dataesr/scientific-paragraphs-categorization huggingface dataset:
6B ). The taxonomic analyses of the three DNBS-challenged groups were performed by applying multivariate analysis (PLS-DA) to the log ratios of genus-level abundance between D13 and D23 (Fig. 6C ). Eighteen variables were used to discriminate among the three groups; the clearest separation was between the CNCM I-3690-treated group and the ΔspaF-treated group. Interestingly, the ΔspaF-treated group had relatively less Streptococcus species and relatively more Desulfovibrio species compared to the two other groups (Fig. 6C ). All the sequence data have been submitted to an ENA (European Nucleotide Archive) database, accession number: PRJEB22185.
Here, we determined that dysfunctional permeability was occurring at the colon and ileum levels and that CNCM I-3690 can also protect and/or restore. OTU data were examined using a principal coordinate analysis of weighted and unweighted UniFrac distances, and group effects were evaluated at each time point using a permutational ANOVA (adonis function in R). Post-hoc tests used Bonferroni corrections (C). Data were also analyzed at the genus level. They were filtered (retained if more than 60% non-zeros in at least one group and mean above 0. 01% in at least one group). A PLS-DA was performed on the log ratios of abundance between D23 and D13 to discriminate among the three groups (two components). Individual plots with 95% confidence ellipses and a correlation plot are presented. Log ratios are plotted for the genera Streptococcus and Desulfovibrio.
Identifying adhesins used by L. rhamnosus CNCM I-3690. A total of 105 bacterial genomes, including those of 23 Lactobacillus species, were examined (Table  S3 ). Predicted nucleotide and protein sequences were obtained from the National Center for Biotechnology Information (NCBI; http://www. ncbi. nlm. nih. gov/) and a local MicroScope database hosted by Genoscope (https://www. genoscope. cns. fr/). We compiled a non-exhaustive list of 63 proteins involved in adhesion: 12 pilins, 2 fimbrial adhesins (FAs), 11 fibronectin-binding proteins (FBPs), 10 choline-binding proteins (CBPs), and 28 mucus-binding proteins (MBPs) (Fig. 1 ). They were identified and analyzed using CLC DNA Workbench software (CLC bio, Denmark) for BLASTP analysis (default parameters)  74. To eliminate proteins with partial domain matches, we used a 75% sequence identity threshold and required coverage of at least 75% of the query sequence length.
The slides were mounted using fluorescent mounting medium (Dako, Agilent Technologies). Tissues were visualized using a high-capacity digital slide scanner (3DHISTECH Ltd. ) and Pannoramic Viewer and CaseViewer software (3DHISTECH Ltd. ) In vivo gut permeability assay. At the end of the probiotic experiment, permeability was determined in vivo using fluorescein-conjugated dextran (FD4 [3000-5000 Da], Sigma-Aldrich) as a tracer as previously described  78. Paracellular pathway permeability was measured using the flow of FD4 through colon and ileum samples, which were opened along the mesenteric border and mounted in Ussing chambers (P2300, Physiologic Instruments, USA). At 37 °C, 0. 2 cm2 of tissue surface was exposed to 2. 5 ml of 10 mM oxygenated Krebs-glucose and 10 mM Krebs-mannitol (serosal and luminal sides, respectively).
Colonic transcriptome analysis. Total RNA was isolated from colon samples (20-30 mg) using the RNeasy Mini Kit (Qiagen)  22. RNA quantity was determined using a NanoDrop spectrophotometer, and RNA integrity was confirmed with an Agilent 2100 Bioanalyzer. The microarray analyses were carried out at the aBridge experimental facility (INRA, Jouy en Josas). We used a complete dye-swap reference design with five biological replicates, and we employed six SurePrint G3 8 × 60 K v2 microarrays (Agilent Technologies, France). Raw data were extracted from the microarray images using Agilent's Feature Extraction software and preprocessed using the R package agilp downloaded from Bioconductor (http://www. bioconductor. org). More than 40% of the samples had undetected probes and were thus excluded from the analyses.
All procedures were performed in accordance with the manufacturers' instructions. Analyses of lymphocyte populations. We obtained mononuclear cells via the gentle extrusion of tissue from the spleen and the mesenteric lymph nodes (MLNs); the cells were analyzed using flow cytometry (Accuri, BD) and CFlow Sampler software (BD Biosciences) as described previously  37. Briefly, 1 × 10 6 -10 7 cells were labeled with anti-CD3 FITC, anti-CD4 PerCP, anti-T-bet APC, and anti-GATA3-PE (all from eBioscience). We performed stimulation experiments in which 2 × 10 5 cells per well were stimulated with anti-CD3/CD28 antibodies (eBioscience, San Diego, USA) as described previously  37. We determined supernatant cytokine concentrations using a cytometric bead array system (Mouse Th1/Th2/Th17/Th22 13-Plex FlowCytomix Multiplex; eBioscience) in accordance with the manufacturer's instructions.
Intestinal microbiota sequencing and analysis. A total of 96 fresh fecal samples were collected from all four groups in the probiotic experiment at three time points (D0, D13, and D23; Fig. S1A ) and stored at -80 °C. DNA was then obtained via mechanical lysis (Fastprep ® FP120 [ThermoSavant]) and phenol/chloroform-based extraction as described previously  80. Amplification was performed using the V3-V4 primers for 16 s rRNA (forward: CCTACGGGNGGCWGCAG, reverse: GACTACHVGGGTATCTAATCC)  81. The samples were loaded into flow cells in an Illumina MiSeq. 300PE Sequencing Platform in accordance with the manufacturer's instructions. Analyses were performed using QIIME (v. 19). After filtering for quality, a mean of 85,073 ± 24,497 sequences per sample were retained. Reads were clustered into operational taxonomic units (OTUs; 97% identity threshold) using VSEARCH, and representative sequences for each OTU were aligned and taxonomically assigned using the SILVA database (v.
119). To characterize diversity, rarefaction was used to obtain 30,000 sequences per sample. Alpha diversity (within samples) was represented using total species richness (Chao1 estimator) and evenness (Shannon index). Beta diversity (between samples) was represented using UniFrac distances calculated from OTU counts. Statistical analyses were performed using SAS 9. 3 and R 3. 3. 0 (vegan and mixOmics packages  82, 83  ).
Acknowledgements R. M. has a postdoctoral contract in the framework of a collaborative project with Danone Research ( 2014-2017 ). N. M. H. was a postdoctoral fellow of the European EraNet  PathoGenomics  project ( 2010-2014 ). We thank the histology facility and aBridge platform of  UMR 1313  GABI and the MIMA2 platform for access to the virtual slide scanner (Pannoramic SCAN,  3DHISTECH ). Authors would like to thank  M. L. Michel ,  S. LeGuin ,  J. Estellé ,  J. M. Natividad ,  S. Ho ,  R. Brazeilles ,  M. Boyer  and all UEAR personal for their help and fruitful discussions. The datasets generated and analyzed during the current study are available in the GEO and ENA repositories.
Care-as-usual (CAU) All participants in this study will continue to receive their routine antenatal and postnatal care. Generally, this involves care from hospital and community-based healthcare specialists, such as midwives, obstetricians and health visitors. The exact care received by each participant will depend on their individual additional health and social care needs and may also engage services from other sources including social work services and voluntary agencies. All care received will be in line with local authority and Government policy and guidelines  [19, [26] [27] [28] [29] [30]. The specific services accessed by each participant as part of their CAU will be captured in service use diaries. Participants randomised to the CAU arm of the trial will not be offered either intervention (ETPB or MB) in THRIVE on completion of data collection.
In these situations, the research team will seek to record the reason for non-attendance. For MB, participants who do not attend either of the first two group sessions will not be invited to subsequent sessions, but will still be eligible for follow-up data collection. For ETPB, participants will be invited to all antenatal group sessions regardless of attendance at previous sessions. THRIVE group facilitators will be independent of the trial, have a variety of health and social care professional backgrounds, and be employed by NHS GGC and NHS A&A. In order to avoid contamination between intervention arms in the trial group, facilitators will be randomly allocated to deliver only one intervention, the only exception being those with prior knowledge of an intervention -in this instance they will be allocated to deliver that intervention.
During the follow-up visit permission will be sought to video-record mother and child interactions around one episode of play and one episode of care, such as feeding or nappy changing. MIIQ will be rated by two research assistants at The University of Manchester (UoM) who will be blinded to the trial arm allocation ensuring single-blind evidence of the effectiveness of the interventions on MIIQ. MIIQ will be measured using both the CARE Index Dyadic Synchrony Score (primary endpoint)  [41]  and the Mellow Parenting Observation System (MPOS)  [52]. As part of this process inter-rater reliability will be established. As the target population of this study is traditionally seen as "hard to reach", a number of strategies will be undertaken in order to obtain follow-up data from as many participants as possible, including the offer of £15 vouchers for completed follow-up questionnaires, contact by phone, email and text to arrange follow-up data collection appointments, confirmation of current contact details with the NHS Clinical Research Facility and sending out congratulations cards at birth with a reminder to inform research staff of changes in contact details.
Economic Evaluation The economic evaluation will assess the implementation costs, resource use and outcomes associated with each intervention and CAU from the NHS and Personal Social Services (PSS) perspective favoured by the National Institute for Health and Care Excellence (NICE). A broader societal perspective will also be adopted to allow for the possibility of costs and outcomes arising beyond the NHS and PSS, such as housing, education, employment and justice. To facilitate measurement of data on resource use, all participants will be asked to keep a service use diary recording attendance at NHS, social care, local authority and voluntary organisations for both mother and child. The diary will be used as an aide memoir to collect mother and child data between baseline and follow up, and will be used to measure additional and unintentional cost burden/savings associated with the intervention.
Participants will additionally be asked to complete a health and social care resource-use questionnaire at follow up based on the same information as the diary. Up-to-date unit costs will be attached to quantities of resource use to generate mean costs per study participant. The incremental costs and benefits of the treatment arms compared with CAU will be reported within an incremental cost-effectiveness ratio (ICER) if appropriate. The inclusion of the EQ-5D generic outcome measure  [35]  will also allow the estimation of quality-adjusted life years (QALYs) facilitating cost-utility analysis, the preferred evaluative technique of NICE. Sensitivity analysis will be carried out on the perspective adopted and the key cost-drivers and outcomes. As per recent economic evaluation guidance, missing data will be predicted as a function of relevant baseline covariates  [53].
1  and a schedule of study activities is shown in a SPIRIT diagram (Fig. 2 ). A Standard protocol items: recommendation for interventional trials (SPIRIT) checklist indicating where standard protocol items for randomised controlled trials are located within this protocol is included in Additional file 4. Planned longer-term follow up using routine data (still to be funded) Longer-term outcomes will be assessed by linking the short-term outcomes identified in the study to longerterm impacts on health and wellbeing for both mother and child via factors identified from the literature. This trial aspect will rely on linking published associative data and any short-term primary outcomes in the trial with long-term costs and benefits in health and education, and other effects such as the effect on employment.
Routine data, such as the Strengths and Difficulties Questionnaire,  [56]  collected by health and social care professionals when the child is around 30 months old, will facilitate the measurement of longer-term outcomes including social and emotional wellbeing, language development, educational attainment, incidences of maltreatment or neglect and placement of children onto the "risk register"/into child protection services. Future linkage will also assess the costs of health, social care and broader education and employment impacts. In addition, it will provide important information in terms of health status and the use of services across the study groups. All data linkage will be initiated by the Robertson Centre for Biostatistics, which is a registered Clinical Trials Unit (CTU), using the NHS GGC's Safe Haven that has been developed to support secondary research use of clinical data.
Randomisation Participants will be allocated a unique identification (ID) number by the research team on entry to the study. This ID number will be used to anonymise completed baseline questionnaires, which will be delivered to the CTU for data entry. The CTU will block-randomise participants to the three trial arms using a computer-generated sequence, stratified by parity (number of children), severity of psychiatric symptoms (measured by the BSI, 53) and history of substance dependency, which will be determined based Fig. 1  Timeline of participant activities. HADS+1, Hospital Anxiety and Depression Scale enhanced by the outwardly-directed irritability questions adopted from the Adult Wellbeing Scale; EQ-5D, EuroQol 5 Dimensions -a standardised instrument used as a generic measure of health; SNiPs, Special needs in pregnancy; CAU, care as usual; ETPB, Enhanced Triple P for Baby; MB, Mellow Bumps on baseline questionnaire responses.
Storage and anonymisation of confidential data All data collected will be stored securely, in accordance with the UoG Best Research Practice Guidelines, and managed in accordance with the Data Protection Act 1998 and the General Data Protection Regulation (from May 2018), in either locked filing cabinets or passwordprotected databases. Data will be accessible only by of the UoG research team and their research partners at GCU, UoM and the Universities of Aberdeen and Newcastle. All of the data collected will be kept separate from any individual participant identifiers and secure. Participants will be given their own unique ID number in order to link their data throughout the trial. All quantitative data collected as part of the study will be securely transferred to the Robertson Centre for Biostatistics CTU for data entry and cleaning.
Qualitative interview data and recordings of intervention delivery sessions will be transcribed by an external (security checked) transcription agency, and securely stored by researchers based at the UoG and GCU. Video-recordings of mother-infant interactions will be transferred to the UoM using a secure Internet platform designed and maintained by the Robertson Centre for Biostatistics for observer-rated coding using the CARE Index and the MPOS. The one exception to this rule is to allow the secure transfer of a small number of anonymous video-recordings to Mellow Parenting for rater quality-control checks. In all cases data sharing and confidentiality agreements will be line with the UoG regulations. Permission will be sought from participants for archiving purposes during trial consent, and the trial consent form will notify participants that their data and their child's data will be made available to the funders in anonymised form.
The sensitivity of the primary outcome analysis to missing values will be explored using multiple imputation, generating 10 imputed data sets, using all available data to predict missing values. Analyses will be conducted for the intention-to-treat population, consisting of all participants who have been randomised to the trial. In addition, analyses will also be undertaken for the per-protocol/on-treatment population. For the economic analysis the incremental costs and benefits in each treatment arm will be reported within an incremental cost-effectiveness ratio (ICER) if appropriate. Within-trial analysis of costs and effects will be undertaken in STATA (StataCorp, TX, USA), adhering to good practice for economic evaluations alongside clinical trials  [58, 59]. Missing data will be explored by employing multiple imputation methods using alternative configurations of baseline covariates  [53, 60].
Monitoring Data Monitoring Committee (DMC) The DMC, chaired by Professor John Norrie (j. norrie@ed. ac. uk), will meet regularly (as required) to assess trial progress based on independent trial data (e. g. , actual recruitment to trial against projected trial recruitment), provided by the Robertson Centre for Biostatistics CTU and will be given the power to stop the trial should the committee see fit. If analysis of follow-up data shows maternal psychological distress significantly worsens after participation in either intervention, we shall seek guidance from the Trial Steering Committee (TSC) and DMC about how to respond, as by that time all of the participants allocated to the ETPB and MB arms will have already received an intervention.
a) Withdrawal from the interventions or trial Participants may choose to withdraw from the intervention group or the trial at any point. Participants will be asked a reason for withdrawal, but will not be required to respond. Participants who withdraw from the intervention but not the trial will still be eligible for follow-up data collection. Any women that report experiencing harm from attending the group will be given the support discussed previously and advised by the research team to stop attending the groups. Participants may also be advised by their health or social care practitioner to stop attending groups or withdraw from the trial, based on ongoing health or social care needs. Any participant found to be inflicting harm on another participant or group facilitator will be asked to leave the group sessions and will be withdrawn from further data collection.
Acknowledgements Members of the  THRIVE Research Team  who contributed to refinements and enhancements to the THRIVE funded Detailed Project Description, and helped to write and refine this paper are:  Dr Catherine Nixon  1 , Catherine. Nixon@glasgow. ac. uk, senior investigator scientist  Shona Shinwell  1 ,  Shona. Shinwell @glasgow. ac. uk, senior investigator scientist Dr Jane White 1 , Jane. White@glasgow. ac. uk, project manager (2013-2014) Karen Crawford 1 , Karen. Crawford@glasgow. ac. uk, project manager ( 2015-2017 )  Dr Rosaleen O'Brien 3  ,  Rosaleen. OBrien @gcu. ac. uk, research associate Caoimhe Clarke 1 , Caoimhe. Clarke@glasgow. ac. uk, investigator scientist ( 2014-2014 )  Dr Kathleen Boyd 4 , Kathleen. Boyd@glasgow. ac. uk, health economist Dr Alice MacLachlan 1 , Alice.
AW, a Senior Lecturer in Clinical Psychology and a clinical psychologist, has experience in perinatal clinical psychology and maternal mental health and will manage the coding of mother-infant interaction in the trial. KB, in conjunction with DW, is the strategic lead on the process evaluation. KB and DW have extensive experience of conducting process evaluations of complex social interventions. EM is an experienced health economist, having led on the economic evaluation of the UK trial of The Oxfordshire Home Visiting Study  [17, 18]  and will lead the economic evaluation element of THRIVE. AM will manage randomisation, the database and processing, statistical analysis and reporting. As the THRIVE lead statistician AM will also hold an active role on the Data Monitoring Committee. PW conducted a pilot study of MB in NHS A&A and NHS GGC, which provided significant information contributing to the design of THRIVE  [25].
Not applicable Ethics approval and consent to participate Ethical consent has been granted by NHS West of Scotland Research Ethics Committee (13/WS/0163, 21 August 2013). Informed written consent will be obtained from all participants. Participants may withdraw from the study at any point without giving a reason; however, we will record and monitor any reasons that are given. Participants will be consented to the trial by research staff prior to all data collection and we will seek permission to link to their routine data and the data on their unborn child up to the child's 16th birthday.
The genomes of 46 environmental and eight clinical strains were screened for known genetic antimicrobial resistance traits in CARD and ResFinder databases. In general, antimicrobial susceptibility of the investigated V. cholerae population was high. The environmental strains were susceptible against most of the 16 tested antibiotics, except sulfonamides (97. 5% resistant strains), streptomycin (39% resistant) and ampicillin (20. 7% resistant). Clinical isolates partly showed additional resistance to amoxicillin-clavulanic acid. Genome analysis showed that crp, a regulator of multidrug efflux genes, and the bicyclomycin/multidrug efflux system of V. cholerae were present in all isolates. Nine isolates additionally carried variants of bla CARB-7 and bla CARB-9 , determinants of beta-lactam resistance and six isolates carried catB9, a determinant of phenicol resistance.
All isolates were paired-end sequenced using MiSeq Reagent Kit v3 with a read length of 2 × 300 base pairs on a MiSeq instrument (Illumina, CA, United States). Velvet version 1. 1. 04 (Zerbino and Birney, 2008)  was used for de novo assembly of raw reads and further WGS data interpretation was carried out in the analysis software SeqSphere + (Ridom, Münster, Germany). The presence of antibiotic resistance genes was assessed with the Comprehensive Antibiotic Resistance Database (CARD)  (Jia et al. , 2017)  using default settings including "Perfect" and "Strict" hits only. In addition, the ResFinder database was used with default settings. Allele libraries for aminoglycosides (167 targets), macrolides (132 targets) and sulfonamides (49 targets) resistance were downloaded from the ResFinder database (11/2017) available from the Center for Genomic Epidemiology 1  and integrated in the SeqSphere + analysis software.
Clinical Isolates Overall, antibiotic resistance profiles were very similar in human and environmental isolates. Resistances against sulfonamides, streptomycin and ampicillin were the most frequently detected (Figure  1 ). The main difference observed was the occurrence of amoxicillin/clavulanic acid resistance in three clinical isolates. Three out of the nine isolates were multidrug resistant. None was pan-susceptible. 2 https://www. ncbi. nlm. nih. gov/bioproject/PRJNA551929/ The full detailed list of all isolates tested and the results of each phenotypic antimicrobial resistance test can be found in the Supplementary Table  S4.