm coupled to the MM3 force-field  [27].
Molecular docking studies of fucose and fucose-containing oligosaccharides have been published using a variety of computational approaches, in protein targets such as human lectins  [28, 29] , antibodies  [30, 31]  or virus capsid proteins  [32]. Molecular docking calculations of fucose and methyl-fucoside in bacterial lectins were also reported even though the presence of calcium ions in some of the binding sites was computationally challenging  [33] [34] [35] [36] [37]. With increasing availability of glycan arrays which allow for rapid deciphering of lectin specificity  [1] , the need for efficient protocols for structural rationalization of data is urgent. In this paper, we propose a docking strategy based on the use of starting oligosaccharides conformations derived from the BIOLIGO database.
Experimental section Material. Human histo-blood group oligosaccharides were obtained from Elicityl (Crolles, France). The two bacterial lectins were produced recombinantly in Escherichia coli as previously described  [14, 19]. Glycan array. Purified LecB sample was labeled with Alexa Fluor 488-TFP (Invitrogen, CA) according to manufacturer's instructions and re-purified on a D-Salt polyacrylamide desalting column (Pierce, Rockford IL). Alexa-labeled protein was used for glycan array screening with standard procedure of the Core H of the Consortium for Functional Glycomics (http://www. functionalglycomics. org, Emory University, Atlanta, GA, USA). The labeled lectin was assayed on the CFG glycan array version 4. 1 comprising 465 natural and synthetic glycans and the data were analyzed in a dose-dependent manner as previously described  [38]  at 10, 1 and 0.