dataesr/scientific-paragraphs-categorization huggingface dataset:
Gene ontology analysis Gene ontology (GO) analysis was performed using the functional annotation cluster and chart tools from the DAVID (Database for Annotation, Visualization and Integrated Discovery) bioinformatics resource  [137, 138]. Briefly, the Uniprot accession ID's of the mRNA probes differentially expressed by nutritional history (Additional file 1, 3-week + Brain; 3-week + Liver) were used as input against a background Uniprot accession ID's of the entire 60 K array probe list and processed with the functional annotation cluster and chart tools from the DAVID bioinformatics resource. The resulting data was used as input in the DAVID Enrichment Map plugin from the Bader Lab  [139, 140]  in the Cytoscape network visualization tool (version 2. 8. 3)  [141] [142] [143].
Pathway analysis Selected mRNA probes differentially expressed by nutritional history (3 week + Brain; 3-week + Liver) and those assigned to be part of a significantly affected GO process (Additional files 5 and 6) were used as inputs in the GeneMania pathway analysis tool  [35] [36] [37]  using the inbuilt Homo sapiens pathway interaction database as background and processed according to the default settings in the GeneMania tool. The pathway maps generated by GeneMania are outlined in Fig. 5  and Additional files 3 and 4.
Funding This work was part of a Postdoctoral fellowship programme to MNB funded by  INRA , under the  INRA-WUR Aquaculture platform. The study was partly funded by  INRA  ( Department Phase, Crédit Incitatif ), by the  VEGEAQUA  project (FUI funding,  French government ) and by the  EU -funded  ARRAINA  project No. 288925:  Advanced Research Initiatives for Nutrition & Aquaculture (EU Seventh Framework Programme ).
This retained information allows the PROBIT approach to return estimates with improved precision compared to the classical (i. e. case counting) approach  [17, 18] , making the method well suited to work with small samples. With these conditions, and using computer-based simulations using data derived from cross-sectional surveys, we calculated that a sample size of n = 96 from each LHZ could be expected to yield a 95 % credible interval (CI) of ±10 % or better at any level of prevalence. A sample size of n = 132 children was selected in order to ensure that useful precision is achieved.
Data collection Two interviewers for the three LHZ were trained to perform the sampling protocol, the required anthropometric measurements, and apply the survey questionnaire. Regular supervisions were conducted to ensure anthropometric measurements were done correctly. Each interviewer visited one Listening Post (PSU) per day, and performed interviews of mothers and measurements (weight and MUAC) of 22 children and top-up sampling when this was required. Data were collected during the first 2 weeks of each month. In order to avoid an interviewer bias, monthly rotations were organized in the visited LP between the two interviewers. 36 monthly rounds of data collection were performed and are included in the analysis presented here. Anthropometric measurement (weight and MUAC), morbidity (prevalence of diarrhoea in the last 15 days), infant and young child feeding (IYCF) practices, food security, and water, sanitation and hygiene (WASH) indicators were collected using a paper based questionnaire.
Data analysis Design effect was calculated by dividing the standard error (SE) with clustering by the SE without clustering. For continuous variables, median and Inter-Quartile-Range (IQR) were calculated for the entire study period. The prevalence of GAM was estimated by MUAC with a case-defining threshold of 125 mm using a Bayesian normal-normal conjugate analysis followed by a PROBIT estimation approach. In the work reported, an objective prior was specified using the sex-combined median MUAC-for-age and the square of the sex-combined median negative z-score for children aged between 6 and 24 months taken from the WHO's World Growth Standard (MGRS) reference population  [28]. We used the population mean and variance parameter of the MGRS reference populations (i. e. 145 mm and 121 mm 2 , respectively).
Using these parameters, the equation used to estimate the mean MUAC was: where n is the number of children in the sample and x is the mean MUAC observed in the survey. We used these values (i. e. the posterior mean and variance) to find the 95 % credible interval for the posterior mean using the inverse cumulative normal distribution (NORMINV) function in Microsoft Excel. We translated the posterior mean and the associated 95 % credible interval into a proportion (i. e. prevalence) using the cumulative normal distribution (NORMDIST) function in Microsoft Excel using a threshold value of 125 mm. By using this function, we estimated the probability that a child selected at random from the monitored population would have a MUAC below 125 mm (which equates to prevalence). Data were analysed by the program manager and validated by the ACF Department for Food and Livelihoods.
Comparison between LP and cross-sectional surveys The external validity of the estimates from the LP survey was assessed by comparing the time trend and variability of LP data with that from other data sources. In Burkina Faso, available data included nutritional cross-sectional surveys using the Standardized Monitoring and Assessment of Relief and Transitions (SMART) methodology  [29] , conducted by ACF in Tapoa Province in March 2011, May 2012, December 2012, May 2013 and October 2013 (data not published but available upon request). In order to have the same age group as used for the LP surveillance system, only 6-24 months aged children were kept from the cross-sectional surveys. First, the individual data of LP surveys from all the three LHZ were pooled. We modelled the time trends of continuous MUAC for both LP and cross-sectional data through forward stepwise curvilinear regression weighted by the population in each LHZ.
β ′ 0 is the intercept of model, β ′ 1 , β ′ 2 and β ′ 3 are the coefficients of respective terms T, T 2 and T 3 , and W is the new variable mentioned above. Then we performed a Wald test to determine whether this new variable made a statistically significant improvement to the global regression model and to determine whether the coefficients in the LP and cross-sectional surveys models were significantly different from each other. Third, we calculated the monthly mean MUAC for cross-sectional surveys and for LP separately, with pooled data weighted by the population of each LHZ. Using the Bayesian-PROBIT estimator, the prevalence of GAM was estimated for each data source, and the differences (D) in prevalence estimates between these two data sources plotted. We calculated the mean difference ( D), the SD of the differences, and the estimated limits of agreement as D ± 1.
Thus the time trends of continuous MUAC were similar between the two models/data sources. The monthly GAM was estimated with its 95 % credible intervals at five time points from cross-sectional surveys and LP surveys (Table  3 ). All differences (D) in prevalence estimates between cross-sectional surveys and LP lay within estimated confidence limits (-8. 47 to 5. 38 %) (Fig. 4 ), indicating fair agreement between the two datasets. However, the plot showed an increase as a function of time, namely as a function of the number of months; the corresponding equation was: indicating a monthly increase of about 0. 26 % in GAM prevalence for cross-sectional compared to LP. Extrapolation of the line crossed the upper border of the confidence interval of the mean at time t = 45. 96 months, indicating that the difference in GAM prevalence would probably become significant 3 years and 10 months after the beginning of the surveillance.
264045t -6. 744944  round. Dataset comparisons between LP and repeated cross-sectional surveys did not detect any statistical difference in estimating mean MUAC over a 3-year period in our setting. Post-hoc power analysis showed that for these comparisons, the working power was between 79 and 97 %, thus the corresponding tests were not underpowered. Moreover, the use of the Bayesian-PROBIT approach to estimate GAM has increased the precision of prevalence estimate compared to the use of a frequentist analysis and classical estimator. Using a reduced agegroup (i. e. <2 years old) proved to be also interesting in term of reducing the design effect close to 1, probably by spreading the sample in each community and hence, increasing the heterogeneity in each cluster. A higher decrease in GAM prevalence (0.
Acknowledgements The history of this project and its methodology came first from a discussion between  Rebecca Brown  ( ACF Nutrition  senior advisor at that time),  Claudine Prudhon  (Epidemiologist at the  World Health Organization ) and  Frances Mason  ( Save the Children France, SCF ). The methodology was then developed by  SCF  ( Anna Taylor ,  Alex Rees ,  Brian Kriz ,  Abigail Perry ,  Mickael Manske ) and  ACF  ( Rebecca Brown ,  Hélène Deret ) with the support of  Brixton Health  ( Mark Myatt ). We are very thankful to all these people. We also thank the field teams of ACF in Burkina Faso, in particular the Listening Post team for gathering data and the  ACF coordination team ,  Thomas Loreaux  ( Head of Mission ) and Claire.
Acknowledgements Dr Jordi Bover  belongs to the  Red Nacional RedinRen [National Kidney Research Network ] ( RD06/0016/0001  and  RD12/0021/0033 ), the  Red de Biobancos Nacional Espa ñola [Spanish National Biobank Network ] ( RD09/0076/00064 ), and to the  Grupo Catalán de Investigación AGAUR [AGAUR Catalan Research Group ] ( 2009 SGR-1116 ). He also collaborates with the  Fundación I ñigo Álvarez de Toledo (FRIAT) [I ñigo Álvarez Foundation of Toledo ]. We also wish to thank  Ricardo Pellejero  for his important bibliographic help.
Data collection Clinical cases. A pediatrician from the CPB carried out the clinical examination of potential cases and decided on the need for hospitalizing each case for severe diarrhea. Clinical observations, including signs of severe dehydration, hemodynamic shock and extra-digestive symptoms, were collected. At the inclusion of each case, a trained nurse conducted a standardized questionnaire with parents or caregivers so as to gather demographic, environmental and clinical information. Anthropometric measures were also collected: weight, length or height and mid-upper arm circumference (MUAC). Treatments used before and during hospitalization were recorded, as well as the duration of hospitalization and status at discharge. Two months after the child was discharged, parents were contacted by phone so that we could assess the child's vital status.
Acknowledgments We would like to express our most sincere thanks to the children and parents participating in this study. We also extend our thanks to all the staff from the  Complexe Pédiatrique de Bangui  and the  Institut Pasteur in Bangui  and its director  Dr Mirdad Kazanji  who made this work possible despite the difficult conditions, particularly  Ernest José Gbao  and  Natacha Zato. We would also like to acknowledge  Kathleen Victoir  from the  Institut Pasteur of Paris  for her support as administrative program manager.
Genome sequencing, assembly, and annotation were done at Lifesequencing S. L. (Valencia, Spain). The resulting reads were assembled de novo using the Hierarchical Genome Assembly Process (HGAP3. 0) approach (SMRT analysis version: 2. 3. 0, patch #4) with default parameters and with the minimum seed read length set at 6,000 bp. The first draft genome sequenced was obtained in 2011 (EMBL accession numbers FR871759 to FR871848) by pyrosequencing technology (GS FLX Titanium system; 454 Life Sciences) and revealed the presence of a circular 3,835,873-bp chromosome (108 contigs) and three plasmids (18 to 53 kb)  (7). However, resequencing of the L. pentosus MP-10 genome by using PacBio RS II technology revealed that the assembly contained six contigs (one chromosome and five plasmids). Further analysis aiming to circularize the contigs derived from the assemblies was done using the publicly available tool Circlator based on the algorithm reported by Hunt et al.
We also identified the presence of two clustered regularly interspaced short palindromic repeat (CRISPR) clusters (types I and II) that represent an acquired "immune system," providing protection against mobile genetic elements (viruses, transposable elements, and conjugative plasmids)  (14). The availability of the complete genome sequence will aid in future investigations into the probiotic properties of the L. pentosus MP-10 strain. Accession number(s). The whole-genome sequence of L. pentosus MP-10 has been deposited at the EMBL Nucleotide Sequence Database under accession numbers FLYG01000001 to FLYG01000006.
Validation of the quantification of ascorbic acid The ascorbic acid concentrations obtained for the validation plan were calculated from the absorbance by applying the calibration lines made during the same series (data not shown, available as supplementary material 1). These experimental results made it possible to calculate the fidelity and the accuracy of the method for each level of concentration (Table  3 ). This method is characterized by coefficients of variation (CV) for repeatability and for reproducibility below 3%, except for the lower concentration of 1. 162 mM for which CV values of 5. 72% and 8. 36% were calculated for repeatability and reproducibility, respectively. However the method was considered validated in terms of fidelity on the whole range because the precision around the mean values never exceeded 10% of variation.
2C ). These new intercept values varied with the total content in AA + DHAA, and therefore with the total absorbance measured after reduction (Atotal). A new regression model was built in order to be able to predict the intercept value (Int) as a function of Atotal (Eq. 5) with a very good determination coefficient (R² = 0. 9921). Int = 1. 014  Atotal + 0. 1529 (5) It could be noticed that all these correction steps have a minimal impact on the adequacy between the experimental data and the values given by the linear models. On Fig. 2A , R 2 coefficients were equal to 0. 9721, 0. 9889 and 0. 9735 for concentrations of 1. 5, 4. 0 and 5. 7 mM, respectively. However, R 2 values could not be determined for the subsequent steps. The adequacy can also be characterized by calculating the relative root mean square error (RMSE) between the experimental values and those calculated thanks to the different linear regressions.
Statistical analysis Analyses were done using SPSS software version 22 (IBM, NY, USA). Crude percentage points differences in hookworm prevalence (with corresponding confidence intervals for proportions) between the intervention and placebo groups were calculated. Effects of the interventions on hookworm infection risk were analyzed using generalized linear mixed models. A logistic mixed model with hookworm infection as the binary outcome at three and seven months and random intercepts for school and child ID was used to account for repeated measurements within subjects and clustering of subjects within schools. Covariates were sex, age in quartiles and baseline hookworm prevalence at the school. In the analysis we focused on the effect of the intervention on hookworm infection in children who were uninfected at baseline, in order to estimate new infection rate.
The fecal calprotectin data were skewed, which could not be corrected by logarithmic transformation. Therefore, fecal calprotectin was analyzed using mixed model analysis with high fecal calprotectin (>50 mg/kg) at seven months as binary outcome and a random intercept for school clustering. Covariates were sex, age in quartiles and high fecal calprotectin at baseline (binary)  [19]. Effect modification was examined by introducing interaction terms into the model, when these showed significant effects (p <0. 05), we stratified the analysis.
Ethics Neutrophils were isolated from venous blood of healthy volunteers managed in the hematology and immunology department of Bichat Hospital, Paris, France. The investigations were approved by the local ethics committee and samples were obtained with the volunteers' and patients' written informed consent. All experiments were approved by the 'Institut National de la Santé et de Recherche Médicale (INSERM)' institutional review board and ethics committee. Data collection and analyses were performed anonymously.
Effect of EtOH and CDE on Erythrocytes-SH groups content In the present study, the effects of EtOH and CDE treatment on SH-group levels were also examined. The data from Fig. 6  showed that acute EtOH administration significantly (P < 0. 0001) decreased the content of -SH groups. CDE (25, 50, and 100 mg/kg; b. w. ) pre-handling significantly (P ≤ 0. 0024) and dose-dependently protected erythrocytes sylfhydryls against depletion caused by alcohol administration. Ascorbic acid pre-treatment, used as.
NeuN expression was visualized with 3,3 0 -diaminobenzidine (DAB as chromogene). NeuN-positive cells were counted in the cortex and striatum, including the caudate-putamen area at the level of the lesion (bregma level 0. 3 mm; magnification Â 40)  (Blondeau et al. , 2009b; Heurteaux et al. , 2006; Nguemeni et al. , 2010). Data were expressed as number of NeuN-positive cells per mm 2. In a separate group of mice, we blindly assessed cellular status at 3 weeks post-MCAo. Tissue characteristics were quantified by measuring ipsilateral and contralateral hemispheric volumes and calculating tissue loss and atrophy using coronal cryosections stained with cresyl violet  (Lee et al. , 2014). Calculations of neuronal density of hippocampal CA1, CA2 and CA3 (Cornu Ammonis) subfields were evaluated on coronal sections of the dorsal hippocampus stained with cresyl violet, corresponding to brain sections located between 1.
Acknowledgments We thank  Dr C. Rovere ,  O. Le Thuc ,  C. Widmann ,  N. Simon-Rousseau ,  C. Simonneau ,  A. Renault  for many helpful discussions and  Dr J. Tauskela  for his critical reading of the manuscript. We are very grateful to  Pr M. Guichardant  and  P. Daira  (lipidomics IbiSA platform of the  LISA Carnot institute ), and  Drs N. Combe ,  L. Fonseca ,  B. Buaud  and  C. Vaysse  ( Iterg, Equipe Nutrition, M etabolisme et Sant e ) for Fatty Acid Analysis.
the application of quantitative methods to various issues in the area of international education and the construction of large education inequalities databases using household surveys. Máiréad Dunne is Professor of Sociology of Education at the University of Sussex and Director of the Centre for International Education. She engages in social and cultural studies of educational and social mobility. Her research has included studies of social class, gender, sexuality and ethnicity in policy and practice contexts in low-income countries as well as the UK. Her concerns are for reflexive research and theoretical development through contextually located and multi-perspectival explorations of educational policy, institutions and practices using mixed methods in approaches. Benjamin Zeitlyn is a Lecturer in International Education and Development working at the University of Sussex.
When a sugar is metabolized by a strain, the number 1 appears in the cell of the table. The number of sugars metabolized by each strain is indicated Branch (1)  Maltose Galactose Xylose Raffinose Lactose L-Sorbose L-rhamnose Sorbitol Mannitol Total (3)  Genome sequence accession number A AZJY00000000 A AZLL00000000 A AZJX00000000 A ACSE00000000 A AZJV00000000 A AZKJ00000000 A AZKG00000000 A AZLR00000000 A ALAF00000000 A AZLM00000000 A AZLS00000000 A 1 AZLJ00000000 A 1 AZLN00000000 A AZKD00000000 A AZLO00000000 A AZJW00000000 A AZLK00000000 A AZLG00000000 A AJTP00000000 A AZLQ00000000 A AZLT00000000 A CP000411 (18) A AZLI00000000 A AZKC00000000 A AZHH00000000 A ALAH00000000 A AZKK00000000 A AZJZ00000000 A 1 AZLP00000000 B AZKB00000000 B 1 AZLH00000000 B 1 1 1 AZIP00000000 B 1 1 1 AZKL00000000 B AAUV00000000 B 1 AZKF00000000 B 1 AZKE00000000 B AZKH00000000 B 1 AZKI00000000 B 1 AZLE00000000 B 1 AZJU00000000 C 1 1 AZLF00000000 8 4 3 2 0 0 0 0 0 20% 10% 7% 5% 0% 0% 0% 0% 0% observed.
To further assign predicted protein functions, we used either the Pfam database (http://pfam/xfam. org), the CAZy database (www. cazy. org/), or, for transport proteins, the TCDB database and the ABCdb database (http://www. tcdb. org/; https://www-abcdb. biotoul. fr/). Analysis also included BLASTp comparisons with nonredundant protein databases (http://www. ncbi. nlm. nih. gov/Blast. cgi) [31].
Additional genes putatively associated with carbohydrate metabolism Additional genes putatively associated with carbohydrate metabolism were found: (i) a gluconate cluster comprising a permease and a gluconate kinase gene (ii), an ABC transporter putatively associated with 2-deoxy-ribose uptake (iii) a pts galactitol operon, gatA. According to TCDB database, PTS galactitol is poorly described and its substrate specificity remains unclear. These 3 gene clusters form part of the core genome. Two non-functional myo-inositol cassettes were specifically found in O. oeni IOEB_0502 and IOEB_C52 (see Fig. 7  for strain IOEB_C52). Furthermore, genes putatively involved in D-arabinose metabolism (gutQ) or L-xylulose (xylA and xylB) were found (Additional file 1: Table  S1 ). Additionally, a α-mannosidase gene was found in 6 of the studied strains (Additional file 1: Table  S1 ).
Data Collection Only mother/infant dyads in which the infant remained exclusively breastfed throughout the first month postpartum were included in the study. Among the 165 women who gave consent, 2 groups of 50 mother-infant dyads (82 from Poitiers and 18 from Chatellerault) completed the entire study. Participating mothers and their infants were investigated at the clinical investigation center Inserm 1402 at 1 month postpartum. Thirty-five of 165 discontinued full breastfeeding and switched to non-exclusive breastfeeding or formula feeding and 30 left the study for other reasons (Fig  1 ). In each group, mothers were primiparous (n = 20) and multiparous (n = 30) with no mismatch; of European origin (n = 42) or African origin (n = 4) and 4 mismatches (European vs. African origin); middle school (n = 5) or higher (n = 30) and 15 mismatches (College vs.
Leptin Analysis Leptin analysis can potentially be affected by different sample handling protocols  [13]. The procedure adopted was based on that previously recommended  [13]. All analyses were carried out on samples that were conserved frozen and only thawed just before analysis. The whole milk samples were vigorously vortexed to ensure sample homogeneity, in particular to disperse fat globules and were diluted 1:1 with assay buffer, as recommended in the assay instructions and in  [13]. Leptin content was measured using Human leptin radioimmunoassay kit (Linco research Inc. , Saint-Charles, MO, USA). All tubes were counted in a gamma counter and leptin concentrations were calculated using automated data reduction procedures. Analysis was performed in duplicate with repeatability below 10% and re-analyzed if above that cutoff.
Statistical Analysis The number of mother-infant dyads to include was calculated to attain the primary aim of the study i. e. to demonstrate a higher human milk leptin concentration in the obese group. The inclusion of 50 obese and 50 normal-weight mothers allowed the detection of a difference of 0. 15 ± 0. 2 ng. mL -1 in milk leptin concentration (95% power, 5% significance level). Data are expressed as means ± standard deviation. Distributions were tested for normality using Shapiro-Wilk test. Comparisons between groups were performed using an unpaired t-test in the case of normality and a Wilcoxon rank sum test for parameters showing a non-normal distribution. Correlation analyses were performed on the whole dataset using Pearson's coefficient. P values <0. 05 were considered statistically significant.