dataesr/scientific-paragraphs-categorization huggingface dataset:
This study sheds new light not only on fetal sensory abilities but also on the specificity of facial responses to different flavors relating to their discriminative abilities. The present study coded 4D ultrasound scans with the validated Fetal Observable Movement System  (Reissland et al. , 2016)  to examine how fetuses from 32 to 36 weeks of gestational age react to different flavors transferred to the fetal environment by maternal ingestion. We compared the FMs obtained from scans from three groups of fetuses exposed to either carrot flavor, kale flavor, or no flavor. Although there is no chemical evidence on the stability of compounds of kale or carrot until they reach the amniotic fluid, multiple data exist on the mother-to-fetus transfer of vegetable aromas (for a review, see  Spahn et al.
Participants One hundred mothers between the ages of 18 and 40 years (M = 29. 92 years, SD = 5. 03) with healthy, singleton fetuses were enrolled in this study. We chose a target sample size of 100 before recruitment to obtain 85% power ( f =. 25) for the main comparison, that is, fetal FMs depending on the flavor exposure. Given that a recent study  (Reissland et al. , 2020)  reported a large and significant effect size in fetal movements at 32 weeks, medium and even large effect sizes are not unusual in this type of research. We opted to stop collecting data in the study when we reached a predetermined number of participants. Although we were able to recruit 100 women, we could not include all scans in the study for a variety of reasons. Some women were unable to attend their 36-week scans because of COVID-19 pandemic restrictions (n = 11) or because they had given birth before their 36-week scans were to take place (n = 3).
In addition to the factors mentioned above, not all scans were of good enough quality to be coded and analyzed (see Table  1 ). All participants were White British, living in the northeast of England. Experimental group participants (carrot: n = 35, kale: n = 34) were recruited in a private ultrasound clinic in Newcastle, UK. For the control group (n = 30), 4D ultrasound scans of healthy fetuses were obtained from anonymized archived data in the Fetal and Neonatal Research Lab at Durham University. All mothers had a healthy 20-week anomaly scan including the evaluation of a normal amount of amniotic fluid. They had no known allergies or mental health and/or medical conditions, had a prepregnancy body mass index (BMI) of 18. 5 to 30 (M = 25. 87, SE =. 30), and were nonsmoking. All control group mothers fulfilled the same inclusion criteria as the experimental groups.
Third, using Pearson correlations, we tested whether dependent variables were correlated with maternal mental health variables (stress, anxiety, and depression) and level of education. For missing data in the maternal and fetal independent variables, series' mean estimations were used. Additionally, an independent-samples t test was conducted to assess whether there were differences between the experimental groups in terms of the frequency of maternal vegetable consumption as assessed by questionnaire and waiting time after the mother's flavor ingestion. Covariates that significantly correlated with the dependent variables were included in further analyses. A multivariate analysis of covariance (MANCOVA) and a series of post hoc analyses, using the Scheffé criterion for significance, tested the impact of the type of flavor stimuli (between groups) on the frequency of discrete FMs and on facial gestalts to interpret fetal reactions to flavors.
Acknowledgements We are thankful to  Houyem Rabah , who kindly supplied a photography of an Emmental cheese. We are also thankful to the financial support from  INRAE (Rennes, France)  and  Institut Agro (Rennes, France). VRR was supported by the  International Cooperation Program CAPES/COFECUB  at the  Federal University of Minas Gerais  funded by  CAPES -the Brazilian Federal Agency for the Support and Evaluation of Graduate Education of the Brazilian Ministry of Education  (number  99999. 000058/2017-2103 ).
MATERIALS AND METHODS Bacterial strains and growth conditions. A total of 354 human and animal gut Bacteroidetes were included in this study. A complete list is provided in Table  S1b , along with species designation based on 16S rRNA gene sequencing and associated metadata. Abigail Salyers (University of Illinois, Urbana-Champagne) kindly provided many of the strains, and 2 large portions of this collection were isolated over several decades, as follows: 99 strains with "WH" designations were collected from fecal samples of healthy human volunteers as part of the Woods Hole Summer Course on Microbial Diversity in the late 1990s, and 95 additional strains with "VPI" designations were collected from human samples at the Virginia Polytechnic Institute in the 1960s to 1970s. Species classifications were made based on alignment of a minimum of 734 bp of 16S rRNA gene sequence to a database containing the type strains of.
All RNA-seq data are available publicly from the National Institutes of Health Gene Expression Omnibus Database under accession numbers GSM4714867 to GSM4714890. Core gene determination and detection of LGT events between B. ovatus and B. xylanisolvens strains. The core gene alignment was generated with cognac (50). The alignment was then partitioned into the individual component genes, and approximate maximum likelihood gene trees were generated with FastTree  (51). Cophylogenetic distances were calculated with ape  (52). A distance threshold of greater than 0. 1 to the same species and less than 0. 1 to the opposite species was used to identify alleles bearing signatures of HGT. All analyses were performed in R (version 3. 6. 3) (53). All code developed for this project are available online at https://github.
ACKNOWLEDGMENTS This work is dedicated to the memory of  Cherie Ziemer. We thank  Thomas Schmidt  ( University of Michigan ) for helpful advice on developing the phenotype clustering score. We thank  Abigail Salyers  ( University of Illinois, Urbana-Champagne ) who kindly provided a large portion of the strains used in this work. Additional support with strain culture and resources was provided by  Nadja Shoemaker  ( University of Illinois, Urbana-Champagne ),  Emma Allen-Vercoe  ( University of Guelph ),  Laurie Comstock  ( Harvard University ),  Jin-Woo Bae  ( Kyung-Hee University, South.
, 2018)  and the CEHS (Children's Environmental Health Study)  (Furlong et al. , 2014). In the CHAMACOS cohort, which included 601 pregnant women between 1999 and 2000 in California, higher prenatal urine OP metabolite levels were associated with more ASD-related traits in 14-year-old adolescents using the "Social Responsiveness Scale" (SRS 2). When exposure to OP pesticides was assessed by residential proximity to agricultural OP use, however, this link did not appear. The case-control study by von  Ehrenstein et al. (2019) , conducted in California, is one of the largest epidemiologic studies on the subject  (2961 ( ASD cases and 35,370 controls, with children born between 1998 ( and 2010)). ASD cases were selected from an administrative database, in which the diagnosis of autism was reported (according to DSM-IV).
OP exposure was assessed by residential proximity to agricultural use of pesticides (home address of pregnant woman and the California State Mandated Pesticide Use Reporting program for agricultural use of pesticides) and focused on 11 pesticides. It reported a higher risk of ASD for 6 pesticides including 3 OPs: chlorpyrifos, diazinon, and malathion. In the Childhood Autism Risks from Genetics and Environment (CHARGE) case-control study,  Shelton et al. (2014)  also reported that the risk of ASD was associated with residential proximity during pregnancy to agricultural use of OPs (970 women included since 2003 in California). Cases were identified from administrative databases of the area completed with additional instruments (Autism Diagnostic Interview-Revised, Autism Diagnostic Observation Schedule).
Several follow-up questionnaires were sent at different ages to collect further information on these families' lifestyles and their children's health and development. The adults participating in this study provided their written informed consent. The Advisory Committee on Information Processing in Health Research (CCTIRS; 2015) and the French National Commission for Information  Technology and Civil Liberties (CNIL; 2002; 2015)  both approved this study. For the present follow-up of the cohort, we provided a written information specifically adapted to the 11-year-old children, explaining the objective of the cohort and the data protection rule, and we encouraged parents to discuss with them about their choice to participate or not.
The laboratory detection limits and molar masses for each molecule are provided in Table  1. The molar masses (g/mol) used were taken from the Toxnet database. The urinary mass concentrations were all converted to molar concentrations to sum the dialkylphosphate metabolites: the sum of dimethylphosphate metabolites (DM: DMP + DMTP + DMDTP), the sum of diethylphosphate metabolites (DE: DEP + DETP + DEDTP) and the overall sum of dialkylphosphate metabolites (DAP: DE + DM). In the rest of our work, the dialkylphosphate metabolites are always used as a sum, to be comparable with the literature  (Bouchard et al. , 2011; Furlong et al. , 2014; Millenson et al. , 2017; van den Dries et al. , 2019).
Exposure data Both the heterogeneous conditions of urine sampling and the analyses in 3 separate chronological series may have influenced the metabolite concentrations. Urinary concentrations of DAP, DM, DE, and diazinon were standardized by a previously published method based on regression residuals  (Binter et al. , 2020; Mortamais et al. , 2012). We used an adjusted censored regression model to take multiple censored data into account to estimate the influence of sampling conditions: day of urine collection, duration of storage before freezing, duration of freezing before analysis, and urinary creatinine  (Austin et al. , 2000; Lubin et al. , 2004). The year and the season of urine sampling were also included in the models, to avoid needing to correct for them, given that they influence the real exposure.
For the DAP and DM sums, more than 70% of the values were above the LOD. Values below the LOD were considered left-censored data and were imputed by using a log-normal distribution  (Jin et al. , 2011). The parameter estimates (means and standard deviations) of the log-normal distribution were calculated from the concentration's distribution in the 2007-2008 measurement series, as it included the largest number of uncensored values. This log-normal distribution was then used to make imputations in each series. The DAP and DM sums were then used in tertiles and as continuous values. For metabolites detected or quantified in 30-70% of the urine samples, i. e. , DE and diazinon, the values were used in 3 classes after standardization: Table  1  List of organophosphate insecticides and their metabolites screened in maternal urine samples, with their limit of quantification (LOQ) or detection (LOD) and molar mass.
Complementary and sensitivity analyses We conducted an additional analysis stratified by gender. The effect of the weighted CAST score was controlled by an analysis limited to the questionnaires without missing data. A second sensitivity analysis excluded the children in our dataset at higher risk of neurodevelopmental disorders, specifically, children born preterm, those with fetal growth restriction, and those with a 5-min Apgar score ≤7. The analyses were performed with R software (version 3. 6. 3). The NADA and survival packages were used for the variables with leftcensored data and their analyses, and the MASS package was used for the negative binomial regression.
Acknowledgments We are grateful to the gynecologists, obstetricians, ultrasonographers, midwives, pediatricians, and all the families who participated and continue to participate in the study. We also particularly thank  Sylvaine Cordier ,  Ronan Garlantézec ,  Nathalie Costet ,  Anne-Claire Binter , and  Véronique Villalon  who contributed to the PELAGIE cohort, and  Gina Muckle ,  Claire Philippat , and  Dave Saint-Amour  for their specific expertise in neuropsychological assessment of children.
Study Population and Design ATLAS is a multicenter, longitudinal, observational, cohort study designed to characterize HM and its association with maternal and infant parameters  (14). Enrollment was performed at multiple sites in 7 European countries, including Spain, France, Italy, Norway, Portugal, Romania, and Sweden. The total duration of participation was 4 months after infant birth. HM collection was standardized across the sites, and timing of collection was fixed at 1100h ± 2 h. Trained and certified research nurses and assistants collected all data from the years 2012-2014. All data captured were directly entered into a secured web-based database (Medidata Rave edc 5. 6. 4). Participant inclusion and exclusion criteria are shown in Table  1. The procedures followed were according to the ethical standards of the respective local ethical committees in each country.
Non-negative Tensor Factorization Non-negative tensor factorization is a non-supervised approach dedicated to the analysis of longitudinal datasets  (19). Specifically, NTF estimates several factors along the three dimensions of the data space: participant × visit × HM component. Each NTF factor represents a particular trend (e. g. , increase/decrease). Participant and parameter loadings along each NTF factor reflect the level of similarity for a given participant and parameter with one trend or another. NTF factor loadings are subsequently used to build bi-clusters of participants and milk parameters sharing similar trends. To guide the NTF analysis for greater focus on the mode of delivery, pre-selected nutrients were included. Repeated ANOVA with the delivery mode as a main effect on 62 milk nutrients (log-transformed), using JMP version 14.
2 (SAS Institute), was conducted to pre-select those nutrients. Participants with missing time points or data were excluded in the repeated ANOVA. In this way, only nutrients were analyzed by NTF that showed some degree of association with the mode of delivery. NTF results are presented as heatmaps (Figures  1, 2 ), with rows corresponding to mothers and  columns corresponding to human milk components. We found that the top rows grouped mothers with a high proportion of C-section deliveries (later referred to as high C-section density), while the bottom rows had a lower proportion of C-section deliveries (later referred to as low C-section density). Therefore, we searched for a cutoff row to divide the subjects into high and low C-section density groups. To do this, we first assigned all subjects to the high-density group, minus the 20 subjects at the bottom who were assigned to the lowdensity group.
RESULTS A total of 370 participants from 7 European countries including Spain (1 center), France (3 centers), Italy (1 center), Norway (1 center), Portugal (3 centers), Romania (2 centers), and Sweden (2 centers) were enrolled for this study and included in the dataset. Participants were counted as pairs of mothers and infants. The current analysis was performed on 317 participants (pairs) after removal of pairs who did not satisfy the inclusion-exclusion criteria, pairs with twins, and with incomplete information on HM composition (Figure  3 ). Two hundred thirty-seven mothers delivered vaginally, whereas 80 had a C-section. Mothers' height was significantly lower in the C-section group (Table  2 ). France and Portugal represented the biggest groups with 88 and 100 mothers, respectively. Vaginal birth was the main mode of delivery for all countries, except Romania, where 34 vs.
Also, data regarding maternal diet and antibiotic use were not collected, while both are known to influence the nutrient composition of HM. Further, the reasons why some of the differences occur at specific time points remain unknown. Our study did not differentiate between elective and emergency C-section, which has been shown to have an impact on HM nutrients. Lastly, these preliminary analyses need validation in other larger cohorts. In summary, our results indicate that using unadjusted analyses, the mode of delivery impacts the HM nutrient composition. HM of mothers who delivered vaginally showed significantly higher levels of n-3 PUFA (anti-inflammatory effects), stearic and palmitoleic acids, and MUFA, whereas HM from mothers undergoing C-section exhibited high levels of n-6 PUFA, as well as higher ARA/DHA and n-6/n-3 ratios (pro-inflammatory effects).
They were then examined with a fluorescence microscope (Eclipse E400, Nikon Instruments France, Champigny-Sur-Marne, France) attached to a digital camera (Digital Still DXM 1200, Nikon Instruments France). The whole section of the tissue was scanned using digital slide scanner (Nanozoomer 2. 0-RS, Hamamatsu Photonics France SARL, Massy, France). Recorded files were analysed using the software ImageJ (https:// rsb. info. nih. gov/ij/) for automatic determination of the number of ghrelin-labelled cells per area of mucosa. qPCR qPCR on antral tissue and hypothalamus was performed as already described  (Menneson et al. , 2019; Arnaud et al. , 2020). For hypothalamus, 100 mg of homogenate of the whole hypothalamus was used for RNA extraction. Primers used are described in Table  2. For each gene in the antrum, transcript level was normalized to the geometric mean transcript level of 2 reference genes (b2m, coding beta2 microglobulin protein and rplp, coding ribosomal protein, lateral stalk subunit P1).
, 2013). Getting data in pigs is therefore valuable as a proxy of the human situation. An increase in ghsr mRNA level was observed between the neonatal piglets and adult pigs. We have to acknowledge that adult pigs were sampled after an overnight fast while piglets were fasted only 1 h. Whether gshr mRNA level is sensitive to the length of the fasting period remains to be evaluated. During the neonatal period, no variation of gshr expression was observed. However, we did not evaluate ghrelin sensitivity in our piglet model, either through eating behavior tests or neuronal response (neuronal firing, activation of intra-cellular signaling, etc. ) to ghrelin exogenous injection. This was beyond the scope of the study but such studies would be important to evaluate the actual role of ghrelin as eating behavior regulator and/or as hypothalamic neuronal development player as demonstrated in mice  (Steculorum et al.
Mapping First, we collect GPS coordinates and socio-economic data. The GPS coordinates list all the households and all the water sources in the village. The socio-economic data are gathered through household surveys that are performed in the village before the installation of the new drinking water source. It includes: • the number of inhabitants per household; • the daily water consumption per household for drinking, cooking, personal hygiene and laundering; • the water source used by each household for each season; • attributes which influence the water source choice (e. g. perceived water quality at existing sources, see below for more detail). A random sample of households in the village is selected to be surveyed. In this article, we assume that the households which are not surveyed fetch water from the same source and have the same characteristics (number of inhabitants, water consumption and attributes which influence the water source choice), as the closest surveyed household  (Meunier, 2019).
Thus, we compute the regression coefficients of Eq. (  2 ) for both seasons. We summarize in Table  1  the regression coefficients, their corresponding p-values and the R 2 for both seasons obtained with the Matlab 'fitlm' function  (MATLAB, 2021a). Results indicate that both predictors have a high statistical significance. In addition, the encountered low R 2 is not uncommon for water source choice studies  (Mu et al. , 1990). To obtain a yearly map, we add the results for the dry and the wet seasons respectively weighted by 7 12 and 5 12.
Results With the data collected in Gogma and Eq. (  2 ), we use the geographic information system software Matlab Mapping Toolbox (MATLAB, 2021b) to plot the four maps described in Section 2. 2. They are shown in Fig. 4:  • Map 1, spatial distribution of the households and the water sources (Fig. 4a ): One road passes through the village. In the east, there are two large groups of households. The first one is near two drinking water sources. The second one is far from drinking water sources. In the northwest, there are two small groups of households which are close to drinking water sources. For Gogma, we chose a grid resolution of 150 m × 150 m as it corresponds to the area explored by a single geophysical tests  (Meunier, 2019). This resolution can of course be adapted to the needs of the considered case study.
Acknowledgments We thank the 280 contributors of the  Turning Sun Into Water  project, the associations Eau Fil du Soleil and Respublica that allowed financing the photovoltaic water pumping system of  Gogma  and the data collection in 2019. We would like to thank the anonymous reviewers for their comments which allowed to improve the article. This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
Aims: The aim of this study was to map the diverse factors impacting change implementation in nursing practices and investigate different implementation strategies. Design: Scoping literature review following PRISMA-ScR extension. Methods: Data were collected from PubMed, Ebsco, Scopus and ScienceDirect databases from 1990 onwards. Only English peer-reviewed studies reporting an implementation of change in nursing practice were included. Of 9,954 studies, 425 abstracts were scanned and 98 full-text articles were screened. Finally, 28 studies were selected. Results: A multifaceted approach, with a tailored intervention, was the most effective implementation strategy. Most identified factors were considered systematic, for example resource availability, leadership and knowledge. However, others related to local social and material context were identified in fewer number of studies.
| Methods Relevant studies were investigated using PubMed (MEDLINE), ScienceDirect (scientific, technical and medical research), Scopus (Elsevier database of peer-reviewed literature for science, technology, medicine and the social sciences) and CINHAL Ebsco (cumulative index for nursing and allied health literature) databases from 1990 onwards. This time point was chosen as the implementation research in health care has grown considerably since the earlier 1990s  (Damschroder et al. , 2009). Study collection step was conducted by one author (blinded for review) and revised by a second author (blinded for review).
| Keywords and eligibility criteria A structured database search was conducted to identify peerreviewed articles related to implementation processes or strategies for change based on scientific evidence in nursing. This was including innovations, evidence-based practice (EBP) and quality procedures (accreditation or certification procedures or QI initiatives) in nurse practices. Also, we used predefined keywords and eligibility criteria by both authors, prior to databases search. Keywords were Implementation, integration, adoption, dissemination, introduction, certification, accreditation, or quality evaluation mechanisms, quality assurance, professionals, caregivers and nurse. We used medical subject headings (MeSH) terms with Boolean operators ("OR" and "AND") to perform searches in PubMed, and similar combinations were used for other databases.