dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgments The members of the  Euro-Peristat Scientific Committee  are:  Gerald Haidinger ,  Department of Epidemiology, The Medical University of Vienna (Austria );  Sophie Alexander ,  School of Public Health, Universite Ĺibre de Bruxelles (Belgium) ;  Pavlos Pavlou ,  Health Monitoring Unit, Ministry of Health (Cyprus); Petr Velebil, Institute for the Care of Mother and Child, Perinatal Centre Prague (Czech Republic );  Jens Langhoff Roos, Obstetrics Clinic Rigshospitalet, Copenhagen University (Denmark) ;  Luule Sakkeus ,  Estonian Institute for Population Studies, Tallinn University (Estonia );  Mika Gissler ,  THL National Institute for Health and Welfare (Finland) ;  Beatrice Blondel, Epidemiological Research Unit on Perinatal and Women's and Children's Health ,  INSERM UMRS 953 ,  Universite Ṕierre-et-Marie Curie Paris6  (France);  Nicholas Lack, Bavarian Working Group for Quality Assurance (Germany) ;  Aris Antsaklis ,  Department of Obstetrics and Gynaecology, Athens University (Greece) ;  Istvan Berbik, Department of Obstetrics and Gynaecology, Vaszary Kolos Teaching Hospital (Hungary) ;  Sheelagh Bonham ,  National Perinatal Reporting Scheme, Economic and Social Research Institute (Ireland) ;  Marina Cuttini ,  Unit of Epidemiology, Pediatric Hospital of Baby Jesus (Italy) ;  Janis Misins ,  Center for Disease Prevention and Control (Latvia) ;  Jone Jaselioniene ,  Department Epidemiology and Biostatistics, Institute of Hygiene (Lithuania );  Yolande Wagener ,  Department of Health, Ministry of Health (Luxembourg) ;  Miriam Gatt ,  Department of Health Information and Research, National Obstetric Information Systems (NOIS) Register (Malta) ;  Jan Nijhuis ,  Department Obstetrics and Gynaecology, Maastricht University Medical Centre (The Netherlands );  Kari Klungsoyr ,  Medical Birth Registry of Norway, University of Bergen (Norway );  Katarzyna Szamotulska ,  Department of Epidemiology ,  National Research Institute of Mother and Child (Poland) ;  Henrique Barros ,  Department of Hygiene and Epidemiology, University of Porto Medical School (Portugal); Maria Chmelova, National Health Information Centre (Slovak Republic ); Z ˇiva  Novak-Antolic, Perinatology Unit, University Medical Center (Slovenia) ;  Francisco Bolu  ´mar,  Department of Health Sciences and Social Medicine, University of Alcala(Spain) ;  Karin Gottvall ,  Department of Statistics, Monitoring and Evaluation, The National Board of Health and Welfare, (Sweden );  Alison Macfarlane , Maternal and  Child Health Research Centre, City University London (United Kingdom ).
Fruit sampling and treatments Fruits were harvested at breaker stage (corresponding to 32 days after anthesis) at dawn and peduncle scars were covered with Terostat to limit water loss. This stage of development was chosen as shading fruits earlier on the vine had no effect on fruit AsA content at harvest, but shading fruit at the green mature stage and later significantly affected fruit AsA content at harvest (data not shown). Harvested fruit were weighed and external colour assayed. They were then split into three groups having similar mean size and colour: one was used to assay pericarp composition at harvest; another one was placed under continuous light for 56h and the last one in darkness for 56h to discriminate the impact of light on fruit composition. This distribution of fruits was repeated for each temperature tested.
Data were acquired, processed and analysed with a computerized system running IOX v1. 56. 8 and Datanalyst v1. 58 software (EMKA Technologies France). An initial load of about 3 g was applied to each segment, which rapidly fell down to a basal tone comprised between 1. 5 and 2. 5 g during the stabilisation period, when the preparations were allowed to stand for thirty minutes with renewal of the Krebs-Henseleit solution every ten minutes. In a first set of experiments, the bronchi were pre-contracted with 10 μM histamine. Increasing concentrations of bitter taste receptor agonists (chloroquine, quinine, denatonium, colchicine, phenanthroline, strychnine, diphenidol, ofloxacin, caffeine and saccharin) or known bronchial relaxants (isoproterenol, formoterol and theophylline) were then added when the equilibrium tension of the previous concentration was reached (generally every 7-10 minutes).
Statistical analysis Values in the text and figures are expressed as the arithmetic mean ± the standard error of the mean (SEM) from experiments with bronchi from n independent donors. Changes in muscle tone (E) were expressed as a percentage of the relaxation obtained with 3 mM theophylline. E max corresponds to the E value obtained with the highest agonist concentration tested. The potency (pD 2 ) of agonists was defined as the negative logarithm of the molar concentration of agonist producing 50% of the maximal effect (EC 50 ) and was calculated from the concentration-response curves. Sigmoidal concentrationresponse curves were plotted and analysed with GraphPad Prism software (version 5. 01, GraphPad Software ® , San Diego, CA, USA) by non-linear regression. The quantitative data obtained from RT-qPCR experiments was expressed as relative expression (2 -ΔCt )  [19] , where ΔC t is the difference between the target gene C t and the mean C t of the reference genes.
Statistical Analysis First, univariate analyses were carried out to investigate the effects of salt content and z-BMI on target food intake, hedonic score and preference rankings. Second, a multivariate analysis was performed using Structural Equation Modeling (SEM) to evaluate the respective weights of the different variables in influencing the intake of the target foods. The significance level was set at p,0. 05. Univariate analyses. The analyses were carried out using SAS Software (9. 1, SAS Institute Inc. , Cary, NC, USA). Intake (g) and hedonic score data for both target foods were analyzed using a linear mixed model (SAS Mixed procedure), with 'child' considered as a random effect. The primary factor tested in the model was salt content, and z-BMI was introduced as a covariate. The model was the following: Intake (or hedonic rating) = food+salt content+z-BMI+food 6salt content+food 6z-BMI+salt content 6 z-BMI+error.
The 'Empirical' option was specified to include a sandwich estimator for the variance-covariance matrix of the fixed-effect parameters. If a significant food 6 salt content interaction was found, the data were analyzed for each target food separately using the mixed linear model: Intake (or hedonic rating) = salt content+z-BMI+salt content 6 z-BMI+error. The preference rankings and saltiness rankings for each food were analyzed according to the model: Ranking = salt content+error. If a significant effect was revealed, multiple mean comparisons were applied using the Dunnett test: the reference salt content (0. 6% added salt) was compared to the other variants. The data are reported as means 6 SEM. Structural equation modeling (SEM) analysis. Structural Equation Modeling and bootstrap analyses were conducted with R2.
10. 1, using the SEM package  [22]  to assess a causal pathway derived from theory  [23]. Dataset structure and variable definition. The SEM method can handle multilevel data  [24]. In this study, the following variables were taken into account: intake (of vegetable salad, chicken, green beans and pasta), hedonic score and preference ranking (of green beans and pasta with different salt contents), salt content and z-BMI. There were two levels of data, as some variables were recorded at the meal level (level 1; intake of each food item), whereas others were recorded at the child level (level 2; hedonic rating or preference ranking for green beans or pasta with a given salt content, z-BMI). For green beans and pasta, the hedonic rating of the variant with 0. 6% added salt was used as a measure of the 'overall hedonic rating' of each food, and the hedonic rating difference relative to the variant with 0.
Results Data for 75 children  (35 girls)  were taken into account in the present analysis. Three hundred forty-nine meals were recorded. One, 3, 17 and 54 children took part in 2, 3, 4 and 5 meals, respectively. The children's mean age was 9. 460. 1 years (range: 8 to 11 years), with a mean BMI of 17. 160. 3 kg/m 2 and a mean z-BMI of 0. 4960. 15 SD (range: 2. 28 to 4. 23 SD). Of these children, 11% were considered overweight or obese (z-BMI. +2 SDs)  [30]. Over the five lunches, the average total intake was 36769 g (range: 137 to 520 g), and the average total energy intake was 41269 kcal (range: 172 to 570 kcal) or 1723638 kJ (range: 720 to 2384 kJ). A paired t test showed that over the five lunches, green bean intake (7564 g; range: 4 to 160 g) was lower than pasta intake (13665 g; range: 61 to 200 g) (t 74 = 10.
Our model could have been improved by including variables that were difficult to measure in the context of the present work, such as parental guidance regarding food consumption or children's cognitive attitudes towards the target foods. Nevertheless, this modeling approach improves our understanding of the positive but moderate role that salt content plays among the other factors that influence intake. We showed that z-BMI was specifically related to pasta intake and not to 'hunger', as we considered in the initial model. This result should be confirmed with a new and independent dataset to reach a definitive conclusion. Nevertheless, this effect is in accordance with a previous observation that heavier 2-to 3year-old children tend to consume more pasta  [16]. It is possible that heavier children seek energy-dense foods: greater BMI correlates with greater intake required to satisfy energy needs  [25].
The results of the present study should be interpreted in light of its strengths and limitations. The study used familiar foods and took place in the children's usual eating context with their classmates and caregivers. This context remained constant over the study duration. Moreover, the intake and hedonic rating data were collected from the same group of children. In other respects, this work has also some limitations. First, children's intakes may have been constrained by the fixed menu; the children could have chosen to eat other saltier foods if they had been available. Another limitation is related to the fact that it is difficult to generalize the present findings to other foods (other vegetables, other starchy foods or other salty foods) because the salt content effect appears to be food specific.
Acknowledgments S. B. wishes to thank the director and staff of Saint Dominique school in Dijon, as well as the children and their parents who took part in this study,  Dr. V. Boggio  for his support and advice, and  V. Feyen ,  E. Szleper ,  G. Enderli ,  V. De Anfrasio ,  J. Pierard ,  C. Puig ,  L. Gourier ,  E. Mugneret  and  F. Durey  for their assistance with food preparation and data collection.
This work was supported by a PhD grant from the  Nutrition, Chemical Food Safety and Consumer Behavior Division of INRA (French National Institute for Agronomical Research, France)  and the  Regional Council of Burgundy  (France) received by SB; and by a research grant (Gustolf) from  Regional Council of Burgundy  (France) received by  SN. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Acknowledgements This work has benefited from research funding from two patients associations:  E3M  ( Entraide aux Malades de Myofasciite à Macrophages ) " Neurodélivrance des particules injectées par voie intra musculaire et sécurité des adjuvants aluminiques " ,  AFM  ( Association Française contre les Myopathies) "Etude des mécanismes de la myofasciite à macrophages" and Dwoskin Foundation  (Nano in brain); from  Région Ile-de-France  through a programme  PICRI (Partenariat Institutions-Citoyens pour la Recherche et l'Innovation)  " Recherche de polymorphismes dans les gènes codant pour des facteurs inflammatoires (chimiokines) dans la myofasciite à macrophages ", and through two post-doctoral positions from  NeRF (Neuropole de Recherche Francilien)  on the topic "The macrophage as a  Trojan horse for brain delivery" and "Brain delivery of i.
Sampling The pre-implementation study comprised 362 mothers (178 in the district of Nyanza and 184 in the district of Bugesera) with a participation rate of 98%. Its aim was to collect basic data to be used to evaluate the impact of HBM after implementation. For the post-implementation study, sample size was calculated to include at least 40% of febrile children aged less than 5 years treated within 24 hours of symptom onset in the experimental district (or two times more than in the control district). With a power of 90% and a 95% confidence interval, taking into account a cluster effect of 2 and a non-response rate of 2%, the minimum number of mothers required in the two districts was 376, or 188 in each district. All mothers took part in the study, a participation rate of 100%. During the two studies, before and after implementation, the mothers investigated were recruited in cells (the smallest administrative unit at the time), which were selected by the cluster sampling method.
In this study, « mother » refers to the carer of the sick child in the household. The aims of the study were first explained to the mothers, who were then included in the study after giving their voluntary informed consent. Mothers who were not resident in the district were excluded from the study. The mothers were interviewed face to face and the questionnaires were directly filled in by the investigators. Experienced investigators were carefully selected and trained in administration of the questionnaire. The questionnaires were translated into kinyarwanda (the native language of Rwanda) and pre-tested before being applied. The completed questionnaires were checked the same day to ensure they were correctly and fully completed. Double data entry was performed using Epi Info 3. 3. 2 (CDC, Atlanta, GA, USA).
Acknowledgments We are grateful to the health and administrative authorities of the districts of  Nyanza and Bugesera  for their excellent collaboration. We are particularly grateful to all the investigators and all the mothers who participated in this study. This study received financial support from the  University of Nantes , France, through  Laboratoire EA 3826  ( Thérapeutiques Cliniques et Experimentales des Infections ) and the  Laboratoire de Santé Publique et d?Epidémiologie of the Faculty of Medicine, University of Nantes.
Licking tests. This test was performed to analyze the shortterm (1-5 min) preference for an LCFA by using computer-controlled lickometers (Med Associates). Animals were successively subjected to the control or the experimental solution, and the number of licks given on each bottle by min was determined. Mice were food and water deprived 6 h before the test, which took place 6 h after the beginning of the dark period. After a training period required to learn the procedure, mice were randomly subjected to a bottle containing a control solution (mineral oil; Cooper, France) or a bottle containing an experimental one [mineral oil + 0. 5% oleic acid (OLA); Sigma-Aldrich] for 15 min. Then mice were offered the other bottle for an additional 15 min session. In this experiment, data were analyzed for 1 or 5 min from the fi rst lick to exclude postingestive signals.
The changes in intracellular Ca 2+ ( F 340 / F 380 ) were monitored under the Nikon microscope (TiU) by using an S-fl uor 40× oil immersion objective. The planes were taken at Z intervals of 0. 3 m, and NIS-Elements software was used to deconvolve the images. The microscope was equipped with an EM-CCD (Lucas) camera for real-time recording of 16 bit digital images. The dual excitation fl uorescence imaging system was used for studies of individual cells. The changes in intracellular Ca 2+ were expressed as ⌬ Ratio, which was calculated as the difference between the peak F 340 / F 380 ratio. The data were summarized from the large number of individual cells (20-40 cells in a single run, with three to nine identical experiments done in at least three cell preparations). For experiments in Ca 2+ Ϫ free medium, CaCl 2 was replaced by EGTA (2 mM).
this observation, Western blotting analysis was performed in CVP. Similar expression levels of CD36 were found in control and obese mice, whatever the duration of HF diet ( Fig. 4B  ) or the composition of obesogenic diet used (HFHS -supplementary data II). It was recently reported in mouse CVP that CD36 protein levels are downregulated by lipids during the postprandial period  ( 11 ) , and a disturbance in this regulation affects the spontaneous attraction for fat  ( 13 ). Therefore, it was tempting to speculate that the lower attractive effect of oily solutions found in obese mice might be due to a dysfunction in this regulatory loop controlling the amounts of CD36 in CVP during a meal. To explore this hypothesis, CD36 protein levels in CVP were compared in fasted and refed controls and DIO mice.
Indeed, this quality improvement project was started after we demonstrated the failure of our regular teaching program to educate the medical team in ordering complex artificial nutrition in ICU patients. To improve nutrition support ordering we created an Excel spreadsheet (Office 2000, Microsoft TM ) providing a simple tool available to all physicians on the workstations dedicated to computer-assisted ordering. This computer help is provided in electronic supplement (File S1). It helps physicians to quickly assess their nutrition support orders according to recommended goals for a given patient. The main objective of this quality-improvement study was to determine whether a simple computer help permitted an improvement in nutrition support orders. The second objective was to determine whether improved nutrition ordering was associated with improved outcome in critically ill patients.
200 ml/6 hours despite administration of prokinetic drugs) as recommended  [20]. No nutrition practices were changed during the study except the use of the computer help for nutrition ordering. Glycemic control was achieved if necessary during both study periods by an insulin drip to target a glucose concentration between 1. 0 and 1. 5 g/L. Evaluated parameters. Baseline data collection included age, sex, height, weight, BMI, Simplified Acute Physiology Score (SAPS II)  [21] , Sequential Organ Failure Assessment (SOFA) score  [22]  and diagnosis category upon admission to the ICU (postoperative intervention of the digestive tract, liver transplant, medical digestive disease, other). The amounts of calories and nitrogen ordered were recorded each day from the first day of stay in ICU (Day-1) until Day-15 in absence of oral feeding, or until the day oral feeding was started without any nutrition support ordering.
Less than 1% of the 29 patients managed with the program were prescribed less than 80% of recommended calorie intake compared to 21% of the 32 patients managed without the program. Although this program is free to access, it functions with Palm OS exploitation system which is rarely used  [13]. Our system has the advantage of being very simple and does not need specific software, Excel being widespread. Furthermore the file is compatible with the Open Office series spreadsheet (Oracle Corporation, Redwood Shores, CA) which is free. The recent widespread use of smartphones by primary care team  [31]  will increase the availability of this simple tool since Excel spreadsheets are easy to use with several smartphones. Enteral nutrition delivery was increased in the computer help group even if it remained lower than parenteral nutrition.
Acknowledgments We are grateful to  INRA Domaine de Vassal, Marseillan (France) ,  INRA Colmar (France)  and  Rancho de la Merced ,  Jerez de la Frontera  (Spain), institutions which provided pips from modern wild grapevines and cultivars, and to  S. Ercisli  ( Erzurum University ) who helped us during field sampling of pips from local cultivars in Eastern Turkey. Many thanks to the directors of the excavations and to their teams who helped us sample the archaeobotanical material:  G. Ayala  (INRAP),  J. -F. Berger  ( CNRS ),  N. Bernigaud (UNSA) ,  R. Bourgaut  (CCNBT),  J. -Y. Breuil  (INRAP),  L. Buffat  (INRAP),  J. -B. Chevance  (INRAP),  M. Compan  (INRAP),  F. Conche  (INRAP),  G. Escalon  (INRAP), L. Fabre (INRAP),  M. Guillaume  (INRAP),  A. Hesnard  ( CNRS ),  C. Jung  (INRAP),  M.
Fluorescence emission spectra were recorded at 20 °C between 400 and 600 nm on a Cary Eclipse spectrofluorimeter (Varian) with an excitation at 346 or 488 nm. Buffer contributions were systematically subtracted. The FRET ratio corresponds to the ratio of the acceptor-emitted fluorescence at 520 nm from excitation at two different wavelengths, 346 and 488 nm  (24). All binding data were analyzed using GraphPad Prism software (version 4. 0). G Protein Activation Assays-Purified G␣ q ␤ 1 ␥ 2 trimer expressed in Sf9 cells  (25)  was used in all assays. GTP␥S binding experiments were carried out for 5 min at 20 °C using the fluorescent BODIPY FL GTP␥S analog  (26). The reaction mixture consisted in 200 nM Gq, 200 nM BODIPY FL GTP␥S and 20 nM ghrelin receptor-containing nanodiscs in a buffer 20 mM Tris-HCl pH 7.
4, 150 mM NaCl, 100 M EDTA, 3 mM MgCl 2. Fluo- rescence emission was recorded at 511 nm with an excitation at 500 nm (Cary Eclipse spectrofluorimeter, Varian). All data were normalized to the fluorescence measured under the same conditions with empty discs. Arrestin recruitment assay-The phosphorylation independent arrestin-2 mutant L68C-R169E was produced in E. coli  (27)  and labeled on Cys-68 with the thiol alkylating fluorescent compound monobromobimane  (28). For the recruitment assay, arrestin was added at a 5:1 arrestin:ghrelin receptor-containing discs molar ratio. A 20 mM Tris-HCl, 250 mM NaCl, 0. 5 mM EDTA (pH 7. 4) buffer was used in all experiments. Incubation was carried out for 45 min at 4 °C. The different ligands were then added at a 10 M concentration (or at increasing concentration for the dose-response experiment) and incubated for 45 additional min at 4 °C.
Fluorescence emission was recorded at 20 °C between 400 and 600 nm on a Cary Eclipse spectrofluorimeter (Varian) with an excitation at 380 nm. All data were normalized to the fluorescence measured under the same conditions with empty discs. Fluorescence Spectroscopy-For the bimane fluorescence measurements, all experiments were carried out at the same bimane concentration (5 M range with similar labeling ratios in all cases). The ghrelin receptor-containing discs were incubated with either increasing or saturating concentrations (50 M) of the different ligands for 30 min. In the experiments with the purified effector proteins, the latter were added to the ligand-free receptor (the receptor-to-G-protein ratio was 1:10 and the receptor-to-arrestin ratio was 1:5) and incubated for 30 min. The different ligands were then added, and incubation was pursued for another 30 min.
However, we cannot totally exclude, at this stage of our analysis, an alternative model where the intermediate change in bimane emission intensity would result from A, BODIPY FL GTP␥S binding to G␣q (G␣ q ␤ 1 ␥ 2 ) induced by GHS-R1a-containing discs in the presence of an increasing concentration in ghrelin. Data are presented as the percentage of maximum BODIPY FL fluorescence change measured in the presence of ghrelin. B, BODIPY FL GTP␥S binding to G␣ q triggered by the purified receptors in the absence and in the presence of ligands (full agonist, ghrelin; partial agonist, JMV3002; neutral antagonist, JMV3011; inverse agonist, SPA; ligand concentration, 10 M). 1a, GHS-R1a monomer; 1b, GHS-R1b monomer; 1a:1a, GHS-R1a-GHS-R1a homodimer; 1a:1b, GHS-R1a-GHS-R1b dimer. In all cases, the data represent the mean Ϯ S.