dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgements and thanks to: Sky for diaries collection and contribution to data analysis;  Liliana Naumik  for participation to subcam data collection;  Bankole Falade  for contribution to data analysis. This article benefitted from a  EURIAS fellowship  at the  Paris Institute for Advanced Studies (France) , with the support of the  European Union 's 7th Framework Programme  for research, and from a funding from the  French State  managed by the  Agence Nationale de la Recherche ,  programme "Investissements d'avenir" , ( ANR-11-LABX-0027-01 Labex RFIEA+ ).
Acknowledgements This work was supported by a  Methusalem grant  from the  University of Leuven  for research on "The  Brain-Gut Axis in Health and Disease: from Mucosal Integrity to Cortical Processing ". Sandra Steensels  is holder of a PhD grant from the  Agency for Innovation by Science and Technology (IWT). The authors would like to thank  Anneleen Geuzens  and  Linda Nys  for their skilful technical assistance.
Statistical analyses Analyses were performed using IBM SPSS21. c 2 and t tests were used to compare case versus controls for categorical (APOE ε4 allele frequency sex, race, dyslipidemia, diabetes, hypertension, and obesity) and continuous variables (age, education, MMSE, and clinical dementia rating sum of boxes scores [CDR-SB]), respectively. In our prior work, we demonstrated that the serum-based proteomic profile was more robust in detecting AD when compared with plasma in this cohort using the MSD platform  [19]. Here, we compared the top 10 biomarker importance rankings across serum and plasma within the same cohort. Correlations across serum and plasma were conducted using Pearson correlations. Analyses were conducted from proteomic data taken from the same participant at the same blood draw only.
In fact, only IL-5, IL-6, and IL-7 were consistently ranked among the top 10 biomarkers across serum and plasma. Next, data from 17 common markers assayed using the MSD and RBM platforms were compared. As listed in Table  5 , 14 of the 17 correlation coefficients are statistically significant (P ,. 05); however, the amount of shared variance in protein concentrations was ,50% for 12 of the 17 markers and. 50% only for FABP, CRP, FVII, IL-18, and b2M. Additionally, as listed in Table  4 , only two of the top 10 markers (IL7 and TNF-a) were common among the top 10 biomarkers across the MSD and RBM platforms.
Acknowledgments Research reported in this publication was supported by the  National Institute on Aging  under award numbers  AG0 39389 ,  AG12300 ,  AG032755 ,  AG047484 , and  AG010483. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. This study was supported, in part, by funding from the  Texas Alzheimer's Research and Care Consortium (TARCC)  by the state of Texas, through the  Texas Council on Alzheimer's Disease and Related Disorders. Investigators from the  Texas Alzheimer's Research and Care Consortium: Baylor College of Medicine :  Rachelle Doody MD, PhD ,  Valory Pavlik PhD ,  Paul Massman PhD ,  Eveleen Darby MA/MS ,  Monica Rodriguear MA ,  Aisha Khaleeq MD ;  Texas Tech University Health Sciences Center :  John C.
Strengths and limitations of this study ▪ The present data represent the best source of information on the dietary habits of a large and nationally representative sample of adults in each country. ▪ Each of the data sets analysed is a flagship national study that informs a nation's food and nutrition policy and provides data to be furnished to the WHO. ▪ Different dietary surveys used different methodologies and nutrient composition databases. ▪ Analyses were based on a limited number of days, which may not capture habitual intakes. ▪ All nutrient intakes were based on self-reports and were subject to reporting errors that may result in under-estimating the consumption of sodium. In addition, sodium intakes from table salt and supplements were not included. multiple challenges. 14 15 First, sodium and potassium intakes are closely tied to energy balance, such that persons with higher energy requirements consume more potassium but also more sodium.
16 Very low sodium diets tend to be low in calories and may not provide adequate nutrition. 15 Uncoupling sodium from dietary potassium can be problematic, since both are present in many of the same foods. 17 In mathematical models based on dietary intakes from the National Health and Nutrition Examination Survey (NHANES), the US sodium and potassium guidelines appeared to be incompatible with each other. 14 In empirical analyses of the 2003-2008 NHANES data, joint compliance with the published US sodium-potassium guidelines (1500 mg sodium and 4700 mg potassium) was estimated between 0 and 0. 015%. 16 e now examined joint compliance with the new WHO sodium and potassium guidelines in four different countries, using nationally representative databases. Since the WHO guidelines  [1] [2] [3]  have an intended global reach, examining sodium and potassium intakes in more than one country is of particular interest.
METHODS Data on sodium and potassium intakes were obtained from publicly available national dietary surveys for the US, Mexico, France and the UK. Each of those studies was approved by institutional review boards in their respective countries. Detailed procedures for data collection have been published previously and are noted below. The National Health and Nutrition Examination Survey (NHANES 2007-2010) is a nationally representative survey of the US population. 18 The present analyses were based on 9720 adults aged ≥20 years with two complete and valid 24 h recalls. For each survey participant, sodium and potassium intakes were obtained from the mean of two non-consecutive 24 h recalls. Although two dietary recalls do not reflect true estimates of habitual intake, they do provide an upper bound of the proportion of the population meeting sodium and potassium goals.
The Encuesta Nacional de Salud y Nutrición 2012 (ENSANUT 2012) in Mexico is based on a random representative sample of children and adults. 19 Dietary intake data are based on a semiquantitative and previously validated 7-day food frequency questionnaire. 20 he present analyses were based on adults aged ≥20 only (n=2879). The databases and documentation of protocols are available online. 19 he Individual and National Study on Food Consumption (INCA2) in France is based on a nationally representative sample of 1455 children ages 3-17 years and 2624 adults aged 18-79 years. The study was conducted by the ANSES government agency (Agence nationale de sécurité sanitaire de l'alimentation, de l'environnement et du travail). 12 Dietary intake data were based on 7-day food diaries, aided by a photographic atlas of portion sizes.
The present analyses were based on adults aged ≥20 years only, excluding under and over reporters (n=1726). The National Diet and Nutrition Survey (NDNS) in the UK is a nationally representative sample of UK residents aged 1. 5 years and older, stratified by age and gender. The survey recruits 1000 participants per year, children as well as adults. 21 Data analysed in this study were for years 1-3 of the rolling programme, with 4-day food diaries available for 3073 individuals. The present analyses were based on a sample of 1472 adults. Further details on sampling, data collection and processing are published. 21 he proportion of persons meeting the sodium and potassium guidelines, separately and jointly, was calculated. 16 Survey weighted medians and 25th and 75th centiles for sodium and potassium intakes were calculated for each survey sample.
These conclusions are consistent with published analyses of the NHANES data by the Centers for Disease Control, which estimated that only 0. 6% of the population met the 1500 mg/day sodium goal and 1. 4% met the goal for potassium. 11 The upper bounds of joint compliance with sodium-potassium, based on the same NHANES data, were estimated by us at 0. 015% for 1500 mg/day sodium and at 0. 12% for 2300 mg/day sodium. 16 iven the surprisingly low levels of compliance with global goals, it is clear that purely educational and individual-level approaches to sodium reduction are unlikely to be successful. The largest contributors of sodium in the diet depend on food classifications evaluated, but yeast breads, pizza, processed meats, cheese and meat/poultry mixed dishes, are among the most important sources of dietary sodium in the USA.
0. 6 he present analysis of the multinational data sets has several limitations. First, the different dietary surveys used different methodologies, including dietary recalls (US), food diaries/records (UK and France) and a food frequency questionnaire (Mexico). Second, analyses were based on a limited number of days for those data derived from dietary recalls and food diaries, which may not capture habitual intakes. This is particularly a concern for the US data where a two-day average was used. Advanced methods are available to estimate habitual intakes based on dietary recalls for a single dietary constituent, though methods for estimating joint compliance based on habitual intakes have not been developed. As a result, our population estimates represent an upper bound of the compliance to sodium, potassium and the joint goals.
Third, all nutrient intakes were based on selfreports and were subject to reporting errors that may result in under-estimating the consumption of sodium, due to omission of sodium-dense foods or potential overreporting of potassium intakes, such as fruits/vegetables. Fourth, sodium intakes from table salt and supplements were not included. Lastly, the nutrient composition databases used by different countries may differ in quality. Despite these limitations, the present data represent the best source of information on the dietary habits of a large and nationally representative sample of adults in each country. Each of the data sets analysed is a flagship national study that informs that nation's food and nutrition policy and provides data to be furnished to the WHO. There is a case to be made for more feasibility research in the formulation of public policy.
Study population A purposive sample of four neonatal units was selected in each of three European regions: Ile-de-France in France, Lazio in Italy and the former Trent region in the UK. The selection aimed to ensure geographical variability (city and suburbs), maternal sociocultural diversity (based on data on maternal age, parity, percentage of foreign mothers and census tract characteristics), and variation in human milk feedings at discharge from the neonatal unit within each region based on the results of the MOSAIC study. 16 An invitation letter was sent to the head of each unit to inform them about the study and ask for permission to approach health professionals within the unit. All invited units agreed to participate in the study.
The framework was further enhanced by a review of the literature regarding lactation and breastfeeding promotion programmes,  [34] [35] [36] [37]  maternal  13 21 26  and staff  30 31  views on lactation and breastfeeding the very preterm infant, as well as barriers and facilitators related to decision-making in clinical practice. 38 New codes and categories emerging from the data were added during the coding of the interviews, while some of the initial codes were modified in an iterative process. Charting data into the framework matrix focused on the principal barriers and facilitators categories related to the attitudes and practices of health professionals. Interpretation of data involved identifying differences and similarities between the regions, finding associations within themes and subthemes, and identifying links that could explain the findings of the quantitative data from the MOSAIC study.
16 Key concepts were illustrated using the respondents' own words (translated into English by professional translators), as advocated as a mean of staying 'true' to the data. 32 Contextual information about structural factors and unit policies related were also abstracted from the interviews. Coding cross-checks were performed by double coding of one interview from each region and by secondary reviews of all interviews by another coauthor ( JZ for the Trent Region, BB for Ile-de-France, MC for Lazio). Discrepancies between authors were solved through consensus agreement. NVivo software V. 9 (QSR International, Australia) was used for data coding and charting. We then selected barriers and facilitators that differed in at least two of the regions, including the interpretation of evidence, views about the patients' role in decisionmaking and their own self-efficacy, as well as environmental factors such as resources and organisational constraints.
Food consumption surveys are performed in many countries. Comparison of results from those surveys across nations is difficult because of differences in methodological approaches. While consensus about the preferred methodology associated with national food consumption surveys is increasing, no inventory of methodological aspects across continents is available. The aims of the present review are (1) to develop a framework of key methodological elements related to national food consumption surveys, (2) to create an inventory of these properties of surveys performed in the continents North-America, South-America, Asia and Australasia, and (3) to discuss and compare these methodological properties cross-continentally. A literature search was performed using a fixed set of search terms in different databases.
Briefly, in the European Food Consumption Survey Method project (EFCOSUM), it was agreed that two non-consecutive 24-HDR (24 h dietary recall), are the most suitable to get internationally comparable data on population means and distributions of actual intake  [1]. In addition, the menu-driven standardized 24-HDR program EPIC-Soft (IARC, Lyon, France) was considered to be the most appropriate software for standardized data collection in a pan-European survey. Following the EFCOSUM project, in the European Food Consumption Validation (EFCOVAL) project, EPIC-Soft was upgraded and adapted, and the two non-consecutive 24-HDRs using EPIC-Soft were validated using urinary biomarkers  [2]. The software was further evaluated for use in the European Union (EU) Menu project  [3] , a pan-European food consumption survey among EU member states led by EFSA via the feasibility studies EMP-PANEU (Food Consumption Data Collection Methodology for the EU Menu Survey) and PANCAKE (Pilot study for Assessment of Nutrient intake and food Consumption Among Kids in Europe)  [4] [5] [6].
In 2014, an EFSA report was published aiming to identify and evaluate available European data collection protocols and tools for capturing food consumption information  [7]. Previously, Huybrechts et al. reported on the experiences from European national or regional dietary monitoring surveys using the standardized EPIC-Soft program  [8] , making a further inventory on this standardized methodology used in Europe redundant and leading to the decision to exclude Europe from this cross-continental inventory. Within the framework of the African Study on Physical Activity and Dietary Assessment Methods (AS-PADAM) project, an inventory questionnaire on the availability of dietary assessment methods was developed and results from eighteen African countries were presented  [9]. In contrast to Europe, the inventory showed that for the African continent, high quality, validated and standardized tools are currently lacking, making it difficult to monitor the different phases and speed of the nutrition transition across its countries.
Search Strategy As proposed by Blanquer et al. [10] , a combined strategy for data acquisition was used. Firstly, a systematic literature search was performed and subsequently, experts were contacted to complete missing information which could not be found in the literature. We used the electronic database MEDLINE (PubMed) and Web of Science to identify studies reporting on food consumption surveys from 1985 to December 2011. Text terms with appropriate truncations, Boolean operators and relevant indexing terms were used. The reference lists in the articles, reviews and textbooks retrieved were also investigated for additional publications yielding a substantial amount of grey literature like reports available on websites of governmental bodies. The key words used in the search were: "national nutrition survey"; "food and nutrition survey"; "dietary consumption survey"; "dietary intake"; "nutrition examination"; "nutrition survey"; and "dietary intake assessment".
Target Population, Survey Design and Sampling Method Table  2  summarizes the study design aspects and methods of the selected surveys. The ages of the target populations ranged from less than 1 year of age to over 80 years. Surveys including all age categories were from Canada, US, Mexico (MHNS-06), China (1991 and onwards), Japan, Korea and Australia. In all surveys, both genders were included except for Mexico (NNS-1999) that included women only. In all surveys, a multistage sampling design was used to select study participants. The sampling frames used for selection of sampling units were based either on census data (US, Mexico, Brazil, Korea and New Zealand), a combination of frames like healthcare registries and labour force data (Canada), strata from counties (China), or enumeration blocks (geographical areas which are artificially created to have about 80 to 120 living quarters (Malaysia)).
Fieldwork Characteristics and Data Controls In Table  5 , the fieldwork aspects of the nutrition surveys are presented. All surveys reported that at least one interview was conducted when the participant was at home. For surveys with multiple interviews, at least one was conducted at home. Interviews could either be a face-to-face or a telephone interview. In cases where the DIA was a dietary record, interviews were performed to review the participant's records and to check for completeness (Brazil and Japan). Another place for administrating the DIA was at mobile examination centres (MEC) (the US, NHANES). The time-span of the fieldwork was at least one year (all seasons) in Canada, the US, Brazil, Korea (KNHANES 2008 and onwards), Malaysia, Australia and New Zealand.
Discussion This review presents an inventory of methodological aspects related to the performance of national food consumption surveys in different continents for which an in depth inventory on the dietary intake assessment methods used was still missing. Inventories covering both standardized and non-standardized data collection protocols and tools for capturing food consumption information on the European and African continent have been published before  [7] [8] [9]. The present inventory comprises a total of twentyeight food consumption surveys performed in ten countries from four continents: North-America, South-America, Asia and Australasia. In six countries (Canada, the US, Mexico, China, Korea and Australia), the FCS was part of a larger health examination survey from which three (the US, China and Korea) have been continuous programs.
Like North America, Europe has standardized its CAI software for future pan-European food consumption surveys  [43]. The EPIC-Soft program, originally developed for the EPIC Study by the International Agency for research on Cancer (IARC), has been validated  [44, 45]  and adapted to fit the purpose of pan-European food consumption surveys  [46]. Recently, a name change of EPIC-Soft to GloboDiet software was announced, since this better suits the current and anticipated use of the increasingly widespread application of the tool worldwide  [47]. Given that individual quantitative dietary intake surveys are expensive and difficult to implement, the Food and Agriculture Organization (FAO) Dietary Diversity questionnaire has been developed as a simple proxy to measure access to food at the household level  [48]  and micronutrient adequacy in women's and children's diets at the individual level  [49, 50].
Recruitment criteria for interviewers in national nutrition surveys are different between Asia and North America. In all Asian countries presented in the overview and Australia, interviews were conducted by either qualified/registered dietitians or nutritionists. In Japan, no interview was performed since dietary records were used; however, dietitians were recruited for data entry. In Canada and the US, it was not mandatory that the interviewers be dietitians or nutritionists. Both surveys rely either on professional interviewers involved in a variety of surveys or survey staff with a given minimal educational qualification, complemented with specific software and interview training. The duration of the training provided to interviewers varied across all available surveys from 2 days to 15 days (median duration: 7.
These sources of information are sometimes not indexed in scientific databases and are, therefore, difficult to obtain using reproducible search strategies. Therefore, narrative reviews can be criticized because of their limited reproducibility. However, for reasons mentioned before, the twostep approach using both available literature and expert consultation, was the best method available to create the comprehensive overview presented. This overview shows that the methods used for dietary intake assessment in national nutrition surveys are relatively similar across continents. The most frequently used method is the 24-HDR, sometimes administered repeatedly to correct for within-person variability, and mostly using interview software. Nevertheless, caution is still warranted when comparing results from food surveys between countries because of differences in conversion factors used for calculating nutrients (e.
g. , energy, protein, etc. ). A variety of errors are introduced because many national or regional food composition tables or databases contain incomplete, outdated and unreliable data, or, countries borrow data from publicly available databases and neighbouring countries when such tables or databases are unavailable or inadequate  [51]. Notwithstanding the growing consensus about the use of the 24-HDR methodology in food consumption surveys, the assessment remains self-reported. The most accurate and precise method for measuring energy expenditure is the doubly labeled water (DLW) method  [52]. In weight stable conditions, one can expect that energy intake equals energy expenditure; hence, DLW is used in studies examining the validity of energy intake assessment. Such validation studies have indicated that the prevalence of energy underreporting in self-reported methods was about 30% (range: 12%-67%), and the magnitude of underestimation of energy intake was roughly 15% (range: 7%-20%)  [53] [54] [55].
Acknowledgments The authors gratefully acknowledge the contributions of the  Health Statistics Division of Statistics Canada ,  Simón Barquera ,  Barry Popkin ,  Chris Killick-Moran  and  Shufa Du. The work presented was part of the PhD dissertation of W. D. K. , who was financially supported by the  Research Fund of University College Ghent. S. A. M. is funded by an  Australian Research Council   Future Fellowship  ( FT100100581 ).
0 Nusser method using C-University) SIDE (Iowa State 〃 2005-2006 〃 USDA Food and Nutrient Database (FNDDS), 3. 0 NCI method 〃 2007-2008 〃 USDA Food and Nutrient Database (FNDDS), 4. 1 〃 〃 2009-2010 〃 USDA Food and Nutrient Database (FNDDS), 5. 0 〃 〃.