dataesr/scientific-paragraphs-categorization huggingface dataset:
Sample size and statistical analysis plan Sample size Using data from the ICE-CUB 1 study, we estimated a 32 % 6-month mortality rate in the control group. Considering an estimated intracluster correlation coefficient of 0. 01, we estimated that 3000 patients would provide a power of 74 % to detect a difference of 6 % in mortality rates between the two groups, with a two-sided type 1 error rate of 0. 05. We planned to recruit 25 centres during an inclusion period of 2 years and a half, based on a predicted average of 56 included patients per year per centre (data from ICE-CUB 1 study).
Ethical considerations and legal requirements The study protocol was approved by the institutional review board (Comité de Protection des Personnes Ile de France), and all responsible authorities from each centres provided consent. Patient's or surrogate decision-makers' non-opposition to trial participation was assessed. An information sheet with contact details was handed to all patients and/or surrogate decision-makers. The authorization to use the patient's data could be withdrawn by the patient or the surrogate decision-makers at any time. The nominative database was approved by CCTIRS and CNIL (reference # 911503). The study was registered on Clinical trials. gov (NCT01508819). The electronic case report form (eCRF) was developed by URC-Ouest (TS) and URC-Est (SA), Paris, using online system CleanWeb (http://www.
Funding The study was funded by the French ministry of health (PHRC 2010 AOM 10154 K100103). The funding source had no interference with the conduct of the study. The research sponsor was the DRCD Ile-de-France who served as an independent Data Safety Monitoring Board (DSMB) (Project Code: K100103/No. IDRCB 2011-A00758-33). The DSMB had full access to the mortality data and could stop the trial in case of important disparity in mortality between groups. None of the members of the scientific committee nor the investigators declared any conflict of interest related to this study.
Acknowledgements The study was funded by a grant from  Programme Hospitalier de Recherche Clinique-PHRC 2010-ministère de la santé. Unité de Recherche Clinique Paris Ile de France Ouest (URCPO) ;  Ph Aegerter ;  Unité de Recherche Clinique-Est ;  T Simon ;  SALHI Sara Nesrine ;  France Guyot-Rousseau ; and all the  TEC  and  ARC  involved in the study. All the ED and ICU teams of the participating centres are acknowledged.
Data collection A Microsoft Excel-based data monitoring system implemented in 2010 provided the data source for this study. Patient outcome (discharge, death, defaulter, referral) and discharge diagnosis stratified by admission weight were entered weekly into the database. Weight refers to admission weight and is not necessarily equal to birth weight. Gestational age assessment is not routinely performed. Details regarding timing of admission, socio-demographic information and maternal and birth risk exposures were not available. Admission referral location (outpatient department or maternity) was recorded in a manual logbook by the clinical officer as patients entered the hospital. Case definitions lacked detail (see Table  2 ) and a single diagnosis was assigned in a defined order of priority.
Data analysis Discharge diagnoses were grouped into six categories: neonatal sepsis, asphyxia, respiratory distress, tetanus, hypoglycaemia (2013-14 only) and other. Descriptive statistics including frequencies and proportions were calculated. The association between admission weight (<2500 g or 2500 g) and mortality was investigated using a chi-squared test at 5% significance level. Trend analysis over 4 years was performed using the Cochrane-Armitage test for trend in proportions at a 5% significance level. All statistical analyses were performed using the statistical package R (version 0. 98. 1091) [5]. This study followed the Strengthening the Reporting of Observational Studies in Epidemiology guidelines for reporting of observational studies  [6]. This retrospective study used routinely collected anonymized programme data only and is exempt from the requirement for ethical approval according to MSF ethics review board rules and confirmed by the Deputy Medical Director of MSF France.
Strengths and limitations All neonates exiting the unit over 4 years are included, so the patient population is large. This also accounts for seasonal variation in mortality that can be a problem in studies of shorter duration. There was a low defaulter rate, allowing an accurate measure of in-hospital mortality. Nonetheless, this study has many limitations and presents several potential areas for improvement in data collection, management and analysis. Limited clinical information is captured in the database and minimal inferences can be drawn from maternal, perinatal and postnatal factors. Gestational age is not routinely assessed and weight is assigned on admission. Birth weight is often unknown for the high proportion of out-born patients. There was no way to examine the effect of referral location, an important prognostic factor, on outcome.
An updated database linking specific exposures with patient outcomes would allow more detailed inferential analysis of determinants of neonatal morbidity and mortality. Given the limitations of the study setting, assignment of clinical diagnosis is inconsistent. Internationally recognized standard case definitions should be developed. There is no diagnostic category for prematurity/LBW-an important consideration, as other studies in sub-Saharan Africa have reported that complications arising from prematurity account for approximately 35% of diagnoses  [24]. Improving diagnostic accuracy could better identify programme needs and highlight priorities for intervention. This study describes outcomes of neonates treated in a hospital setting and represents a specific group of neonates whose families had sufficient means to present to hospital.
VITAMIN K1 MEASUREMENT The LC-APCI/MS/MS used was a 6120 Quadrupole LC/MS with an Atmospheric Pressure Chemical Ionisation (APCI) interface and a LCMS Chemstation software from Agilent Technologies (Palo Alto, CA, USA). Chromatographic separation was performed using a XTerra MS C18 column (2. 1mm × 50mm, 2. 5µm, Waters, Milford, MA, USA) with a mobile phase of methanol, 0. 1% acetic acid (96:4) in isochratic conditions. The column temperature was 48°C. The flow rate in the LC column was 0. 4mL/min. The injection volume was 20µL. The temperature of the autosampler tray was set to 5°C and the samples were protected from the daylight. Detection was by MS with APCI source in positive mode. Nebulizer pressure was set to 60psi, dry gas temperature to 350°C, dry gas flow to 5 L/min, and vaporizer temperature to 400°C.
A significant difference was observed between male rats and female rats for the prothrombin and the factor X slope values. Consequently, the half-lives of these two factors were different between males and females. Concerning female factor VII, only values from 4 hours were including in the linear regression. Indeed, during these 4 first hours, female factor VII activities did not decay. The slope of the female factor VII plateau was not significantly different from 0 (p-value = 0. 409). One, 2, 4, 8, 10, 13, 16, 20, 24, 32, 48  and 72 hours after the per os difethialone administration, difethialone concentration in plasma liver was determined. The concentration of difethialone in plasma (data not shown) and liver (Figure  5 ) increased rapidly after an oral administration in males and females, reached a peak about 8-12 h after the administration, and then decreased slowly an a time-dependent manner.
Membranes were washed, incubated with an HRP-coupled secondary antibody (1:5000, Invitrogen), washed again, and finally incubated with Western Lightning ECL (Perkin Elmer, Waltham, MA, USA). ECL signal was detected with a Syngene Pxi4 imager, and densitometry was performed with ImageJ (http://rsbweb. nih. gov/ij/); all data were normalized to actin.
Blood pressure measurement Blood pressure was measured in male mice only by radiotelemetry using PA-C10 transmitters (Data Sciences Inc. , St. Paul. MN, USA) implanted in the left carotid artery, with the transmitter inserted into a pocket in the body cavity, as previously described  (McCormick et al. 2014). Mice were anaesthetized using isoflurane (5% in O 2 to induce, 1. 5-2% to maintain). Following surgery, mice received 0. 1 mg kg -1 buprenorphine I. P. twice daily for 3 days as analgesia. Animals were monitored for alertness, activity and loss of weight, and given at least 7 days to recover from surgery before measurements were recorded for 10 s every 10 min. Twenty-four hour averages were used to calculate mean systolic blood pressure (SBP).
MaxQuant v. 1. 5. 1. 2 (Cox & Mann, 2008)  was used to search MS data with carbamidomethyl (C) as a fixed modification and acetyl (N-terminal), deamidation (NQ), oxidation (M) and phospho (STY) as variable modifications, ࣘ 3 missed cleavages, ࣙ 5 amino acid length and 1% false discovery rate. MaxQuant search results were further processed in Perseus v. 1. 5. 0. 31. 22 Na + uptake assays Functional expression of wild type and mutant NCC was assessed in the heterologous expression system of Xenopus laevis oocytes. Usage of X. laevis was approved by the Universidad Nacional Aut ónoma de México Animal Care and Usage Committee. Oocytes were extracted from female Xenopus frogs (three in total were used) and processed as previously described  (Monroy et al. 2000). Oocytes were injected with wild type or mutant T122D, S124D or T122D/S124D mouse NCC cRNA and 48 h later 22 Na + uptake was assessed in control conditions or after 16 h of low chloride hypotonic stress, which is known to activate the cotransporter via WNK-SPAK phosphorylation of the amino terminal threonines 53 and 58, as previously described  (Pacheco-Alvarez et al.
Funding This research was supported by  National Institutes of Health  Grants  R01DK098141  to J. A. M. , and  R01GM117230  and  P01DK017433  to J. R. and  CONACYT  Mexico Grant  165815  to G. G. K. W. B. is supported by  NIH -T32 GM100884  and the  National Science Foundation Graduate Research Fellowship  under Grant No. DGE-1122492.
The present study is based on data from 3C wave 1 in Bordeaux. NuAge study: The NuAge study is a four-year longitudinal study designed to evaluate the role of nutrition on physical and cognitive status, functional autonomy and social participation  [20]. The study included 1793 individuals aged 67-84 years at baseline in 2003-2005. Participants in good general physical health and cognitively normal (Modified Mini-Mental State Examination score above 80 out of 100) were selected from a random sample obtained from the Quebec Medicare database using stratified sampling by age and sex  [21]. After baseline examination, participants were re-examined annually over a three-year period. Trained dietitians and nurses assessed participants in face-to-face interviews or by direct measurement, at the research centers.
Dietary Assessments, Harmonization of Nutrient and Food Intake In 3C, individual nutrient intakes were computed from the 24-h recall using the BILNUT ® software (Cerelles, France), which converts food intake data into nutrient intake data using French food composition tables  [22]. These tables were augmented for fatty acids from the Food Composition and Nutrition tables  [23]. As the 24-h recall was open-ended, additional data were also obtained by consulting a French table developed by the National Institute of Health and Medical Research (Inserm) and the University of Montreal  [24] , the USDA National Nutrient Database, food packaging, and directly contacting food manufacturers. Extended information about the dietary habits of the Bordeaux sample have been described in detail elsewhere  [25, 26].
Moreover, a qualitative FFQ, including 148 food and non-alcoholic beverage items, was administered during the same dietary survey  [26]. Based on the FFQ, weekly frequency of consumption of 40 categories of foods and beverages for each of the three main meals and three between-meal snacks was recorded in 11 classes. The FFQ data were used to compare the frequency of food group consumptions between different nutrient patterns, and could not be used to estimate nutrient intake because portion size was not assessed. In NuAge, daily nutrient intake levels were computed from the first of the three 24-h recalls at baseline using the CANDAT-Nutrient Calculation System (version 10, London, ON, Canada) based on the 2005 version of the Canadian Nutrient File, augmented by a database of 1200 additional foods that was developed on-site  [27].
A 78-item validated semi-quantitative FFQ  [28]  was also administrated at recruitment to assess usual food intake. As in 3C, FFQ data enabled description of average food intake within each nutrient pattern. Eleven food groups based on common food items to the two studies were defined. Nutrient-dense beverages such as sugary drinks were included in the sweet products group. As water and other hot beverages are not nutrient-dense beverages, they were not considered as contributors to nutrient intake. In addition, 21 nutrients whose consumption was available in 3C and NuAge were selected to derive nutrient patterns in both studies.
Data Harmonization for Sociodemographic and Lifestyle Variables In both studies, living arrangement was categorized according to two modalities: living alone vs. in a couple or cohabitation. Smoking status was classified as current, ex-smoker, or never smoker. Education was categorized as 0-6 years, 7-9 years, 10-13 years and ě14 years. In 3C, monthly income was reported in four pre-determined categories according to the French economic situation in 1999-2000  [25]. Yearly income was further computed (converting French francs, the past French currency, to Euros), and created a three-category variable: low income (<18,000 euros (€)/year), moderate income (18,000-27,000 €/year) and high income (ě27,000 €/year). In NuAge, income was reported as a continuous variable. Because of differences in cost of living in 1999-2000 in France (baseline 3C) versus in 2003-2005 in Quebec (baseline NuAge), income values were not directly comparable.
) or mixed (arts, culture, sales, etc. ). Body mass index (BMI) was computed as the weight (kg)/height squared (m 2 ). In 3C, missing data in food intake from the FFQ (66 participants, 3. 7% of the sample) were imputed using Multivariate Imputation as described by Samieri et al. [35]. With respect to NuAge, 92 implausible FFQs among 1688 subjects (5%) with both 24-h recall and FFQs identified using a set of criteria developed by Shatenstein et al. [36]  were excluded, leaving 1596 subjects for the final analysis. In both studies, missing values for covariates representing less than 5% of the sample were excluded, and dummy variables were created for variables with a frequency of missing values between 5% and 10%.
In that study, the Western pattern consisted of high consumption of sweets and candy, processed meats and salty snacks. The prudent pattern was strongly positively correlated with a higher mean adequacy ratio of essential nutrients, whereas the Western pattern was inversely correlated with this ratio. Correlations with global nutritional quality of the diet indices were not reported. In a sample of 4693 older people (mean age 60 years) from the UK Whitehall II study, using dietary data from a FFQ, Akbaraly et al. [43]  also identified a whole food pattern and a processed food pattern, similar to the healthy and Western patterns identified in our study. As in the NuAge sample, higher adherence to the whole food pattern was associated with a higher level of education and being ex-smokers. The reverse was true for the processed food pattern.
Similar findings were also reported by Kesse-Guyot et al. [44]  in a French population of 3054 subjects studied at midlife, aged on average 52 years old at nutritional assessment. The authors described a healthy pattern derived from dietary data from a 24-h dietary record that was also correlated with high consumption of fruits, dairy products, vegetables, and fish. This healthy pattern was inversely correlated with meat and processed meat, which is similar to the healthy patterns from both 3C and NuAge samples. Food habits in South-West of France, leading to the phenomenon known as the French paradox  [45] , are typically related to consumption of charcuterie and wine as well as fish/seafood, especially in the Bordeaux area due to the proximity of the Atlantic Ocean. Thus, a traditional food pattern has been previously reported composed of both recommended and non-recommended food and associated nutrients  [46].
In Quebec, the traditional food pattern was related to higher intake of dairy products and fish, which used to be part of their traditional diet. This pattern may be explained in part by an advertising campaign promoting dairy products for the prevention of osteoporosis, a wider distribution of fish to markets and publicity for the prevention of cardiovascular disease and memory deficits with advancing age. However, this dietary pattern explicated a small amount of the total variance. To assess nutritional quality of the diet, we chose the C-HEI because items necessary to compute this score are based on food groups and nutrient intake data that were available in both NuAge and 3C samples. Thus, the healthy patterns appeared to be associated with healthy food habits in each country, in line with the Canadian dietary guidelines, whereas the Western patterns may reflect an unbalanced diet with low adherence to these guidelines.
Socioeconomic position, lifestyle and other habits such as smoking are potentially associated with nutrient patterns. In both 3C and NuAge, higher education was associated with a healthy pattern as found in some studies  [13, 15, 41]. However, comparisons between the two samples revealed that the association between higher education and healthy pattern seemed to be stronger in the NuAge sample (data not shown). We also compared the results of the associations between healthy pattern and additional socio-economic characteristics in the two samples. They were associated with healthy pattern only in NuAge, suggesting that socioeconomic position may have a significant influence on dietary choices in this population, similar to the results from Parrott et al. [41]. People with a higher level of education may have better nutrition knowledge and greater earning power, even though income was not statistically associated in our study, allowing them to choose expensive healthy food  [16, 48].
However, the cross-sectional design of this study does not allow us to ascertain temporality of the relationship between BMI and identified patterns. Some limitations to our findings must be recognized. One of them is that dietary data were based on a single 24-h recall. However, it has been suggested that a single recall can provide an accurate estimation of average nutrient intake in large study samples  [50]. In order to improve comparability between studies, we decided to use only the first 24-h recall to derive nutrient patterns in NuAge as in 3C. Analyses showed that percentage of explained variance of diet from the three nutrient patterns in NuAge was very similar when using three 24-h recalls (data not shown). Regarding the FFQ, for a same food group, we gathered frequencies of consumption of food items that were not estimated using the same method.
Acknowledgments: The authors thank  Katherine Gray-Donald  for her critical review of the draft. This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors. Benjamin Allès  was supported for this joint PhD work by a funding from  Region Aquitaine and Faculty of Pharmacy ,  Université Laval  and awards from  Programme Frontenac  and  Jean Walter-Zellidja ,  Académie française. D. Laurin  was supported by a scientist award from the  Fonds de la recherche du Québec-Santé (FRQS). The NuAge study was funded by the  Canadian Institutes of Health Research (CIHR)  and the  Quebec Network for Research on Aging , a thematic network of the FRQS. The 3C study is conducted under a partnership agreement between the  Institut National de la Santé et de la Recherche Médicale (INSERM) , the  University Bordeaux 2 Victor Segalen and Sanofi-Aventis.
The  Fondation pour la Recherche Médicale  funded the preparation and initiation of the study. The 3C study is also supported by the  Caisse Nationale Maladie des Travailleurs Salariés ,  Direction Générale de la Santé ,  MGEN, Institut de la Longévité, Conseils Régionaux d'Aquitaine et Bourgogne ,  Fondation de France ,  Ministry of Research-INSERM Programme "Cohortes et collections de données biologiques" ,  Agence Nationale de la Recherche   COGINUT ANR-06-PNRA-005 , the  Fondation Plan Alzheimer  ( FCS 2009-2012 ), and the  Caisse Nationale pour la Solidarité et l'Autonomie (CNSA).
The spectra were collected in a fluorescence mode using a 30-element Ge solid-state fluorescence detector (Canberra). The energy was calibrated with Cu metallic foils, such that the maximum energy of the first derivative was set at 8979 eV. Cu data were collected from 8830 to 8960 eV using 5 eV step and 2 s counting time, from 8960 to 9020 eV using 0. 5 eV step and 3 s counting time, and from 9020 to 9300 eV with a k-step of 0. 05 Å -1 and the counting time increasing from 2 to 10 s. For each sample, three spectra were averaged and the resulting XANES spectra were background-corrected by linear regression through the pre-edge region and a polynomial through the post-edge region and normalized to the edge jump. The beam was moved to a different position on the sample for each scan to avoid potential Cu photoreduction.
Acknowledgements The authors acknowledge  L. Debrauwer  and  E. Jamin  for providing the Orbitrap mass spectrometer (MetaToul-AXIOM,  INRA ,  UMR1331 Toxalim, Toulouse, France ) and the  ESRF  for provision of synchrotron radiation on the FAME beamline (Proposal  30-02-1099 ). L. Rechignat is acknowledged for EPR experiments and  M. Jones  is acknowledged for the preparation of oxidized peptide and the  UV-Vis spectra. This work was supported by the  French National Agency of Research  ( ANR-13-BSV5-0016 ). C. H. thanks the  ERC aLzINK  -Contract no. 638712  for their financial support.
Segmentation was applied to the maximum intensity projection of 3-6 confocal slices taken from stained guts using a self-developed ImageJ macro based on K-means clustering  60. Statistical analyses of the ENS network and ENCC-free areas in guts were performed using the Kruskal Wallis test for multiple comparisons with Matlab. Principal component analysis (PCA) was carried out as described previously  28  based on texture analysis of the segmentation. PCA allows either the detection of distinct network organisations for which their position in the PCA space is separated by a decision line or of similar populations for which their dots are in the same zone of PCA space. For ex-vivo gut cultures analyses, individual ENCCs were manually tracked using Metamorph 7. 7. 3. 0 software to determine their speed of locomotion and persistence (the straightness of the trajectory, obtained by dividing the distance of the straight line between the initial and final point of the tracked cell by the total distance covered by the cell), as described previously  5.