dataesr/scientific-paragraphs-categorization huggingface dataset:
Diet, lifestyle, and anthropometric data Lifestyle questionnaires were used to obtain information on education, smoking habits, alcohol consumption, physical activity and breastfeeding. Data on occupational, recreational, and household PA during the past year either were obtained through a standardized questionnaire. The Cambridge Index of PA was derived by combining occupational with recreational activity level and is summarized into 4 groups: active, moderately active, moderately inactive, and inactive  [19]. Anthropometric measures (body weight and height) were measured at physical examination (except in France, Norway and Oxford UK, self-reported). Body mass index (BMI) was defined as weight divided by squared height (kg/m 2 ). Usual diet over the previous 12 months was assessed at study baseline using validated country/center specific dietary questionnaires  [17, 18] , allowing the calculation of food group and individual nutrient intakes (derived from the EPIC nutrient database  [20] ).
Computation of diet quality scores A total of ten scores were examined; two of them included a combination of dietary and lifestyle variables, while the remaining scores had dietary information only. A large number of diet quality scores exist in the literature  [3, 23, 24]. We based our selection on existing reviews  [24, 25]  and selected scores which have been widely examined, were developed for international comparisons, included only non-invasive data, are recommended by leading guidelines and if different versions existed, in their most recent version. Scores for which two components or more were unavailable in the study population were excluded e. g. alternate Healthy Eating Index (aHEI)  [26] , that requires data on sodium and trans fat, both unavailable in EPIC. The ten selected scores reflect different concepts and can be classified in three broad categories: 1) scores based on general nutritional guidelines: Diet Quality Index International (DQI-I)  [27] , Healthy Eating Index 2010 (HEI-2010)  [28] , WHO Healthy Diet Indicator (WHO HDI)  [5]  and Healthy Lifestyle Index (HLI)  [29] ; 2) scores which measure adherence to disease-specific dietary and lifestyle guidelines: WCRF/AICR guideline score for the prevention of cancer  [13] , the Dietary Approaches to Stop Hypertension (DASH)  [30] ; 3) scores that measure adherence to a regional diet, namely the Mediterranean diet through conceptually different scores, the Mediterranean Diet Score (MDS)  [4] , the relative Med diet score (rMED)  [31]  and the Mediterranean Style Dietary Pattern Score (MSDPS)  [32] , and a score that includes the healthy components of a Nordic diet, the Healthy Nordic Food Index (HNFI)  [33].
Two scores also included lifestyle factors in addition to dietary information: HLI includes BMI, physical activity and smoking and WCRF/AICR score includes BMI, physical activity, and breastfeeding. Computation and the scoring system for each score are summarized in Table  1  and the list of dietary items composing the different scores is provided in S1 Table. When one component of the score could not be computed due to data availability (sodium intake), we calculated a modified version of the score without the sodium component (total maximum score equals total score minus maximum score for the sodium component).
Outcomes All-cause mortality risk was the primary outcome of this analysis and CVD and cancer mortality the secondary outcomes. We also performed sensitivity analysis looking at cancers strongly associated with obesity (including esophagus, liver, pancreas, colorectal, breast, endometrial, kidney, prostate and gall bladder cancer mortality) as their association with diet might be stronger compared to the overall cancer mortality group  [34]. Data on causes of deaths were coded according to the International Classification of Diseases, 10 th Revision (ICD-10)  [35]. Due to differences across participating centers in time to reporting the causes of deaths, followup length was truncated at the date when 80% of causes were known. Causal mortality information was available for 82% of all recorded deaths.
Population dependent Simple Rank intake into tertiles Requires data on olive oil. (Continued) did and did not have the mortality event) and calibration (to what extent the predicted probabilities agree with the reported risk) measures. Discrimination was assessed by the Harrell's Cstatistic, similar to the area under the receiver operator characteristic curve, AUC, adapted to survival analysis  [36]. This indicator ranges from 0. 5 (no discrimination) to 1 (perfect discrimination). Calibration was assessed graphically by plotting the observed risk per decile of predicted risk. A perfect calibration would be seen if the curve falls along the identity line. The predicted-to-observed risk ratios were also calculated. To investigate heterogeneity between different countries we performed sensitivity analyses by fitting our Cox regression models in each country.
We estimated the summary effect with random-effect meta-analyses and heterogeneity via the I 2 metric  [37]. We also used random effects meta-analyses to summarize the discrimination of the models across countries. Stratified analyses by sex and age categories (<50 and 50 years old) were carried out as sensitivity analyses. All analyses were conducted using SAS (Cary, NC), version 9. 3, R version 3. 0. 1 and Stata MP version 13. 1.
Data collection Trained staff administered standardized questionnaires and performed clinical examination at baseline and at the 4-year follow-up. Socio-demographic data, education level, monthly income, smoking status, and medical history were recorded. History of CVD included coronary heart disease, myocardial infarction, heart failure, stroke, peripheral artery disease, and artery surgery or angioplasty. Obesity was defined as a body mass index (BMI) 30 kg/m². Medication use was collected and coded according to the World Health Organization's Anatomical Therapeutic Chemical classification system. All three centers collected blood at baseline. For financial reasons and because of the specific objectives in each center, only two centers (Bordeaux and Dijon) collected blood at 4 years and only one (Bordeaux) urine.
Acknowledgments The  Three-City Study  is conducted under a partnership agreement between the  Institut National de la Santé et de la Recherche Médicale (INSERM) , the  Victor Segalen-Bordeaux II University, and Sanofi-Aventis. The  Fondation pour la Recherche Médicale  funded the preparation and initiation of the study. The  Fondation Plan Alzheimer  partly funded the follow-up of the study. The 3C Study is also supported by the  Caisse Nationale Maladie des Travailleurs Salariés ,  Direction Générale de la Santé ,  MGEN, Institut de la Longévité, Conseils Régionaux of Aquitaine and Bourgogne ,  Fondation de France , and  Ministry of Research-INSERM Programme "Cohortes et collections de données biologiques ". The study also received a grant from the  Agence Nationale de la Recherche (ANR).
Dietary records To assess the adequacy of nutrient intake, a consecutive dietary record over 7 days was completed. All participants received a detailed verbal explanation and written instructions on data collection procedures. Participants were asked to continue with their usual dietary habits during the period of dietary recording and to be as accurate as possible in recording the amounts and types of food and fluid consumed. A list of common household measures, such as cups and tablespoons, and specific information about the quantity in each measurement (grams, etc. ) were given to each participant. Each individual's diet was calculated using the Bilnut 4 software package (SCDA Nutrisoft, Cerelles, France) and the food composition tables published by the Tunisian National Institute of Statistics in 1978.
Statistical analyses All statistical tests were processed using STATISTICA 10. 0 Software (Stat-Soft, Maisons-Alfort, France). Normality of the distribution was confirmed using the Shapiro-Wilks W-test. Paired simple t-test was used to analyze the effect of POMj supplementation on physical performances and RPE. To analyze the effect of POMj supplementation on the biological responses during training sessions (pre-post values), a two-way ANOVA (2 levels [supplementation (PLA and POMj] × 2 levels [training (Pre and Post]) with repeated measures was used. To analyze the effect of POMj supplementation in the recovery kinetic of the selected parameters, one-way ANOVA was used. Post hoc tests were conducted when significant main effects were found using Tukey's honest significance difference (HSD) test.
Telemetry Mice (25-30g) were implanted with TA11PA-C10 (Datasciences Inc. , USA) telemetric implants under pentobarbital anesthesia (12%, Ceva Santé Animale, France). The catheter was placed into the ascending aorta via the right carotid artery and the emitter subcutaneously in the right flank. Animals were then allowed for at least 1 week recovery before first baseline recordings. Heart rate (HR), systolic (SBP), diastolic (DBP) and mean arterial pressure (MBP = DBP+1/3(SBP-DBP)) were collected using the Dataquest ART system version 1. 1. PP was defined as the difference between SBP and DBP. Data were sampled by averaging the last 15 seconds of each 15 minutes period and stored on a hard disc. These measurements were performed during two consecutive days, every weekend to avoid disturbances (presence of coworkers in the animal facility).
Activities of ISA-type and PUL-type DBEs toward pullulan In this study, the reactivity of DBEs toward pullulan was examined by detecting MOS liberated from pullulan after the enzymatic reactions. It was proven that the CytISA reaction product contained maltotriose, maltotexaose, and other MOSs of DP3n (Fig  11A ), as found in the OsPUL reaction products, indicating that CytISA can react to pullulan. However, no such MOSs were detected in the OsISA1 and EcoGlgX reaction products (Fig  11A ). Although Yokobayashi et al. [65]  reported that PsaISA possesses a slight activity toward pullulan, no such activity was detected in our experimental conditions (data not shown). Thus, CytISA is a unique DBE with significant catalytic properties of both ISA-type and PUL-type. The slight activities of cyanobacteria ISAs from Cyanothece (CytISA), Synechochoccus (ScoISA), and Synechocystis sp.
Acknowledgments The present study was funded by the  Ministry of Education, Sports, Science and Technology [ Grant-in-Aid for Scientific Research  (A), 20248002] and the  Research Project Fund of APU President  to Y. N. and N. F. , respectively. The DNA sequence analysis was performed with the aid of the  Biotechnology Center, APU. The DNA sequencing in this study was conducted with the aid of the  Biotechnology Center, APU. We thank  Drs. Hikaru Satoh  and  Eiji Suzuki  for providing us with rice cultivars and Cyanobacteria cells, respectively. We also thank  Ms. Masami Ono  for growing rice plants in the experimental field of  APU. The Pseudomonas amyloderamosa ISA (PsaISA) was kindly provided by  Hayashibara Biochemical Laboratories Inc. (Okayama, Japan ).
Oilseed meal is an important source of essential amino acids (EAA) for livestock production. It is the second most important ingredient in pig feed after grains. Optimal use of these ingredients requires precise knowledge of amino acid standardized ileal digestibility (SID), which may vary depending on several factors including botanical variety or processing treatments. A metaanalysis was performed in order to derive models for predicting the SID of soybean, cotton and rapeseed meal EAA, based on chemical composition data such as CP, total concentration of each EAA and fibre (crude fibre, ADF and NDF) content. A database of 47 references (224 experimental treatments) was built. A model incorporating processing method of the meals (e. g. cold pressed, expeller pressed, solvent extracted), experimental surgical procedure (T-cannula, re-entrant cannula, post valve T-cannula and ileo-rectal anastomosis) and pig growth stage (BW⩽ or ⩾25 kg) was tested.
Data collection and coding This study is based on an exhaustive compilation of published EAA SID and dEAA in pigs and analyses of CP, crude fibre (CF), ADF, NDF, ADL, hemicellulose, total EAA and anti-nutritional factors in oilseed meals. The literature search was conducted between October 2011 and December 2012, and the selection of publications began with research using currently available databases (Web of Science, CAB abstracts, Prod INRA and Science Direct) and keywords such as amino acid, apparent ileal digestibility, standardized ileal digestibility, oilseed meal, pigs and swine. The references cited in the papers selected were also consulted. The final data set included 224 treatments reported in 47 peerreviewed articles published between 1981 and 2012. Data involving treatments with exogenous enzymes (i.
When possible, missing data were estimated from other parameters found in the publication using prediction models. These models were developed to predict the EAA profile from CP and SID of EAA from AID and fibre content  (Messad et al. , 2015; unpublished data). For missing NDF values, a data set comprising 173 treatments reported in 36 peer-reviewed articles published between 1977 and 2012 was used. The best predictor of NDF in SBM, CSM and RSM was ADF (R 2 = 0. 96). These equations (data not shown) of NDF prediction were used to obtain six of the 156 NDF values including in the database. Data and statistical analysis Descriptive statistics (number of observations, mean and standard deviation) were generated for each variable in the selected subgroups (Table  1 ). A correlation matrix was also performed between all nutritional parameters (data not shown).
When ingredient composition or dietary content was not indicated in the publication, we used the ingredient composition from tables  (Sauvant et al. , 2004; NRC, 2012) ; only 1. 5% of the data were estimated using this method. All independent nutrient compositions of ingredients were therefore available for each experiment in the database. Normal distribution of the data and homogeneity of variances were tested using the Shapiro-Wilk and Levene tests, respectively. To verify the model stability, the influence of secondary variation factors on each parameter was tested. Individual within-experiment slopes were regressed on interfering factors to check that the model did not need an additional dependant (X) variable. The residuals (inter and intra) and the least squares means of the model, representing for each experimental group i the predicted Y i for the co-variable X averaged across all experimental groups (X ij ), were also regressed on the major potentially quantitative interfering factors to ensure that there were no residual effects  (Loncke et al.
g. type of non-digestible marker, laboratory analysis, duration of digesta collection;  Cromwell et al. , 2000; Olukosi et al. , 2012; Favero et al. , 2014). In our  In swine. Studies: the list of references used for the meta-analysis is given in Supplementary Material S3. 2 Digestible amino acid content is variable Y; NDF content is variable X. *P < 0. 05, **P < 0. 01, ***P < 0. 001, ns = not significant (P > 0. 10). Messad, Létourneau-Montminy, Charbonneau, Sauvant and Guay database, 25% of the studies were conducted in Europe, 22% in Asia and 53% in North America. This might explain why our consensus figures more closely matched North American data (NRC, 2012).
, 1994). For each EAA SID model, corrected Z i factors were calculated to adjust the model to each oilseed meal. These were generally positive for SBM and RSM and consistent with higher SID (or reduced specific endogenous losses) for SBM and RSM than for CSM. They also showed that the relationship between NDF and EAA SID was similar regardless of oilseed (no interaction, data not shown). The effect of NDF on EAA SID thus was not dependent on oilseed meal type. However, it is interesting to note that the slope of NDF v. SID varied from one EAA to the next. Lysine SID was the most affected by NDF. For example, increasing NDF in SBM by 1% decreased the SID of Lys and Met, respectively, by -0. 459% and -0. 325%. This greater negative impact of NDF on digestibility was observed for AAs with positively charged side groups (Arg, His and Lys) and aromatic side groups (Phe and Trp).
This may be due to greater variation between the different sources of RSM, allowing the distribution of RSM in two distinct groups: NDF higher or lower than 28% dry matter (DM). Essential AA SID was consistent with these groupings, with greater NDF content reducing EAA SID, as   reported by  Messerschmidt et al. (2014)  for different sources of RSM. In the case of SBM and CSM, estimation of EAA SID from NDF (or other chemical analyses) was not reliable. This may be due to the smaller amount of data for CSM and smaller variability (RSD = 3. 70%) in the NDF content of SBM in our database compared with the variability (RSD = 6. 51%) reported in the NRC (2012). In this study, surgical technique of canulation, meal processing and BW did not appear to have an effect on SID measurement (Supplementary Material S2).
Statistical analysis For all data, normality of distribution was confirmed using the Kolmogorov-Smirnov and Shapiro-Wilk tests and equality of variance was checked with Levene's test, prior to further analyses. All data from the study were analysed in a mixed model with diet and group as fixed effects and with dog subject randomized within group. For all analyses, Superior Performing Software Systems version 19 (SPSS Inc. , Chicago, Illinois, USA) was used. Statistical significance was set at P < 0. 05 and a P value between 0. 1 and 0. 05 was defined as a trend.
Acknowledgements The authors gratefully acknowledge  Herman De Rycke  for food and faecal sample analyses;  Jia Xu ,  Daisy Liu ,  An Cools ,  Lien Bruynsteen , and  Jana Pauwels  for technical assistance with blood sampling as well as  Laura Statius ,  Steven Galle  and  Amy Deluycker  for animal care taking, faecal and urine collection.
Study design and intervention This was a prospective, multicenter, randomized, placebo-controlled, double-blind, phase 3 study comparing rhBSSL treatment with placebo (www. clinicaltrials. gov registration no: NCT01413581). The primary objective was to demonstrate that rhBSSL improves growth in preterm infants compared to placebo when administered in infant formula or PBM. Secondary objectives included assessment of decreasing the risk of growth restriction, shortening time of hospital stay, improving early development, decreasing re-admittance to hospital, increasing the serum concentrations of DHA and AA, and to compare the safety and tolerability of rhBSSL treatment with placebo. An interactive voice response system (IVRS) was used for the randomization. A randomization schedule for IVRS was generated linking sequential patient randomization numbers to treatment codes.
Safety assessments Serious adverse events (SAEs) were reported once the informed consent was signed and until the 12-month follow-up visit, non-serious adverse events (AEs) were reported from treatment initiation to the 3 months follow-up visit. It was up to each investigator to judge if a clinical sign or an AE was considered related to the study drug. An independent data safety monitoring board reviewed unblinded data when 10%, 30%, 50% and 75% of the patients had completed treatment. As part of the safety objective, neurodevelopment was assessed using Bayley Scales III  [18]  at 12 months corrected age. Another secondary safety variable was development of ADA.
Body weight, feeding utilization, length and head circumference were analyzed using covariance models including factors for treatment, feeding regimen, and size for gestational age category, with the baseline value included as a covariate. For the comparison between groups, the point estimate, associated 95% CI, and p-value were calculated. The binary endpoints, a weight below the 10 th percentile at 4 weeks and a growth velocity below 15 g/kg/day during treatment, were analyzed using logistic regression models with treatment, feeding regimen and size for gestational age category as explanatory variables. A statistical analysis plan was finalized prior to database lock. Sample size calculation was performed using nQuery Advisor software Version 4. 0 (Statistical Solutions Ltd, Ireland). All output was produced using SAS software (SAS Institute, NC, USA).
Study design GARFIELD-AF is a worldwide observational prospective registry of adults with newly diagnosed non-valvular AF  [2]. Women and men aged !18 years with a diagnosis of non-valvular AF within the past 6 weeks and at least one additional investigator-defined risk factor for stroke are eligible for enrolment, regardless of therapy. Patients with a transient reversible cause of AF and those for whom follow-up is unlikely are excluded. Patients are enrolled from 2010 to 2016. This paper reports 1-year follow-up data for prospective patients enrolled from May 2010 to September 2015 treated with VKA (with or without antiplatelet therapy). The data were extracted from the study database on 28 July 2016.
Data collection Data were collected using an electronic case report form (eCRF) and captured by trained personnel. The eCRF was designed by Dendrite Clinical Systems Ltd, Henley-on-Thames, UK, which is also responsible for ongoing database program management. Outcome events were reported by investigators, after review of patient notes and clinical records, and audited using a combination of remote electronic monitoring and more conventional onsite monitoring (including source data verification on 20% of cases)  [2].
Baseline patient characteristics In total, 39,898 patients were enrolled in GARFIELD-AF. Of the 39,368 patients with data on antithrombotic treatment at baseline,  16 ,852 (42. 8%) were treated with VKAs (with or without antiplatelet therapy). Among the VKA-treated patients, 6440 (38. 2%) had <3 INR readings and were excluded from the analysis. Of the 10,412 remaining patients, 478 (4. 6%) who had INR readings with a gap of >90 days were excluded, leaving 9934 patients (58. 9% of VKAtreated patients) who had at least three INR readings with an interval not exceeding 90 days, with a total of 136,082 INR measurements. Among the patients included in the analysis, 82. 1% had 6+ INR readings. The number of patients enrolled in each of the 35 countries participating in GARFIELD-AF is shown in S1 Table.
Discussion Contemporary, observational, worldwide data from 10,614 patients in the GARFIELD-AF registry, enrolled from 2009 to 2011 in 19 countries, have shown that anticoagulants are often overused in patients at low risk and underused in those at high risk of stroke  [3]. VKAs remain a commonly prescribed anticoagulant therapy in patients with AF, even after the introduction of NOACs. This paper is the first publication of GARFIELD-AF analysing outcomes related to quality of VKA control. The analysis includes 9934 VKA-treated patients with at least three INR readings, out of a total of 39,898 patients recruited in GARFIELD-AF from 2010 to 2015 in 35 countries. All patients had newly diagnosed non-valvular AF and were followed up for 1 year. European and American guidelines for stroke prevention in AF recommend an INR range of 2.