dataesr/scientific-paragraphs-categorization huggingface dataset:
A homemade database of most abundant human milk proteins was used for the peptide sequencing in MASCOT v2. 4 software. No specific enzyme cleavage was used. Peptide mass tolerance was set to 0. 1% and 0. 5 Da for MS and MS/MS analysis, respectively. Biotools version 3. 2 (Bruker Daltonics, Bremen, Germany) was used for the interpretation of the matched MS/MS spectra. The list of peptides appearing in the selected number of subjects was compiled through Venn diagrams using the Venny tool  [25]. The representation of the peptide profile was performed with Peptigram  [26]. Bioactive sequences were searched in the MPDB (Nielsen, New York, NY, USA). With the identified peptides after simulated digestion, hierarchical clustering trees were built and optimized using the PermutMatrix software version 1.
Protein Profile of Human Milks by MALDI-TOF Mass Spectrometry The profile of individual milks counting large peptides and small proteins was examined by MALDI-TOF mass spectrometry. The spectra from colostrum, transitional milk and mature milk from mothers corresponding to the different BMI groups, NW (Figure  1 ) and OW/Ob subjects (Figure  2 ) were first contrasted. In the gel-like view of human colostrum, transitional milk and mature milk of all individual spectral data are shown as lines and the grey level represents the peak intensity, which permits to visualize individual variability. In contrast, the spectrum view represents the average profile from all samples. In the protein profile, the main peak around 14 kDa corresponds to α-LA, although adjacent small signals can be ascribed to lysozyme C and other less abundant proteins in human milk.
Name Accession Number Peptides Identified in Two or More Subjects (N) Mol. Weight, Parent Protein (kDa) Sequence Length, Parent Protein Score (Digest Matches) β-casein P05814 123 25. 38 226 332. 54 α s1 -casein P47710 26 21. 67 185 46. 73 κ-casein P07498 11 20. 31 182 36. 41 Lactotransferrin P02788 121 78. 18 710 103. 31 α-lactalbumin P00709 61 16. 23 142 277. 99 Bile Salt-activated lipase P19835 19 79. 32 753 30. 53 Immunoglobulin heavy constant alpha 2 P01877 18 36. 59 340 27. 96 Butyrophilin subfamily 1 member A1 Q13410 23 58. 96 526 28. 9 Polymericimmunoglobulin receptor P01833 25 83. 28 764 37. 73 Tenascin P24821 59 240. 85 2201 29. 5 Mucin-4 Q99102 56 231. 52 2169 38. 42 Xanthine dehydrogenase/oxidase P47989 44 146. 42 1333 23. 27 Receptor tyrosine-proteinkinase erbB-4 Q15303 29 146.
, 2014). More recently, rabbit gastric extract (RGE) has been introduced to provide gastric lipase (GL) in addition to pepsin in simulated gastric fluid  (Brodkorb et al. , 2019). Prior to performing in vitro digestion experiments, it is essential to assess the activities of these enzyme preparations in order to use enzyme concentrations that mimic physiological conditions, are consistent between experiments and enable comparison. With that in mind, standard protocols have been established based on in vivo data collected during the digestion of test meals, especially within the INFOGEST network, an international and multidisciplinary consortium of researchers from more than 35 countries (http://www. cost-infogest. eu). Within INFOGEST, a subgroup (WG4) is collaborating and sharing expertise in the field of lipid digestion phenomena and digestive lipases.
Statistical analysis The data of enzyme activity for the 3 sources of lipases were analysed using SPSS version 24. 0 and the coefficients of variation (CVs) calculated. The International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH) guidelines were used to define and assess the parameters of precision and evaluate the magnitude of variation among the activity assessment within and between labs (International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human  Use, 2005). For all tests, the significance level was set at P < 0. 05 (2 tailed). All data are expressed as means ± SD. Differences between enzyme preparation concentrations, for a same enzyme source, were analysed by Student's paired t-test. For each enzyme preparation and concentration tested, 63 measurements of lipase activity were performed (three replicates for laboratories) and analysed using the Shapiro-Wilk implementation in XLSTAT.
Specific activities of the lipase preparations The 21 laboratories involved measured the lipase activities, with tributyrin as a substrate, of a single batch of RGE as well as a single batch of each of the two different porcine pancreatin sources from Sigma and Nordmark, respectively. Assays were performed in triplicate using different amounts of enzyme preparation in each case. Only one laboratory (lab 5) deviated from the average CV for all repeated replicates and was identified as a statistically significant outlier with the Dixon test having the highest mean CV of 14. 2%. The values of this lab were therefore removed from the mean calculation and the data presented below. Table  1  shows the average (mean ± SD) of the specific activities obtained for each amount of enzyme preparation tested.
Coefficient of variations (CVs in %) were estimated for individual and for all laboratories involved. For complete data sets, see Tables  S1  and S3  in Supplementary Data. available for lipase adsorption and activity at the oil-water interface. Some laboratories have, for instance, introduced correction factors to compare results obtained with different types of equipment or by different collaborators. This is not satisfactory since the result of an assay should not depend on the equipment utilised to be considered robust and widely applicable. A water-insoluble substrate, emulsified in the reaction vessel, can create this dependency and therefore, protocols should also include recommendations about the parameters of the pHstat equipment to be used. This was the main objective of the ring trial described in this study and designed by the INFOGEST working group on lipid digestion and digestive lipases (WG4).
Acknowledgements The authors thank the  European Commission COST  Action  FA1005 INFOGEST  and  INRAE  for financing the meetings and conferences that enable the 21 laboratories to network and organise the work presented in this article. We also acknowledge the  'Healthy and Safe Food System  ( KB-37 )' knowledge base program of the  Dutch Ministry of Agriculture, Nature and Food Quality (LNV) , with grant number  KB-37-001-007  for funding of this work performed at  Wageningen Food & Biobased Research. We are grateful to  Dr Sawsan Amara  ( CEO of Lipolytech SA. , Marseille, France ) for her generous gift of RGE and to  Drs Jan Lüdemann ,  Anja Jensen ,  Olaf Friedrich  and  Claus Middelberg  from  Nordmark Arzneimittel GmbH & Co. KG (Uetersen, Germany ) for their generous gift of Nordmark pancreatin.
The PRISMA flow charts of the searches are included as Appendix A. The search strings and the eligibility criteria in the protocol are reported as Appendices D and E. 2. 1. 1. Linoleic acid and alpha-linolenic acid concentration and their release from adipose tissue during weight loss Two searches were conducted to retrieve evidence 1) for the LA and ALA concentration of AT and 2) for the release of these FA from AT during weight loss. Owing to the high overlap between publications of the two searches, the data retrieved were combined and screened together (Q1). Publications retrieved were human intervention or observational studies conducted in populations living in Europe investigating LA and ALA concentration in healthy normal weight adults or overweight or obese adults 8 either without apparent co-morbidity or with the following diseases that are frequently associated with obesity: type 2 diabetes mellitus (T2DM), hypertension, hyperlipidaemia.
Supplemental magnesium and risk of developing diarrhoea Publications retrieved were human intervention studies reporting on the development of diarrhoea or on adverse effects following administration of two different interventions (i. e. placebo vs. Mg; or Mg vs. Mg at different doses) of readily dissociable Mg salts consumed by participants. The initial eligibility considerations were to include only studies that reported the criteria used for the diagnosis of diarrhoea and applying the World Health Organisation (WHO) criteria (i. e. stool frequency of ≥ 3 loose or watery stools per day 11 ). As this type of data was not retrievable, cross-over studies were considered to decrease uncertainty of the outcome assessment (i. e. diarrhoea) as subjects act as their own controls (protocol amendment 3).
Data from this cohort were included in the assessment through consideration of the publication by  Dahm et al. (2011). Two studies that originally met the inclusion criteria  (Heemskerk et al. , 2015; Sikorska-Wisniewska et al. , 2020)  were excluded from further review, as they reported implausibly low ALA concentrations in AT that could also not be explained by the authors upon contacting them. Hence, a total of 80 studies were considered. AT samples in the studies were obtained either via needle biopsy, a biopsy during surgery or during autopsy. Studies were available from 20 European countries. They were heterogeneous in terms of population (specific subgroup of a population or random samples from the general populations), weight status of individuals, sample size, sampling site of the body, method of FA extraction, method of FA derivatisation to FA methyl esters  12  and unit in which the FA concentration was reported (e.
Data analysis across the included studies: scatter plots for the predefined list of influencing factors The overall data set was evaluated visually in the form of scatter plots, for each of the two FA LA and ALA, for the following potentially influencing factors for which enough data were available to create informative plots: gender (Appendices C. 1 and C. 10), weight status (i. e. overweight and obese, overweight, obese, normal weight, mixed, not reported; Appendices C. 4, C. 5, C. 13, C. 14), and sampling site (i. e. visceral (VC) or superficial subcutaneous (SC) AT from various sites; Appendices C. 8 and C. 17). However, these graphical presentations did not reveal a pattern suggesting an association between the factors investigated and the reported LA and ALA concentrations in AT. For other factors, such an evaluation was not feasible because (1) the data set did not allow categories to be created, e.
The E% provided by polyunsaturated FA did not change, neither in the rowers nor in the control subjects, during the study. This was assessed by a 3-day dietary history. There were no data to evaluate the influence of medication use. Overall, the Panel considers that there is no evidence that the data set would need to be stratified for the factors listed above for the subsequent evaluation of data. The only exception was for age, for which stratification may have been relevant. However, in the absence of access to the individual data, only the age categories reported in the papers were available, which were too broad to create a meaningful stratification.
The fifth percentiles (P5) of the empirical distributions of the mean LA and ALA concentrations in AT were, however, only based on data from two (LA) and three (ALA) countries and on 156 and 249 subjects, respectively. Considering the uncertainties around the robustness of the values for P5 derived from a limited number of countries and subjects, the Panel decided to explore the use of statistical modelling or resampling (i. e. bootstrapping) techniques in order to increase the confidence in the values observed in the lower tails of the empirical distributions. The decision to fit the most appropriate probability distribution to the mean values of LA and ALA concentrations in AT reported in the included studies (using the R package 'rriskDistributions') instead of bootstrapping was taken based on a simulation exercise done in another context by EFSA (internal data).
This study recruited families with at least one overweight and obese parent that underwent an 8-week TDR intervention with 3,200 kJ/day (766 kcal/day), supplemented with 400 g/day of vegetables, before randomisation into one of five energy ad libitum diets. Data on abdominal SC AT composition are presented for 195 subjects (out of 773 adults randomised). During the TDR period, subjects lost on average 11 kg of weight. ALA concentrations were statistically significantly reduced by around 13% during this period. No changes were observed for LA. The Panel notes that the limited data available indicate that the relative release of ALA from AT during weight loss is higher than of LA. The Panel considers that the available evidence does not allow to establish whether a correction factor needs to be applied to the LA and ALA concentrations of AT in order to derive the amount of these FAs that is released from AT during weight loss.
Hence, the results of this study with respect to loss of fat mass were not taken into account. The percentage of weight that is lost as fat was estimated by the Panel as average of the values cited above (i. e. 57 and 76%) and rounding up to the closest 10% (i. e. 66. 5% rounded up to 70%). Weekly fat loss in all included studies was therefore calculated by multiplying by 0. 7 the weekly mean weight loss extracted from these studies. To these data (15 data points in total 13  ), a theoretical distribution was fitted, as was done for LA and ALA concentrations in AT tissue (Section 3. 1). The best fit was observed for the normal distribution (Figure  3 ), based on the lowest value for AIC (215. 84). The P5 of this theoretical distribution for fat mass loss was 863 g/week, as compared with the P5 of the empirical distribution of 949 g/week.
The use of a gamma distribution (AIC = -338. 34) to the data on LA concentration in AT resulted in a P5 of LA release from AT during weight loss of 92. 3 g/week (13. 2 g/day), and the use of a beta distribution (AIC = -335. 72) in a P5 of 89. 9 g/week (12. 8 g/day). For ALA, the use of the beta distribution (AIC = -634. 29) and lognormal distribution (AIC = -634. 28) resulted in P5 of 4. 14 and 4. 28 g/week, respectively (0. 59 and 0. 61 g/day). Sensitivity analyses were also conducted for data on fat mass loss with the second and third best fitting distributions (i. e. gamma and Weibull distributions). The best fitting distributions for LA (i. e. lognormal distribution) and ALA (i. e. gamma distribution) concentration in AT were kept. The use of gamma and Weibull distributions (both AIC = 215.
The comprehensive literature search for intervention studies investigating the effect of different fat contents in energy-restricted diets on gallstone formation, biliary sludge formation and/or gallbladder emptying did not yield any results. Therefore, the Panel relied on the four intervention studies that had already been reviewed in its previous Opinion  (Stone et al. , 1992; Gebhard et al. , 1996; Festi et al. , 1998; Vezina et al. , 1998). As supporting evidence, the Panel also considered data from observational studies or intervention studies that were either single-arm or in which only one arm consumed a TDR without further co-intervention, even if they did not meet the initial inclusion criteria of the search (protocol amendment 5). These studies were retrieved by an additional non-systematic search of the literature not foreseen in the protocol.
Search strings are provided in Appendix E with numbers of items identified prior to deduplication. Hand search will be undertaken through the comprehensive reviews and meta-analyses excluded during the screening but identified (with a label in Distiller) as potentially useful for this assessment. In addition, data that could be provided spontaneously by stakeholders and interested parties will be screened for their eligibility. Regarding Mg, previously published scientific reports of officially recognised scientific bodies, and the studies therein, e. g. SCF (2001)  and VKM (2016), may be considered. Planned approach towards the evidence retrieval from the scientific literature The following sections will summarise the approach taken for the evidence retrieval to answer the predefined subquestions (Section 1.
• To be finally included, • articles providing quantitative data on LA (18:2 (n-6)) and/or ALA (18:3 (nÀ3)) concentration of AT. Preferably, full-text papers should report on the study population characteristics (including age, sex), diet, weight and health status to be included. For large observational studies, this information may be provided in other publications on the same studies. Not eligible are: • Systematic or narrative reviews and meta-analyses. Although these may be used to provide background information to the general sections of the statement or for hand search of relevant references. • Protocols (as no results are reported), commentaries, editorials, letters to the editor, grey literature (PhD theses, extended abstracts, conference proceedings, etc. ), or other publication types not peer-reviewed (except contributions from stakeholders and interested parties).
Data processing Raman spectra were plotted as intensity (Arbitrary unit) against Raman shift (cm -1 ). Plot processing and handling (normalisation, baseline, band fitting) were carried out using OPUS software (Bruker Optik, GmbH). Each individual spectrum was first corrected from the baseline with a concave elastic correction method developed within OPUS software. Then, a min-max normalisation was applied. Finally, the 36 spectra obtained for each mixing level were averaged. To determine changes in the conformation of disulphide bonds, a spectral subtraction of a starch reference spectrum was required to completely remove the intense starch band at 478 cm -1 which masks the contribution of the S-S bands. The conformations of disulphide bridges (500-560 cm -1 ), Amide I band (1625-1700 cm -1 ), Amide III band (1200-1330 cm -1 ), tyrosine doublet (I(850)/I(830)), and tryptophan doublet (I(1360)/I(1340) were analysed using a deconvolution by fitting a mix of Gaussian and Lorentzian curves (Figure  S1 , Figure  S2 , Figure  S3 , Figure  S4  and Figure  S5  are provided in Supplementary Material).
Acknowledging individual variability in the FA status at birth, the requirements for specific PUFAs in formula may best be described as a range rather than a single value. Generally, it is assumed that the estimated average requirement plus/minus 2 SDs of the variation in infant requirements will cover the needs of almost all healthy individuals in a population. Crossing either side of the lower or upper margin could increase the risk of negative consequences for the infant's metabolism, physiological functions, and short-and long-term health outcomes. Although in theory this seems plausible, the current evidence is too limited to provide a strong rationale for clear cutoff values for specific FAs. As an example, adverse health effects were observed in clinical studies conducted in the 1940s and 1950s using experimental infant feeding concepts with very low LA levels (see also below).
Acknowledgments We thank  Chantal Kleijer ,  Linda de Groot , and  Nana Bartke  for their support in the preparation of the discussion sessions and their critical review of the final manuscript. The current paper is the outcome of a series of discussion sessions initiated and facilitated by  Danone Nutricia Research (DNR)  in which all co-authors actively participated. The academic participants SEC, JTB, CA, PCC, SF, PL, BVK and BM were invited by DNR based on their expertise. Each session was prepared by  DNR. The academic experts provided input on a specific set of preformed statements about fatty acid in infant nutrition to discuss different aspects of the topic. The authors' responsibilities were as follows-LS, BJMvdH, MA-B, and EMvdB: prepared the initial draft of the manuscript; SEC, JTB, CA, PCC, SF, PL, BVK and BM: contributed to the writing of the manuscript, critically reviewed several manuscript versions; all authors read and approved the final manuscript.
Background: The role of nutrition in the primary prevention of peripheral artery disease (PAD), the third leading cause of atherosclerotic cardiovascular disease, is undetermined. Flavonoids may attenuate atherosclerosis and therefore persons who consume flavonoid-rich foods may have a lower risk of developing PAD. Objectives: We aimed to examine the association between flavonoid intake and PAD hospitalizations and investigate if the association differs according to established risk factors for PAD. Methods: Baseline data from 55,647 participants of the Danish Diet, Cancer, and Health Study without PAD, recruited from 1993 to 1997, were cross-linked with Danish nationwide registries. Flavonoid intake was calculated from FFQs using the Phenol-Explorer database. Associations were examined using multivariableadjusted restricted cubic splines based on Cox proportional hazards models.
Study population Participants were recruited from the greater areas of Copenhagen and Aarhus between 1993 and 1997 as part of the Danish Diet, Cancer, and Health study. Of the 57,053 participants recruited, 56,468 completed an FFQ and were without a cancer diagnosis before enrollment. All Danish residents are assigned a unique and permanent number allowing cross-linking of participants to nationwide registers. The following databases were cross-linked to the cohort: the Civil Registration System, the Integrated Database for Labor Market Research, and the Danish National Patient Register, which contains information on all hospital admissions in Denmark since 1978. For all admissions this includes 1 primary diagnosis and ≥1 secondary diagnoses defined by the International Classification of Diseases (ICD): the 8 th revision (ICD-8) until 1993 and the 10 th revision (ICD-10) from 1994  (10).
Exposures Exposures were intakes of total flavonoids, flavonoid subclasses, and individual flavonoid compounds with mean intakes > 5 mg/d. The calculations of flavonoid intake we used have been described previously  (11). Briefly, estimates of the flavonoid content of all foods and beverages in the FFQ were obtained from the Phenol-Explorer database  (12). Because the average intakes of isoflavones, dihydrochalcones, dihydroflavonols, and chalcones were <5 mg/d, they were not included in the individual subclass analyses. Total flavonoid intake was calculated by summing each of the 219 flavonoid compounds.
Covariates Data on sex, age, education, smoking habits, alcohol consumption, daily activity, and diet were obtained from questionnaires completed by participants upon study enrollment. Smoking status was defined as "current smoker" if the participant indicated that they currently smoked daily, "previous smoker" if the participant indicated that they smoked daily for ≥1 y at any stage of their life, and "never smoker" if the participant was neither a current nor a previous smoker, as defined above. Anthropometry and total cholesterol were measured at the study centers. Mean annual income over 5 y (defined as household income after taxation and interest, using the value of the Danish currency in 2015) was used to represent socioeconomic status. ICD-8 and ICD-10 codes were used to determine prevalent chronic kidney disease, chronic obstructive pulmonary disease (COPD), ischemic heart disease, ischemic stroke, heart failure, atrial fibrillation, and cancers (Supplemental Table  2 ).
Supported by  Danish Heart Foundation  grant  17-R115-A7443-22062  (to FD),  Gangstedfonden  grant  A35136  (to FD),  National Health and Medical Research Council   Early Career Fellowship  grant  APP1159914  (to NPB),  National Health and Medical Research Council Career Development Fellowship  grant  APP1107474  (to JRL), and  National Health and Medical Research Council Senior Research Fellowship  grant  APP1116937  (to JMH). The  Danish Diet, Cancer , and  Health Study  was funded by the  Danish Cancer Society, Denmark. Where authors are identified as personnel of the  International Agency for Research on Cancer/WHO , the authors alone are responsible for the views expressed in this article and they do not necessarily represent the decisions, policy, or views of the  International Agency for Research on Cancer/WHO.