dataesr/scientific-paragraphs-categorization huggingface dataset:
(f) Whole-mount staining of embryo using an anti-OCT4 and anti-SALL4 antibodies; a stack of images was acquired in confocal microscopy and reconstituted as a 3D image using AMIRA software. The merged image is shown in the centre. DE, definitive endoderm, VE visceral endoderm. (g) Anti-OCT4 immunostaining of E7. 5 embryos derived from a MesP1 cre/+ breeder crossed with Rosa26 tDTomato female. Whole-mount staining. (h) The posterior region of the embryo was enzymatically dissociated and cells were plated and immediately fixed on coverslip to be stained by an anti-OCT4 antibody and a secondary anti-alexa488 secondary antibody. Arrows indicate OCT4 + cells in the MesP1 cell lineage. OCT4 is either nuclear (h1) or cytosolic (h2, h3 and h4). Scale bars, 50 µm. (e) Anti-OCT4 immunoprecipitation of whole cell extract from control (Ctrl) or OCT4-overexpressing mesendodermal cells (Oct4OE).
The blot was incubated with both anti-OCT4 and anti-RAD21 antibodies. (f) Anti-OCT4 ChIP-PCR was performed from chromatin of control ZHBTc6 ESCs (Ctrl) or OCT4-overexpressing mesendodermal cells (Oct4OE). Sox-17 promoter was interrogated. Data are representative of three to four experiments (mean ± s. e. m). *Student's t-test, P≤0. 01. and Oct4OE (ZHBTc6 induced) mesendodermal cells. Interactions frequencies were normalized using the GAPDH locus whose 3D configuration was assumed not to change, as GAPDH is expressed to the same extent in both pluripotent ESCs and OCT4OE (ZHBTc6 induced) mesendodermal cells. The relative interaction frequency value is thus set to one for the interaction measured between the control GAPDH fragments. Data are representative of four experiments (mean ± s. e. m.
). 2  were used in PCR. Control primers, such as in exons, were used as controls (cartoons, a-c). Interaction frequencies were normalized using the GAPDH locus. The graphs show the frequency of interactions between chromosomes (Chr) 1 and 3. The gels show the specificity of the amplicons of the peaks of interaction; the sequence of amplicons was checked by sequencing. The relative interaction frequency value is set to one for the interaction measured between the control GAPDH fragments. Data are representative of four experiments (mean ± s. e. m. ). (b) Illustration of FISH experiments using a Sox2alexa488 and Sox17alexa568 probes showing the interaction between chromosomes 1 and 3 for both alleles (the nucleus is representative of 116 imaged nuclei of pluripotent stem cells; upper panels).
Acknowledgments We are grateful to the  Zootechnie team of Genethon  and his leader  Frederic Benevaut  for expert managing of the mouse colonies (Evry France). We thank  Daniel Stockolm  expert in cell imaging at the  Genethon Imaging facility  and the team of the  UCSD Neuroscience Microscopy Shared Facility. We are very grateful to  Drs Nicola Iovino  and  Giacomo Cavalli  ( Chromatin and Cell Biology lab, Institute of Human Genetics, CNRS, Montpellier, France ) for the critical reading of the manuscript and advices. We thank  Marie Cécile Gaillard  and  Dr Frédérique Magdinier  ( INSERM UMR910 ) for sharing protocols and advices for FISH assay. This study was funded by the  Agence Nationale de la Recherche (ANR Specistem  to M. P. ), la  Fondation de la Recherche Médicale (FRM  to M. P.
Spatial analysis Variations in the locations, infection status and strains of rats trapped across the study area were visualized spatially using the ArcGIS software, version 9. 3 (ESRI, Redlands, CA, USA). The mean distance between colonies in which a given strain was identified was compared with the mean distance between colonies in which different strains were identified using Student's T test; an alpha value of 0. 05 was used to identify significant differences. The statistical analyses were conducted using the R software, version 3. 0. 1 (R Development Core Team (2013), R Foundation for Statistical Computing, Vienna, Austria).
Conclusions Our study demonstrates the relevance of MST for the accurate characterization of Leptospira interrogans extracted-DNA from rat tissues. Improved typing methods are required to investigate the molecular epidemiology of leptospirosis, and MST could aid in achievement of the level of definition that is needed for proper interpretation, thereby offering novel perspectives for epidemiological surveillance and investigations. In the future, large-scale Leptospira genotyping using MST could provide substantial knowledge of leptospirosis in various host populations and habitats. This approach could generate valuable information that could be used to generate a phylogeographical database to improve epidemiological investigations and to track the sources of this disease in a particular epidemiological catchment area.
Acknowledgments We thank the city of Lyon and its public health department ( Dr. Gilbert Gault ), the waste plant  UIOM de Lyon  ( Mr. Joël Baud ) and the  Parc de la Tête d'Or  ( Drs. David Gomis  and  Guillaume Douay , managers) for assisting with rat and census data collection. We thank  Philippe Berny  and  Joffrey Goulois  for assisting with rat collections.
Subsequently, excess Congo red solution was blotted off the slide and the samples were analysed using both bright and polarized light. Infrared spectroscopy (FT-IR). Infrared spectra were recorded at RT using a Nicolet iS50 FT-IR spectrometer equipped with a DTGS detector. Peptides were analysed as solutions (after heating at 100 °C to break any pre-formed fibrils) or gels at 15 mM in D 2 O (for DFNKF 75 mM concentration was used). Spectra represent an average of 64 scans recorded in a single-beam mode with a 4 cm À 1 resolution and corrected for the background. The second-derivative analyses of the spectra were performed using the Nicolet FTIR software, Omnic 9. 0, with a 13-point and third polynomial order Savitzky and Golay function. Secondderivative spectra generated negative bands as compared with the original spectra, thus for comparison all the second-derivative spectra were multiplied by À 1.
Raman spectroscopy. Raman spectra were acquired at RT by using a Horiba Xplora MicroRaman instrument equipped with an Olympus BX-41 Microscope. An excitation wavelength of 785 nm was used. Laser power was attenuated by neutral density filters with a final power density of B0. 07 mW mm À 2. The low wavenumber detection limit is 140 cm À 1. Each spectrum was acquired with an exposure time of 5 s over 35 cycles. The raw data were first corrected from the baseline, using the JASCO Nicolet FTIR software, Omnic 9. 0, between 140.
, 2000 ; Figure  S1A ). E4F1-binding regions were defined by combining bioinformatic toolboxes provided by CisGenome and Qeseq software systems. Raw sequencing data are available on Gene Expression Omnibus (GEO) dataset repository (GSE57228). Genome sequences significantly enriched (Table  S1 ) by this E4F1 ChIP-seq were then annotated according to the transcription start site (TSS) of the closest gene (Table  S2 ). Peak read densities, displayed as a heatmap (Seqminer 1. 3. 3) of the 10kb (Figure  2A ) or 100-kb window (Figure  S2C ), centered on gene TSS. Our analyses identified 126 E4F1-binding sites that are mainly located in the promoter (<1,000 bp from TSS), 5 0 UTR, or first exons (Figure  S2B ) of 111 genes that are distributed along all chromosomes (Figure  S2A ). Strikingly, this ChIPseq profile was very similar in primary and p53 K0 ;Ha-Ras V12 MEFs, indicating this E4F1 cistrome is independent of p53 and of cell transformation (Figure  S2F ).
In parallel, we performed differential transcriptomic analyses (microarray GEO dataset GSE57240) on E4F1 WT ;p53 KO and E4F1 KO ;p53 KO cells or their Ha-Ras V12 transformed counterparts. Gene lists identified by these transcriptomic analyses were intersected with the list of genes directly bound by E4F1 according to our ChiP-seq (Figure  2B ). This led to the identification of a common set of 38 genes, the expression of which depends on the presence of E4F1 nearby or on their TSS, in all tested cell populations. Notably, 36 of these 38 genes were downregulated upon E4F1 inactivation, suggesting that E4F1 acts mainly as a transactivator for its target genes (Figure  2E ). A set of 26 genes was further validated as direct targets for E4F1 by ChIP-qPCR experiments performed in E4F1 WT and E4F1 KO MEFs.
To challenge the evolutionary conservation and specificity of this dual E4F1 transcriptional program, we monitored by ChIP-qPCR the presence of E4F1 at the human orthologous region of the Dnajc19, Ndufs5, Dlat, Chek1, and Rad52 genes in human U2OS cells. This assay confirmed that E4F1 was recruited on these genes in human cells (Figure  S2E ). Altogether, our data indicate that, regardless of the p53 status of the cells, E4F1 is bound to a novel regulatory motif located nearby the TSS of a limited set of genes involved in mitochondria homeostasis and stress responses, and it exerts a positive control on their expression. all cells (E4F1 KO and E4F1 WT ) were still viable (annexin-V negative) and actively growing. The overlap defines a set of 38 genes bound and regulated by E4F1in all cell lines.
High levels of ROS and decreased neo-synthesis of nucleosides both have been described as potent sources of DNA damage. Therefore, we also checked by comet assay whether E4F1 KO cells contained DNA damage. We observed that E4F1 KO primary MEFs exhibited increased comet assay tail moment (Figures  4G  and S4B ), and this defect was exacerbated in E4F1 KO transformed MEFs. In accordance with the presence of extensive DNA damage, we detected higher levels of g-H2AX (Figure  4H ) in E4F1 KO transformed cells. Altogether, these data indicate that E4F1 KO cells have accumulated uncompensated oxidative damage to proteins and extensive DNA damage. FL1-H (DCFDA) (legend continued on next page) E4F1 Directly Controls Chek1 Gene Expression with Impact on the CHK1-Dependent DNA Damage Response Our list of E4F1 target genes indicated the existence of a second E4F1 transcriptional sub-program involved in DNA damage responses and cell-cycle checkpoints (Figure  2 ) that pointed to the Chek1 gene.
Nucleotides Analysis and ATP/AMP Measurements To determine the concentration of purine and pyrimidine intermediates in p53 KO ;E4F1 WT ;Ha-Ras V12 and p53 KO ;E4F1 KO ;Ha-Ras V12 transformed MEFs (2 3 10 7 cells), soluble extracts were prepared and analyzed by gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-tandem mass spectrometry (LC-MS/MS) platforms (Metabolon) on eight independent samples for each cell line. ATP and AMP concentrations (Figure  3B ) were measured by high-performance liquid chromatography (HPLC) from 5 3 10 6 cells lysed in 65% perchloric acid. ATP levels, normalized to total protein levels, were confirmed on 2 3 10 4 cells using Cell Titer Glo (Promega) luminescent assay. See Supplemental Experimental Procedures for additional detail. ChIP-qPCR and ChIP-Seq Detailed protocols and primer sequences used for ChIP, as well as Bioinformatic tools and parameters used to treat ChIP-seq data and annotate E4F1-bound regions, are detailed in the Supplemental Experimental Procedures.
qRT-PCR and Differential Transcriptomic Analyses To identify genes with expression levels differentially expressed between E4F1 WT and E4F1 KO cells, total RNA was recovered using RNeasy Mini kits (QIAGEN). Of total RNA samples, 1 mg was amplified and Cy3-and Cy5labeled using Amino Allyl Message Amp II aRNA amplification kit (Ambion), hybridized on mouse HD12 plex Nimblegen arrays (135,000 probes/44,170 genes, platform MGX-Montpellier GenomiX, www. mgx. cnrs. fr/), and scanned on an Innoscan900 scanner (Innopsys). Raw data were normalized by Loess (Limma Package) and differentially expressed genes identified with both LIMMA and SAM packages with a false discovery rate (FDR) of 1% or 5%. Expression arrays are accessible at GEO dataset GSE57240. For validation RT-PCR, total RNAs were isolated in TRIZOL (Invitrogen) and used to generate cDNAs by SuperScript III reverse transcription (Invitrogen) in the presence of random hexamers.
Venn diagram of the overlaps among all E4F1-bound genes identified by ChIP-seq in p53 KO ;HaRas V12 transformed MEFs (GSE57228, in red) and genes differentially expressed (transcriptiome arrays GSE57240) between E4F1 WT and E4F1 KO cells (p53 KO ;E4F1 KO versus p53 KO ;E4F1 WT primary MEFs [blue] and p53 KO ;HaRas V12 ;E4F1 KO versus p53 KO ;HaRas V12 ;E4F1 WT transformed MEFs [green]) is shown. These genome-wide analyses were performed at a time when.
ACKNOWLEDGMENTS This work was supported by grants from the  French Ligue Nationale Contre le Cancer  (LNCC, C. S. Equipe labellisee 2011), from the  Agence Nationale pour la Recherche  ( ANR SVSE2-YinE4F1Yang2  and  MetaboCycle 2  to C. S. and L. L. C. ), and from the  Association pour la Recherche contre le Cancer  (to G. R. ). Institutional support was provided by the  Institut National de la Sante ét de la Recherche Medicale  (L. L. C. ) and the  Centre National de la Recherche Scientifique  (C. S. ), and technical support by the  Montpellier Rio Imaging (MRI) ,  Genomics (MGX)  and animal facilities. T. H. and M. L. were supported by fellowships from the  LNCC , and O. K. and H. D. by fellowships financed on the  ANR  grants  JCJC-0014-01  and  SVSE2-YinE4F1Yang2.
Venn diagram of the overlaps among all E4F1-bound genes identified by ChIP-seq in p53 KO ;HaRas V12 transformed MEFs (GSE57228, in red) and genes differentially expressed (transcriptiome arrays GSE57240) between E4F1 WT and E4F1 KO cells (p53 KO ;E4F1 KO versus p53 KO ;E4F1 WT primary MEFs [blue] and p53 KO ;HaRas V12 ;E4F1 KO versus p53 KO ;HaRas V12 ;E4F1 WT transformed MEFs [green]) is shown. These genome-wide analyses were performed at a time when Down E Ratio Pos. to Gene KO/WT TSS Motif Function Dnajc19 0,06 74 + Mito Ndufs5 0,11 -45 + Mito Mrfap1 0,14 -106 + 1700025K23Rik 0,18 352 - Psmb6 0,18 16 + Ipo8 0,2 -60 + Senp8 0,23 -168 + DDR/Chk Dlat 0,24 161 + Mito E4f1 0,25 -18 + mefs Taz Tsen2 0,25 0,26 164 53 + + Mito Elp3 0,27 -102 + Pbrm1 0,27 76 + Hax1 0,31 -91 + Mito Mrpl15 0,32 -67 + Mito Ncoa5 0,32 -195 + Brp44l 0,33 -128 + Mito Rad52 0,33 34 + DDR/Chk Dnajc9 0,34 -67 + E4F1 Ch-IP Eef1g 0,36 144 + Fktn 0,42 46 + AA408296 0,43 -79 + Bag5 0,43 -107 + Tube1 0,43 21 + Chek1 0,44 -56 + DDR/Chk Tgds 0,47 -112 + 4930402E16Rik 0,48 -45 + Mito Chek2 Wdr7 0,49 51 + BC019943/Tti2 0,52 -38 + DDR/Chk D1Bwg0212e 0,52 28 + E4F1 Ch-IP Plod1* Taf5 0,52 0,61 -4189 12 + + 2510003E04Rik 0,63 -94 + Mito 2510039O18Rik* 0,64 71 + 2310003H01Rik 0,65 -114 + DDR/Chk Mcts2 0,69 -9 + Lsm4 2,54 95 + Cep290 2,67 -598 + Figure 2.
Such a brick is called an edge-brick of G. Two vertices of B that are in G adjacent to the same vertex not in B are called a pair of B (with respect to G). Two semi-edges incident to vertices of the same pair of B are also called a pair. By definition an edge-brick of G contains two pairs of semi-edges. Notice that there exist bricks that are not direct-bricks. One example can be downloaded from the graph database HoG  [6]  by searching for the keyword Not_direct_brick  [7]. On another hand, we could show that any brick is an edge-brick of some cyclically 4-edge-connected cubic graph  [7]. We will show that Class 2 bricks can be obtained from the dot product of snarks. Before explaining this, we will give some useful properties that were noticed by Isaacs. Lemma 4  (Isaacs, 1975 [19] ) Let G be a snark and let B be a direct-brick of G.
Type 2 snarks Now, we are able to present the main result of this paper. Since a junction of a Class 2 brick with a Type 2 brick gives a Type 2 snark, we can construct Type 2 snarks. Theorem 5 There exist Type 2 snarks for each even order n ≥ 40. Proof: Any junction of the Type 2 brick of order 22 of Figure  3  and a Class 2 brick of order 18 as described in Section 3 (Figure  2 ) is a Type 2 snark of order 40. Using a computer to construct all possible combinations it was found that up to isomorphism there are 11 such Type 2 snarks of order 40. Figure  6  presents one of them. All graphs can be downloaded from the graph database HoG  [6]  by searching for the keyword Type2_Class2_40. From any Class 2 or Type 2 brick B it is easy to obtain a new one with two more vertices v and w: delete two semi-edges x•, y• and add edges xv, vw, wy and semi-edges v•, w•.
They can be downloaded from the graph database HoG  [6]  by searching for the keyword Type2_quad_free. Allowing squares and forbidding triangles, there are already more than 4. 000. 000 Type 2 graphs on up to 26 vertices. Fig. 7 : The only two Type 2 square-free cubic graphs of order up to 32. The first one is the graph obtained from K3,3 by replacing all vertices of one set of the bipartition by triangles, and the second one is the generalized Petersen graph P (9, 3).
Materials and Methods All reagents were obtained from commercial sources unless otherwise noted, and used as received. Heated experiments were conducted using thermostatically controlled oil baths and were performed under an atmosphere oxygenfree in oven-dried glassware. All reactions were monitored by analytical thin layer chromatography (TLC) or by Gas chromatography-Mass spectrometry (GC-MS). TLC was performed on aluminium sheets precoated silica gel plates (60 F254, Merck). TLC plates were visualized using irradiation with light at 254 nm or in an iodine chamber as appropriate. Flash column chromatography was http://sciforum. net/conference/mol2net-1 carried out when necessary using silica gel 60 (particle size 0. 040-0. 063 mm, Merck). All synthesized compounds were characterized by NMR, IR, MS data and by the TLC behavior.
B A C K G R O U N D Despite falling incidence of coronary heart disease and stroke, which makes up the majority of cardiovascular disease, there is increasing prevalence due to lower case-fatality. It remains the leading cause of death in both high-and middle-income countries  (WHO 2008) , and is increasingly the cause in low-income countries. In 2013, cardiovascular disease caused an estimated 30% of all global deaths, and killed 17. 3 million people worldwide (WHO 2011). In the United Kingdom (UK), in 2010, cardiovascular disease caused 32% of deaths, and killed just over 179,000 people. Analysing this data according to gender demonstrates no significant overall difference in numbers between men and women; 31% of women died from cardiovascular disease in 2010 in the UK (British Heart Foundation Statistics Database 2012).
The burden of coronary heart disease is costly, both in terms of reduced patient health-related quality of life, and healthcare costs in the management of these conditions. Morbidity statistics indicate that cardiovascular disease is the leading single cause of disability in Europe, with a prevalence of 6. 0% to 6. 5% in men and 4. 0% to 4. 5% in women within the UK. Cardiovascular disease is therefore costly in terms of both direct and indirect healthcare costs, accounting for 9. 8% of total disability-adjusted years (Townsend 2012). In 2009, it was estimated that cardiovascular disease cost the UK healthcare system approximately GBP 8. 6 billion, equating to approximately just under GBP 141 per capita. Overall, the cost from cardiovascular disease in the UK is estimated to be GBP 19 billion, the balance attributed to lost productivity and caring for those with cardiovascular disease (British Heart Foundation Statistics Database 2012).
Following these observational studies two large RCTs, the Heart and Estrogen/progestin Replacement Study, assessing secondary prevention (HERS I 1998) and the Women's Health Initiative, assessing primary prevention (WHI I 2002) were carried out and both appeared to contradict the evidence from observational studies. In light of these trials not confirming a cardioprotective effect of oestrogen, attention was focused on the age of the women enrolled in both HERS I 1998 and WHI I 2002 (mean age: 67 and 63 years, respectively), as non-significant data trends suggested hormone therapy did not lead to excess coronary risk when started shortly after the menopause and interest alighted upon the timing of initiation of hormone therapy in relation to the time of menopause. This 'timing hypothesis', first proposed in 2002, states that there may be a window of opportunity where hormone therapy is beneficial for prevention of cardiovascular disease in women when started in early menopause, with this benefit lost in older women.
Electronic searches We identified randomised controlled trials (RCTs) that assessed the effects of hormone therapy compared to placebo or no treatment with a minimum of six months duration through searching the following electronic databases on 25 February 2014: • Cochrane Central Register of Controlled Trials (CENTRAL;  Issue 1, 2014)  in The Cochrane Library, • MEDLINE (Ovid; 1946 to week 9 2014), • EMBASE (Ovid; 1980 to week 9 2014), • LILACS (http://lilacs. bvsalud. org/en/) (1982 to 25 February 2014). Additionally, we searched the following trials and research registers for any ongoing trials on cardiovascular disease on 25 February 2014: ClinicalTrials. gov ( www. clinicaltrials. gov), the World Health Organization ( WHO) International Clinical Trials Registry Platform ( www. who. int/ictrp/), the UK Clinical Research Network Portfolio Database ( http://public.
Selection of studies We identified relevant studies in two stages. Two review authors (HB and LH) independently screened the titles and abstracts returned by the database searches for relevance. The full text of any references that were considered as potentially relevant by either author were obtained. They then independently assessed the relevance of each paper, according to the review's prespecified eligibility criteria. This assessment was performed unblinded. Any discrepancies between the authors were resolved by recourse to the papers, and if necessary, a third author was consulted.
Results of the search For this update, we retrieved 3930 records from the database searches and found 33 additional records through other sources, bringing the total results to 3963. Of these, we excluded 3866 records after assessment of titles and abstracts. We considered the full text of 97 references for inclusion. We found six new trials (12 papers) for inclusion and additional 25 papers on ten previously included studies. We excluded 58 papers. One study has completed and is awaiting classification ( NCT00154180) and one study is ongoing (NCT00114517). The process of study selection for the original review in Figure  1  and for this updated review is presented in Figure  2. A summary of the main characteristics of the included trials is displayed in Table  2.
Implications for research Currently there is a lack of evidence regarding factors that may modulate the risks involved in hormone therapy treatment, such as different oestrogen and progestogen preparations, different durations, doses and routes of administration (for example, skin patches and creams). There is one recently published study (NCT00154180) and one ongoing study (NCT00114517) that assess the timing hypothesis through surrogate endpoints. They should lay the foundation for future research in this area, especially as supportive evidence for the timing hypothesis in this review comes from post-protocol subgroup analyses. Future updates of this review will look to incorporate their findings fully, but it may be that analysis of data at the level of individual participants from the existing trials is needed to evaluate the credibility of the timing hypothesis on mortality and coronary heart disease.
Exclusion criteria: • CHD event within six months of randomisation Data were not reported as events stratified to years since menopause. However, the mean age since menopause was 18 years and 84% of the study participants were > 60 years old when enrolled. For the subgroup analysis of when treatment was started, the entirety of events in this study were analysed as if all participants had started treatment more than 10 years after their menopause.