dataesr/scientific-paragraphs-categorization huggingface dataset:
Discussion These studies investigated different aspects of current practices and use of CN in oncology, based on the real-world administrative datasets from three European countries (France, Germany, and Italy), using different analytical methodologies. The data provide a broad overview of different characteristics, including actual clinical practices, areas with existing clinical unmet needs, and a potential for improvement in treating cancer-related malnutrition. In general, the study results from all three countries suggest that the diagnosis of malnutrition in clinical practice occurs later and less frequently than what is recommended according to the current clinical guidelines  2, 19  or what is generally reported in the literature. 4, 14 20, 21  More up-to-date data would be necessary to understand current adherence to the recently published ESPEN guidelines for clinical nutritional care in patients with cancer.
Limitations There are several limitations that should be kept in mind when interpreting the findings from these studies in each country. The primary limitation for each study was that the data from administrative were not collected specifically to be used in health-related scientific research and lacked detailed clinical information. Secondly, the data generated from the three large national databases in France, Germany, and Italy were not merged, as the datasets were not directly comparable due to different design, methodological approaches used, and only descriptive and exploratory analyses performed. Furthermore, the additional subanalyses stratified by each cancer type conducted in each country to understand the use of healthcare resources and clinical outcomes in patients receiving CN, compared with those who not receiving CN, were not included in this assessment and will be published separately.
The content of this manuscript is based on three retrospective observational analyses of administrative databases conducted by the investigators in France, Germany and Italy. Presentations of the results were made and discussions held at the ESMO congress on 19-23 October 2018 in Munich, Germany, and at the International Society for Pharmacoeconomics and Outcomes Research European congress on 10-14 November 2018 in Barcelona, Spain. Three retrospective observational analyses of existing administrative databases in France, Germany and Italy were performed. Due to the nature of the studies, nonclinical anonymised aggregated data from each administrative database were acquired without identifying patients; therefore, formal approval from independent ethics committees was not required. Formal approval for data utilization was obtained from the Institutions responsible for the databases administration (French Hospital database PMSI; German Statutory Health Insurances and Italian LHUs).
Experimental procedure Rats were placed in the ACREM-equipped cages for the duration of the study. Baseline data was collected for 1 wk. Tap water was then replaced by 1. 8% sodium chloride for 4 d and then by 2. 7% sodium chloride for another 4 d. The solute intake during salt loading reflected the intake of salt solutions. Thereafter, rats were allowed to drink tap water and the study continued until their body weight returned to baseline. Water or solutes intake and body weight were measured daily.
Statistical analysis Results were analyzed using GraphPad Prism 5. 02 (GraphPad Software Inc. , San Diego, CA, USA). Normality was evaluated by the KolmogorovÀSmirnov test. Group differences were measured by the analysis of variance (ANOVA) or the nonparametric KruskalÀWallis (KÀW) test with the Tukey's or Dunn's post-tests, according to the normality results. Where appropriate, individual groups were compared using the Student's t test or the MannÀWhitney (M-W) two-sided tests, according to the normality results. Food intake and meal pattern were compared between the corresponding means of four periods: before dehydration, 1. 8% sodium chloride, 2. 7% sodium chloride, and after dehydration. Data are shown as means § SEM, and for all tests, P < 0. 05 was considered statistically significant.
2) Analyse multicentrique des résultats des bilans biologiques (le focus reste biochimique mais peut s'enrichir) des patients selon une classification : patients aux urgences, en réanimation/post-réanimation, en unités médicales COVID (médecine interne ; infectiologie), pédiatrie, gériatrie, patients suivis en ville. Les bilans à distance après guérison pourront être analysés, si envisageable. Dans la mesure Synthèse du possible, l'analyse englobera, si elles sont accessibles, les données démographiques, comorbidités, traitements et tiendra compte du parcours du patient et des évènements le jalonnant. Cette étape peut ouvrir la voie à la constitution de bases de données, terrain de recherches futures. 3) Recherche de marqueurs biochimiques pronostiques de l'évolution de la pathologie et/ou en suivi thérapeutique.
Codigestion was optimized by choosing a manufacturer carrying both enzymes and a universal digestion buffer. Primer pairs were designed with the Primer3 software (http://biotools. umassmed. edu/bioapps/primer3_www. cgi) and carefully chosen in the proposed sets, based on the absence (or very low frequency) of SNPs in hybridization sequences at the 3′ end of primers. Because the putative restriction sites are unique, undigested fragments might result from accidentally undigested fragment rather than from the absence of restriction sites. Thus, an internal control was added by the mean of coampli-fication of an FZD1 gene fragment encompassing one SexAI and one BspHI restriction site. Both primers were labeled allowing using this sole fragment for control of both enzymes. The FGA STR (UniSTS240635, GenBank accession M64982), a complex tetranucleotide repeat, was amplified with published primers (https://strbase.
nist. gov//str_FGA. htm accessed 03 03 2020). The SE33 STR (GenBank accession V00481) is an AAAG repeat which was amplified with primers described in https://strbase. nist. gov//str_SE33. htm. Allele calling was performed with the GeneMapper® Software version 5. 0 (Applied Biosystems). For comparison methods, 60 consecutive DNAs referred to our laboratory were analyzed by dideoxy-sequencing. Primers for amplification and Sanger sequencing were 5 ′ ACA TGG TTA AGG CCT GTT GC and 5 ′ GCC ACA TCT GGC TTG AAA TT for HFE exon 2 and 5 ′ TGG CAA GGG TAA ACA GAT CC and 5 ′ CTC AGG CAC TCC TCT CAA CC for exon 4. Amplifications were performed with AmpliTaq Gold 360 mastermix (Applied Biosystems), initial denaturation steps for 10 min at 95 °C, then 30 cycles of denaturation at 95 °C for 30 secs, hybridization at 54 °C for 30 secs, and elongation at 72 °C for 1 min followed by a final elongation step at 72 °C for 7 min.
Initial Setup and Validation. We took advantage of the QIAGEN Multiplex PCR Kit designed for multiplex amplifications. Amplifications were performed in 10 μl final volume. Each primer pair was tested in individual reactions on control DNAs (data not shown) before being mixed in multiplex reactions. After testing the initial mix at the recommended primer concentration in setup reactions (0. 2 μM final for each primer), we concluded it was not necessary to adjust individual primer pair concentrations to limit unbalanced amplification. Codigestions were performed with SexAI and BspHI (0. 75 and 1. 5 UI/μl final, respectively) overnight at 37 °C in the universal buffer provided by the manufacturer. The chosen final conditions are presented in Table  1. Since the primers were chosen to generate fragments markedly differing in size, many fluorochrome combinations are possible.
Many enzymes are available that can differentially digest the sequences of interest. RsaI use was not possible because it digests GTCA sequences which are very frequent and spread on the amplified sequences reported here. We used SexAI instead (A/CCWGGT) and replaced MboI (formerly in use in our laboratory for H63D typing) for BspHI (T/CATGA). These enzymes are used with the same buffer and do not cut FGA and SE33 STRs. However, no internal digestion control was present. Although enzymes are mixed prior to be added in the PCR product, failure of digestion and/or enzyme distribution in the tube might occur. To overcome these difficulties, we added in the multiplex amplification an FZD1 fragment that harbors both BspHI and SexAI sites. The identification of a sequence with these two restriction sites was facilitated by interrogation of the intronless gene database  [9]  http://www.
FT, AN and JML wrote this manuscript. All authors read and approved the final version of the manuscript. Financial support: This work was supported by CEEREAL e. V. CEEREAL e. V. had no role in the design, analysis or writing of this review. Conflicts of interest: FT is consultant to CEEREAL e. V. and received research financial support for conducting the literature search and drafting the manuscript. AN and JML declare no conflict of interest. 10 Summary more whole grain, bran-based and fibre-rich options and developing universally agreed quantitative recommendation for whole grain consumption. Cereals have been consumed by humans since approximately 100,000 years ago. Cereals have to be processed in some way in order to be consumed by humans. Cereal processing is one of the oldest and given the role of cereals for its contribution to meeting nutrition requirements, one of the most important food technologies.
| Gut microbiota analysis Neonates who had a stool sample collected at the time of an enteropathy event (from -2 to + 5 days) were enrolled in the gut microbiota analysis. Two control neonates were selected per case and matched on the following criteria: absence of enteropathy, stool specimen collected in the same postnatal week, birth GA (± 1. 5 weeks), birthweight (± 100g), mode of delivery and neonatal intensive care unit. Total DNA was extracted from 0. 2g of faecal samples as previously described. 14 Bacterial diversity and composition were assessed by 16S rRNA gene sequencing-based method. Variable regions V3-V4 were amplified by polymerase chain reaction (PCR) and sequenced on an Illumina MiSeq platform. Next-generation sequencing data set was analysed using the open-source bioinformatics pipeline Find, Rapidly, OTUs with Galaxy Solution (FROGS).
Ingenuity Pathway Analysis of the RNA-Seq data identified several pathways that were significantly affected by the absence of Mfrn1 and Mfrn2 in liver including amino acid metabolism, small molecule biochemistry, cellular movement, function and maintenance, molecular transport (Fig. 6B , black bars), as well as liver proliferation, inflammation, fibrosis, hepatocellular carcinoma, and hyperproliferation (Fig. 6B , gray bars). The most significantly (p , 0. 0001) altered pathway was amino acid metabolism with nine genes transcript levels changed. We confirmed that amino acid metabolism was affected using LC-MS metabolomic analysis. Loss of Mfrn1 and Mfrn2 in the liver significantly changed amino acid levels, specifically tryptophan and arginine were elevated and valine, glutamine, glutamic acid, and asparagine were significantly reduced in the Alb-CreMfrn1 f/f Mfrn2 2/2 mouse livers compared with WT livers (Fig.
An Agilent 6545 UPLC-QToF (Agilent Technologies, Inc. , Santa Clara, CA) run in the positive mode was used for analysis. Separation was achieved using a Waters BEH amide 2. 1 3 100-mm column with BEH amide pre-column (Waters Corporation, Milford, MA). An initial concentration of 99% ACN with 5% 10 mM NH 4 OAc (A) and 1% 10 mM NH 4 OAc in H 2 O (pH 7, B) was held for 1. 33 min. B was increased linearly to 30% at 5. 13 min and again to 60% at 6. 33 min. Finally, B was increased to 70% at 6. 87 min and held for 2 min. Eluents were returned to starting conditions over 2 min. The system was allowed to re-equilibrate for 4 min between runs. LC-MS data analysis-Data were collected using Mass-Hunter software (Agilent). Metabolites were identified and their peak area was recorded using MassHunter Quant.
These data were transferred to an Excel spread sheet (Microsoft, Redmond, WA). Metabolite identity was established using a combination of an in-house metabolite library developed using pure purchased standards and the METLIN library (RRID:SCR_ 010500). Further analysis was performed using Metaboana-lyst4. 0 (RRID:SCR_015539). To determine whether known metabolites were altered we used fold-change threshold = 1. 5, p value threshold = 0. 05; FDR-adjusted off.
RNA extraction and real-time qPCR analysis Total RNA was extracted using the RNeasy Mini Kit® (Qiagen) following the manufacturer's protocol. The yield and purity of RNA were measured using a NanoDrop ND-1000® spectrophotometer (Nanodrop Technologies). For reverse transcriptase-polymerase chain reaction (RT-PCR) analysis, first-strand cDNA was synthesized on 1 µg of RNA with oligo(dT) primer and random 6mers, using the High-capacity cDNA Reverse Transcription (Applied Biosystems) according to the manufacturer's protocol. Real-time PCR was performed using Absolute QPCR SYBR Green ROX Mix (Thermo-Scientific, Waltham, MA, USA) on a ABI PRISM 7900HT (Applied Biosystems, Life Technologies Corporation, Carlsbad, CA, USA). Realtime PCR analyzes were performed with the SDS software 2. 3 (Applied biosystems).
Urinary PrP C concentration measurements in individuals with cardiopulmonary bypass To monitor PrP C in the setting of ischemia-reperfusion injury (IRI), we took advantage of the biocollection of a previous study  12. From 17 February 2017 to 26 April 2017, 42 patients undergoing scheduled cardiac surgery with CPB were enrolled. The exclusion criteria were: an eGFR <30 ml/ min/1. 73 m 2 , infusion of a radio contrast agent within the 24 h before surgery, a preoperative left ventricular ejection fraction <40%, age <18 years, pregnancy, and the inability to provide consent. AKI was diagnosed according to the KDIGO Clinical Practice Guideline for AKI criteria (http:// kdigo. org/) using serum creatinine levels and urine output after the surgery. This single-center, prospective, pilot study was approved by the French ethical committee on 7 February 2017 (CPP Sud Est III n°2016-072 B) and registered under the EudraCT n°2016-A01871-50.
All patients provided written consent for study participation and for the biological analysis before inclusion. Urine samples were collected from a urinary catheter at three different times: (1)  after the induction of anesthesia and before the start of cardiopulmonary bypass (CBP), (2) at the end of the CPB procedure, and (3) on the day after surgery in the ICU. Urine samples were collected in Corning 50-ml conical tubes and centrifuged at 2000 g for 20 min within 4 hours of collection. Cell pellets were conserved in 350 μL of RLT® buffer (Qiagen™, France) and stored until mRNA extraction. Supernatants and cell pellets were stored at -80 °C until analysis. Clinical data were prospectively extracted from the hospital's electronic medical records. All clinical data and samples were de-identified.
(2) Labeled fragments (amplicons) were separated by size using capillary electrophoresis, and the fluorescence intensity was measured using the Applied Biosystems™ 3730xl DNA Analyzer. One of the dye colors (GENESCAN® ROX 400 HD size standard, Applied Biosystems™, red) was used to detect a labeled size standard in each sample. Fragments and ROX 400 HD were mixed with HiDi™ Formamide (Applied Biosystems) prior to capillary electrophoresis. (3) The data were analyzed using GeneMapper® Software to determine the relative size of each dye-labeled fragment in the sample by comparing fragments with the standard curve for that specific sample.
Statistical analysis All data are represented as individual values and means ± SEM of at least two independent experiments, unless otherwise specified. Graphs were generated using GraphPad Prism 7 Software (GraphPad Software, Inc. ). According to current discussion and criticisms on the performance and interpretation of statistical tests in experimental settings, and in particular the misuse and misinterpretation of p values  [13] [14] [15]  , we choose not to systematically perform comparison of biological data using statistic tests to compute p values for significance. When deemed necessary, ie when the size effect appeared small, we provided mean and 95% confidence intervals of the two groups of values for interpretation.
Acknowledgements Y. B. was supported by a fellowship from  Agence Nationale de la Recherche. Grant support was provided by the following:  Agence Nationale de la Recherche , and  INSERM. 1 INSERM U1138 ,  Centre de Recherche des Cordeliers, INSERM, Sorbonne Université de Paris, F-75006 Paris, France. 2 Service de Néphrologie, Hôpital Européen Georges Pompidou, Assistance Publique Hôpitaux de Paris, Paris, France. 3  Université Paris Saclay, INRAE, AgroparisTech ,  UMR1313 , Génétique animale et biologie intégrative, F78350 Jouy-en-Josas, France. 4  Service de Biochimie, Hôpital Européen Georges Pompidou, Assistance Publique Hôpitaux de Paris, Paris , France.
Alexa 488-and Alexa 546-conjugated anti-immunoglobulin G were used as secondary antibodies (1:400; Molecular Probes, Life Technologies, Saint-Aubin, France). The nuclei were stained with 4′-6diamidino-2-phenylindole (DAPI) to assess the monolayer integrity. The cells were examined by microscopy using an Axio Imager 2 microscope equipped with Apotome. 2, allowing optical sectioning (Zeiss, Oberkochen, Germany). Images were acquired by ZEN 2011® software (Zeiss) and analyzed in ImageJ 1. 46c (https://imagej. nih. gov/ij/index. html).
Western blotting Caco-2/TC7 cells were lysed as previously described  [19]. Protein levels were detected in cell lysates using a Wes™ capillary electrophoresis system (ProteinSimple, San José, CA, USA) according to the manufacturer's instructions. Reconstituted images and quantification were performed using Compass software for Simple Western (ProteinSimple). The primary antibodies were rabbit anti-tricellulin (1:2000; MARVELD2 700191; Thermo Fisher Scientific), rabbit anti-ZO-1 (1:200; ZO1-1A12; 33-9100; Thermo Fisher Scientific), rabbit anti-occludin (1:25; 71-1500; Thermo Fisher Scientific), and rabbit anti-E-cadherin (1:1000; clone 36, 610181; BD Biosciences, Rungis, France). The secondary antibodies and reagents were provided in the separation and detection module kits (ProteinSimple).
Data collection tools For the quantitative component, a paper-based questionnaire captured data on socio-demographic characteristics, dietary intake in the previous 24 h and the context of eating events. Dietary intake data were collected using the qualitative 24 h recall method  [18]. Participants were asked to describe all food and drink consumed inside or outside the home on the day before the interview. However, unlike the traditional quantitative 24 h recall, participants did not estimate quantities consumed  [18]. To prompt recall, a modified multi-pass method was used  [19]. To this end, participants first listed all food and drink consumed the previous day from when they woke up until just before they slept  [19]. Then, participants provided detailed descriptions of each item listed, specifying food preparation methods, such as boiled, fried or deep-fried beef.
Data analysis Dietary practices Dietary typologies were generated using a two-step process. First, multiple correspondence analysis (MCA) was applied to the dietary data collected among the larger sample of participants that took part in the quantitative component of the study. MCA, a multi-variate datareduction method, was used to group foods because the dietary data was in the form of a binary variable, i. e. consumed/not consumed, and not in quantifiable terms  [22] [23] [24]. The MCA was run on 15 food groups (Table  S2 ), which were formed based on various criteria  [22] [23] [24] [25] , i. e. conventional food groups in the literature, reported frequency of consumption of the resulting food groups among study participants, environmental impact of constituent foods per 100 g and knowledge of the local context.
Coding was first performed manually on paper with highlighter pens with a sample of transcripts (n = 3 rural and n = 3 urban) to generate a thematic framework. Coding for manually coded transcripts (n = 6) was later replicated in Nvivo. The thematic framework was then applied to the remaining interview transcripts (n = 12), themes generated and links and patterns between themes identified  [29, 30]. Data validity and credibility were ensured by: i. recruiting a diverse quota sample, ii. relaying their narratives to each participant during the interviews to check for correctness, iii. using the thematic framework analysis method and iv. providing detailed descriptions of study methodology to allow a reader to make their own judgement on robustness  [28, [31] [32] [33] [34] [35]. Management and analysis for qualitative data were performed using Nvivo Version 12.
In the present study, the three aspects of the chosen sensomics methodology are summarized in Figure  1. First, enzymatic hydrolyses were performed from micellar casein proteins using commercially available and food-grade proteases to produce sixteen hydrolysates of varying bitterness. Indeed, several factors, such as the type of enzyme used to hydrolyze the protein and the hydrolysis processing conditions (e. g. , pH, temperature, degree of hydrolysis, etc. ), influence the taste of the hydrolysates  [32]. Second, the organoleptic features of hydrolysates and more particularly bitterness and off-flavors were studied using a trained sensory panel to judge and characterize the produced hydrolysates. Third, hydrolysis generated peptides were characterized by a peptidomics approach combining the peptide chromatographic separation by reverse-phase high-pressure liquid chromatography (RP-HPLC), the detection and fragmentation of peptides by tandem mass spectrometry (MS/MS), and the mass data management using Progenesis QI for proteomics (Waters, Manchester, UK), Peaks studio (Bioinformatics Solution Inc.
, Waterloo, ON, Canada), and the UniProt-extracted bovine protein database. Those tools lead to characterize the amino acid sequences of identified peptides, to measure their intensity but also to carry out comparative statistical analysis to highlight the qualitative and quantitative relevant differences. Finally, the peptides identified from hydrolysates by peptidomics approach were compared with the sensory characteristics of hydrolysates using appropriate statistical tools, such as the RV coefficient, in order to evaluate the overall similarity of the two matrices and then a correlation test (Pearson) to identify the correlation between the sensory and the analytical data.
The hydrolysis monitoring was carried out by collecting data from pH, temperature, osmometry, and the degree of hydrolysis using a method based on the reaction of primary amino groups with o-phthaldialdehyde (OPA). A calibration curve was established at 340 nm with a known concentration of leucine. The degree of hydrolysis is determined by the relationship: DH = (h/h total) × dilution × 100 (in %) (1) with h = number of hydrolyzed peptide bonds; h total = total number of mmol of NH 2 released after total acid chemical hydrolysis measured per 100 mg of micellar casein (h total = 0. 6885); dilution of the hydrolysate sample = 100. 8 h = ((AH -ANH)/εl) with AH = absorbance of the sample at hydrolysis time « t » ANH = absorbance of the sample at t0 before hydrolysis (3) εl = right slope (4) After seven to nine hours of hydrolysis, enzymes were inactivated by heating at 98 • C for 3 min and an aliquot of each hydrolysis was frozen at -20 • C before further analytical characterizations.