dataesr/scientific-paragraphs-categorization huggingface dataset:
Anthropometric recovery was defined as MUAC of 125 mm or larger in the OptiMA group and MUAC of 125 mm or larger or WHZ score of -1•5 or higher in the standard group (appendix 2 p 1). Since anthropometric recovery corresponds to the end of treatment criteria specific to each strategy, we retained the definition used by each strategy (ie, based on MUAC only with the OptiMA strategy and based either on MUAC or on WHZ score with the standard one). Children in both groups were monitored for 6 months from inclusion. Children in both groups receiving RUTF were asked to visit the trial centre once a week for those living in villages less than 14 km from the health centre, and once a fortnight for those living more than 14 km away. At each visit, the following data were collected: MUAC and weight; whether any RUTF had been provided; whether a rapid diagnostic test for malaria was needed, with artemisinin-based combination therapy provided for those who tested positive; and whether any clinical symptoms were present.
Children were referred to the hospital as indicated. Height was measured once a month. Children not receiving RUTF (ie, those in either group for whom RUTF was stopped after recovery, and those in the standard group who never started RUTF) were visited every 2 weeks in their village until 6 months after inclusion. During home visits in the village, a nurse research officer assisted by one or two community health workers monitored the anthropometric and clinical status of the children. At each visit, the following data were collected: MUAC and weight; a rapid diagnostic test for malaria was administered if indicated and artemisinin-based combination therapy was provided as needed; and whether any clinical symptoms were present. Any child who needed nutritional or medical care was referred to either the trial centre or the Kamuesha general hospital.
Fifth, even if there are true benefits of the OptiMA strategy in terms of weight gain, it might not replete the children in terms of key micronutrients important for haemopoiesis and brain development. Further studies should explore this point. Sixth, the pattern of acute malnutrition, including the proportion of children with moderate acute malnutrition and severe acute malnutrition and the frequency of oedema, differs across geographical areas. It might not be appropriate, therefore, to generalise our conclusions for all contexts. A three-arm trial comparing the ComPAS, OptiMA, and national standard strategies is underway in Niger (NCT04698070)  30  and will allow not only for testing the OptiMA strategy in another context but also for putting it in perspective with the ComPAS strategy. Finally, only part of the population meeting the current WHO definition of moderate acute malnutrition and severe acute malnutrition was included in the trial.
Acknowledgments The study was primarily supported by the Innocent Foundation (London, UK, grant number ALIMA-2018-DRC) and received additional funding from the European Commission through the European Civil Protection and Humanitarian Aid Operations (ECHO, Brussels, Belgium, grant number ECHO/COD/BUD/2018/91023). This Article covers humanitarian aid activities implemented with the financial assistance of the EU. The views expressed herein should not be taken, in any way, to reflect the official opinion of the EU, and the European Commission is not responsible for any use that might be made of the information it contains. We thank the caregivers and children who participated in the study. We also thank the ALIMA operational team in the Democratic Republic of the Congo who managed the trial and the nutrition programme on a day-to-day basis.
Each sample injection was followed by "blanks" in order to perfectly clean the column and thus avoid "carry-over" problems between two injections. The data was transformed with MSConvert into a mzXML file (peak picking level 1-2) before being interpreted using the software X!TandemPipeline version 0. 2. 38, e-value < 0. 05 per peptide and minimum two peptides per protein. To identify peptides, LMD-9 Proteins fasta file was used. Results were interpreted against Uniprot database available online: https://www. uniprot. org/ (accessed on 15 November 2021) and loctree3 available online: https://rostlab. org/services/loctree3/ (accessed on 15 November 2021).
After blocking 1 h at room temperature with Tris-buffered saline Tween 20 (TBST) containing 5% non-fat milk powder, the membranes were treated with primary antibodies (1:1000) for 15 h at 4 • C against IL-1β, COX-2 (RD systems, Rennes, France), and β-actin (Sigma-Aldrich, Saint Quentin Fallavier, France) as a loading control for the quantity and quality of the extracted proteins. After washing with TBST, the membranes were incubated with horseradish peroxidase (HRP)-conjugated secondary antibodies (1:3000) at room temperature for 1 h according to manufacturer's recommendations (RD systems, Rennes, France). The protein bands were detected by ECL Western Blotting Detection Reagent (GE Healthcare, Buc, France). Results were quantified using Image Lab software (Bio-Rad, Roanne, France). Bands of Pro-IL-1β and COX-2 were normalized to β-actin.
Statistical Analysis The results of ELISA and Western blot were expressed as mean ± standard error of mean (SEM) from three independent experiments (n = 3). Data were subjected to oneway analysis of variance (ANOVA), and the statistical differences between samples were compared using Dunnett's test. All statistical analyses were carried out with GraphPad Prism 9. 0. 2 (GraphPad Software, San Diego, CA, USA). A p-value of < 0. 05 was considered statistically significant.
These dipeptides are present in some proteins belonging to the proteome of S. thermophilus. According to Proteome pI database  [65] , these eight dipeptides represent 3. 7% of the 400 possible theoretical combinations that can be released from the proteome of S. thermophilus, a percentage higher than that which can be calculated assuming that each dipeptide exists with the same probability (2%). These eight dipeptides were found in numerous peptide sequences generated after tryptic shaving of the LMD-9 strain. Moreover, it has already been shown that a mixture of peptides (PepMix) exhibited greater anti-inflammatory activity than any individual peptide at the same concentration  [63]. The highlighted anti-inflammatory activity could come from peptide(s) generated from the PrtS protein and/or from the modular protein (2 :3 -cyclic nucleotide 2 -phosphodiesterase), considering the large number of different peptides obtained from these proteins, the high coverage rate of these sequences and the abundance of anti-inflammatory dipeptides cited above in these sequences.
0003-50 mg/ L. Injection volume was 1 µL and the flow was set at 0. 4 mL/min. The temperature of the column was maintained at 40 • C. The main parameters of the HRMS source were: Spray voltage (4000 V), Sheath gas (60 a. u); Auxiliary Gas (20 a. u. ), Capillary temperature and probe heater temperature (200 • C), S-lens RF level (50). A FullScan mode in the range m/z 100-400 was selected for the acquisition at a resolution of 70,000 (FWHM). The automatic gain control target was set at 3. 10 6 ions and the maximum injection time was set at 200 ms. Subsequent data analysis was performed by Xcalibur Software (version 3. 0. 63), to confirm compound identification and quantify the different analytes, using the molecular formula and exact mass of the indole compounds, both of which are available in public databases, such as PubChem and ChemSpider.
Acknowledgements The authors are very grateful to the  Spanish Government  for its financial assistance (Plan Estatal  2013-2016 ,  Ministerio de Economía y Competitividad  Project  AGL2016-77505-C3-2-R  and M. G. F predoctoral contract;  Plan Estatal 2017-2020 ,  Ministerio de Ciencia, Innovación y Universidades , Project  PID2019-108722RB-C32 ,) and  Junta de Andalucía ,  Consejería de Economía  y  Conocimiento  Project  P18-RT-3098. We acknowledge the services of  Science Institute of Vine and Wine (Bordeaux)  and  Pablo de Olavide University , and the  Bordeaux Metabolome Facility and MetaboHUB  ( ANR-11-INBS-0010 ) project.
, 2004) , which are known to provide bitterness and astringency to cocoa products  (Lesschaeve & Noble, 2005). A high concentration of these compounds can therefore mask the fine flavors of cocoa. However, these compounds do not only bring defects. Thanks to its richness in polyphenols, cocoa contributes to good mental health and cardiovascular protection  (Andújar et al. , 2012; Tuenter et al. , 2018). To study the genetic and biochemical determinants of bitterness and astringency of the Ecuadorian cocoa trees, as well as their fat and protein contents, two important factors interacting with flavors, the nonvolatile compounds contained in fermented roasted and nonroasted beans, were characterized by NIRS. Sensorial analyses on liquors were also carried out. All these data were used to conduct a genome-wide association study (GWAS) on all these traits using molecular genotyping data obtained by genotyping-by-sequencing (GBS).
Genetic analysis 1. 6. 1 Linkage disequilibrium calculation For the modern Nacional population, linkage disequilibrium (LD) calculations were performed by  Loor (2007). For the Amazonian population, the LD was calculated with Haploview v4. 2  (Barrett et al. , 2005)  following the method of  Sardos et al. (2016). The graphical representation of the LD decay was done with the R package ggplot2 following  Sardos et al. (2016).
1. 6. 2 Genome-wide association study For the modern Nacional population, we performed a GWAS with SNP markers associated with biochemical (169 accessions × 5,195 markers) and sensory (144 accessions × 5,195 markers) traits using TASSEL 219 v5. For all the traits, we used a mixed linear model (MLM) the detailed information was described in  Colonges et al. (2021a). For the Amazonian population, through GBS, ∼50,000 SNP markers were detected. Markers with missing data or with a frequency of presence of the minor allele <5% were discarded. After these different filters, 5,337 SNP markers were selected. A GWAS was performed on SNP markers associated with biochemical (202 genotypes × 5,337 markers) and sensory (159 accessions × 5337 markers) traits using the TAS-SEL v5 software. For all traits, the choice of the MLM was the most relevant.
1a , Day 4). To better characterize the different types of organoids, morphological and growth parameters were analyzed from single-cell dissociated organoid cultures (Fig. 1b-e ). The number of organoids generated from 1000 single epithelial cells seeded, was evaluated after 4 days in culture. This parameter ranged between 11. 33 ± 9. 15 to 7. 35 ± 4. 20 organoids, with no statistically differences among the different intestinal organoids (P = NS) (Fig. 1b ). Regarding growth parameters, organoids developed from single cells took more days to grow in size, compared with the culture isolated from crypts. By day 8, all organoids had increased their area several times compared with day 4 (Fig. 1c ) and their aspect resembled those of organoids derived from intestinal crypts at day 4 of culture (data not shown).
Organoids were www. nature. com/scientificreports/ incubated at 37 °C in a 5% CO 2 humidified atmosphere. For maintenance, the medium was renewed every 3 days with organoid media without inhibitors. Organoids were split every 4-7 days in a ratio of 1:2. All the assays were performed using organoids in passages 4-12, at day 4 of culture, unless otherwise specified. Organoids were imaged on days 1 and 4 of culture using a bright field of an inverted microscope Olympus IX81 (Japan) equipped with 10× objective lenses. Images were acquired with µManager software and analyzed with ImageJ software  35. Colony forming assay, morphological parameters and histological analysis. Intestinal organoids obtained from two mice were dissociated into single cells using TrypLE Express and further filtered using a 50-µm cell strainer.
Acknowledgements We thank  Gabriel Fernández  for the transgenic mouse colony management, and  Micaela Sureda  and  Irith Bergsma  for their initial contribution to this work. The authors gratefully acknowledge the  Advanced Bioimaging Unit at the Institut Pasteur de Montevideo  for their support and assistance in the present work. This project was funded by  ANII  ( PhD fellowship ,  FMV_1_2019_1_156213  and  EQL_2013_X_1_2 ) and  FOCEM (MERCOSUR Structural Convergence Fund) ,  COF 03/11. HD received a fellowship from  Sistema Nacional de Investigadores, ANII , FD received a fellowship from  Fondation Pierre Ledoux-Jeunesse Internationale (Fellowship)  and  MC, MBF  and RP are members of  SNI (National Research System, Uruguay ) and PEDECIBA.
Funding This project was funded by  ANII  ( PhD fellowship ,  FMV_1_2019_1_156213  and  EQL_2013_X_1_2 ) and  FOCEM (MERCOSUR Structural Convergence Fund) ,  COF 03/11. HD received a fellowship from  Sistema Nacional de Investigadores, ANII , FD received a fellowship from  Fondation Pierre Ledoux-Jeunesse Internationale (Fellowship)  and  MC, MBF  and RP are members of  SNI (National Research System, Uruguay ) and PEDECIBA.
, 2013)  and influences homeostatic immune activation in adult and aged mice  (Schaupp et al. , 2020; Stebegg et al. , 2020). This also includes the IFN gene expression profile in DC  (Stefan et al. , 2020). Interestingly, some bacterial taxa might harbor a particularly strong ISG inducing activity such as lactobacilli, Blautia coccidioides and the anaerobic commensal bacteria of the Bacteroides species  (Ayala, 2021; Kawashima et al. , 2018; Kawashima et al. , 2013; Stefan et al. , 2020; Yang et al. , 2021). In our dataset, Bacteroides spp. were absent from the PND11 microbiota in our metagenomic analysis and, although found only at low abundance in adult mice, could drive intestinal innate immune stimulation and type I IFN expression  (Stefan et al. , 2020). Alternatively, infections with unknown viral pathogens or subclinical reactivation of latent or endogenous viruses may contribute to tonic IFN expression.
, 2018). Unsupervised clustering was performed using a shared nearest neighbors graph with a resolution of 0. 8 and k = 15. The following parameters were used to build UMAP representations: min dist = 0. 3, max. dim = 2, seed. use = 36). To determine cluster specific markers, we implemented the FindMarkers gene function with an adjusted p value of 0. 05. Differential gene expression analysis was performed with Seurat using the Wilcoxon test. Next, we used monocle (version 2. 12. 0)  (Trapnell et al. , 2014)  in the integrated data to reconstruct cell development trajectories. For the reconstruction of cell development trajectories, we employed the 1000 most relevant genes identified by Monocle's unsupervised feature selection approach (dpFeature). The root of the trajectory was defined choosing the branch with the highest S-score, which also correlated with the expression of stemness-associated genes such as Birc5.
For the PND11 PBS vs. PND11 R848 and adult PBS vs. adult R848 scRNA-seq data set data integration was performed by anchors identification based on the results of CCA analysis. The first 20 CCs were used for the anchor identification and first 20 PCs from PCA analysis were used for UMAP representation. For clustering resolution was set to 0. 5. Raw data were deposited under GEO accession number GSE188714.
The first 10bp on each read before mapping and regions with an average score below 10 were also trimmed but undone after mapping (untrim). The host filtered reads of the metagenomic DNA were then assembled using MEGAhit  (Li et al. , 2015)  using a kmer list of  21, 27, 33, 37, 43, 55, 63, 77, 83, 99 , with a minimum multiplicity for filtering kmers of 5. PROKKA was used to predict the proteome from the assembled contigs using default options  (Seemann, 2014). The predicted proteome was functionally annotated against the KEGG database using Kofamscan  (Aramaki et al. , 2020). Host filtered reads to the iMGMC non-redundant collection of metagenome-assembled genomes (MAGs)  (Lesker et al. , 2020)  were aligned using BBsplit  (Bushnell, 2014)  with a minimum identity of 90% to produce a coverage statistics file which was converted into TPM via the makeTPMfromCovStats.
sh script from the iMGMC best-practices repository. The TPM values were used to calculate the minimal number of species that covered the maximal amount of the data based on the knee point, implemented in python using the Kneed module  (Satopa, 2011). Only MAGs with a TPM value >100 in >2 samples were retained for further analysis. A phylogenomic tree of the 153 iMGMC-derived MAGs was generated using their predicted proteomes in Phylophlan3 v3. 0. 60  (Asnicar et al. , 2020). Diversity was set as high using the 'supermatrix_aa. cfg' config file. The tree was visualized in iTOL  (Letunic and Bork, 2019). Raw data were deposited under BioProject accession number PRJNA794356.
08 % formic acid in water (B). Full MS spectra (350-1,550 m/z) were acquired on the Orbitrap at a resolution of 120,000 with an automatic gain control (AGC) target value of 3×10 6 ions. Data resulting from LC-MS/MS measurements were analyzed with the Proteome Discoverer (v. 2. 4, Thermo Fischer Scientific) using SEQUEST HT. Protein identification was performed using a self-built reference database downloaded from UniProt (reference numbers: UP000008827. fasta, UP000019116. fasta, UP000007305. fasta and the predicted proteome from the combined metagenomic assembly). Searches were conducted with the following parameters: Trypsin as enzyme specificity and two missed cleavages allowed. A peptide ion tolerance of 10 ppm and an MS/MS tolerance of 0. 05 Da. As modifications, oxidation (methionine) and carbamidomethylation (cysteine) were selected.
Peptides that scored a q-value >1% based on a decoy database and with a peptide rank of 1, were considered identified. For the differential analysis of the proteomics data the R package DeqMS 1. 8. 0 (https://doi. org/10. 1074/mcp. TIR119. 001646) was used. For each group (PND11 and adult), proteins with valid quantification in at least half of the samples (3/6) were included.
Statistical Analyses The statistical analyses were performed using the software package SPSS (IBM SPSS Version 25). Prior to one-way analysis of variance (ANOVA) based on treatment number, data were tested for normal distribution by Kolmogorov-Smirnov test (zootechnical performance) or Shapiro-Wilk test (physiological data) and variance homogeneity by Levene's test. Covariates (parity number, sow, birth weight) were included to the statistical model in only case of significant impact on single target parameters. All treatment means were compared with each other using Tukey's test (variance homogeneity) or Games-Howell test (variance heterogeneity). The statistical tests are shown in the footnotes of the respective data tables. Mean differences with a probability of P ≤ 0. 05 were accepted as statistically significant and mean differences with 0.
Statistical Analyses Statistical analyses were performed with StatView software (version 5. 0, Abacus Concepts Inc. , Berkeley, CA, USA) and SPSS Statistics software (version 25. 0). Data were analyzed using one-way and two-way ANOVA and KHI2 assay. The independence of endpoints measured in littermates was evaluated by one-way ANOVA for each parameter and treatment group to assess intra and intergroup effects. Except for body weight at PND3 and PND21 in control group, litter effect was not detected. Offspring were thus considered a valid experimental unit for the F1 impact analyses. In all analyses, the threshold of statistical significance was set at p < 0. 05.
At each timepoint, anthropometric and developmental measurements were collected. A longer follow-up period between visits in later years was chosen as motor and cognitive development changes more slowly at older ages. Data from children over 5 years were excluded from the present analysis. As most children were older than 5 years in the 2020 follow-up, only data collected up until June 2019 were used for the current analysis. From 2016 to 2017, between 6 and 11% of children were lost to follow-up at each round, mainly due to moving, especially in Phnom Penh which is a very dynamic urban area, with many households depending on labour in the garment industry. The flow chart of children included in the cohort study is described in Fig. 1. Ethical approval for the study was obtained from the Cambodia National Ethical Committee for Health Research.
The study was conducted in accordance to the Declaration of Helsinki for the protection of human subjects involved in research including confidentiality of personal information. Informed consent was obtained from all participants, with consent obtained from parents or guardians for participating children. Measurement and data sources. Sociodemographic and economic characteristics. Sociodemographic and economic characteristics (SEC) included province, age, gender, mother education (divided in four groups: 'no formal school education' , 'primary' , 'secondary' , 'high school or university') and the economic level of the household. Because of large differences in SEC between the provinces, economic level was assessed for each province separately, with an index constructed from multiple correspondence analyses of a set of SEC variables collected at baseline and comprising household assets, living conditions (ownership of computer, phone, generator, radio or TV, non-motorised vehicle, motorised vehicle, principal source of light, principal source of energy for cooking), and hygiene (principal source of water for drinking, type of latrines)  19.
To minimize subjective judgement, interviewers attended specific training sessions before each follow-up. In the present study we define child development as the ability to achieve the developmental milestones. Data management and statistical analyses. Data were collected on tablets, using a KoBo Toolbox questionnaire, by an experienced and trained team. Data were pseudonymised and stored on a KoBo Toolbox server, with a limited access to the core team of researchers only. First, quality checks were performed at data entry on the same day as data collection. Additional data cleaning and data management were then performed using Microsoft Excel 2016 (Microsoft Corporation) and R version 4. 1. 0 (The R Foundation for Statistical Computing). Statistical analyses were performed using R version 4.
Acknowledging the multiple factors that contribute to delays in motor and cognitive development as well as to stunting and wasting are essential when designing programs to improve motor and cognitive development. Supplementary longitudinal follow-ups could be useful to better describe developmental trajectories and the nature of delays, and to disambiguate between chronic disability and transient delays, enabling better defining of effective intervention programs. Promoting nutritional programs in the first 1000 days to prevent malnutrition are essential to further not only optimal growth, but also motor and cognitive development of Cambodian children.
2E ). We obtained very similar results when we treated CS with Cu 21 under aerobic conditions (Fig. 2E ; Fig. S3 ). We concluded from these results that both redox states of Cu cause a loss of protein structure and function in vitro. Identification and comparative analysis of copper-induced protein aggregates. We next asked whether proteins differ in their aggregation sensitivity following Cu 21  or Cu 1 stress. To address this issue, we conducted a comparative proteomic analysis of aggregates from lysates treated with 100 mM Cu 1 under anaerobic conditions or with 100 mM Cu 21 under aerobic conditions (Fig. 2A ). As controls, we analyzed the protein aggregates from lysates incubated for 30 min at 30 or 45°C. To identify and quantify changes in protein abundance in the different samples, we applied label-free quantification (LFQ) using the MaxQuant software  (25).