dataesr/scientific-paragraphs-categorization huggingface dataset:
Methods A narrative review was undertaken. The databases CINAHL plus, EBSCOhost, and Medline were searched in January 2018 using the term/s Bfeeding intolerance^and Btoleranceâ nd Bchild^or Bpediatric. ^We also replicated the search strategy of the systematic review of feeding intolerance in adult intensive care  [2]. Inclusion criteria were papers published in English or French and related to critically ill children (aged term to 17 years) without a limit applied to search years. However, as only one review paper specifically discussed feeding intolerance  [46] , we broadened our search to any study in critically ill children where feeding intolerance was defined. For this, we searched the PICU trials registry PICUTrials. net  [29]  and searched for common nutritional interventions where feeding intolerance may have been used as an outcome.
Statistical analysis 107 The statistical analysis, such as statistical tests and box-plots, were per-108 formed with R software (R Core Team (2016), R: A language and environ-  Therefore, this law directly relates the attenuation of light to the optical properties of the bulk microstructure. It is worth noting that κ depends only on physical parameters without introducing any arbitrary variable. I = I 0 exp(-κh) (1) To check the validity of this law, we performed light transmission measurement at the center of HV kernel cheek cross-sections with thicknesses varying from 0. 9 to 1. 8 mm. Figure  2   The validity of the Beer-Lambert law to describe the transmission of light through the wheat endosperm gives way to characterize wheat propensity to transmit light with a sound physical parameter: the absorption coefficient.
Identifiability testing can be helpful to provide guidelines to deal with non-identifiability, either providing hints on how to simplify the model structure or indicating when more information (measured data) are needed for the specific experiment  [31]. Let us consider M(p) a fixed model structure with a set of parameters p describing the input-output behavior of the system under study. The structural identfiability of the parameter p i is determined from the following equality M(p) = M(p * ) ⇒ p i = p * i ( 10 ) If the equality  (10)   [32, 28, 33]. To facilitate identifiability testing, software tools such as DAISY (Differential Algebra for Identifiability of SYstems)  [31]  and GenSSI have been developed  [34]. DAISY is implemented in 11 the symbolic language REDUCE and GenSSI is implemented in Matlab.
A structural identifiability analysis was performed for the β-casein model by using both DAISY software tool  [31]  and GenSSI-Matlab  [34] , to evaluate how the identifiability properties of the model change with respect to the level of specification or granularity and the candidate constitutive equations. Table  3  summarizes the identifiability and intepretability analysis. It can be noted that the basic structure of the model is interpretable but its identifiability cannot be tested because r(•) is not a scalar. However, its identifiability analysis is latter We deduce that a PBSM can have an extended structure to identify its parameters and an extended structure to interpret the model parameters. In 13 the case of the β-casein model, two extended structures of the model can be considered depending on the interest: if the interest is to perform parameters identification, the mathematical expression containing parameters b 1 and b 2 is more convenient.
Growth studies of Bacteroidetes spp. on complex AGP revealed three keystone organisms that facilitated utilisation of the glycan by 17 recipient bacteria, which included B. thetaiotaomicron. A surface endo-β1,3-galactanase, when engineered into B. thetaiotaomicron, enabled the bacterium to utilise complex AGPs and act as a keystone organism. The human gut microbiota (HGM) contributes to the physiology and health of its host1. Glycans, the major nutrients for the HGM, are degraded primarily by Bacteroides species within this ecosystem2-4. Understanding glycan utilisation in the HGM underpins prebiotic and probiotic strategies that promote human health. Glycan degradation is mediated by carbohydrate active enzymes (CAZymes), primarily glycoside hydrolases (GHs) and polysaccharide lyases (PLs)5, which are grouped into sequence-based families on the CAZy database (http://www.
Electrospray ionisation mass spectrometry (ESI-MS) The molecular mass of purified oligosaccharides (in 10 mM ammonium acetate, pH 7. 0) were analysed via negative ion mode infusion/offline ESI-MS following dilution (typically 1:1 (v/v)) with 5% trimethylamine in acetonitrile. Electrospray MS data was acquired using an LTQ-FT mass spectrometer (Thermo) with a FT-MS resolution setting of 100,000 at m/z = 400 and an injection target value of 1,000,000. Infusion spray analyses were performed on 5-10 μl of samples using medium 'nanoES' spray capillaries (Thermo) for offline nanospray mass spectrometry in negative ion mode at 1 kV.
An HCD collision energy of 30% was used, the AGC target was set to 1 x 10 4 and a 40 ms injection time was allowed. The number of MS/MS events between full scans was determined on-thefly to maintain a 3 s fixed duty cycle. Dynamic exclusion of ions within a ± 10 p. p. m. m/z window was implemented using a 35 s exclusion duration. An electrospray voltage of 2. 0 kV and capillary temperature of 275 °C, with no sheath and auxiliary gas flow, was used. Mass spectrometry data analysis-All tandem mass spectra were analysed using MaxQuant 1. 5. Peak list generation was performed within MaxQuant and searches were performed using default parameters and the built-in Andromeda search engine51. The enzyme specificity was set to consider fully tryptic peptides, and two missed cleavages were allowed. Oxidation of methionine, N-terminal acetylation and deamidation of asparagine and glutamine was allowed as variable modifications.
Crystals formed under these condiotns were then back soaked, in mother liquor overnight to remove the rhamnose. These crystals were then transferred to a fresh drop and soaked with galactose, galactodeoxynorijmycin or galactoimidazole, as desired, at concerntaions in >30 mM. These crystals were left overnight and then cryo protected with paratone oil. Data collection and processing-Diffraction data for BT0290 and BT3674 were collected at the Diamond Light Source, U. K. , on beamline I02, whilst, all other data was collected on bealine IO4-1, at a temperature of 100 °K. Alldata were processed and integrated with XDS and scaled using Aimless38, 39. For all datasets, the space groups were determined using pointless and later confirmed during refinement40. The phase problem was solved by molecular replacement using Phaser41.
PDB 3D3A was used as search model for BT0290; BT3674 was solved using 4QJY; BT0265 was solved using 3VSF and a truncated version of BT0265, lacking the C-terminal Ig domain was used to solve BT3683. Additional automated model building for BT0265 was carried out using buccaneer42. Solvent molecules were added using COOT43 and checked manually. All other computing used the CCP4 suite of programs44. Five percent of the observations were randomly selected for the Rfree set. The models were validated using Molprobity45. The data statistics and refinement details are reported in Supplementary Table  6.
Comparative genomics analysis Using a similar strategy to the identification pectin PULs, AGP PULs were searched for in Bacteroidetes genomes. The identification of similar PULs was based on PUL alignments. Gene composition and order of Bacteroidetes PULs were computed using the PUL predictor described in PULDB46. Then, in a manner similar to amino acid sequence alignments, the predicted PULs were aligned to the appropriate pectin PULs according to their modularity as proposed in the RADS/RAMPAGE method47. Modules taken into account include CAZy families, sensor-regulators and suscd-like genes. Finally, PUL boundaries and limit cases were refined by BLASTP-based analysis. The glycoside hydrolase families discovered in this study are listed in the main text.
1. 750, and searched against a combined database of Bacteroides thetaiotaomicron VPI-5482 (containing 4782 entries), B. cellulosilyticus MGS:158 (containing 4369 entries) and the B. cellulosilyticus BACCELL_00844 glycosyl hydrolase family 16 protein. Protein sequences were downloaded from Uniprot on May 10th 2018.
Acknowledgements This work was supported in part by an  Advanced Grant  from the  European Research Council  (Grant No. 322820 ) awarded to H. J. G. and B. H. supporting D. N. , A. C. , J. M. -M. , J. B. , N. T. , a  Wellcome Trust Senior Investigator Award  to HJG (grant No. WT097907MA ) that supported E. C. L. The  Biotechnology and Biological Research Council  project " Ricefuel " (grant numbers  BB/K020358/1 ) awarded to H. J. G. supported A. L. We thank Diamond.
Strengths and limitations To our knowledge this is the first study to investigate the role of FGF23 in patients with worsening symptoms of heart failure. Strengths of this study are the number of patients enrolled in this observational, European, multicentre, multinational cohort, and the extensive clinical data available, such as markers of RAAS activation. Limitations of this study include the observational design of this study, in which residual confounding potentially influenced our results. Also, both new-onset and worsening heart failure patients, as well as in-and outpatients were enrolled in our study. However, in subgroup analyses there was no difference in prognostic value. Data during hospitalization for heart failure and repeated measures of FGF23 and other biomarkers were not available, and we were therefore not able to establish the association between FGF23 and efficiency of decongestion.
21 In this method, samples are prepared by removal of proteins and derivatization to produce fluorescent thiochrome compounds that are separated on a reverse phase analytical column, then detected and quantified. 14 ethods using mass spectrometry have also been developed. 18 Liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) allows sensitive and selective measurement of underivatized ThDP. LC-MS/MS methods require smaller sample volumes and are faster, but the instruments are more expensive than an HPLC with an optical detector. Data analysis and presentation. Since there are no standard reference ranges currently accepted for ThDP, the data should be presented with the reference interval used by the reporting laboratory. For erythrocytes, ThDP concentrations should be reported in nmol/L red blood cells (RBCs).
FBS data suggest inadequate availability of thiamine in the national food supply of Botswana, Somalia, Libya, Guinea Bissau, and the Gambia. More work is needed in these countries and others in the African regions to assess the possible extent of thiamine deficiency. While there is some co-occurrence with riboflavin deficiency, it is not well correlated with thiamine deficiency. These analyses considered the fact that rice and wheat fortification programs may be in place in a given country, as indicated in Figure  8. Countries highlighted in turquoise are those where the estimated mean thiamine availability is lower than the RNI for men (1. 2 mg/day). Countries shaded in yellow have rice or wheat flour fortification programs in place that include thiamine; but the coverage of these programs is not known, so their impact on the population risk of thiamine deficiency is uncertain.
Countries shaded in gray have an estimated mean thiamine availability above the RNI for men. In the Americas, only the Dominican Republic, Haiti, Ecuador, and Uruguay had inadequate thiamine availability. However, all of these countries except Uruguay fortify wheat and/or maize with thiamine. Thiamine intake has also been assessed by micronutrient status surveys that use 24-h recalls or food frequency questionnaires (FFQs) to estimate intake. Table  5  shows the results of published studies of micronutrient intakes, including thiamine intakes, of pregnant and lactating women in LMIC. These studies suggest the need to assess thiamine status in a number of areas outside of Southeast Asia, including parts of Africa (e. g. , Burkina Faso) and South America (e. g. , Colombia and Peru). While the risk of inadequate thiamine intake has been assessed most frequently through the use of dietary intake surveys and national FBSs, household consumption and expenditure survey (HCES) data are now being used more frequently to estimate household-level micronutrient intake.
These surveys provide several advantages in that the data are collected routinely in many countries; and the results are easily subdivided by socioeconomic status and geographical area, both of which can affect the risk of inadequate thiamine intakes. For example, India, a large country with a diverse population, is not identified by FBS data as a country with thiamine deficiency. However, infantile beriberi cases have been reported in recent years in the northern region of Kashmir, where diets consist largely of polished rice. 75, 79, 114 The ability to disaggregate dietary data for specific population subgroups can be useful in assessing the risk for thiamine deficiency. Infant mortality data. Month-specific infant mortality rates may also be used to identify regions at high risk of widespread thiamine deficiency.
Individual quantitative dietary assessment. Usual thiamine intake can be assessed by quantitative dietary intake data collected in a representative sample of the population of interest using methods such as 24-h recalls, estimated or weighed food records, or FFQs. 107 The preferred assessment method is a multiple-pass, interviewer-administered, 24-h recall, in which individuals are asked to recall intake over the previous 24-h period with one or more nonconsecutive repeat days to determine the distribution of "usual intakes in the population" by removing intraindividual day-to-day variation. 107, 121 After dietary intake data are collected, thiamine intake is determined using a food composition database, and then the dietary reference intakes can be used to assess dietary adequacy of the population.
124 Nevertheless, if the FBSs indicate that there is a shortfall in thiamine availability nationally, at least some individuals in the population are likely to have inadequate intakes. A recent analysis of FBSs from 17 countries in the Western Pacific highlighted potential dietary thiamine inadequacy in Cambodia and Mongolia. 123 A global analysis of FBSs indicated that several countries outside Southeast Asia may also have significant inadequacies in thiamine intake. 116 hese include Bangladesh, Sri Lanka, Mozambique, Zimbabwe, Madagascar, Sierra Leone, Congo, and Liberia, where more than 40% of the population was estimated to have inadequate thiamine intake. Household consumption and expenditure survey. A nationally representative dataset that could be harnessed for analysis is the World Bank HCES, which includes several subsurveys including the Household Income and Expenditure Survey.
Acknowledgments This paper was developed with the support of the technical consultation on " Global Prevalence and Disease Burden of Thiamin Deficiency ," convened by the  Sackler Institute for Nutrition Science , a program of the  New York Academy of Sciences, in January and March 2017. The consultation and the development of this paper were supported by funding from the  Bill & Melinda Gates Foundation. The findings and conclusions of this report are those of the authors and do not necessarily represent the official position of the  Centers for Disease Control and Prevention. The authors thank  Tiffany Bowman  for her assistance in creating many of the figures. L. B. is Research Director of the  F. R. S. -FNRS (Belgium).
ACKNOWLEDGEMENTS We thank  Dr. S. Kozma  and  Dr. G. Thomas  ( IDIBELL, Barcelona ) for the use of S6K1-KO mice. We thank the animal facility and the genotyping platform of the  INSERM U1215 NeuroCentre Magendie , funded by  INSERM and Labex Brain  ( ANR-10-LABX-43 ), for animal care and mouse genotyping. The help of  Delphine Gonzales  and  Philippe Alzieu  is acknowledged. M. H. was recipient of an  MD/PhD fellowship  from the  University of Bordeaux and Labex Brain. The microscopy was done in the  Bordeaux Imaging Center , a service unit of the  CNRS-INSERM and Bordeaux University , member of the national infrastructure  France BioImaging. The help of  Fabrice Cordelières  is acknowledged. This work was supported by  INSERM (DC)  and  Aquitaine Region (DC) ,  ANR-13-BSV4-0006   Neuronutrisens (DC ),  ANR-2010-1414-01  (DC),  Labex BRAIN   ANR-10-LABX-43  (DC, MH), equipex OPTOPATH  ANR-10-EQPX-08  (DC),  University of Bordeaux MD/ PhD Programme (MH) ,  PhD  fellowship from the  French Ministry of National Education, Higher Education and Research (VS) ,  Inserm/Region  and FRM PhD fellowship FDT20150532545 (NS),  University Hospital Center of Bordeaux (AT, MH) ,  Master fellowship "année recherche" University of Bordeaux/University Hospital Center of Bordeaux (AF) ,  Post-doctoral fellowship  from the  Mexican Consejo Nacional de Ciencia y Tecnologia (CONACYT) (OG-Q) ,  Novartis Pharma  (DC, AT), and  Fondation Francophone pour la Recherche sur le Diabète (FFRD) , which is sponsored by  Fédération Française des Diabétiques ,  AstraZeneca ,  Eli Lilly ,  Merck Sharp & Dohme ,  Novo Nordisk , and  Sanofi (DC).
Validation of qPCR and qRT-PCR tools We developed primer sets (Additional file 1: Table  S1 ) to specifically amplify acdS gene sequences in the acdS reference database constructed. Eight primer pairs were discarded as they failed to specifically amplify acdS from pure bacterial genomic samples. Another one was discarded as it could not amplify acdS genes from a soil community, and only pair acdSF5/acdSR8 (Additional file 1: Tables S1, S2 and Additional file 2: Figure  S1 ) was kept. qPCR conditions were optimized to obtain an amplification efficiency of > 80% and an error below 0. 1 with genomic DNA of acdS strains P. kilonenesis F113 (i. e. , 81. 2% and 0. 06, respectively) and Burkholderia cenocepacia J2315 (i. e. , 100% and 0. 007, respectively). The detection limit of the qPCR method on pure cultures was 6 acdS gene copies (corresponding to 50 fg of J2315 genomic DNA template).
When tested on total DNA or cDNA (reverse transcription on total RNA) obtained from rhizosphere of the different Poaceae, amplification efficiencies above 80% and errors below 0. 1 were also obtained, for both soils tested. acdS could always be detected by qPCR in the two bulk soils (Additional file 3: Figure  S2 ). Illumina MiSeq sequencing of acdSF5/acdSR8 amplicons from bulk soils and rhizosphere soils gave 3,903,982 reads (44,287 OTUs) from cropped soil and 1,673,758 reads (28,759 OTUs) from meadow soil. Similarities of acdS sequences with known references were assessed with the in-house core-acdS database extracted from the FunGene database. The phylogenetic tree showed that none of the sequences clustered within the D-cystein-sulfydrase outgroup (Additional file 4: Figure  S3 ). The OTUs obtained clustered in numerous clades encompassing all the known diversity of the acdS gene (Proteobacteria, Actinobacteria, and microeukaryotes; Additional file 4: Figure  S3 ).
2 ). Therefore, this work a d c Fig. 4  Pairwise comparison plant phylogenetic distance between Poaceae (X-axis) with the corresponding distance between their root-associated ACC deaminase functional group (Y-axis). The 18 maize-based comparisons are indicated using black triangles (maize-maize; n = 6), diamonds (maize-teosinte; n = 4), circles (maize-sorghum; n = 4), or squares (maize-wheat; n = 4), and the three other comparisons using a white circle (teosinte-sorghum), white triangle (teosinte-wheat), or white square (sorghum-wheat). Distances were calculated two by two, using Kimura two-parameter model for plant phylogeny, Bray-Curtis distance between rhizobacterial communities (a) and Euclidean distance for qPCR (b, c) or qRT-PCR data (d, e). The Spearman correlation coefficient is indicated proposes a novel tool that can be used to monitor the size, transcription, and diversity of the acdS functional group in various plant, soil, and environmental conditions.
Identification of acdS primers All available (in February 2016) sequences from the acdS/D-cysteine-sulfhydrase FunGene sequence database were retrieved and aligned using MUSCLE. Key amino acid positions known to be important for ACC deaminase activity, namely Lys51, Ser78, Tyr295, Glu296, and Leu322  [59]  were searched using Pseudomonas kilonensis F113 as a reference. Sequences presenting different amino acids in the key positions were discarded, as they are likely to correspond to D-cysteine desulfhydrases  [59]. The acdS sequences and acdS homologs (also included in the alignment to serve as non-target sequences) from the D-cysteine desulfhydrase producer strains Pseudomonas syringae DC3000 (AE16853), Achromobacter xylosoxidans BM1 (AY604540), Achromobacter sp. CM1 (AY604541), Rhizobium sp.
Development of acdS qPCR and qRT-PCR Quantitative PCR assays were conducted using LightCycler 480 SYBR Green I Master mix in a final volume of 20 μL and a LightCycler 480 (Roche Applied Science, Meylan, France). Cycle threshold (Ct) of individual samples was calculated using the second derivative maximum method in the LightCycler Software v. 1. 5 (Roche Applied Science). The standard curves were obtained by plotting the mean Ct value of the three replicates (per DNA concentration) against the log-transformed DNA concentration. Amplification efficiency (E), calculated as E = 10 (-1/slope) -1, and the error of the method (mean squared error of the standard curve) were determined using the LightCycler Software v. 1. 5 (Roche Applied Science). Standard curves were generated using genomic DNA of P.
The final qPCR protocol used primers acdSF5/acdSR8 amplifying a fragment of 133 nt. Reaction mix contained 10 μL of LightCycler 480 SYBR Green I Master (Roche Applied Science), 1 μM of each primer, and 2 μL of DNA extract. The final cycling program included a 10-min incubation at 95 °C, 50 amplification cycles of 30 s at 94 °C, 7 s at 67 °C, and 15 s at 72 °C, and the fusion program for melting curve analysis described above. The generated standard curve from genomic DNA of B. cenocepacia J2315 was subsequently used as the external standard curve for determination of acdS copy number in uncharacterized DNA samples. Two DNA standards from genomic DNA of B. cenocepacia J2315 were included as reference in each run to detect between-run variations.
qPCR and qRT-PCR analyses of acdS The quantities of acdS genes (qPCR) and mRNA (qRT-PCR) were estimated using 20-μL containing 4 μL of PCR grade water, 1 μL of each primer (final concentration 1 μM), 10 μL of LightCycler-DNA Master SYBR Green I master mix (Roche Applied Science), and 2 μL of sample DNA (10 ng). The cycling program entailed 10 min incubation at 95 °C, followed by 50 cycles of 94 °C for 15 s, 67 °C for 15 s, and 72 °C for 10 s. The fusion program for melting curve analysis is described above. Amplification specificity was assessed by melting curve analysis of PCR and RT-PCR products, done by ramping the temperature to 95 °C for 10 s and back to 65 °C for 15 s, followed by increases of 0. 1 °C s -1 up to 95 °C. Melting curve calculation and determination of Tm values were performed using the polynomial algorithm function of LightCycler Software v.