dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgements. NH is a recipient of a PhD award from the  Ministere de la Recherche (Paris, France ). FL and AP-G are supported by  AECC  project,  UTE  project  FIMA  agreement,  RTICCC C03/10 ,  PI042284  and  PI10/01580  grants. This work was supported in part by  Inserm. We warmly thank the support of the  Nice-Sophia Antipolis Transcriptome Platform of the Marseille-Nice Genopole. We thank  Prof Van der Westhuizen  ( North West University, Potchefstroom, South Africa ) for providing the MT2A-pIRES vector. We thank  Dr. Alsafadi  ( Inserm U981, Villejuif, France ) for her helpful discussion and technical support in p53-family analyses. We thank  Mrs. Marty ,  Miss. Chantrenne  and  Dr. Ostertag  ( Inserm U606, Paris, France ) and  Mrs. Goubar  ( Inserm U981, Villejuif, France ) for their technical contributions.
pylori strain 26695. Briefly, cells were lysed in cold Catenin lysis buffer 1% Triton X-100 (Sigma) in PBS enriched with a protease inhibitor cocktail (Roche) and a phosphatase inhibitor cocktail (Sigma). Proteins were quantified using a modified Bradford assay (Bio-Rad). Thirty-mg of proteins were loaded on a 7. 5% or 12% SDS-PAGE. Donkey anti-rabbit (Amersham Biosciences) or sheep anti-mouse (Amersham Biosciences) HRP-conjugated secondary antibodies were used. Immunoblots were revealed by ECL detection (Amersham Biosciences) and quantified using the Quantity One Software (Bio-Rad).
Image analysis The stained 2-DE gels were scanned with a calibrated densitometer (GS-800, Biorad) with 36. 3636. 3 (X6Y) microns resolution, 700 dpi. The spot 2D-detection, background removal and matching were performed by the PDQuest software v8. 01 (Bio-Rad). In order to quantify and to compare the individual proteins spots, all the gel images were normalized using a local regression model. Three biological replicates with four gels were performed for each control and DHA treated samples. For this comparative analysis, only the spots present in every replicate were considered. Proteins were classified as being differentially expressed in DHA treated samples when spot intensity showed a difference higher than 1. 4 fold in comparison to the untreated control. All the matching spots were rechecked manually.
In order to analyze if DHA alters bacteria attachment to epithelial cells, AGS cells were incubated 30 min either with H. pylori strain 26695 previously treated for 24 h with increasing concentrations of DHA or with non-treated bacteria. The adherence of bacteria was quantified using an anti-Helicobacter antibody by ELISA. As reported in Figure  3A , the percentage of bacterial adhesion to epithelial cells decreased significantly when bacteria were pre-treated with DHA. Adhesion was completely inhibited at the highest concentration of 250 mM. These data were confirmed by TEM observation of co-cultures performed under the same conditions. Pre-treatment of bacteria with 100 mM of DHA led to a lower number of bacteria attached to cells compared to cells infected with non-treated bacteria (Figure  3B ).
This study was supported by the  ERA-NET Pathogenomics  ( ERA-PTG/0001/2010 ) and by the  Portuguese Foundation for Science and Technology  ( FCT -PTDC/SAU-SAP/120024/2010 ). MC is supported by an  FCT  fellowship  BD/36689/2007. The  Acco ˜es integradas Luso-Francesas  ( CRUP-PAULIF ) Portugal and France also provided financial support ( AF-8/09 ). Mathilde Bonis  was supported by a  PhD fellowship (Ministere de l'Enseignement Superieur et de la Recherche, France). This study was also supported by the  ERC  starting grant (PGNfromSHAPEtoVIR number  202283 ) to  Ivo G. Boneca. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Statistical Analysis Results were analyzed in two steps from our database: a descriptive analysis of the whole population and of the group with stricture, and a comparative analysis of groups with and without stricture. Descriptive data are expressed (for quantitative variables) as means 6 standard deviations for homogeneous distributions, and by the median and interquartile range (IR) for heterogeneous distribution; for qualitative variables, data are expressed as percentages. Comparative analyses are univariate, using the Chi 2 test for qualitative variables, with the Yates correction if necessary, and the Student's t test for quantitative variables. The threshold for significance was fixed at p = 0. 05.
Data on height, weight, village and self-reported ethnicity were also collected. A blood sample was collected before 16 weeks of pregnancy (defined as early pregnancy) and at 16-33 weeks of pregnancy (defined as "later pregnancy"). Blood samples were available from 134 women at early pregnancy, of whom 99 were followed up in the ENID study at later pregnancy and had blood samples available from this stage of pregnancy. Both sets of blood samples from these 99 women were used for this study to investigate aflatoxin exposure at different pregnancy stages and the impact of seasonality on exposure. For individual women there was a minimum of six weeks between the collection of the early and later pregnancy samples. The blood sampling fell either in the rainy (June to October) or dry (November to May) season.
Statistical analysis AF-alb was not normally distributed and was natural-log transformed prior to statistical analyses. Geometric means (GM) with 95% confidence intervals (CI) are presented for AFalb levels. Differences in albumin and AF-alb levels by stage of pregnancy and by season of blood collection were tested using the Student's t-test. The ANOVA model was used to test the interaction relationship between the stage of pregnancy and season of blood collection in relation to AF-alb or albumin levels. Spearman rank correlation analysis was used to assess the relationship between the AF-alb at the two stages of pregnancy. A P < 0. 05 was considered statistically significant, and P <0. 01 as highly significant. All data analyses were performed on Stata IC software (version 11, StataCorp, College Station, TX, USA).
Acknowledgments We thank all the study participants as well as the field, laboratory and data office staff at MRC  Keneba. YY Gong  and CP Wild are supported by the  National Institute of Environmental Health Sciences, USA. We would also like to acknowledge the finance contribution from  IARC toward JM Castelino 's PhD study. MRC Keneba is supported by the  UK Medical Research Council  and the study within which this analysis was embedded was funded by the  Wellome Trust.
They promote vessel formation in adult, and it was recently reported that they have the ability to incorporate into tumor tissues  (Carmeliet, 2005; Bussolati et al. , 2011). In this regard, TRPC1 has been suggested to contribute to regulation of cell migration of EPCs isolated from rats bone marrow. Interestingly TRPC1 downregulation dramatically reduces SOCE in EPC  (Kuang et al. , 2012)  (Table  1 ). These data are in accordance with data obtained from EPC isolated from peripheral blood of patients affected by renal cellular carcinoma (RCC; RCC-EPCs) and control EPCs (N-EPCs). In this study in fact Lodola and co workers report that TRPC1 is upregulated in RCC-EPCs where it's involved in SOCE  (Lodola et al. , 2012). On the other hand no data are at the moment available for a direct role for TRPC1 in human EPC.
We used that coding scheme to assign all FAFH into appropriate subcategories. This differentiation of FAFH into subcategories by food location of origin can help inform public policy on ways to improve the quality of the American diet. In particular, the subcategories allow us to estimate sodium consumption from stores vs. restaurants, both FSR and QSR. Specific food sources of sodium can also be identified with greater precision. Dietary intake data from the 2005-2006 NHANES were recently aggregated into 96 mutually exclusive food groups by the National Cancer Institute  [12]. This classification scheme for sources of dietary sodium was prominently featured in the 2010 Dietary Guidelines  [13]. Food codes representing similar foods-such as the various types of pasta dishes-were combined to provide an indication of how much sodium was provided by that food group to the total diet.
Dietary Intake Databases Data from three cycles of NHANES for  2003-2004, 2005-2006, and 2007-2008  were used to identify the main sources of dietary sodium by age group, food location of origin, and by specific food source. Separate analyses were conducted for children  (6) (7) (8) (9) (10) (11) , adolescents  (12) (13) (14) (15) (16) (17) (18) (19) , and for younger (20-50) and older adults (≥51). The 2003-8 NHANES database includes 3033 children; 5432 adolescents, and 14,387 adults for a total of 22,852 persons. The present analyses used Day 1 responses, based on in-person interviews with respondents listing the types and amounts of all food and beverages consumed in the preceding 24-hours. The first recall day was used here since we were most interested in population-level consumption patterns rather than the patterns of individuals.
Specific Food Sources The Food and Nutrient Database for Dietary Studies (FNDDS) provided a detailed description for each food and beverage consumed by NHANES participants  [19]. All FNDDS foods were aggregated into eight broad food groups and 96 food subgroups, based on food groups developed by the National Cancer Institute (NCI)  [12]. Linking of FNDDS codes with NCI food groups was done by the study authors. These groupings are useful because they show that the food sources that are the highest in sodium may not be the most important sources of dietary sodium on a population-level. Examples of food groups were soda, energy and sports drinks, yeast breads, grain-based desserts, burgers, fried potatoes, pizza, sandwiches, chicken dishes, or mixed Mexican dishes. A list of these food groups can be found in the Appendix.
7%) were followed by QSR pizza (3. 7%) and store bought sausage (3. 4%), chicken (2. 7%) and beef (2. 7%). QSR chicken contributed 2. 6% and QSR burgers 1. 8%. Table  5  shows sodium intake data for adults ages ≥51. The top 16 sodium sources came from the store, led by yeast breads (7. 2%), sausage (3. 6%), soups (3. 3%), pasta (2. 9%), beef (2. 8%), cold cuts (2. 8%) and grain-based desserts (2. 6%). The top restaurant item was chicken dishes from QSR with 1. 4% and chicken dishes from FSR with 1. 2%. QSR burgers contributed 1. 0%. 2 Others include all other categories, which contribute <1. 3% of total sodium for the total population; 3 Burgers, as defined in the database, can only come from quick-service restaurants. All burgers reported from store or full-service restaurants are composed of individual ingredients.
Therefore, components of hamburgers/cheeseburgers will be present in the yeast breads, beef and beef mixed dishes, regular cheese and other food groupings. Includes school cafeteria, workplace cafeteria, vending machine, gift/from someone else, and other sources; 2 Sorted by contribution to 6-11 year-olds; 3 Others include all other categories, which contribute <1. 3% of total sodium for the total population; 4 Burgers, as defined in the database, can only come from quick-service restaurants. All burgers reported from store or full-service restaurants are composed of individual ingredients. Therefore, components of hamburgers/cheeseburgers will be present in the yeast breads, beef and beef mixed dishes, regular cheese and other food groupings. ¶ Indicates relative standard error is between 30% and 39.
9% of the mean and potentially statistically unreliable. Others include all other categories, which contribute <1. 3% of total sodium for the total population; 4 Burgers, as defined in the database, can only come from quick-service restaurants. All burgers reported from store or full-service restaurants are composed of individual ingredients. Therefore, components of hamburgers/cheeseburgers will be present in the yeast breads, beef and beef mixed dishes, regular cheese and other food groupings. ¶ Indicates relative standard error is between 30% and 39. 9% of the mean and potentially statistically unreliable. 1 Includes school cafeteria, workplace cafeteria, vending machine, gift/from someone else, and other sources; 2 Sorted by contribution to 6-11 year-olds; 3 Others include all other categories, which contribute <1.
3% of total sodium for the total population; 4 Burgers, as defined in the database, can only come from quick-service restaurants. All burgers reported from store or full-service restaurants are composed of individual ingredients. Therefore, components of hamburgers/cheeseburgers will be present in the yeast breads, beef and beef mixed dishes, regular cheese and other food groupings. Others include all other categories, which contribute <1. 3% of total sodium for the total population; 4 Burgers, as defined in the database, can only come from quick-service restaurants. All burgers reported from store or full-service restaurants are composed of individual ingredients. Therefore, components of hamburgers/cheeseburgers will be present in the yeast breads, beef and beef mixed dishes, regular cheese and other food groupings.
Discussion The present analyses of nationally representative NHANES 2003-2008 data provide important insight into sodium intakes by age group, race/ethnicity, food location of origin and specific food source. The parallel evaluation of food location of origin (e. g. , store and QSR) and food sources (e. g. , pizza and yeast breads) by age group is novel and enhances approaches of dietary surveillance, while also providing context to potential population-wide interventions. Food locations of origin were derived from the current classification of NHANES data, whereas specific food sources were based on the National Cancer Institute food classification scheme. The NCI scheme was featured prominently in the 2010 Dietary Guidelines for Americans (DGA)  [13]  to identify the major sources of sodium and other nutrients in the American diet.
While on a per-calorie basis, more sodium is obtained from QSR/FSR than from the store  [22] , these data suggest that interventions to reduce sodium intakes among adults for all race/ethnicity groups must engage intakes from all sources, including stores. Studies based on analyses of NHANES data share many of the same limitations. First, the increasingly important category of store prepared foods could not be taken into account and would be misclassified here. Second, a single 24-h recall is not necessarily representative of a habitual diet of individuals, though it is an adequate tool for identifying the habits of large populations. Third, there are many ways of aggregating individual foods into food groups and food categories. The present option was chosen since it was developed by a federal agency and was presented as part of the 2010 Dietary Guidelines.
Conclusions The present analyses represent the first demonstration of how sodium intakes are partitioned by location and source and provide important information about dietary habits by age group and race/ethnicity. Future analyses, utilizing the same data and approach, could provide data by family income, education, place of birth or any other variable measured in the NHANES data. Although the majority of sodium consumption was derived from foods purchased from stores and prepared at home, almost one third of total sodium came from restaurant foods. One frequently expressed concern has been that Americans do not compensate for away from home foods by making healthier food choices at home  [7]. Reducing sodium intake at the population-level will require modifying food purchase behaviors at both stores and restaurants.
Data Collection Mothers or caretakers of children were surveyed at home for socioeconomic characteristics of the households. Birth dates of children were recorded from the school lists and checked with birth certificate or identity card. When official documents were missing, children's mothers or caretakers were questioned using a local events calendar. Children were defined as participants less than 10 y, and teenagers as participants from 10 y and above, according to the World Health Organization (WHO) definition  [15]. The nutritional assessment period lasted 6 weeks between February to March 2010, with one school visited each day. Blood, urine samples and anthropometric measurements were collected at schools in the morning between 8 and 10 AM. They were then verified for their identity.
Data Management and Statistical Analysis Data entry, including quality checks and validation by double entry of questionnaires, was performed with EpiData version 3. 1 (EpiData Association, Odense, Denmark). Data management and analyses were performed with the SAS software version 9. 2 (SAS, V9. 2; SAS Institute, Cary, NC). All analyses took into account characteristics of the cluster sampling design using the appropriate survey procedures of SAS. Categorical variables were expressed as percentages and standard errors of prevalence (surveyfreq procedure). Interval variables were expressed as arithmetic means and standard errors of means (surveymeans procedure), except ferritin and transferrin whose distributions were not normal and which were also expressed as geometric means and standard errors of means.
Most recently, researchers identified chronic dehydration from heat stress as the most likely causal factor in a perplexing epidemic of chronic kidney disease (CKD) in Central America  [24, 25]. To examine the cross-sectional associations between water intake, CKD and cardiovascular disease (CVD) in the general population, we analyzed data from the National Health and Nutrition Examination Survey (NHANES). We also examined whether the relationship with total water intake differed for low vs. high intake of plain water vs. beverages other than plain water.
Sample NHANES is an ongoing survey conducted in the USA by the National Center for Health Statistics (NCHS) of the Centers for Disease Control and Prevention. Data from the 2005-2006 cohort were analyzed in the present study. NHANES participants (noninstitutionalized US residents) are selected using a stratified, multistage national probability sampling design. Ethics approval for NHANES was obtained from the NCHS Research Ethics Review Board. Data collection for NHANES was approved by the NCHS Research Ethics Review Board. Analysis of de-identified data from the survey is exempt from the federal regulations for the protection of human research participants. Additional information about the 2005-2006 NHANES survey and methodology is available at www. cdc. gov/nchs/nhanes. htm.
Data Collection and Measures Participants completed an in-person structured interview, a physical examination (including height, weight and blood pressure measurements), and a computer-assisted 24-hour dietary recall. The dietary recall is a 5-step interview that includes multiple passes through the previous 24 h using standardized questions to help respondents recall and describe foods and beverages consumed  [27, 28]. Total water intake was estimated from all foods and beverages consumed within the previous 24 h. Water intake from beverages was grouped as follows: plain water (defined by the NCHS as tap water, water from a drinking fountain or water cooler, non-carbonated bottled water, and spring water); energy drinks, sugar-or artificiallysweetened drinks (carbonated or non-carbonated); alcoholic drinks; coffee or tea; fruit and vegetable juices, and milk, soymilk and other dairy drinks.
Comet Analysis. The following study design has been applied: 50 cells scored per slide, replicate slides from each experimental unit, and 3 animals per group. The slides were observed at 400x magnification, in a Nikon Labophot fluorescence microscope attached to a Sony 3CCD video camera and connected to a personal computer-based image acquisition system. Images were analysed using CometScore software (version 1. 5 of TriTek Corporation, free download from http://www. autocomet. com/). DNA damage was quantified as percentage of DNA in tail (% tail DNA)  [31]. 2. 5. Drugs. Acetylcholine chloride, atropine, propranolol hydrochloride, isoprenaline, N  -nitro-L-arginine methyl ester hydrochloride (L-NAME), indomethacin, glibenclamide, tetraethylammonium, cyclophosphamide, Hank's Balanced Salt Solution (HBSS), ethylenediaminetetraacetic acid (EDTA), Trizma base, Triton X, and propidium iodide were purchased from Sigma Chemicals.
Data Analysis. Results from bronchorelaxant effect evaluation are expressed as means ± SEM of measurements in n preparations from different animals, except for the EC 50 , where it is given as the geometric mean accompanied by its respective 95% confidence limit. The EC 50 (i. e. , the concentration of drug causing half-maximum relaxant response) and the pEC 50 (the negative logarithm to base 10 of the EC 50 of an agonist) were calculated in each concentration-response curve, by nonlinear regression analysis. Student's t-tests for paired and unpaired samples were used to determine the significance of differences between mean values in all control and test tissues. For the comet assay, data were statistically analyzed using Prism Software. Normality and homogeneity of variance were verified by Kolmogorov-Smirnov test and Bartlett's test, respectively.
Analysis of variance (ANOVA) for multiplesample comparison was applied when normality and homogeneity of variance in several distributions of investigated parameters were satisfied, followed by Tukey's post hoc analysis. Nonnormal data were log-transformed to attain normality, thus allowing the application of parametric statistics ANOVA  [32]. Data were analyzed with GraphPad software (GraphPad Software Inc. , San Diego, CA, USA). Differences were considered statistically significant when  values were <0. 05 ( * ), <0. 01 ( * * ), and <0. 001 ( * * * ).
Acknowledgements This study was funded by  UNICEF, Vietnam and IRD, France. The authors would like to acknowledge the assistance of the directors and teachers from 2 Kindergartens in Trac Van and  Tien Noi  communes,  Duy Tien  district, the leader of Commune Health Centers in these two communes and the director and staff of the  Provincial Health Center in Ha Nam province. We like also to thank  Dr Ou Kevanna  from  National Nutrition Program, Cambodia  who generously provided the Plumpy'nut® RUTF for this study,  Mr. Eric Fettke , executive chef of  Intercontinental Hanoi Westlake Hotel  and his staff for use of the 50L mixer in the kitchen of the hotel, and  Mr. Marco Sarh  of  Oasis shop, Hanoi  for use of the seal machine in the initial phase of the product development. The study was approved by the  Scientific and Ethical committees  of the  National Institute of Nutrition, Ministry of Health, Hanoi, Vietnam.
ESI-MS/MS analysis UPLC-MS/MS analysis was carried out on a Xevo TQD® (Waters Corporation, Milford, U. S. A. ). We used parameters of detection as detailed by  Armenta et al. (2010). The ESI source was operated at 150°C with a desolvatation temperature of 450°C, a 900 L/h desolvatation gas flow rate and a capillary voltage set at 3. 2 kV. The extractor voltage was set at 3. 0 V, and the radio frequency voltage at 2. 5 V. The cone voltage varied from 27-39 V, depending on the amino acid investigated. Argon was used as the collision gas, and collision energies varied from 19 to 35 eV. Multiple Reaction Monitoring (MRM) was performed in the positive mode. Integration and quantitation were performed using the Waters Targe-tLinksTM software.