dataesr/scientific-paragraphs-categorization huggingface dataset:
A questionnaire on lifestyle and health problems was administered, and a number of anthropometric, biochemical, biophysical and medical measurements were taken. The data presented here are limited to individuals aged 35 through 74 years in cohort 1 and in cohort 2. The following variables measured at the entry examination were used for the present analysis: age, sex, SBP and diastolic BP (DBP) measured according to a standardized procedure (see below), total serum cholesterol, high-density lipoprotein (HDL), smoking status, body mass index (BMI). Biochemical measurements were assayed by enzymatic methods: they were performed partly under the external control of the WHO Lipid Reference Center of Prague. In separate analyses (detailed results not reported) we used also fasting blood glucose (FBG).
Individuals from the IRA study were only men of two villages of Northern (Crevalcore) and Central Italy (Montegiorgio), the latter not far from Gubbio. The analysis refers to baseline data of entry field examination held in 1960 (Fig. 2 ), when the cohorts were aged 40-59 years, with a participation rate of 98. 5%, and a follow-up for mortality of 50 years  12. The 45 baseline variables included age at baseline, family and social indicators, skeletal and anthropometric measurements, biophysical and biochemical measurements, clinical observations and diagnoses of selected major diseases. The following information and measurements taken at the entry examination were used for the present analysis: age in years, approximated to the nearest birthday, sex, SBP according to a standardized procedure (see below), serum cholesterol in mmol/L measured on a casual blood sample, smoking status (the number of cigarettes smoked on average per day, recorded from a standard questionnaire: 0 cigarettes for ex and never smokers), BMI expressed in kg/m 2 , derived from height and weight measured according to the technique described in the WHO Cardiovascular Survey Methods manual  13.
The Abel-Kendall method modified by Anderson and Keys was used for cholesterol measurements  14. Baseline data were collected in the early 1960s before the era of the Helsinki Declaration. Later, oral informed consent was obtained in view of collecting follow-up data. Blood pressure measurements. In the Gubbio cohort, BP was measured by a physician with the participant in a sitting position, on the right arm positioned at heart level, using a mercury sphygmomanometer with appropriate-sized cuffs. Three measurements were taken following the procedure described in the 1975 WHO Manual  15. The first measurement was taken at baseline after 5 min rest, then the remaining two measurements were taken approximately 1 minute each apart while the physician remained in the office. Measurements were made by four physicians who had undergone a specific training in BP measurement at the Istituto Superiore di Sanità (National Institute of Health) in Rome and at the London School of Hygiene and Tropical Medicine.
Follow-up and outcomes definition. In the Gubbio study, the follow-up was conducted during approximately 20 years (median 185 months), lasting from 13. 5 to 19. 5 years after the entry examination depending on the cohorts involved (either Exam 1 or 2). In the IRA study, the follow-up was obtained at quinquennial re-examinations (until year 40 of follow-up, except for year 15) and performing systematic searches of possible new events during 50 years. In both studies, CV events were identified using data collected in subsequent field examinations and for those who did not attend, review of hospital records, interview with subjects, family physicians and telephone interviews. Home visits and postal questionnaires were performed only in the IRA study. Subjects were classified as lost to follow-up after systematic telephone search, home visits, and review of local municipality registers assigning a date when presumably last seen alive.
The same criteria described above were used to identify prevalent cases of CVD recorded at entry examination that were excluded from analysis, together with other less common heart diseases, when appropriate. In all cases, only the first event was used for the analysis. Major cardiovascular events were coded following the 9th Revision of the WHO-International Classification of Diseases  17  for the Gubbio study and 8th Revision of the WHO-International Classification of Diseases for the IRA study  18. Details on the diagnostic procedures and criteria are reported elsewhere for Gubbio  19, 20  or IRA studies  21, 22. Statistical analysis. Briefly 5 data were expressed as means ± SD or percentage. Comparisons between groups were done by Student's t-test or chi 2 -test, where appropriate. Survival curves were estimated using the Kaplan-Meier product-limit method and were compared by the Mantel log-rank test.
Informed written consent was given by and filed from all participants. The study was chaired by a steering committee until early 2016 when the Centro Studi Epidemiologici di Gubbio (CeSEG) came into effect to chair it, under the auspices of the Italian Authority for Privacy. For the IRA study, baseline data were collected in the early 1960s before the era of the Helsinki Declaration. Later, oral informed consent was obtained in view of collecting follow-up data.
On the other hand, the time difference between measurements was much shorter than that commonly used in this kind of approach. Limitations. The Gubbio and IRA studies did not perform ABPM neither was BP measured at home. For the Gubbio study, standard risk factors were measured in the context of an epidemiological investigation in the 80's which had, among its goals, that of assessing the impact of community control of BP and the relationships between mortality and changes in CVD risk factor levels although the use of questionnaires may well be considered a limitation  28. On the other hand, the IRA study was made to identify CVD risk factors at the beginning of the sixties and ABPM did not exist at the time. Moreover, the analysis and interpretation of the IRA data might have slightly different meaning compared to those of the Gubbio study.
Acknowledgements The Authors acknowledge the role of the Municipal ad  Health Authorities of Gubbio, of the CeSEG and of the citizens of Gubbio. The research described in this paper was carried out in the context of a PhD Thesis at the  University of Caen-Normandie, France , and the analysis was undertaken at the  Department of Pharmacology, CHU, Caen, France , after authorization and approval by CeSEG as of January 20, 2017, under the auspices of the Italian Authority for Privacy. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Reliable and accurate detection of native proteins was obtained by optimizing instrumental and biochemical parameters as described in a previous work  19  and in agreement with the work by Chen and Russell 20. For "native" experiments instrumental and hardware parameters were optimized to reach the best average signal to noise ratio while preserving intact quaternary and tertiary structures. Ion mobility data were also recorded in the same experiments. For analysis under non-denaturing conditions the following instrumental parameters were used: capillary voltage = 4. 5 kV, sampling cone = 150 V, source offset, 150 V, nebulization gas pressure = 5 bar, source temperature, 40 °C, desolvation temperature, 75 °C. For ion mobility (IMS) experiments in nitrogen as drift gas, the following instrumental parameters were used:: Trap gas flow = 7 ml/min; He gas flow = 120 ml/min, IMS gas flow = 45 ml/min, Trap wave velocity = 300 m/s, Trap wave height = 4 V, IMS wave velocity = 800 m/s, IMS wave height = 40 V, Transfer wave velocity = 110 m/s and Transfer wave height = 4 V.
Data analyses, processing and interpretation of ion mobility experiments. After recording ion mobility data, we extracted all information, such as mass to charge ratios (m/z), drift times (t d ) and intensities, using the peak detection procedure of Driftscope TM software. All the data were gathered in a raw data file (. csv). Then our home-made script  8  allowed extracting information only related to the protein of interest by entering its average molecular mass, the m/z accuracy, limits of the charge states distribution as well as collisional cross section (Ω = CCS = collisional cross sections) calibration parameters. This allowed us to rapidly process the data and plot Ω = f (z) (Ω = CCS = collisional cross sections; z = charge state) graphs to reveal the conformational landscape of PrP that were used to explore our data.
This experimental set-up was designed to form 8 supplemented males, originating from 4 different litters, per group at each studied age. Due to the death of one of the pups during the supplementation period (this pup was then replaced by an untreated one to equilibrate the litter size), the number of pups in the FOS group at PND14/15 was reduced to 7. These values are maximum numbers that are not always found in each of the analyses (see the illustration legends). This stemed from either physiological reasons (e. g. , 2 animals did not eat at all during the fasting-refeeding test), or because of quality requirements (e. g. , reliable data from in physiological cages could only be obtained for n = 7 in CTL and GOS/In groups; n = 6 in FOS group and n = 5 in αGOS group), or statistical inconsistency (e.
Meal Pattern Between PND74 and PND99, eating behavior was analyzed in physiological cages (Phecomb cages, Bioseb, Vitrol, France) as previously described  [8]. Briefly, the rats were housed individually and following 24 h of acclimatization to the cage and refilling with fresh food between 9. 00 a. m. and 11. 00 a. m. , data were recorded every 5 s over a 20-h period. Due to the intervention during the diurnal phase, the analysis was reduced to 8 h whereas the nocturnal phase was 12 h. The exact feeding pattern was defined with a minimal size of 0. 1 g, a minimum duration of 10 s and a minimum inter-meal interval of 10 min. Events such as large vibrations (contact with the feed tray without eating) were filtered by the Phecomb system monitoring software (Compulse v1. 1. 01). The reliability percentage of the quality signal was calculated by the software and only experiments with a percentage >80% were used.
Immunochemistry Tissue sections (4-5 µm) of fixed ileum and proximal colon were double-stained with a goat polyclonal antibody raised against GLP-1 diluted at 1/200 (Santa Cruz Biotechnology Inc, Santa Cruz, USA) and a rabbit anti-chromograninA (chrgA, diluted at 1/1000 (ImmunoStar Inc, Hudson, USA), followed by incubation with anti-goat and anti-rabbit fluorescent secondary antibodies (1/1000). Nuclei were counterstained with 4 ,6-Diamidine-2 -phenylindole dihydrochloride (DAPI, Sigma-Aldrich, St. Quentin Fallavier, France). Tissues sections were mounted in Prolong Gold anti-fading medium (Molecular Probes, Thermo Scientific, Courtaboeuf, France). Three sections per sample were analyzed with a Nanozoomer (×20) (Hamamatsu Photonics France, Massy, France). The number of fluorescent cells along the crypt-villus axis unit was counted twice by a blind operator, using the NDP view software (Hamamatsu, Photonics France, Massy, France).
Paired-end sequencing was performed on a HiSeq 2500 System (Illumina, San Diego, CA, USA) with v3 reagents, producing 250 bp reads per end, following the manufacturer's instructions by the GeT+-PlaGe platform (INRA, Toulouse, France). The 16S rDNA raw sequences were analyzed with FROGS v2 pipeline (http://frogs. toulouse. inra. fr/) [39]. After de-multiplexing, quality filtering and chimera removing, the taxonomic assignments were conducted for OTUs with abundance >0. 005% with Blast using Silva 128 database containing sequences with a pintail score at 80 to determine the bacterial compositions. FROGSSTAT Phyloseq tools were used to normalize raw abundances by rarefaction and to calculate alpha and beta diversity indices.
Statistical Analysis Statistical analyses were carried out using GraphPad Prism 6 software (GraphPad Software Inc. , San Diego, USA) or R (librairies "stats v3. 5. 1" and "corrplot v0. 84",  [40] ). Differences between treatments were searched using one-way ANOVA followed by Tukey's multiple comparison tests for most data, with the exception of growth and food consumption data which were subjected to multiple t-tests with correction for multiple comparison using the Holm-Sidak method. Sweet taste preference test was analyzed by the one sample t-test to compare to compare data against the 50% (no preference) value. A p value < 0. 05 was considered statistically significant.
The total amount of GLP-1 secreted during this period, quantified by AUC, did not differ significantly between the groups (Figure  7C ). PYY secretion did not show any postprandial peak or significant differences between the groups (data not shown). Similarly, at PND 124/126, plasma concentrations of GLP-1 (CTL: 34. 4 ± 13. 5; GOS/In: 38. 6 ±28. 6; αGOS: 28. 9 ± 10. 0 and FOS: 37. 9 ± 20. 6 pM) and PYY (CTL: 84. 7 ± 4. 0; GOS/In: 88. 7 ± 7. 8; αGOS: 91. 4 ± 7. 3 and FOS: 91. 5 ± 5. 8 pM) measured 2h after an oral bolus of glucose did not show any significant difference between groups. To investigate the long-term effect of a neonatal supplementation of OS on subsequent eating behavior, we followed up the food consumption from weaning to adulthood, performed a refined analysis of feeding pattern using physiological cages from PND75 to PND100 and assessed the preference for sugar taste between PND109 and PND111.
Acknowledgments: Authors thank  Vincent Paillé  and  Fanny Morel  for their scientific advices;  Edith Gouyon ,  Aurélie Reufflet ,  Agnès David-Sochard ,  Martine Rival ,  Guillaume Poupeau  and  Elise Beneteau  for their technical assistance. They are also grateful to the  Genotoul platforms (GetPlaGe, Genotoul-bioinfo and Sigenae, INRA, Toulouse-Midi-Pyrénées, France ) for 16S rDNA sequencing and for providing help in computing and storage resources thanks to Galaxy instance.
Method This research project was undertaken as part of the European Knowledge Hub "Malnutrition in the Elderly (MaNuEL)," which aimed to tackle the problem of malnutrition in the older population by targeted cooperation of 22 research groups from seven countries  (Visser et al. , 2017). During a two-day live-meeting in April 2018 in Biedenkopf/Germany, determinants of malnutrition, their interrelations, and the mechanisms underlying the development of malnutrition were discussed by eight MaNuEL partners (involved in the MaNuEL work-package about determinants of protein-energy malnutrition) and eight external experts in the field of geriatric nutrition. All MaNuEL partners qualified in national competitions for participation in the MaNuEL Knowledge Hub. External experts were a convenience sample of renowned international experts with relevant scientific and/or clinical experience and complementary professional background, selected by the first and last authors of this article (D.
Acknowledgments The authors are grateful to the following experts who contributed to the development the model in addition to the authors (in alphabetical order):  Anne Marie Beck ,  Clare Corish ,  Andrea Correa-Perez ,  Dominique Dardevet ,  Marion Flechtner-Mors ,  Corinna Geisler ,  Lisette de Groot ,  Mary Hickson ,  Sylvie Issanchou ,  Gabriele Nagel ,  Eiblhìs O'Connor ,  Maryam Pourhassan ,  Tamara Ranzenberger-Haider ,  Ilse Reinders ,  Yves Rolland ,  Melanie Streicher ,  Claire Sulmont-Rossé ,  Ruth Teh , and  Virginie van Wymelbeke.
15HDHL2 ); Spain:  Instituto de Salud Carlos III , and the SENATOR trial (Grant No. FP7-HEALTH-2012-305930 ); The Netherlands: The  Netherlands Organization for Health Research and Development (ZonMw ; Grant No. 529051008 ). This work was further supported by the BANSS foundation who enabled a two-day live meeting of the experts without any obligation. The funders were not involved in the development of the model at any time.
001 and 1000%. The evolution of G′ allowed to identify the critical stress τc (Pa) limiting the linear viscoelastic region (LVR). The critical stress was determined when the G′ value decreases more than 5% with respect to the previous average value. This critical stress corresponding to the LVR G', was considered as the viscoelastic response. Data were recorded with the Rheopus software and analyses were performed at least in duplicate.
Statistical analyses All analyses were performed in duplicate or triplicate and the results presented as mean ± SD. Statistical significance of differences between sample means was determined using analysis of variance (ANOVA) followed by a Duncan's test at 95% confidence level using Statistica 7. 1 software (StatSoft, Maison-Alfort, France). The Minitab 18 program was used to generate the experimental design and mathematical models, as well as for construction of the graphs. The models were subjected to analysis of variance (ANOVA) to assess the level of significance, the coefficient of determination (R 2 ) and the lack of fit of the model. The results of the experimental design were exploited in the form of specific response surfaces for each parameter. This presentation makes it possible to visualize the evolution of the predicted parameters according to the different explanatory variables (fermented cassava, sweet potato and sorghum flour proportions).
Acknowledgments This work was carried out within the framework of the  PDMACIM (Cassava Sustainable Production in Central Africa and Market Integration ) project funded by the  European Union  ( DCI-FOOD/2010/ 252-886 ) and coordinated by  PRASAC (Pôle Régional de Recherche Appliquée au dévelopement des Systèmes Agricoles d'Afrique Centrale). Our thanks go to  Thierry GOLI  for his expertise in the development and exploitation of the results of the mixing design.
Materials and Methods This is an observational study using milk bank data. In our level III Maternity Hospital, mothers' own milk is pasteurized for premature infants. After pasteurization, we routinely analyze breast milk composition to verify the appropriateness of standardized fortification. For the purpose of the study, we collected data for all of the milk batches that each mother provided to the milk bank regardless of the time of the milk collection to evaluate the milk composition variation throughout the first five weeks of lactation. Each batch is a pool of one to three days, depending on the volume collected and frozen by each mother at home. Once a volume of at least 500 mL was collected, the mother would hand over the frozen batch to the milk bank for pasteurization. Hand-over occurred daily to twice a week.
Mothers who delivered a premature infant before 34 weeks' gestation at our unit were enrolled within five days after delivery when they announced their choice for breastfeeding. Mothers' dietary preference and nutritional intake data were obtained during personalized interviews with experienced dieticians. They used standardized questionnaires based on validated documents in the National French survey. The dieticians recalled dietary intake information from the two weeks prior to the interview. Perinatal data were prospectively collected at the time of the interview and from the mothers' file. We analyzed maternal diet and macronutrient intake from the recall data averaged per day with appropriate software (Geni ® V7. 0, Micro6, Villers les Nancy-F, France). For milk analysis, we used the same protocol as described in the literature  [7, 8]  and advised by the manufacturer.
3 μM were incubated with 10 μM thioflavin T (ThT) in 10 mM Na-acetate buffer, pH 5. 0 for 1 min at room temperature before fluorescence measurements. ThT emission spectra were recorded after excitation at 450 nm. The excitation and emission slit widths were 4 nm. Proteinase K Digestion. Fibrils were treated with proteinase K (proteinase K to PrP ratio of 1:100) at 37 °C for 1 h. 5 μg of PrP fibrils were thus digested using 0. 05 μg of PK, and the digestion reaction was stopped with 2 mM phenylmethylsulfonyl fluoride. Samples were heated in denaturing sample buffer (60 mM Tris-HCl, 2% SDS, 5% β -mercaptoethanol, 2. 25 M urea) at 95 °C for 10 min and separated on 12% Criterion ™ XT Bis-Tris Precast Gels (Bio-Rad) followed by silver staining. Quantification of protein-band intensities was performed by densitometric analysis using Image Lab software (Biorad).
Estimation of the Kinetic Parameters. static Light scattering temperature Ramping. Static light scattering temperature ramping experiments were performed on a homemade device using a 407-nm laser beam in 2-mm quartz cuvettes and in a thermostated cell holder starting at 20 °C and up to 90 °C. Light-scattered signals were recorded at a 112° angle. Signals were processed with a homemade MatLab program. For both types of experiments, PrP fibril concentration was fixed at 1 μM (monomer equivalent). The cuvette was removed from the holder at high temperature and gently inverted to mix the sample. No change in the scattered light was observed suggesting the complete dissociation of the protein assembly. FTIR-ATR Spectroscopy. Spectra were recorded on a Bruker Equinox 55 spectrometer equipped with a MCT detector, using a spectral resolution of 4 cm -1.
Materials and Methods In order to delineate the olfactory and gustatory genes, scaffolds (sf. , see supplementary data set S1, Supplementary Material online) from the draft of the catshark genome (to be published elsewhere) and recent elephant shark genome  (Venkatesh et al. 2014)  were obtained by genome-wide searches using TBlastN with the representative TAS1R, TAS2R, OR, TAAR, ORA, and V2R sequences from mouse, frog, elephant shark, Latimeria and zebrafish as queries, and recursively in follow-up searches. For TAS1R phylogeny we additionally searched for spotted gar sequences. Homology regions above 200 amino acid length were considered further. Splicing predictions were made by comparing related protein sequences to genomic DNA sequences with the online-tool GeneWise  (Birney et al. 2004 ).
bio. ed. ac. uk/software/figtree/, last accessed January 22, 2019). Newly predicted genes were named according to previously named orthologs or closest paralogs from other species, starting with more basal genes. Gene with one or more stop codons was labelled as pseudogene. One or gene may either represent pseudogenes or databank inaccuracies due to the preliminary assembly (fig. 2 , supplementary data set 1, Supplementary Material online). Fifteen genes are full or nearly full length (above 700 aa), three are partial (between 550 and 700 aa), fifteen and nine sequences were restricted to one of the large exons (exon 3 and exon 6, respectively). In those cases, where exon 3 and exon 6 might be derived from the same gene, we distinguished with a letter, for example, Sc-V2R2a and Sc-V2R2b.
Acknowledgments We thank the  Genoscope-Centre National de S equenc¸age (Evry, France)  for sequencing the catshark draft genome used in this work,  H elene Mayeur  ( UMR 7232 ,  Observatoire Oc eanologique, Banyuls sur Mer, France ) and  Jean-Marc Aury (Genoscope)  for assembling these data. This work was supported by the  German Science foundation  (grant  KO 1046/7-1  to S. I. K. ).