dataesr/scientific-paragraphs-categorization huggingface dataset:
In addition, standardized EDI-2, BSQ, and HAD questionnaires were filled in. The EDI-2 has been validated to determine personality traits and comorbidities frequently associated in patients with ED  [24]. The Body Shape Questionnaire (BSQ) is a standardized questionnaire assessing patients' bodily concerns  [25]. Finally, the HAD questionnaire was used to evaluate anxiety and depression  [26]. In order to determine significant differences according to EDI-2 and BSQ, the cut-off corresponds to the median of the scores. For the HAD sub-item, the scores higher than the cut-off  (11)  mean that patients have certain anxiety/depression and vice versa. All data used in this article are from the first self-questionnaire provided to the 120 patients enrolled between April 2015 and January 2018. As part of their usual care, patients came back to the hospital within a few weeks for a comprehensive evaluation on a morning day hospital basis.
Therefore, in order to combine biological and clinical profiles, we pooled the patients included in this study in 3 broad categories of restrictive (R), bulimic (B), and compulsive (C) ED. The R category includes AN, restrictive food intake disorder, and atypical AN; B category includes BN or atypical BN of low frequency or duration; and the C group includes BED, BED of low frequency or duration, and night eating syndrome. "Restrictive" patients are characterized by a Body Mass Index (BMI) lower than normal according to the WHO [BMI <18. 5]. "Bulimic" patients are normal weight or overweight [18. 5 < BMI < 30]. On the contrary, "compulsive" patients have obesity and therefore a BMI greater than 30. Clinical and biological data will be presented in the following sections according to these 3 broad groups, except for PYY concentrations for which data will be presented separately according to typical and atypical ED.
5 nM. Here, 60 µL of each sample dilution were injected at 30 µL/min followed by 5 min of dissociation. Finally, the binding surface was regenerated with 50 mM NaOH resulting in the return of the sensorgram baseline. The affinity kinetic data were analyzed with the BioEvaluation 4. 1. 1 program (GE Healthcare) and kinetics curves were fitted using Langmuir's 1:1 model after correction with the reference cell. For affinity measurements, the coefficients of variation are less than 5%.
Statistical Analysis Data were analyzed in the Xlstat and R statistical software (version 3. 5. 0, The R Foundation for Statistical Analysis). Comparison of clinical data among ED subtypes groups was performed by the Kruskal-Wallis test, but the comparison of the sex ratio was performed by Fisher's exact test. All biological data were rank transformed before multivariable analysis to be consistent with rank tests; then, ranks were divided by the number of observations and multiplied by 100 in order to express these variables as empirical percentiles of the overall distribution (three ED groups pooled). Unadjusted, age-and sex-adjusted, then age-, sex-, and BMI-adjusted general linear models were then estimated on the transformed variables (percentiles). The small number of patients in the bulimic group did not allow a reliable statistical interpretation; the results were thus presented just as descriptive data.
So, the C group was compared to the R group. The correlogram (graphical representation of a correlation matrix) was made using the Spearman's correlation coefficient. Three principal component analyses (PCAs) were performed after percentiles transformation for: (1) All IgG quantifications, (2) all IgG affinities, and (3) all peptides measures. These PCAs were designed to perform a dimensional reduction of the data set and their performances were analyzed by scree plots, showing eigenvalues of the data set associated to the eigenvalues of 20 simulated PCAs in a dataset of the same size but with no correlation between any biological variable. Twenty-three fully adjusted (adjusted on age, sex, and BMI) comparisons of percentiles of raw biological variables among ED subtypes were performed with a Bonferroni multiple testing procedure keeping a family-wise error rate (FWER) equal to 5%.
Diversity indices were calculated using the software Past 4. 02 (Hammer, Ø. , Harper, D. A. T. , and P. D. Ryan, 2001. PAST: Paleontological Statistics Software Package for Education and Data Analysis. Palaeontologia Electronica 4(1): 9pp). The predictive functional analysis of the gut microbiota was performed via PICRUSt  [19]. Diseases and host genetic variation linked to NEC-1_21-30 d-associated gut microbiota were identified via MicrobiomeAnalyst  [20] , with the Taxon Set Enrichment Analysis module.
Statistical Analysis The results are presented as mean ± SEM for histograms and box and whiskers graphs. Statistical analyses were performed by two-way analysis of variance (ANOVA) followed by a two-stage linear step-up procedure of Benjamini, Krieger and Yekutieli to correct for multiple comparisons by controlling the false discovery rate (<0. 05) (for histograms) or the Mann-Whitney test (for box and whiskers), as indicated in the figure legend, by using GraphPad Prism version 7. 05 for Windows Vista (GraphPad Software, San Diego, CA, USA). For Table  1 , results are presented as median or as indicated and P value was calculated using Fisher's exact test. Significant values were considered starting at P < 0. 05. For the taxonomical and predictive functional analysis of gut microbiota, significant values were considered, starting at P < 0.
NEC-1 microbiome showed increased activity for pathway related to transcription, glycosaminoglycan degradation and lysosome, compared to healthy children (Supplementary Figure  S2D ). Then, we analyzed the fecal metabolome to appreciate NEC-1-induced changes in gut microbial metabolic activity. NEC-1 children displayed a reduced intragroup variation and significantly lower levels of ethanol (Supplementary Figure  S2E ). Overall, these data show that NEC-1 is characterized by a precise gut microbiota, microbiome and gut microbial metabolites profile.
Conclusions The small cohort represents a limitation of our work, due to the difficulty to investigate NEC at its early onset. However, our data may provide neonatal departments with immediate indications to blunt NEC-1 evolution such as: i) increasing the enteral volume of nutrition, especially in the first days of life; ii) revising and reducing antibiotic therapy up to the first week of life in preterm infants. Availability of data and materials: All data are available in the main text or the supplementary materials and via the following repositories: Sequence Read Archive (SRA) database with the assigned identifier PRJNA579480. Ethics approval and consent to participate: This study was approved (number of the approval: DC 2016-2804) by Neonatal and Pediatric Intensive Care Unit and Neonatology Department of Purpan Hospital in Toulouse, France.
5e4. 49) of 52 rBDs and Group 3 of 48 rBDs (AI > 4. 5). Dietary intake was assessed using the 3 day food recall and the Food Processor, computer program for nutrient analysis. sTAS was measured in all samples and correlated with atheromatic index too. Results: Our study showed that rBDs with low dietary intake of all vitamins, U3 fatty acids, trans fatty acids and dietary cholesterol presented an increased atheromatic index. On the other hand rBDs with high dietary intake of saturated fat, total fats, monounsaturated and polyunsaturated fats and sugar showed increased atheromatic index. In addition, groups with the higher atheromatic index presented statistically significant higher total antioxidant status. Trans FA are also positively associated with sTAS and on the other hand dietary cholesterol is negatively associated with sTAS and positively in groups B and C.
Dietary intake (DI) assessment A 3 day food recall (one weekend day and two weekdays) was used to estimate the dietary intake. All participants were asked to describe in detail the quantity and type of food consumed those 3 days. The 3 day dietary intake recalls were conducted in face-toface interviews. Written and verbal instructions were given in order to complete their food recalls. Dietary intake was assessed using the Food Processor, computer program for nutrient analysis, (version 7. 4) with Greek foods included and was expressed as the mean of the three recalled days.
Statistical analysis For statistical analysis, SPSS tool version 22. 0 was used. Descriptive statistics presented as mean ± standard deviation and frequencies as percentages. KolmogoroveSmirnov analysis verified the normality of the data set. Pearson's chi-square test or chisquare test of association was used to discover if there is a relationship between the categorized data, while Fisher's exact test was used when expected variable were <2% of total number of variables. Additionally, independent sample t-test was used to compare between means. In all statistical analysis, level of significance (p-value) was set at a ¼ 0. 05.
Cell imaging was performed with a confocal microscope (Leica DM5500 TCS SPE). Flow cytometry. Cells were resuspended in PBS + 2 mM EDTA, labeled with 100 nM TMRM (T5428, Sigma-Aldrich) and analyzed with FACSCcalibur (BD Biosciences). Data were quantified with the FlowJo software (FlowJo, LLC). Guinea pig plasma analysis. 3-week Dunkin-Hartley guinea pigs (Charles River) were fed for fifteen days with a standard diet (400 mg ascorbate/kg, Safediet ref. 106) or an ascorbate-deficient diet (< 50 mg ascorbate/ kg). Blood samples were collected in Hypoxytubes; plasma ascorbate concentration and pO 2 were determined as described above. Procedure approved by the Institut Pasteur ethics committee (auth. n°190127).
Acknowledgements This work was supported by the  French National Research Agency :  ANR JCJC 2017-17-CE15-0012  (BSM). We thank  Dr. Naomie Taylor  ( NIH ),  Pr. Cormac Taylor  ( University Dublin ) and  Dr. Nicolas Prat  ( Institut de Recherche Biomédicale des Armées ) for their critical and challenging reviews of the manuscript.
Summary Background. -Sub-Saharan Africa is experiencing a rising burden of hypertension. Antihypertensive medications and diet are the cornerstone of effective hypertension control. Aims. -To assess adherence to medication and salt restriction in 12 sub-Saharan countries, and to study the relationship between adherence and blood pressure control in patients with hypertension. Methods. -We conducted a cross-sectional survey in urban clinics in twelve sub-Saharan countries. Data were collected on demographics, treatment and adequacy of blood pressure control in patients with hypertension attending the clinics. Adherence was assessed by questionnaires completed by the patients. Hypertension grades were defined according to European Society of Cardiology guidelines. Association between adherence and blood pressure control was investigated using multilevel logistic regression analysis, adjusting for age, sex and country.
Questionnaire The questionnaire was conceived by the authors of the study, and included two major sections. The first section was completed by patients, and collected data on patient demographics (age, sex, marital status, etc. ), individual salt consumption and adherence to treatment. The second section was filled out by the physician during the consultation, and collected data on the patient's socioeconomic status, drug regimen, clinical data, BP values (measured in standardized conditions; see below) and cardiovascular risk factors.
Statistical methods Continuous and categorical variables are expressed as means ± standard deviation and numbers (percentages), as appropriate. The characteristics of the study participants were compared according to their adherence category using logistic regression, adjusting for country. First, logistic regression models were used to quantify the association between uncontrolled BP and poor adherence, using good adherence as the reference category. Then, polytomous logistic regressions were used to quantify the association between hypertension grades and poor adherence categories, using good adherence as the reference category. All regression models were adjusted for age, sex and country. All analyses were performed through scripts developed in R software, (version 3. 2. 3). The level of significance was set at P < 0.
Participants We enrolled 2198 individuals in 12 sub-Saharan countries between January 2014 and November 2015. Patients' baseline data are reported in Table  1 ; 60. 2% were women, and the mean age was 57. 7 ± 12. 0 years for women and 59. 2 ± 11. 4 years for men. Among participants, 41. 6% had a low education level (no education or primary education), 33. 3% had a medium level (secondary school) and 25. 1% had a high level (tertiary or above). The majority of patients were living in an urban setting (n = 1702, 78. 9%). Most patients (n = 1816, 84. 4%) had been diagnosed with hypertension for more than a year. During the consultation, 1692 patients (77. 4%) had uncontrolled BP. A total of 648 (38. 3%), 558 (33. 0%) and 486 (28. 7%) patients had grade 1, 2 and 3 hypertension, respectively. Overall, 2094 participants were aware of their condition (95.
Quantifying travelling waves As demonstrated by both theoretical and experimental evidence  (Nunez, 2000; Nunez and Srinivasan, 2014; Nunez and Srinivasan, 2009) , in most systems, including the human brain, travelling waves occur in groups (or packets) over some range of spatial wavelengths having multiple spatial and temporal frequencies. Given any configurations of electrodes, only parts of these packets can be successfully detected, i. e. waves shorter than the spatial extent of the array, and waves longer than twice the electrode separation distance (Nyquist criterion in space). In scalp recordings, the shorter waves may be mostly removed by volume conduction. As a consequence, waves recorded directly from the cortex emphasize shorter waves than the scalp recorded waves. Specifically, in the case of small cortical arrays, the overlap between cortical and scalp data may be minimal, and the estimated wave properties (including propagation direction) may differ.
Does DMT influence travelling waves? After defining our measure of the waves' amount and direction, we investigated whether the intake of DMT alters the cortical pattern of travelling waves. Participants underwent two sessions in which they were injected with either placebo or DMT (see Materials and methods for details). Importantly, during all of the experiments, participants rested in a semi-supine position, with their eyes closed. EEG recordings were collected 5 min prior to drug administration and up to 20 min after. The left column of Figure  2A  shows the amount of BW and FW waves in the 5 min preceding and following drug injection (either placebo or DMT). Consistent with previous observations on independent data  (Alamia and VanRullen, 2019) , during quiet closed-eyes restfulness a significant amount of BW waves spread from higher to lower regions (as confirmed by a Bayesian t-test against zero for both DMT and Placebo conditions, BFs 10 >>100, error <0.
16, q-band: BF 10 = 19. 23, a-band: BF 10 = 16. 04, b-band: BF 10 = 0. 64; all errors < 0. 001%) and BW waves (d-band: BF 10 = 82. 56, q-band: BF 10 = 30. 58, a-band: BF 10 = 549. 54, b-band: BF 10 = 1. 43; all errors < 0. 005%). This result corroborates a previous analysis performed on EEG recordings from the same dataset (Timmermann et al. , 2019) as well as independent data pertaining to O-Phosphoryl-4-hydroxy-N,N-DMT (psilocybin), a related compound  (Muthukumaraswamy et al. , 2013). Moreover, we investigated how DMT influences the amount of waves at each frequency. As shown in Figure  3B , and in agreement with previous analyses, DMT induces an overall reduction in the amount of waves at each frequency, specifically in the alpha-band BW waves, but with the notable exception in the FW alpha band, in which DMT induces an increase in the waves' direction.
Participants and experimental procedure In this study we analysed a dataset presented in a previous publication  (Timmermann et al. , 2019) , to address a very different scientific question using another analytical approach. Consequently, the information reported in this and the next paragraphs overlaps with the previous study (to which we refer the reader for additional details). Thirteen participants took part in this study (six females, age 34. 4 ± 9. 1 SD), sample size was chosen based on prior EEG and MEG studies and effect sizes with similar compounds. All participants provided written informed consent, and the study was approved by the National Research Ethics (NRES) Committee London -Brent and the Health Research Authority. The study was conducted in-line with the Declaration of Helsinki and the National Health Service Research Governance Framework.
, 2011) , which could have led to confounding effects on the following session if DMT had been administered in the first session. Additionally, we aimed at ensuring familiarity with the research environment and the study team before providing the psychedelics compound. Given the lack of human data with DMT, progressively increasing doses were provided to different participants (four different doses were used: 7, 14, 18 and 20 mg, to 3, 4, 1, and 5 successive participants, respectively). EEG signals were recorded before and up to 20 min after drug delivery. Participants rested in a semi-supine position with their eyes closed during the duration of the whole experiment. The eyes-closed instruction was confirmed by visual inspection of the participants during dosing. At each minute, participants provided an intensity rating, while blood samples were taken at given time-points (the same for placebo and DMT conditions) via a cannula inserted in the participants' arm.
EEG preprocessing EEG signals were recorded using a 32-channels Brainproduct EEG system sampling at 1000 Hz. A high-pass filter at 0. 1 Hz and an anti-aliasing low-pass filter at 450 Hz were applied before applying a band-pass filter at 1-45 Hz. Epochs with artifacts were manually removed upon visual inspection. Independent-component analysis (ICA) was performed and components corresponding to eyemovement and cardiac-related artifacts were removed from the EEG signal. The data were re-referenced to the average of all electrodes. All the preprocessing was carried out using the Fieldtrip toolbox  (Oostenveld et al. , 2011) , while the following analysis were run using custom scripts in MATLAB.
Statistical analysis All the analyses regarding the EEG signals were performed in MATLAB. Bayesian analyses were run in JASP  (Team, 2018). We ran separate Bayesian ANOVA for FW and BW conditions, and we considered as factors the time of injection (pre-post, see Figure  2A ) and drug condition (DMT vs Placebo). Subjects were considered to account for random factors. Regarding the minute-by-minute analysis (Figure  2A , right panels), we performed a t-test at each time-bin against zero, and we corrected all the p-values according to the False Discovery Rate  (Benjamini and Yekutieli, 2005). All data and code to perform the analysis are available at https://osf. io/wujgp/.
, 2019). Samples were run in duplicate. Primers (Table  1 ) were designed using OLIGO 6. 42 software (MedProbe, Norway). The lower the cycle threshold (Ct) value the higher the amount of mRNA, RT negative controls and no-template controls had Ct values > 40. RT negative controls and no-template controls had Ct values > 40. cDNAs from HEK293 cells were used to validate primers of human genes of interest. The relative expression of each gene of interest X as compared to the expression of the housekeeping gene encoding TATA box-binding protein (TBP) was calculated as 2 -(Ct(X)-Ct(TBP)). Gene expression of genes having a Ct higher than 33 was not quantified.
Two height measurements were taken and recorded to the nearest millimeter using stadiometers (model 208; Seca, Hamburg, Germany). Weight was measured in duplicate and recorded to the nearest 100 g using an electronic scale (model HS-302; Tanita, Tokyo, Japan). Mean values were used for calculating height and body mass index (BMI), which were subsequently transformed into height for age z-scores (HAZ) and BMI for age z-scores (BAZ) using WHO AnthroPlus software  19, 20. Hemoglobin concentrations were measured onsite at a field laboratory using an automated cell counter (ABX Micro 60; Horiba, Montpellier, France). The blood samples were then frozen at -70°C on dry ice and shipped to São Paulo, where they were subsequently analyzed within 6 months of collection. Plasma ferritin and soluble transferrin receptor concentrations were assessed using commercially available enzyme immunoassays (Ramco, Houston, Texas).
Funding: This study was funded by the  Brazilian National Council of Technological and Scientific Development, CNPq  (Grant nos. 551359/2001-3 ,  502937/2003-3 ,  307728/2006-4 , and  470573/2007-4 ) and the  São Paulo Research Foundation ,  FAPESP  (Grant no. 2007/53042-1 ). KJF was supported by the  MIRES Mobility Grant  from l' Université Sorbonne Paris Cité, France.
Parental Selenium Resulted in a Weak Group-Wise DNA Methylation Clustering Reduced representation bisulfite sequencing (RRBS) data were first processed and aligned to the rainbow trout genome (Table  A1 ). For downstream analysis, only uniquely mapped reads (47. 6 ± 1. 4%) were used. Of the 12 samples sequenced (4 per dietary group), none appeared as an outlier. In the search for the global methylation pattern with all the mapped CpG sites, t-SNE (t-distribution stochastic neighbor embedding) was used. The individual methylation pattern was stronger compared to group-wise global patterns, with only a weak group-wise clustering identified when using the 95th percentile of the CpC variance (Figure  4 ). The stronger individual variation compared to group-wise clustering was confirmed using other methods including PCA, hierarchical clustering and correlation analysis (Figure  A1 ).
SS and NC vs. SO was detected on 3663 genes, whereas SS vs. SO displays a specific effect of the Se source on 2387 genes. In all datasets, multiple KEGG pathways were significantly enriched-22 in SS:NC, 18 in SO:NC and 20 in SO:SS (Figure  A2 ). These KEGG pathways relate to diverse biological mechanisms, mainly cellular metabolism and environmental information processing, but also the organismal system and cellular processing. Among the five genes with the highest number of DMCs listed for each of the sub-regions (exon, intron, proximal promoter, promoter and distal promoter) in Tables C1-C3, three genes were common. The limbic system-associated membrane, transcript variant X5 protein (Isamp) belongs to the immunoglobulin super-family, known to be expressed and excreted in the developing forebrain showed 15 DMCs in SS:NC, 24 in SO:NC and 22 in SO:SS, all located in the intron region.
Parental Selenium also Affects Methylation in Genes Related to the 1C Metabolism Several genes related to the methionine cycle and transsulfuration pathway were identified, but mostly they contained only single DMC sites (Table  3 ). An effect on the genes that provide selenocysteine for the selenoprotein synthesis was only detected in the organic Se treatment. Nevertheless, selenoprotein I and selenoprotein U had DMCs in both Se-supplemented treatments. In all datasets, multiple KEGG pathways were significantly enriched-22 in SS:NC, 18 in SO:NC and 20 in SO:SS (Figure  A2 ). These KEGG pathways relate to diverse biological mechanisms, mainly cellular metabolism and environmental information processing, but also the organismal system and cellular processing. Among the five genes with the highest number of DMCs listed for each of the sub-regions (exon, intron, proximal promoter, promoter and distal promoter) in Tables A2-A4, three genes were common.