dataesr/scientific-paragraphs-categorization huggingface dataset:
In 2013, a comprehensive review of PIC randomised controlled trials  (1)  analyzed 248 trials from 1879 until April 2013 and found 82% were single centre, with mostly small sample sizes. Of these, 63% examined medications, 11% devices and 8% were nutritional interventions. Critically, primary outcome measures were identified in only 67% of trials, suggesting a need for the agreement around appropriate outcome measures. One way to improve consistency in the outcomes reported for an intervention is by developing an agreed, standardized collection of specific outcomes, a 'core outcome set' (COS)  (2). A COS promotes the reporting of these outcomes, defined in a consistent manner (as a minimum) in future PIC Nutrition trials. The Core Outcome Measures in Effectiveness Trials (COMET) database has registered over 300 studies aiming to develop core outcome sets.
Methods Our aim was to systematically describe all outcome measures used when a nutritional intervention has been evaluated in a Pediatric Intensive Care (PIC) randomised controlled trial (RCT) since 1 January 1996. The study population included all children from birth (>37 weeks' gestation term infants) until the age of 17 years. Trials were targeted because the development of a COS relates primarily to randomized controlled studies where an intervention is tested  (2). Additionally, trial citations were also extracted from the online database picutrials. net. The study was registered with the Core Outcome Measures in Effectiveness Trials (COMET) initiative online organization. http://www. comet-initiative. org (7). Adult intensive care trials were excluded. Specifically, neonatal intensive care trials were also excluded but PIC trials including term newborn infants were analyzed.
We also excluded pilot studies, to avoid including preliminary interventions where outcomes may have been subject to adaptation prior to a larger study being performed. One reviewer (KG) conducted the search and independently screened articles for eligibility using titles and abstracts of papers initially. Full texts including supplementary material were then retrieved. The searches and trial selection were then reviewed by the two other authors (LT, FV) to confirm inclusion. Figure  1  shows the screening process. The trial aims, primary and secondary trial outcome measures, together with their definitions were extracted using a standardized data extraction tool. The database was reviewed by all the authors during the process to confirm trial inclusion and how outcomes measured were categorized.
systematic literature search was undertaken of all studies involving a trial of a nutritional intervention in PIC from 1 January 1996 until 20 February 2018. Medline (United States National Library of Medicine), Excerpta Medica Database (EMBASE), Cumulative Index to Nursing and Allied Health Literature (CINAHL), Allied and Complementary Medicine Database (AMED), British Nursing Index (BNI), Health Business Elite (HBE), Health Management Information Consortium (HMIC) and PsychINFO (American Psychological Association) databases were searched. The search terms used were: 1. Young (adult OR people OR person) 2. (adolescent OR teenage) 3. (pediatric OR paediatric OR child OR infant*) 4. (PICU or PIC OR ((critical OR intensive) (care OR unit)) 5. (((enteral OR parenteral OR venous OR total OR deliver) ADJ4 nutrition*) OR TPN OR CVN OR PPN OR EN) 6.
A systematic literature search was undertaken of all studies involving a trial of a nutritional intervention in PIC from 1 January 1996 until 20 February 2018. Medline (United States National Library of Medicine), Excerpta Medica Database (EMBASE), Cumulative Index to Nursing and Allied Health Literature (CINAHL), Allied and Complementary Medicine Database (AMED), British Nursing Index (BNI), Health Business Elite (HBE), Health Management Information Consortium (HMIC) and PsychINFO (American Psychological Association) databases were searched. The search terms used were: 1. Young (adult OR people OR person) 2. (adolescent OR teenage) 3. (pediatric OR paediatric OR child OR infant*) 4. (PICU or PIC OR ((critical OR intensive) (care OR unit)) 5. (((enteral OR parenteral OR venous OR total OR deliver) ADJ4 nutrition*) OR TPN OR CVN OR PPN OR EN) 6.
Statistical methods Data for antioxidant levels were not normally distributed and were therefore logarithmically transformed before analysis. Results were summarised using the geometric mean and inter-quartile range. Correlation coefficients between fruit and vegetable consumption and antioxidant measures were assessed. Antioxidant levels were compared between men with and without a CVD outcome and all-cause mortality using independent samples t-tests. Lifestyle behaviours were compared across socioeconomic variables either by chi-square test for categorical variables or by Kruskal-Wallis one way ANOVA for continuous variables. Cox proportional hazards models were used for analysis of antioxidant status for cardiovascular outcomes (first cardiovascular event) and separately for all-cause mortality, during a 10-year follow-up period.
Hazard ratios were compared across quarters of antioxidant distribution by a test for trend, and a likelihood ratio test was used to check for non-linearity by comparing the trend model with a model specifying a different hazard for each quarter. Additional sensitivity analyses considered the exclusion of variables that could potentially contribute to the causal pathway of CVD or all-cause mortality. Tests of the hazard proportionality assumption in the Cox model were performed using Schoenfeld residuals. All tests were conducted at the p < 0. 05 significance level using SPSS version 25 (IBM Corp, Armonk, NY, USA) and Stata release 14 (StatCorp, College Station, TX, USA). To check for possible effect modification, interactions between country and antioxidants were added to the Cox proportional hazards models.
001 level. Despite controlling for the most important covariates, additional residual confounding may exist. Furthermore, additional dietary factors not considered within the analyses may be associated with antioxidant levels. Moreover, the sensitivity of nutritional biomarkers is somewhat limited by the influences of individual genetic variation associated with dietary intake and nutrient metabolism, a complex multistage process that includes ingestion, digestion, absorption and transportation in the blood  [48, 49]. The categorical analyses by quartiles depends on certain parametric modelling assumptions (proportional hazards, linearity, etc. ), although analyses of antioxidant levels as continuous variables demonstrated similar levels of significance (data not shown). In addition, while we evaluated daily FVJ consumption, the use of FFQ data may lead to an overestimation of the intakes of some healthy foods, which may impact the interpretation of the associations observed, although this had little effect on the associated hazard ratio estimates.
Acknowledgements We acknowledge the contributions from the  PRIME  study participants over the duration of the investigation period. The  PRIME Study  was organised under an agreement between INSERM and the  Merck, Sharpe and Dohme-Chibret Laboratory , with the following participating Laboratories: The  Strasbourg MONICA Project ,  Strasbourg ,  France  ( D. Arveiler ,  B. Haas ). The Toulouse.
ADES-ED study design Patient demographics were collected from administrative data of each participating center over the same 8-week enrolment period. These data were compared with the overall study population to verify the representativeness of the studied ED population  [26]. All adult patients presenting to the ED during one of the randomly assigned time slots were eligible for study participation. All patients entering the study signed an informed consent form. Self-medication and medical history were assessed by a standardized questionnaire. This questionnaire was developed and validated by Roulet et al. [27]. The questionnaire contained a set of 20 closed-ended questions exploring all indications and dimensions of self-medication, and data regarding medical history.
in their retrospective analysis of a single-center database in Switzerland  [21]. Thus, an adequate biological monitoring is also warranted in hypertensive patients who are at risk of hypokalemia. Our study has several limitations. First, the initial reasons for measuring potassium were not recorded and assessed, although the chief complaint of our population was comparable to those of the ADES-ED population (trauma in about one-third of the patients, with the other most frequent complaints being abdominal pain, weakness and cardiovascular diseases)  [26] , except for trauma which was second. This fact can be easily explained since patients with no potassium measurements were excluded in our study and patients with non-surgical trauma had no blood test. Secondly, data collection on drug consumption did not include dietary supplements, which can also generate iatrogenic effects, especially on potassium levels.
Thirdly, the present dataset does not allow ruling out a pseudo-hyperkalemia phenomenon  [47] , in addition we don't know which machines were used to test their potassium values and what are the hospitals cut-offs for potassium. However, hyperkalemia was very uncommon in the present series. Another important limitation was that mortality was only assessed in the ED, while a more long-term analysis (i. e. during hospital stay) may also be relevant. Lastly, our population only included people who have had a blood test with electrolytes. This fact selects patients who are probably sicker than those who did not have blood tests. Notwithstanding, the strength of the present study lies in its multicenter and prospective recruitment approach while describing for the first time a population presenting at the ED without unstable medical illness.
Acknowledgments The authors deeply thank the study steering committee ( Francoise Ballereau ,  Jacques Bouget ,  Nadine Foucher ,  Patrice Queneau ,  Bertrand Renaud ,  Lucien Roulet ,  Gerald Kierzek ,  Aurore Armand-Perroux ,  Gilles Potel ,  Jeannot Schmidt  and  Francoise Carpentier)  for granting us access to the clinical database. The authors thank  Pierre Pothier  for the editing the manuscript.
3C  and Fig. S4 ). To this end, cells were spread on agar plates with or without 25 µM CdCl 2. Menadione soaked filter discs were used to assess growth inhibition. Under respiratory condition, growth inhibition zones were comparable, regardless of the supplement of 25 µM CdCl 2 for the wild-type, DsodB and DcadA strains. In contrast, the DcadAsodB strain exhibited a very strong phenotype in presence of both CdCl 2 and menadione, as growth was completely inhibited on plate (Fig. 3C  and Fig. S4 ). In presence of menadione alone, however, the diameter of bacterium-free zone for DcadAsodB and DsodB was comparable. Altogether, these data showed that the high toxicity of Cd 2+ in the absence of the CadA efflux pump was exacerbated by the absence of the superoxide detoxification system. SodB was also crucial for survival under copper stress only in the Cu + -efflux ATPase-deficient mutant copA À Similar to cadmium, copper is extruded from the bacterial cytoplasm mainly by the dedicated Cu + -efflux ATPase CopA  (Rensing et al.
Acknowledgements We gratefully acknowledge the support of the  CNRS  and the Microbiology Department of I2BC. We are very grateful to  Prof. Peter Graumann  and  Antje Sch€ afer at Marburg, Germany , and to  Prof. Sanjay Swarup  and  Miko Poh Chin Hong  at  NUS Singapore  for providing strains. We also acknowledge the  National BioResource  Project,  National Institute of Genetics, Japan , for providing E. coli strains.
3H-M ). functions, including in synaptic refinement  19. Therefore, we investigated whether and how n-3 PUFA deficiency modulates the homeostatic molecular signature of microglia isolated from n-3 deficient vs. n-3 sufficient mouse brains. Using a Nanostringbased mRNA chip containing 550 microglia-enriched genes  20  , 154 of these genes were found to be significantly down-regulated and 41 genes up-regulated in microglia from n-3 deficient mice whole brains (Fig. 2g, j  and Table  1 ). Among the 40 genes reported to be unique to homeostatic microglia by  20  , 20 were significantly dysregulated, indicating that maternal n-3 PUFA deficiency alters homeostatic functions of microglia (Fig. 2g ). We next sought to define the diet-specific microglial phenotype by assessing patterns of gene co-expression using unbiased network analysis software, Miru  21.
The 20 homeostatic microglia unique genes that were significantly affected by the diet are labelled. h Number of microglial genes that are up-regulated, down-regulated or not regulated by the diet. i A transcript-totranscript correlation network graph of transcripts significantly differentially expressed by diet groups was generated in Miru (Pearson correlation threshold r ≥ 0. 85). Nodes represent transcripts (probe sets), and edges represent the degree of correlation in expression between them. The network graph was clustered using a Markov clustering algorithm, and transcripts were assigned a color according to cluster membership. j Mean expression profile of all transcripts within clusters 1, 2, and 3 where each point represents an animal and the average gene expression of all genes within that cluster for that animal.
1 × 10 7 microspheres/ml for 30 min at 37 °C, intensively washed, and finally fixed with 4% paraformaldehyde. Cells were stained with anti-Iba1 antibodies. A blinded experimenter counted beads per cell using NIS Elements AR 3. 26 software. To measure phagocytic activity by cytometry, cells were incubated for 60 or 120 min with 150 µg of synaptosomes per well. Medium was removed and cell collected following trypsin treatment, pelleted, rinsed in PBS/1% BSA, and stained with CD11b-FITC [clone M1/70, BDBiosciences] antibody for cytometry analysis. FACS data were acquired using an LSR Fortessa 2-Blue 6-Violet 3-Red 5-YelGr laser configuration (BD Biosciences). Diva 8. 0 (BD Biosciences) and FlowJo 10. 5 (FlowJo, LLC) were used for data analyses. Microglia fatty acid analysis. Fatty acid analyses requiring lots of material, we pooled microglia from 4 brains for n = 1.
Network analysis. To investigate gene coexpression relationships between groups, a pairwise transcript-to-transcript matrix was calculated in the software tool Miru (Kajeka, UK) from the set of differentially expressed transcripts using a Pearson correlation threshold r = 0. 85. A network graph was generated where nodes represent individual probe sets (transcripts/genes), and edges between them correlation of expression pattern with Pearson correlation coefficients above the selected threshold. The graph was clustered into discrete 6 groups of transcripts sharing similar expression profiles using the Markov clustering algorithm (inflation 2. 2). Electron microscopy. Mice were anesthetized with sodium pentobarbital (80 mg/ kg, i. p. ) and perfused with 0. 2% glutaraldehyde in 4% PFA. Transverse sections of the brain (50 µm thick) were cut in PBS (50 mM at pH 7.
Cellular profiles were identified according to criteria previously defined  89. For quantitative analysis, each captured Iba1-positive microglial process was analyzed. A phagocytic index was compiled by summing up the vacuoles and endosomes containing cellular materials such as membranes, axon terminals with 40-nm synaptic vesicles and dendritic spines with a postsynaptic density, on a microglial process basis  16. Images were analyzed using the AMT Image Capture Engine Software 601. 384. Immunohistochemistry. Mice were deeply anesthetized with isoflurane and transcardially perfused with PBS followed by 4% PFA. Brain was removed, postfixed in PFA overnight at 4 °C and cryoprotected in 30% sucrose at 4 °C. Immunohistochemistry experiments were performed on free-floating coronal 30 μm cryostat slices.
Image analysis. Densitometry: Individual images were analyzed with Fiji or Image J software (Image J, open source), using the following procedure: (1) user-defined thresholding value applied to each image, (2) calculation of area of staining from background for each protein of interest. Final values are represented as a surface area in pixel values. Control sections for all studies in which primary or secondary antibodies were omitted resulted in negative staining (not shown). Stereological analysis: Iba1-and GFAP-immunoreactive cell numbers and volume of the hippocampus were thoroughly determined in the hippocampus with the unbiased stereological sampling method based on optical dissector stereological probe. Apoptotic cells counting: The number of apoptotic cells (cells with pycnotic/ karryorhectic morphology) was estimated using unbiased stereology methods, and is reported as cells/mm3.
PCRs were analyzed with the QX200 droplet reader (Bio-Rad) and data analysis was performed with QuantaSoft software (version 1. 7; Bio-Rad). qPCR primer sequences: Eeflal (GenBank NM_010106): Forward TGAACCATCCAGGCCAAATC, Reverse: GCATGCTATGTGGGCTGTGT; Ppia (GenBank NM_008907): Forward CAAATGCTGGACCAAACACAA, Reverse: GCCATCCAGCCATTCAGTCT; C3ar1 (GenBank NM_009779): Forward TCCCATCTCTCCCTACTTTGCA, Reverse: TGTTTTAGGCACACCATGGTAAA; Itgam (GenBank NM_001082960): Forward CTCATCACTGCTGGCCTATACAA, Reverse: GCAGCTTCATTCATCATGTCCTT; Gpr31b (GenBank NM_001013832): Forward GCTGCAGTGTCCAGCAAGC, Reverse: TGTACTGTGCAGGCAGGTGAG. Golgi staining. Brains were processed for Golgi-Cox staining using the FD Rapid Golgi Staining kit (FD Neurotechnologies, Inc). Brains were left in the staining solution for 12 days, frozen in isopentane solution and kept at -80 °C until sectioning and coloration.
The brains were cryostat-cut at a thickness of 100 μm. Sections were mounted on gelatin-coated slides and analyzed using a motorized Leica DM5000 microscope at ×63 magnification. The images were acquired using a CCD Coolsnap camera and Metamorph software. For analysis, we randomly selected pyramidal neurons from the CA1 region of the dorsal hippocampus that were fully penetrated by the Golgi coloration and distinguishable from other neurons (n-3 deficient mice had less usable neurons than n-3 sufficient mice). Spine density in these neurons was determined by counting the number of spines on at least 3 basal and 3 apical dendritic segments of 10 μm in length. Segments from dendrites situated as far from the cell body as possible, with no overlap with other dendrites were randomly selected. Primary dendrites were never used for analysis as their thickness hampers detection of spines.
After extraction, synaptosomes were lysed using sonication in TB. Quantifications were performed according to manufacturer instructions, in duplicates and by loading 5 μg of proteins extract per well, and using the following software Wallac 1420 instrument Workout 2. 5 (PerkinElmer). Y maze task. P21-old mice were handled daily and weighed before and during behavioral experiments. Sessions were recorded with a ceiling-mounted video camera and analyzed using Smart software (Panlab, Barcelona, Spain). The Y-maze was used to assess spatial working memory  90. Each arm was 34 cm long, 8 cm wide, and 14 cm high. The floor of the maze was covered with corn cob litter, which was mixed between each trial to remove olfactory cues. Visual cues were placed in the testing room and kept constant during the whole test.
In the first trial, one arm was closed with a guillotine door and mice were allowed to visit two arms of the maze for 5 min. After a 30-min to 3 h inter-trial interval (ITI), mice were placed back in the start arm and allowed free access to the three arms for 5 min. Start and closed arms were randomly assigned for each mouse. When required, baicalein was injected intraperitoneally at a concentration of 20 mg/kg, at P14, P17, and 30 min prior the first trial (at P21 or P30 depending on the experiments). Data are presented as the time spent exploring the novel and the familiar arms during the second trial. Statistical analyses. For most experiments, experimental groups were compared using Student t-test or non-parametric Mann-Whitney test (when equality of variance or normality failed). We used the Grubbs' test, also called the ESD method (extreme studentized deviate), to determine whether the most extreme value in the list is a significant outlier from the rest.
Acknowledgements Funding for this research was provided by the  Institut National pour la Recherche Agronomique (INRAE) , the  Bordeaux Univ , the  Foundation for Medical Research (FRM ,  DEQ20170336724  to S. L. ), the  French Foundation  (FDF, # 00070700 ) and the  Fédération pour la Recherche sur le Cerveau  ( FRC Connect ). C. M. was funded by the  French Ministry for Research  and by the  Fondation pour la Recherche Medicale  ( ARF201909009101 ), CBB was supported by the  French National Agency for Research  ( ANR-12-BSV4-0025-04 , to S. L. ) and Agreenskills (MSCA cofund-INRAE), J. C. D. was supported by the  Region Nouvelle Aquitaine  ( 2011. 1303003 , to S. L. ), Q. L. was supported by the  Region Ile de France (PICRI , the  Ceberal Palsy Foundation  # 13020605 , to A. N. ) and the  FRM , AT was supported by the  French National Agency for Research  ( ANR-2010-BLAN-141403 , to S.
L. ), ADG was supported by  Agreenskills  ( MSCA cofund-INRAE ) and  Marie-Curie European Grant , C. L. was supported by  Idex  grant, M. M. was funded by  FRM  ( DEQ20170336724 , to S. L. ) and M. R. was supported by the  Region Nouvelle-Aquitaine  ( 2017-1R30237-00013179 , to S. L. ). A. S. was supported by grants from the  Spanish Ministry of Economy and Competitiveness  with  FEDER  funds to AS ( BFU2015-66689 ,  RYC-2013-12817 ), a  BBVA Foundation  Grant for Researchers and Cultural Creators to A. S. , and a  Basque Government  grant ( PI_2016_1_0011 ) to AS. PG was supported by  Inserm ,  Université de Paris ,  ERA-NET Neuron (Micromet). This work was partly funded by  NeurATRIS   ANR-11-INBS-0011  of the  French Investissements d'Avenir Program  run by the  ANR. MET, C. L. , and K.
Study Design and Sampling For our study, data from the cohort Cambodia Health and Nutrition Monitoring Study known as "MyHealth" were used. The MyHealth study started in March 2016, and infants and children were recruited into the study until September 2018. Infants and children were seen at regular follow-ups (FUs), with the 1st FU to the 5th FU being conducted every 4 months, while the 6th FU was conducted 14 months after the 5th FU (Table  1 ). The study was conducted in 6 districts of the 3 provinces in Cambodia, an urban poor area (Phnom Penh), and in rural areas to the northeast (Kratie and Ratanakiri). At the 1st FU, 7738 children aged less than 24 months were randomly selected from the population list provided by Village Health Support Groups (VHSGs). All information on each child's demography, wealth index, feeding practices, hygiene practices, and anthropometric measurements was collected using electronic tablets.
This information was collected by experienced and trained teams. PP = data collection was conducted in Phnom Penh; KR = data collected was conducted in Kratie; and RT = data collection was conducted in Ratanakiri. FU = follow-up. X = presenting the availability of the data collection for each follow-up. For our study, only children aged 0-12 months at the 1st FU were selected to investigate their feeding practices for the first year of life. Out of these 2418 children, only those with complete data on feeding practices and anthropometric measurements were included for analysis. Hence, the sample size for the current data analysis was 1079 children in the 1st FU, with a total number of 5984 follow up visits (Figure  1 ). PP = data collection was conducted in Phnom Penh; KR = data collected was conducted in Kratie; and RT = data collection was conducted in Ratanakiri.