dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgements This study has been supported by the projects  PRODEX ACROSAT  ( 2014-2015 ) of the  European Space Agency  funded by the  Belgian Science Policy Office, GlobEmission  ( 2011-2016 ) funded by the  European Space Agency , and the  Sino-European   MARCOPOLO  project ( 2014-2016 ) funded by the  European Commission  within the  Seventh Framework Programme  (grant agreement:  606593 ). We acknowledge the free use of tropospheric NO 2 column data from the OMI sensor from www. temis. nl. The authors would like to acknowledge access to the FINNv1. 5,GFED, and GFAS fire emission databases.
The questionnaire was developed and pretested in English and translated into 9 languages (Spanish, German, Portuguese, Italian, French, Dutch, Russian, Mandarin and Japanese). Native speaker intensive care doctors and/or infection control practitioners translated the questionnaire. Each translation was independently verified by a second native speaking physician. Participation was anonymous. We used Limesurvey ® 2. 0, an open source web survey application, to collect the data  [19].
Data analysis Descriptive statistics were used to summarize characteristics of the study population Standard errors were calculated by dividing the standard deviations of each estimate by the square root of the sample size (n). Based on the 2015 World Bank classification  [20]  we categorized countries as low, middle and high-income. We computed weighted estimates for middle and highincome countries using total country population  [20]  as the weight (to correct for contributing responses from each country) for those that provided at least 10 completed replies (arbitrary cut-off ). Analyses were conducted using STATA 13 (svyset and svy commands for survey data for weighted estimates). Detailed country specific data are available as a Additional file 1. Data are freely available and have been deposited in the Dryad Digital Repository: http://dx.
Acknowledgments We are grateful to the following collaborating partners for their contribution to the project:  Aragao Irene ,  Cardoso Teresa ,  Lavorato Fabiana ,  De Vlaeminck Veronique ,  Francois Guy ,  Gusmao Dimitri ,  Lacroix Jacques ,  Quach Caroline ,  Amin Pravin ,  Bin Du ,  Watanabe Eizo ,  Kurahashi Kiyoyasu ,  Hosokawa Koji ,  Dongelmans Daniel ,  Schultz Marcus ,  Muzlovic Igor ,  Gutierrez Fernando Rafael ,  Gritsan Alexey ,  Grigoriev Evgeny ,  Buns Jeffrey ,  Taylor Phil ,  Su Fuhong ,  Nazer Lama ,  De Waele Jan ,  Vos Bénédicte ,  Ecoffey Claude ,  LaTerre Pierre Francois ,  Catry Boudewijn ,  Muehlen Marion.
Acknowledgments The authors would like to express their thanks to the curators and staff of the  Herbaria BR, BRLU, COI, G, K, MO , P, WAG, Z for making accessible their collections through loans or digital images. We are also indebted to  Barbara Mackinder  and  David Harris  (E) who have made available unpublished results on phylogeny of Englerophytum and allied genera. Many thanks also to  Antonio Fernandez ,  Gabriela Loza ,  Lucy Smith  and  Alice Tangerini  for their nice drawings. Paul Maas kindly allowed us to publish his photograph of Englerophytum paludosum and  Moses Sainge  one of the photographs of E. sylverianum. The  Center for Tropical Forest Science -Forest Global Earth Observatory of the Smithsonian Tropical Research institute  is thanked for their support of fieldwork that led to the discovery of E.
Whether this difference in effect of the α7 subtype between AZD3043 and propofol in the lower concentration range translates to a clinical finding needs to be explored. The affinity to several receptors other than those that are the primary targets for general anesthesia may give rise to side effects of general anesthetics, but may also have potentially-advantageous properties  [3]. One of these is the muscle relaxant effect of propofol when given in higher doses  [9]. It is generally accepted that propofol is the general anesthetic with the highest muscle relaxant effect on laryngeal and pharyngeal muscles, however the exact mechanism behind the muscle relaxation properties of propofol is not fully understood and conflicting data exists  [20] [21] [22]. In order to evaluate the relevance of the propofol-and AZD3043-induced inhibition of the nAChR subtypes studied here, the IC 50 values needs to be correlated with clinically relevant concentrations for both drugs.
The IC 50 values presented here for propofol and AZD3043 at the nAChR subtypes studied are higher compared to the concentrations needed for a positive modulation of the GABA A receptor, but are comparable to the exposure after a high bolus dose of propofol given during induction. The in vitro data presented here also needs to be correlated with effects measured in the intact NMJ of animal and in humans. However, if the proposed muscle relaxant effects during induction can be confirmed in such systems a potential use of AZD3043 could be as an intravenous anesthetic with muscle relaxant properties in addition to the predicted anesthetic effect. Again, this needs to be confirmed in animal and human models and, therefore, more studies are warranted both on AZD3043 and propofol in this aspect.
When propofol and AZD3043-induced inhibition was studied, the same equation was used and EC 50 was replaced by IC 50 , which is the concentration of antagonist eliciting half maximal inhibition. Data are presented as mean ˘S. E. M or 95% confidence interval (95% CI) as appropriate. The concentration-response curves are global fits of all oocytes, whereas the IC 50 values were analyzed statistically on the basis of individual oocyte fits that were analyzed as sets. IC 50 values for the effect of propofol and AZD3043 in individual oocytes were compared using independent t-tests for each nAChR subtype. GraphPad Prism (Prism 6. 0, GraphPad, San Diego, CA, USA) was used for statistics and graphs. A P-value of <0. 05 was considered significant.
Background: While the main causes of maternal mortality in low and middle income countries are well understood, less is known about whether patterns for causes of maternal deaths among adolescents are the same as for older women. This study systematically reviews the literature on cause of maternal death in adolescence. Where possible we compare the main causes for adolescents with those for older women to ascertain differences and similarity in mortality patterns. Methods: An initial search for papers and grey literature in English, Spanish and Portuguese was carried out using a number of electronic databases based on a pre-determined search strategy. The outcome of interest was the proportion of maternal deaths amongst adolescents by cause of death. A total of 15 papers met the inclusion criteria established in the study protocol.
Methods Our study was designed to comply with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement  [12] , and in order to make our study replicable, we developed and followed a clearly defined protocol. We initially searched the following datasets for papers in English, Spanish and Portuguese published since 1974 to February 2015: Pubmed (which includes Medline), Embase, CINAHL, POPLINE, the Latin American and Caribbean Health Sciences Literature database (LILACS), and the Index Medicus for the World Health Organization's Africa, South East Asia and Eastern Mediterranean regions (there were no comparable resources for other WHO regions). We also searched the Cochrane library and the WHO Reproductive Health Library. A summary of search terms used (which were adapted somewhat for different databases) is included in the Appendix.
One team (SM and SN) carried out the review of the English language papers, and a separate team (AVC and FS) reviewed the Spanish and Portuguese literature. One review author from each team performed the search and the initial screening of the titles and abstracts. Studies judged to be potentially eligible for inclusion and studies of uncertain but possible relevance were retrieved in full. These were then reviewed by two authors independently to apply the eligibility criteria outlined above. Any disagreement was resolved by discussion. Data extracted were entered into a predesigned data extraction form based on the criteria proposed by the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement  [14]  and the Transparent Reporting of Evaluations with Nonrandomized Designs (TREND) statement  [15].
The key information included: country/region, study design/ methodology, sampling, data source, number of deaths reported (including the number of adolescent maternal deaths), description of the population studied and the study setting (context) and resultsi. e. cause of death. Where available, we also extracted data on cause of death in older age groups for comparative purposes. Maternal death was defined as "the death of a woman while pregnant or within 42 days of termination of pregnancy, irrespective of the duration and site of the pregnancy, from any cause related to or aggravated by the pregnancy or its management but not from accidental or incidental causes 1 "  [16]. If papers included incidental causes these were removed, and the proportions recalculated. Two papers contained numbers of cases for each cause of maternal death, along with an estimate of numbers for all maternal deaths in the sample but did not report the data in a form which fulfilled our criteria i.
Studies of causes of maternal mortality overall suggest geographical variation  [10] , so findings were grouped by region. We used WHO regions for this, slightly adapted by the use of "sub-Saharan Africa", rather than "Africa", because no studies from North African countries were identified during the review. Because the groupings of causes were not consistent across the studies, and we expected heterogeneity between regions, meta-analysis was not appropriate so the results are written up and presented as a narrative synthesis. The search of the databases yielded 1735 English language abstracts and 187 Spanish and Portuguese language abstracts. Following their assessment 51 English and 36 Spanish and Portuguese full texts were requested of which three were unobtainable (see Fig. 1  for PRISMA Flow Chart).
However, it was not possible to identify any clear differences in major causes between community or hospital based studies in the papers included. A further problem was lack of consistency between the studies as to how the causes of maternal deaths were categorised: only six of the fifteen studies  [17] [18] [19] [31] [32] [33]  attempted to draw on the International Classification of Diseases (ICD) system when grouping causes of death. A recent study  [51]  demonstrated the feasibility of applying the most recent WHO maternal mortality ICD developed in 2012  [52]  to retrospective classification of causes of maternal mortality, and found it a feasible tool for use with existing datasets of maternal death reviews. It has an additional advantage of also allowing underlying and contributing factors to be recorded and analysed separately.
Data were registered using an analogue-digital converter (MP150, BIOPAC Systems Inc. ) and the AcqKnowledge software. Data acquisition rate was 100 Hz. Quantitative waveform analysis was done by measuring the time between the minimum value of the original radial pressure wave and the peak value of the reflection wave. Additionally, the relative time-position of the reflected wave within the pressure cycle (i. e. , time between the minimum value of the original pressure wave and the peak value of the reflection wave divided by the overall cycle length) was studied to test the hypothesis of the reflection wave travelling faster as a result of the increased vascular tone. Systolic and diastolic arterial pressure values were computed from the maximum and minimum values of the original radial pressure wave.
EXPERIMENTAL DATA In order to test the hypothesis that the presence of the dicrotic notch is related to the degree of peripheral vasoconstriction, we recorded the arterial pressure waveform registered continuously from the arterial line of patients undergoing peripheral vascular surgery. Data were taken from short, stable periods during the surgery, in which the only modification introduced was the injection of an intravenous bolus of phenylephrine. No vascular clamping or additional drug modifications were taking place at the time. Periodic oscillations in pressure waves were due to respiratory variations, which may be emphasized in patients under mechanical ventilation. Figure  2A  shows data from Patient 1, an 81 year-old female smoker with arterial hypertension undergoing abdominal aorta prosthetic replacement after the diagnosis of an infrarenal abdominal aortic aneurysm.
1% Tween 20) with specific antibodies overnight at 4 °C. After overnight incubation in primary antibodies, membranes were washed three times in TBST and subsequently incubated with species-appropriate, peroxidaseconjugated secondary antibodies (Santa Cruz Biotechnology) for 1 h. Blots were washed three times with TBST and once with TBS without Tween and developed using an enhanced chemiluminescence system (GE Healthcare). Images were captured on the Gel-Doc system (Bio-Rad), and densitometry analysis was performed using ImageJ software (National Institutes of Health). Integrated density of phospho-modification of target proteins was normalized with its total protein levels, and the target protein was normalized with the indicated internal controls (␤-actin or GAPDH); the mean was plotted in graphs.
6). Statistical significance of differentially expressed genes was ascertained in terms of the false discovery rate  (36). Complete dataset was submitted to the GEO repository (GSE68803). Principal components analysis based on gene expression demonstrated a clear separation between the three experimental groups and no outliers. Microarray-derived transcript expression was validated by RT-qPCR of top hit genes. A list of putative FOXO1 target genes was extracted from the FOXO1-ChIP-Seq data reported by Shin et al. (37)  and compared with gene expression data from euthyroid, hyperthyroid, and FOXO1 knockdown ϩ hyperthyroid groups of mice. Pathway enrichment analysis was conducted via the Gene Set Enrichment Analysis tool (38) using a list of KEGG pathways extracted from the Molecular Signatures Database (39) and a custom pathway constructed from the list of FOXO1 target genes  (37).
Pathways with greater than 260 genes or less than 10 genes were excluded from the analysis. All analyses were conducted using mouse gene symbols. Significance of pathway enrichment was ascertained by permutation testing of gene sets and calculation of the false discovery rate (FDR q value Ͻ0. 050). THRB1-ChIP-Seq data set was generated and used as described previously  (37, 40). Analysis of NAD ϩ /NADH Ratio-NAD ϩ /NADH cell-based assay kit (Cayman chemicals) was used to measure the NAD ϩ / NADH ratio in cultured cells in a 96-well plate format according to the manufacturer's protocol. Oxygen Consumption Rate (OCR) Measurement-To determine cellular oxygen consumption in HepG2 cells, the Seahorse Extracellular Flux Analyzer XF24 (Seahorse Bioscience, Billerica, MA), which measures the OCR, was used.
0%) were regulated by T 3 alone despite having Foxo1-binding sites. We further examined the 37 genes that either were regulated by T 3 alone (subset of 10 genes) or co-regulated by both T 3 as well as Foxo1 (subset of 27 genes) by analyzing a database containing hepatic Thrb1-binding sites generated by our previous ChIP-seq study (Fig. 1D ; Table  1 )  (40). Among the 10 genes regulated by T 3 alone, only two genes had Thrb1 binding within the proximal promoter or in the gene body (500 bp upstream of the transcription start site to the transcription end site) (Table  2 ) suggesting that other T 3 -regulated transcription factors/co-regulators may indirectly activate transcription of those genes. Of note, our previous study showed that almost all functional binding sites of T 3 -regulated target genes occurred in this proximal region of the promoter  (40).
Acknowledgments-We thank Dr. Parmeen Akhtar, Benjamin Livingston Farah (Cardiovascular and Metabolic Disorders Program, Duke-NUS Graduate Medical School), Dr. Ronny Lesmana (Universitas Padjadjaran, Indonesia and Cardiovascular and Metabolic Disorders Program, Duke-NUS Graduate Medical School), and Cyrielle Billon (Institut de Génomique Fonctionnelle de Lyon, Université de Lyon, Lyon, France ) for their helpful advice and constructive comments. We also acknowledge  Prof. Martin L. Privalsky  for the kind gift of HepG2 cells ectopically expressing THRB1 or no receptor vector as used in this study.
* This work was supported by  Duke-NUS Graduate Medical School Faculty Funds  (to P. M. Y. ),  National Medical Research Council/Early Development  Grant  1044/2011 ,  National Medical Research Council/Clinical   Investigator Research Grant   1340/2012 , and  National Medical Research Council /Clinician Scientist Award Grant   MH95:03/1-8 ,  Ministry of Health, Ministry of Education , and  Ministry of Trade, Singapore , and  A*StaR. The authors declare that they have no conflicts of interest with the contents of this article.
RNA-seq analysis Reads were mapped to the mm9 genome using tophat  (22)  (version 2. 0. 7) supplied with ensembl annotation (parameters: -G, -no coverage search). Transcriptomes were assembled with cufflinks (23) (version 2. 0. 2, parameters:q, -u, -b) and combined into a single assembly, including mm9 ensembl annotation with cuffmerge (parameters: -g, -s). The joint assembly was used as a reference for differential expression testing using cuffdiff (23) (parameters: -q, -N, -u, -b). Gene level differential expression analysis was performed with the aid of the R package 'cummeRbund'  (24)  by applying the following contrasts (␣ = 0. 05): NI (non-induced, i. e. solvent only) versus Dex, NI versus GW, NI versus DexGW, Dex versus DexGW and GW versus DexGW. Differentially expressed genes were combined into a single list (excluding non-protein coding genes), FPKM expression values were scaled across conditions (Z-score) and genes were re-ordered using a hierarchical clustering based on Euclidean distances.
Data were partitioned into clusters by cutting the clustering tree at the height of 2. 3, which resulted in 10 clusters. The result was visualized (Supplementary Figure  S4 ) and expression patterns were examined to identify the main patterns of interaction between the ligands and guide significance testing for co-regulated genes. Two smallest clusters with 1 and 3 genes, respectively, where omitted from the visualization and peak/gene ontology (GO) enrichment analysis. The following filter was used to extract cooperatively induced genes: up-regulation by DexGW as compared to NI and significantly higher expression in DexGW as compared to Dex and GW alone. GO-analysis of gene clusters was performed using 'goseq' R-package  (25). All enrichment p-values in GO analysis were corrected for multiple testing using the Benjamini-Hochberg method.
Accession numbers ChIP-seq and RNA-seq data have been uploaded to the NCBI-SRA repository and are available under SRP058743 accession. qPCR and ChIP-qPCR qPCR's were performed using Light Cycler 480 SYBR Green I Master Mix (Roche, cat. 04887352001) (primer list provided in the Supplementary Materials and Methods). qPCR data were normalized and quantified relative to the two most stable reference genes with qBase (26) and expressed relative to the control (NI) condition. Statistical analysis was performed using R (R Core Team (2014) R: A Language and Environment for Statistical Computing) and GraphPad Prism (see details in figure legends).
ns: non-specific band. GST-ctrl: GST fused to a 5HT7 serotonin receptor domain was used as a negative control. Catabolic fasting in mice correlates with an increased recruitment of phosphorylated AMPK at the Pdk4 enhancer (A) Mice (5 mice/group) were subject to overnight fasting, and subsequently allowed to a refeeding step for 30 min or kept at a fasting state. After the sacrifice, livers were collected, snap-frozen and used for ChIP-qPCR or for WB. ChIP-qPCR with anti-pAMPK antibody or IgG: The enrichment data are presented relative to input chromatin and represents the mean value from 5 mice ± SE. The statistical significance was assessed using a two-tailed t-test and '*' denotes P-value < 0. 05. (B) Western analysis result of one group of the experiment in (A) probed for liver AMPK and pAMPK (left panel) and of liver GR and phospho-Ser211 GR (right panel) in fast-refed and fast-fast samples, using actin as a loading control.
(C) Mice (5 mice/group) were subject to 3 h or 16 h fasting, followed by i. p. injection with either solvent or with Dex (2 mg/kg) and GW (2 mg/kg) for 4 h. After sacrifice, livers were collected, snap-frozen and further processed for mRNA analysis via qPCR. Household genes were selected via GENORM (qBase software package) and relative expression levels were calculated. Data were analyzed for statistical significance using a non-parametric Wilcoxon rank sum test; * and ** denote P-values < 0. 05 and < 0. 01, respectively. cooperative responses at the gene expression level can be pushed further when exogenously administering synthetic GR and PPAR␣ ligands over a background of (catabolic) fasting, we compared groups of mice fasted for either 3 h or 16 h, after which Dex (2 mg/kg) and GW (2 mg/kg) was given i.
Figure7. Catabolic fasting in mice correlates with an increased recruitment of phosphorylated AMPK at the Pdk4 enhancer (A) Mice (5 mice/group) were subject to overnight fasting, and subsequently allowed to a refeeding step for 30 min or kept at a fasting state. After the sacrifice, livers were collected, snap-frozen and used for ChIP-qPCR or for WB. ChIP-qPCR with anti-pAMPK antibody or IgG: The enrichment data are presented relative to input chromatin and represents the mean value from 5 mice ± SE. The statistical significance was assessed using a two-tailed t-test and '*' denotes P-value < 0. 05. (B) Western analysis result of one group of the experiment in (A) probed for liver AMPK and pAMPK (left panel) and of liver GR and phospho-Ser211 GR (right panel) in fast-refed and fast-fast samples, using actin as a loading control.
(C) Mice (5 mice/group) were subject to 3 h or 16 h fasting, followed by i. p. injection with either solvent or with Dex (2 mg/kg) and GW (2 mg/kg) for 4 h. After sacrifice, livers were collected, snap-frozen and further processed for mRNA analysis via qPCR. Household genes were selected via GENORM (qBase software package) and relative expression levels were calculated. Data were analyzed for statistical significance using a non-parametric Wilcoxon rank sum test; * and ** denote P-values < 0. 05 and < 0. 01, respectively.
ACKNOWLEDGEMENT The authors thank  Dr Stéphane Plaisance  from the  VIB Bio Informatics Training and Service Facility (VIB-BITS)  for useful discussions and tutorials,  Dieter Defever  and  Anne-Sophie De Smet  ( Receptor Research Laboratories, VIB ) for the technical assistance with MAPPIT experiments and  Dr Anje Cauwels  for help with hepatocyte isolations.
ACKNOWLEDGMENTS We are very grateful to  H. Ulrich  for the anti-SMT3 antibodies;  F. Stutz  and  L. Texari  for their help with the tethering experiments;  S. Jentsch ,  F. Holstege ,  G. Prelich ,  Z. Wang , and  B. Johnson  for strains and plasmids; and  F. Jourquin  for technical help. V. G. is supported by the  Ligue Nationale Contre le Cancer  and by  L'Institut National Du Cancer  (TELOCHROM and  PLBIO14-012 ). M. L. was supported by the  Danish Council for Independent Research , the  Villum Foundation , and the  European Research Council  (ERCStG,  242905 ). S. S. was supported by the Fundaca ˜o para a Ciência e a Tecnologia.