Emmenopterys henryi. We found that geography played a predominant role at all levels – phylogeographic clades are broadly geographically structured, the deepest levels of divergence are associated with major geological or pre-Quaternary climatic events, and isolation by distance (IBD) primarily explained population genetic structure. However, environmental factors are clearly also important – climatic fluctuations since the Last Interglacial (LIG) have likely contributed to phylogeographic structure, and the population genetic structure (in our AFLP dataset) was partly explained by isolation by environment (IBE), which may have resulted from natural selection in environments with divergent climates. Thus, historical and contemporary geography and historical and contemporary environments have all shaped patterns of genetic structure in E. henryi, and, in fact, changes in the landscape through time have also been critical factors.Examining how historical and contemporary geographic and environmental factors contribute to genetic divergence at different evolutionary scales is a central yet largely unexplored question in ecology and evolution. Here, we examine this key question by investigating how environmental and geographic factors across different epochs have driven genetic divergence at deeper (phylogeographic) and shallower (landscape genetic) evolutionary scales in the Chinese Tertiary relict tree  Understanding the contemporary and historical ecological  factors shaping population genetic diversity, structure, and divergence is of great interest to molecular ecology, evolutionary biology and conservation biology1245678941112131416For example, climatic fluctuations during the Quaternary which resulted in population isolation in multiple refugia are considered major drivers of population divergence and broad phylogeographic patterns1819521Cathaya, Ginkgo, Metasequoia, Davidia, Emmenopterys) are thought to represent remnants of the so-called ‘boreotropical flora’ that likely formed a belt of vegetation around the Northern Hemisphere during the Early Tertiary/Eocene2728Emmenopterys henryi Oliv. (Rubiaceae).So, how do historical and contemporary geographic and environmental factors contribute to genetic divergence at different evolutionary scales? This is a central yet largely unexplored question in ecology and evolution16232425Emmenopterys henryi is a particular suitable species for addressing these issues. This deciduous tree, which is the only extant species of its genus, is native to subtropical China, where it occurs in disjunct montane valleys of mainly warm-temperate deciduous (WTD) forests, at elevations ranging from c. 400–1600 (2000) m above sea levelE. henryiEmmenopterys species are known from the Eocene of North America and GermanyE. henryi. However, there is dated molecular evidence to suggest that the origin of this species dates back to the Early MioceneE. henryi exhibits significant population genetic structure and divergenceE. henryi across subtropical China. Our main objectives were to: (i) estimate the timing and pattern of divergence among populations of E. henryi; (ii) investigate how climatic and geographical variation over space and time explain patterns of phylogeographic and population genetic structure; and (iii) explore the specific environmental variables that may underlie local adaptation through natural selection in divergent environments.In this study, we integrate genetic markers that capture signatures from historical (chloroplast DNA) and contemporary  divergenceE. henryi were aligned along a total length of 2163 bp with 26 single-site mutations (including two 1-bp indels), 18 length polymorphisms (2–78 bp) and one inversion (27 bp) observed  was estimated to be 0.928 and within-population diversity (hS) was 0.332 , but πs was weakly related to latitude .The three cpDNA-IGS regions surveyed across the 443 individuals of observed . A totalal China ; Fig. 1Aal China ; Fig. 1Aas 0.332 . Regressbeast supported the monophyly of E. henryi [posterior probability (PP) = 1], and two main (‘Northern’ vs. ‘Southern’) lineages were recognized with weak support . The four cpDNA groups identified are populations S1–S6 in the east (Southeast group), S7–S23 in the middle , N1–N6 in the northeast (Northeast group), and N7–N15 in the northwest (Northwest group). This grouping is mostly consistent with the phylogenetic analyses . Hierarchical AMOVA, however, revealed that of the total genetic variation, 36.48% was distributed between the Northern lineage and the Southern lineage (ΦCT = 0.365), 45.43% was explained by variation among populations within regions (ΦSC = 0.715), and only 18.10% was found within populations  when compared to the Northern lineage  and in the Southern lineage , but no such structure was found in the Northern lineage  and the region scale .Non-hierarchical AMOVA  revealedE. henryi were aligned with a total of length of 767 bp, exhibiting 10 nucleotide substitutions  of otype R1 .E. henryi and P. bracteata diverged at c. 22 Ma . The onset of lineage diversification was estimated as 3.42 Ma  and 3.64 Ma . For this cpDNA-IGS chronogram, we recovered an average substitution rate of 6.225 × 10−10 s/s/y by the beast analysis, which is much lower than the average values generally reported for noncoding regions of the chloroplast genome (e.g. 1.2–1.7 × 10−9 s/s/y)373839Based on the assumption that E. henryi, at least one of the estimates of Tajima’s D and Fu’s FS was generally significant, except for the Central-Southwest group , with the exception of the Northeast group , we dated the three spatial expansions to the last glacial cycle(s)  were polymorphic. Different primer pairs amplified variable numbers of fragments, from 38 to 69, with an average of 50.8 ± 10.1 fragments per primer combination  varied widely , with PPF = 57.77%, I = 0.035, and HE = 0.023. Regression analyses showed that HE was weakly related to latitude .The nine primer combinations employed with samples from 37 populations  of bination . The perbination . Becaused widely . The higbaps identified nine different clusters , levels of population subdivision still remained high (ΦSC = 0.364), but were markedly higher in the Southern lineage (ΦST = 0.416) than in the Northern one  produced by clusters . All popclusters . In the clusters . The NJ clusters . With feclusters  and S2B.maxent model for E. henryi had high predictive power and did not overfit the presence data (AUC = 0.804 ± 0.003). The current distributional predictions  in this species. In both analyses, IBD explained more of the variation in genetic differentiation than IBE  and estimated that IBD (βD = 0.360 ± 0.037) contributed about twice as much as IBE (βE = 0.181 ± 0.151) to genetic distance. Similarly, MMRR also estimated the contribution of IBD  to be larger than that of IBE . Each analysis detected low levels of covariation between geographical and environmental distance (0.133 ± 0.028 in SEM and 0.488 in MMRR), although the covariation based on the MMRR analysis was approaching the reliability limit of 0.5  and multiple matrix regression with randomization (MMRR) analyses both revealed significant effects of IBD and IBE on neutral (non-outlier) AFLP divergence  and bio7  were the primary contributors, followed by bio1 , bio5 (max temperature of warmest month), bio9 (mean temperature of driest quarter), and bio15 . By contrast, slope, soil, and bio12  had very minor contributions.For the SEM analysis, we also quantified the contributions of the individual environmental variables to the composition of the environmental dissimilarity latent variable . The resfdist, 67 of 457 loci (14.66%) showed high probability (99.5%) for divergent selection among the nine baps groups, including 21 loci under directional selection and 46 loci under balancing selection  associated with at least two of the eight selected environmental variables , bio4 , bio5 (maximum temperature of the warmest month), bio12  and bio15  were most highly associated with the potential loci under selection.Using election . Additiobayescan . Eventua . The boundary between these lineages is located in the region of the Yangtze River and next to the Three Gorges Mountain Region  of E. henryi, at approximately the Mio-/Pliocene boundary [c. 5.06 Ma (1.68–8.91) Ma; see node 2 in 4345c. 3.4 Ma)46E. henryi through habitat fragmentation and the formation of physical barriers to gene flowTaxus wallichianaCercidiphyllum japonicumKalopanax septemlobusE. henryi during the last glaciations, indeed, is supported by our ENM analysis, which indicates larger distribution ranges of this lineage at the LGM compared to both the LIG and present  of its range. These groups  harbor lower genetic diversity (E. henryi phylogeny (tcs networks (c. 0.19 Ma (95% CI: 0.111–0.314 Ma) and c. 0.26 Ma , although, due to the broad confidence intervals, this interpretation requires some caution. In fact, the species is not predicted to have occurred in the northern Sichuan Basin and the Daba/Qinling Mts. during the LIG  once more coincides with the penultimate (Riss) glacial (see above). In addition to the ENM and MDA analyses . Thus, we found evidence of both isolation by distance (IBD)E. henryi populations, and broad-scale geographic and climatic factors appear to have shaped the spatial distribution of genetic variation in this species at both deeper evolutionary and more recent ecological time scales.Clearly, at broad phylogeographic scales, our results demonstrate distinct geographic genetic structure across the range of baps clusters of E. henryi along environmental clines. All four loci identified by both fdist and bayescan as undergoing putative diversifying selection . Altogether, these results are consistent with population genetic divergence under natural selection in divergent environments, suggesting this may have been the process generating IBE in this system.To examine the potential mechanism driving the pattern of IBE, we tested for loci under selection, in our AFLP dataset, and their associations with environmental/climatic variables. In identifying outlier AFLP loci, we sought to determine how selection might play a role in shaping genetic differentiation of the nine election  were asselection , suggestE. henryi, and, in fact, changes in the landscape through time have also been critical factors.In conclusion, by using phylogeographic, landscape genetic, and ecological niche modeling analysis together, we were able to identify the many factors, both historical and contemporary, that have shaped spatial genetic structure in this Tertiary relict species. At various spatial and evolutionary scales, we found that both geographical and environmental/climatic factors contribute to patterns of genetic structure. Geography played a predominant role at all levels – phylogeographic clades are broadly geographically structured, the deepest levels of divergence are associated with major geological or pre-Quaternary climatic events, and IBD primarily explained population genetic structure. However, environmental factors are clearly also important – climatic fluctuations since the LIG have likely contributed to phylogeographic structure, and the population genetic structure (in our AFLP dataset) was partly explained by IBE, which may have resulted from natural selection in environments with divergent climates. Thus, historical and contemporary geography and historical and contemporary environments have all shaped patterns of genetic structure in Emmenopterys henryi throughout its range (n = 212) was also sequenced at the entire internal transcribed spacer (ITS) region of nuclear ribosomal DNA (nrDNA). Of these 433 individuals, 394  were surveyed for AFLPs (Pinckneya bracteata (Bartram) Raf., collected from the JC Raulston Arboretum , was selected as an outgroup for the phylogenetic analyses based on a previous molecular phylogenetic study of RubiaceaeE. henryi are stored at the Herbarium of Zhejiang University .We obtained silica-dried leaf material from 38 populations of or AFLPs ; Fig. 1ApsbA–trnH, trnL–trnF, trnT–trnL) and the ITS region (i.e. ITS1 + 5.8S + ITS2). The primers and methodology for amplification of these four DNA regions were described in Shaw et al.et al.geneious v.4.8.5For the phylogeographic DNA analyses, we sequenced three cpDNA-IGS regions  and nucleotide (π) diversities were calculated for each population and the species overall using dnasp v.5.10tcs v.1.21permut was employed to compare parameters of population differentiation with unordered and ordered alleles  based on 1000 random permutationssamova v.1.0FST/(1 − FST) against the logarithm (log10) of geographic distance for all pairs of populations, or subsets thereof, following RoussetFor both cpDNA and ITS, haplotype (FT), the percentage of fragments that are polymorphic within each population (PPF), Nei’s (1973) gene diversity (HE), and Shannon’s information index I following the method of Lynch & Milliganaflpsurv v.1.0DW; according to Schönswetter & TribschK) in the AFLP dataset, we used three approaches. First, we used baps v.6.0q) with regard to the detected clusters. Second, we utilized genalex v.6.4phylip package 3.6 with 1000 bootstraps  selected by jmodeltest v.2.0ucld) model, and a coalescent model assuming constant population size were used to model the tree prior. Since no reliable fossils of E. henryi are currently known (see Introduction), we used the divergence time between E. henryi and P. bracteata, inferred from a fossil-calibrated cpDNA phylogeny of Rubiaceae, as a secondary calibration point to calibrate the stem node of E. henryitracer v.1.5 (http://tree.bio.ed.ac.uk/software/tracer/) to ensure that parameter values were fluctuating at stable levels. Based on these results, the first 5000 trees were discarded as burn-in, and the remaining samples were summarized as a maximum clade credibility (MCC) tree with mean divergence times and 95% highest posterior density (HPD) intervals of age estimates in treeannotator v.1.8.0figtree v.1.3.1 (http://tree.bio.ed.ac.uk/software/figtree/).To relate differentiation among cpDNA haplotypes of DFSarlequin to infer the demographic history of two main lineages identified  from their combined cpDNA-IGS sequences by mismatch distribution analysis (MDA) (further details in Tajima’s E. henryi has not changed (and will not change) its climatic preference over at least the last glacial/interglacial cycle and into the futureE. henryi across its range under present (1950–2000), past [the Last Glacial Maximum 80c. 130–114 kya)maxent v.3.2.1. In addition to the 38 distribution records included in this study, 76 herbarium-recorded presences were sourced from the Chinese Virtual Herbarium (www.cvh.org.cn) and the National Specimen Information Infrastructure of China (www.nsii.org.cn). Based on a total of 114 records, a current distribution model was developed using six bioclimatic data layers  available from the WorldClim database (www.worldclim.org)39http://gisweb.ciat.cgiar.org/GCMPage/) with 30 arc-second resolution.Assuming maxent. Values of the area under the ROC curve (AUC) between 0.7 and 0.9 indicate good fitModel performance was evaluated using receiver operating characteristic (ROC) analyses in FST) with arlequin using all putatively neutral (non-outlier) AFLP loci (i.e. 451 loci) described above. We obtained a total of 21 environmental and geographical variables for our study area, including 19 bioclimatic variables with 30 arc-second resolution (http://www.bioclim.org), a slope layer based on a digital elevation model with 1-km resolution from the USGS EROS database (http://eros.usgs.gov), and soil type from the Chinese soil taxonomy recordTo quantify the roles of geography and ecology in spatial genetic divergence, we quantified isolation by distance (IBD)588FST). MMRR provides a straightforward method for estimating linear regressions among distance matrices, while SEM allows for flexibility in defining the relationships among variables and utilizes latent variable modelling. For the MMRR analysis, we constructed an environmental distance matrix by taking the population pairwise Euclidian distances across all 21 environmental variables. We then analyzed the effects of environmental distance and geographic distance, as explanatory variables, on genetic distance, as the response variable, using the ‘MMRR’ function in Rhttp://cran.r-project.org/web/packages/lavaan/). Prior to analysis, all environmental, geographic, and genetic distance matrices were standardized. In each case, the analysis was used to test three alternative hypotheses: (1) only geographical distance contributes significantly to genetic distance, (2) only environmental distance contributes significantly to genetic distance, and (3) geographical distance and environmental distance each contribute significantly to genetic distance. We performed both analyses on AFLP pairwise genetic distances (FST) for all populations.We then employed two related methods to quantify IBD and IBE: multiple matrix regression with randomization (MMRR)FST comparisons to identify the loci that are significantly different than expected under neutrality and a given demographic model; and (ii) correlative methods that look for associations between genetic variation and environmental variables. The key to using these approaches together is that they identify links between putative loci under selection and individual environmental variables. Hence, our primary purpose for using these tests was to identify the specific environmental variables that are potential drivers of genetic differentiation via divergent natural selection (e.g. IBE resulting from selection in divergent environments).Two different basic approaches allow screening for AFLP loci that are putatively under selection: (i) a genome scan test procedure based on fdistbayescanbaps analysis (K = 9). Then, to detect associations between allele frequencies and environmental variables, we used Multiple Linear Regression (MLR)fdist and bayescan, we computed their population pairwise frequencies of AFLP alleles at the 37 sampling sites. We extracted values for the geographical coordinates of each population from 19 bioclimatic GIS data layers with 30 arc-second resolution . We then regressed the allele frequencies of the retained outlier loci (dependent variables) on the selected environmental variables  using the MLR model . Sci. Rep. 6, 24041; doi: 10.1038/srep24041 (2016).


Background. Impaired fasting glucose (IFG) through the nondiabetic range (100–125 mg/dL) is not considered in the cardiovascular (CV) risk profile. Aim. To compare the clustering of CV risk factors (RFs) in nondiabetic subjects with normal fasting glucose (NFG) and IFG. Material and Methods. Cross-sectional study in 3739 nondiabetic subjects. Demographics, medical history, and CV risk factors were collected and lipid profile, fasting glucose levels (FBG), C-reactive protein (hsCRP), blood pressure (BP), anthropometric measurements, and aerobic capacity were determined. Results. 559 (15%) subjects had IFG: they had a higher mean age, BMI, waist circumference, non-HDL cholesterol, BP, and hsCRP (p < 0.0001) and lower HDL (p < 0.001) and aerobic capacity (p < 0.001). They also had a higher prevalence of hypertension , dyslipidemia , and obesity  and a higher Framingham risk score . The probability of presenting 3 or more CV RFs adjusted by age and gender was significantly higher in the top quintile of fasting glucose . Conclusions. IFG in the nondiabetic range is associated with increased cardiovascular RF clustering. According to the last National Health Survey 2009), the prevalence of diabetes in Chile has increased 50% after six years from 6.3 to 9.4%) , 2. This009, the  to 9.4% Metabolic syndrome is characterized by the clustering of several risk factors for diabetes and CV disease . InsulinDespite the clear relationship between MS, diabetes, and coronary heart disease, impaired fasting blood glucose (IFG) in the nondiabetic range (100–125 mg/dL) has not been contemplated as part of the CV risk profile, nor has its prevalence been determined across the National Health Survey. Moreover, there are some scientific societies that do not believe in the concept of the metabolic syndrome. Some relevant epidemiological studies and meta-analysis, including the Framingham study, have reported a higher risk of coronary events in patients with IFG. However, the relative risk is modest and in some cases it becomes nonsignificant when adjusted for traditional cardiovascular RF such as blood pressure (BP), cholesterol, smoking, and obesity , 8–10.Although current literature does not consider IFG (100–125 mg/dL) as an independent cardiovascular RF, it is important to consider that it maintains a close relationship with traditional CV RFs. Therefore, IFG could be a marker of RF clustering. This is important since it is known that clustering of CV RF has a multiplicative effect on the risk of CV disease and is associated with subclinical changes of carotid intima-media thickness (C-IMT) . In addiThe main aim of this study was to compare the clustering of cardiovascular RF between nondiabetic subjects normal fasting glucose (NFG) and IFG.This was a cross-sectional study in 3739 subjects (36% women) who were evaluated in a CV prevention program in Santiago between 2002 and 2014. Exclusion criteria were subjects with a previous diagnosis of diabetes, fasting blood glucose ≥ 126 mg/dL and those in treatment with metformin. All subjects signed an informed consent, which authorized to use their data anonymously for academic purposes.Subjects were interviewed by the nurse of the program, who collected demographic data, medical history, medication intake, and history of traditional cardiovascular RF: dyslipidemia (DLP), hypertension (HTA), smoking, physical activity, and obesity.Subjects presented with 12-hour fasting and venous samples were taken to determine lipid profile, fasting blood glucose, and high sensitive C-reactive protein (hsCRP). Systolic blood pressure (SBP) and diastolic (DBP) blood pressure were measured on three separate occasions and the average was calculated according to the guidelines of “Seventh Report of the Joint National Committee” . The estFinally, subjects underwent a submaximal exercise stress test in which aerobic capacity in METS was determined when subjects reached the theoretical maximum heart rate or when they were exhausted.Total cholesterol, HDL cholesterol, and triglycerides were determined by standard enzymatic methods .LDL cholesterol was calculated by the Friedewald formula.Glucose was determined with the glucose oxidase method.hsCRP was measured in a subsample of 1618 subjects with the nephelometric method (Dade Behring).The lipid profile, fasting blood glucose, and hsCRP were determined in the laboratory with the following techniques:The following criteria were used to determine CV risk factors. (1) Dyslipidemia. Subjects with a previous diagnosis of DLP with or without drug treatment and/or LDL ≥130, HDL <40 in men and <50 in women, and non-HDL cholesterol ≥ 160 mg/dL, respectively. (2) Hypertension. Subjects with a previous diagnosis of hypertension with or without drug treatment or with SBP ≥ 140 mmHg and/or DBP ≥ 90 mmHg during the study. (3) Current Smoking. Subjects who had smoked daily ≥ 1 cigarette in the last month. (4) Physical Inactivity. Subjects who did not engage in any regular physical activity at least 1 time per week. (5) Obesity. Subjects with a BMI ≥ 30 kg/m2.t-test for independent samples. Significant differences were considered when the p value was <0.05.For analysis, subjects were divided into two groups according to fasting blood glucose: (1) impaired fasting blood glucose (IFG): subjects with FBG between 100 and 125 mg/dL; (2) controls with normal fasting glucose (NFG): those with FBG < 100 mg/dL. Cardiovascular RF and demographic data were compared between groups using In addition, a proportional odds model adjusted by gender and age was calculated to determine differences in the clustering of CV RF among FBG levels. Proportional odds determined the probability of presenting ≥1 CV RF and ≥3 CV RF according to fasting blood glucose level, as a continuous variable and quintiles .Mean age of the sample was 52 ± 13 years (36% were women); 559 (15%) subjects had IFG, 74% had DLP, 30% had hypertension, 21% were current smokers, and 52% were physically inactive. Only 43 hyperglycemic subjects (8%) presented with isolated IFG.p < 0.001), hypertension , and obesity  than NFG subjects. There were no significant differences in the prevalence of reported physical inactivity and smoking. However, aerobic capacity measured in METS was significantly lower in subjects with IFG compared to subjects with NFG . In addition, IFG subjects had a significantly higher Framingham risk score than NFG subjects .p < 0.001) and lower HDL (p < 0.001).p < 0.001) and women . According to the proportional odds model, the best determinants of RF clustering were age and FBG . There were no significant differences between genders  work together increasing future CV and metabolic risk. In our study, IFG subjects presented with worse parameters: lower HDL, higher triglycerides, higher BP levels, and higher waist circumference. Furthermore, IFG subjects had higher hsCRP levels than subjects with NFG. Today, hsCRP is accepted as a CV and metabolic risk factor. This is relevant in clinical practice, because both IFG and NFG subjects present with similar LDL cholesterol levels, which could be interpreted by clinicians as if these subjects would have the same CV risk, if fasting glucose levels were not considered in the risk equation.In 2002, Hoogwerf et al. reported that fasting glucose quintiles throughout the nondiabetic range were graded and continuously associated with cardiovascular RF . They alRecently, the American Heart Association (AHA) has described the concept of “ideal cardiovascular health,” in which subjects might meet criteria for both, a healthy lifestyle  and optimal values for biochemical parameters  . Within The last Chilean National Health Survey revealed a median fasting blood glucose of 98 mg/dL, which means that 50% of the Chilean population had a FBG value ≥ 98 mg/dL that despite being in an “optimal range” would be associated with a double chance of having 3 or more cardiovascular RFs according to our present study when compared to subjects with FBG ≤ 83 mg/dL . LookingIn summary, IFG is a marker of increased cardiovascular RF clustering in nondiabetic subjects even through normal FBG ranges (<100 mg/dL). This study emphasizes the importance of FBG as a factor to consider in the prevention of overall cardiovascular risk.This study has limitations. First, it is not free of selection biases as subjects were those who voluntarily attended a primary CV prevention program. Second, insulin resistance was not measured although it has been associated with MS pathophysiology. However, in the last definition of MS (ATP III harmonized) it has not been included. Neither was glucose tolerance measured. Postload glucose levels have shown a better association with CV risk than IFG , 15. How


A battery of cognitive tests was administered to evaluate working memory, attention and executive function.p ≤ 0.035) compared to the Controls. The PCOS group had 9–14% lower CMRglu in specific regions of the frontal, parietal and temporal cortices (p ≤ 0.018). A significant negative relation was found between the CMRglu and HOMA2-IR mainly in the frontal, parietal and temporal cortices as well as in the hippocampus and the amygdala (p ≤ 0.05). Globally, cognitive performance was normal in both groups but scores on the PASAT test of working memory tended to be low in the PCOS group.The PCOS group had 10% higher fasting glucose and 40% higher HOMA2-IR (glu that correlated inversely with HOMA2-IR in several brain regions and which resembled the pattern seen in aging and early Alzheimer’s disease. These results suggest that a direct association between mild insulin resistance and brain glucose hypometabolism independent of overweight or obesity can exist in young adults in their 20s. Further investigation of the influence of insulin resistance on brain glucose metabolism and cognition in younger and middle-aged adults is warranted.The PCOS group exhibited a pattern of low regional CMR In humase (FDG) ,3,4. These (FDG) . Indeed,se (FDG) . Craft’sse (FDG) . A recense (FDG)  and regise (FDG)  are alsoglu) in gray matter of brain regions associated with AD. The secondary aims were to determine whether differences in CMRglu in PCOS were associated with insulin resistance, or altered cognitive performance. PCOS is commonly associated with higher body-mass index (BMI) but we specifically selected cases with normal BMI in order to reduce the potential confounding effect of higher body weight on CMRglu [Our aim in the present study was to assess a condition in which the possible influence of mild insulin resistance on brain glucose metabolism could be studied independently of aging and obesity. Polycystic ovary syndrome (PCOS) is an endocrine disorder involving infertility, hyperandrogenism, and insulin resistance in women ,12. Manyn CMRglu .PCOS (n = 7) was diagnosed during a clinical examination using the Rotterdam criteria . Both thglu expressed as μmoles/100 g/min. In the regional analysis of CMRglu, the brain was segmented into 74 regions as defined by Freesurfer parcellation labels (Freesurfer Suite 5.0). CMRglu was calculated according to the Patlak method [glu were performed using tools implemented in PMOD 3.3 , as previously described [glu included a magnetic resonance (MR)-based correction for partial volume effect and differences in brain volume.For each participant, brain positron emission tomography (PET) images were obtained on a PET/CT scanner . Briefly, after a fasting period of 6–7 h, each participant was positioned in the PET-scanner in the early afternoon in a dark quiet environment. After intravenous administration of 5.6 ± 0.6 mCuries of FDG via a forearm vein catheter, dynamic scans  were obtained over a total duration of 60 min . Several blood samples were obtained to detect FDG radioactivity with a gamma counter  in order to determine the plasma time–activity curves required for the quantification of CMRk method . All regescribed . Calcula◦ and 1 mm isotropic voxels) were obtained for each participant using a 1.5 Tesla scanner . Regional and whole brain volumes were determined using FreeSurfer Suite 5.0 . Cortical brain anatomy was automatically parcellated into 33 regions of interest according to the Desikan-Killiany atlas [As previously described , T1-weigny atlas . Subcortny atlas .Most plasma parameters were measured using an automated clinical chemistry analyzer . Plasma total testosterone which was assayed by radioimmunoassay . Plasma insulin was analyzed by commercial ultra-sensitive enzyme-linked immunosorbent assay  with a Victor X4 multi-label plate reader . The homeostasis model assessment computational method was used to estimate insulin resistance (HOMA2-IR) from fasting plasma glucose and insulin .Evaluation of working memory and attention was based on performance on the Paced Auditory Serial Addition Test (PASAT)  and the p≤0.05. All regional imaging data including CMRglu comparisons underwent a p ≤ 0.05 false discovery rate (FDR) correction for multiple comparisons. Linear regression modeling was used to test whether HOMA2-IR was associated with CMRglu.Data are presented as mean ± SD. All statistical analyses were carried out using SPSS 17.0 software . The Mann–Whitney U-test was used for comparisons between the two groups with a statistical threshold of p ≤ 0.035; p ≤ 0.02).Fasting glucose and HOMA2-IR were significantly higher in the PCOS group compared to Controls . In the regional analysis, the PCOS group had significantly lower CMRglu in the right superior frontal cortex , left middle frontal cortex , right middle frontal cortex , left supramarginal cortex  and left middle temporal cortex   ; Fig 1.p ≤ 0.035 FDR-corrected): 10% smaller left superior frontal cortex , 14% smaller left supramarginal cortex  and 10% smaller right superior parietal cortex . Total intracranial volume, ventricle volume and cortical thickness were not different between the two groups .In comparison to the controls, the PCOS group had 10–17% lower volume of several brain regions, mainly in the frontal and parietal cortex .Globally, the PCOS group did not show any clinically significant cognitive impairment, ducation . Howeverducation . No corrglu in several cortical regions and in the hippocampus and amygdala was significantly inversely related to higher HOMA2-IR . The potential relationship between plasma total testosterone and CMRglu in the PCOS group was assessed but no significant correlation was found between these two parameters .CMRHOMA2-IR ; Fig 2. glu in the frontal, parietal and temporal cortex, and that HOMA2-IR was significantly inversely associated with CMRglu in several brain regions. Our findings add young women with PCOS to previous reports of regional glucose hypometabolism in the parietal and temporal regions in middle-aged and older people with insulin resistance as defined by the HOMA-IR [Our main observations are that in comparison with healthy women of similar age, education and BMI, women with PCOS had lower CMR HOMA-IR ,26,27,28glu in frontal, parieto-temporal, and cingulate regions in adults with pre-diabetes; a relationship that was not affected by age [glu in the middle temporal cortex, a region involved in auditory processing and language, and in the caudate, which is part of the motor circuit and is related to body’s voluntary movements. Our results agree with a recent study showing a negative relationship between serum glucose and CMRglu in the primary auditory and motor cortices of non-diabetic young adults aged 28 ± 8 y [Insulin resistance is a well-recognised feature of PCOS . In the d by age . In a lad by age . In AD, d by age . We obse28 ± 8 y .glu during aging, a deficit that spreads to the parietal and temporal cortices early in AD [e.g. mental rotation test, TAP Divided Attention, etc.) and episodic memory retrieval and consolidation . More complex tests should be used in order to avoid any potential ceiling effect in episodic memory retrieval. In the present study, no statistically significant relationship was found between insulin resistance and the different cognitive domains evaluated. However, others have found that HOMA-IR is negatively correlated to executive function in healthy women aged 35 [Globally, our PCOS group did not show any clinically significant cognitive impairment. However, five of the seven participants underperformed on the PASAT, an indication of potential cognitive difficulties in working memory. Some PCOS participants also had low-normal scores for episodic memory retrieval according to results from the delayed recall test and as confirmed by low-normal composite cognitive Z-scores. Several PET studies in normal aging have reported a relation between deficits in these cognitive domains and functional changes in the prefrontal cortex . The froly in AD ,32,33,34ly in AD . Schattmly in AD . Women wly in AD , visuosply in AD . Future  aged 35  and 45 y aged 35 .i.e. all HOMA2-IR scores were <1.5. Although insulin resistance is widely accepted to play a key role in the pathogenesis of PCOS [The present study was controlled for BMI and age, both of which negatively influence glucose uptake by the brain ,41,42. O of PCOS ,29 and i of PCOS , our PCO of PCOS . A previ of PCOS ; in futu of PCOS  and brai of PCOS . No corrOur results show that untreated normal weight women with PCOS had lower regional brain glucose uptake in a pattern that resembles that seen in older persons and, to a lesser extent, in early AD. Thus, mild insulin resistance and hyperandrogenism can be associated with regional brain glucose hypometabolism in young adults in their 20s. There was a non-significant trend towards potential cognitive difficulties that specifically involve working memory in the PCOS group. Further investigation and replication of the influence of mild insulin resistance on brain glucose metabolism and cognition in younger and middle-aged adults is warranted.


Angiogenesis-associated expression of VEGF , PF4 , PDGF-BB , and TGF-β1  differed in the PP samples of cancer and control subjects. In addition, protein concentrations were associated with clinical characteristics (P < 0.05). Circulating platelets in breast cancer sequester higher levels of PF4, VEGF, PDGF-BB, and TGF-β1, suggesting a possible target for early diagnosis. VEGF, PDGF, and TGF-β1 concentrations in platelets may be associated with prognosis.Platelets play a role in tumor angiogenesis and growth and are the main transporters of several angiogenesis regulators. Here, we aimed to determine the levels of angiogenesis regulators and epithelial-mesenchymal transition factors sequestered by circulating platelets in breast cancer patients and age-matched healthy controls. Platelet pellets (PP) and platelet-poor plasma (PPP) were collected by routine protocols. Vascular endothelial growth factor (VEGF), platelet-derived growth factor BB (PDGF-BB), thrombospondin-1 (TSP-1), platelet factor 4 (PF4), and transforming growth factor- Breast cancer is a common malignancy in women and has a high mortality rate . There aβ, and bFGF [The oncology community has long been interested in biological markers for tumor surveillance, early recurrence, and therapeutic efficacy. Tumor growth and metastasis depend on angiogenesis , 3 and aand bFGF –17. Mostand bFGF . Studiesand bFGF . It has and bFGF . Howeverβ1 in breast cancer patients and healthy controls. In addition, we investigated the association between these indicators and clinical characteristics.In the present study, we aim to explore whether the increased protein levels in circulating platelets are associated with breast cancer progression and if these proteins can be biomarkers for breast cancer diagnosis. Therefore, we measured VEGF, TSP-1, PF4, and PDGF as well as analyzed the epithelial-mesenchymal transition factor TGF-n = 37). Patients with platelet disorders or a medication history that would affect platelet physiology were excluded. Samples from the Department of General Surgery were collected before the operations. Samples from the Department of Oncology were collected at least 3 months after the conclusion of chemotherapy, radiotherapy, or medications for thrombocytopenia. The control group was selected from age-matched healthy female candidates with no history of platelet disorders or medications that may affect platelet function.Breast cancer samples at different tumor stages were collected from patients at the Surgery and Oncology Departments at Liaocheng People's Hospital .All patients were registered in the hospital admission system. Information regarding age, gender, surgical resection, tumor histology, hormonal receptor evaluation, and so forth could be accessed and collected from this system. Breast cancer staging was performed after surgery by histology and pathology according to the 2009 American Joint Committee Cancer Staging Manual. Hormonal receptors for estrogen (ER) and progesterone (PR) were regularly quantified by immunohistochemistry at the Department of Pathology, Liaocheng People's Hospital, following histology evaluation for breast cancer.Platelet isolation from whole blood was performed as described by Bergers et al. . In brieμL) was added to each pellet sample and vigorously mixed by pipetting and vortexing. PBS was used to dilute the lysed samples.Platelet pellet lysis was performed by using Abcam platelet isolation methods . Lysis buffer (2x) consisted of 2% NP40, 30 mM Hepes, 150 mM NaCl, and 2 mM EDTA, at pH 7.4. Lysis buffer (50 β1 (HG00468), IBL, Germany}. Preliminary experiments were performed to determine the optimal dilution range for each marker.Angiogenesis regulators were measured in PP and PPP. Patients with platelet disorders or a medication history that would affect platelet physiology were excluded from the study. All proteins were assessed by commercial ELISA kits according to manufacturer's protocols {human PDGF (HG04176), human TSP-1 (HG02106), human PF4 (HG021006), human actin (HG00954), human VEGF (HG06076), and human TGF-β1 was performed by acidifying with HCl and neutralizing with NaOH [μL sample was added to precoated wells and incubated for 1-2 h at 37°C as described in the kit protocols. After washing, 100 μL of conjugated secondary antibody was added and incubated for 1 h at 37°C or room temperature. The plates were washed three times; the substrate was added and incubated for 30 min at 37°C, followed by addition of the detection substrate and incubation for 25 min at room temperature. After a final wash, TMB substrate (100 μL) was added, and the mixture was incubated at 37°C for 30 min. The colorimetric reaction was stopped after 30 min with 100 μL stop solution. The results were analyzed by a Thermo Scientific microplate spectrophotometer at 450 nm.Activation of latent TGF-ith NaOH . BrieflyActin levels were used to normalize the platelet contents in each sample. Protein contents in PP samples were also normalized to actin, thus eliminating potential bias introduced during processing and lysis. By associating platelet actin levels with platelet counts, we verified our method of PP lysis. A reference PP sample (platelet control), made from PPP samples, was used to monitor platelet lysis, dilution, and testing as a common reference for conversion from platelet counts to platelet protein level . All stan = 37) were compared to those of healthy controls (n = 65) using the nonparametric Mann-Whitney U test. Protein contents in PP were normalized and expressed per 106 platelets; the results are shown in box-and-whisker plots [χ2 test or Fisher's exact test was applied to identify differences in protein levels between patient groups. The Statistical Package for Social Sciences v. 16.0 was used for all statistical analyses and significance was defined as P < 0.05.Median levels and interquartile ranges of each protein in breast cancer patients (er plots . Receiveer plots . Patient9/L). Clinical characteristics and ER/PR results are listed in The cancer patients represented four cancer stages and were aged 26 to 68 years. Platelet counts for all patients were within the normal range . However, in the PPP samples, TGF-β1 was lower in the cancer group than in the healthy controls; this maybe possibly due to sequestration of TGF-β1 by circulating platelets .TGF-β1  in PP is significantly different between the cancer groups and control groups (P < 0.0001) , PF4 , VEGF , and TGF-l groups . The ROCl groups . Combine 0.0001) .β1 in platelet was associated with clinical characteristics , cancer stage (stages I+II versus stages III+IV), hormonal receptor expression (low versus medium versus high). We found that the level of VEGF, PDGF-BB, and TGF-eristics .β1, angiopoietin-1 (Ang-1), and basic fibroblast growth factor (bFGF). These factors can promote vascular endothelial cell proliferation and formation of new blood vessels, which provide a suitable microenvironment for implantation and growth of tumor cells [Numerous reports have suggested the activation role of platelets in cancer progression, tumor growth, and metastasis –28. Theror cells .Recent study has found that the level of angiogenesis protein was increased in serum and tumor cells in patients with cancer –32. Angiβ1 levels were elevated in PP of the cancer group but not in PPP. These were consistent with the previous study of McDowell et al. [Our current data indicated that VEGF, PF4, PDGF-BB, and TGF-l et al. , and we Zaslavsky et al. demonstrated that the expression of TSP-1 in platelet is increased in a mouse model with Lewis lung cancer cell lines , suggestβ1 sequestration was increased in PP but decreased in PPP, although changes of concentration in PP are more robust. This may be due to elevated sequestration of TGF-β1 by platelets in cancer patients.In the present study, TGF-β1 was associated with lymph node metastasis, clinical stage, and molecular subtype. Molecular portraits of human breast tumors are usually divided into four subtypes: luminal A, luminal B, HER-2(+), and basal-like [β1 was higher than the latter two subtypes. This result is consistent with previous findings that ER-, PR-negative breast cancer has a high microvascular transfer rate and blood transfer risk [Angiogenesis factors are strongly correlated with the prognosis and clinical pathology, especially for breast cancer –40. VEGFsal-like . Luminalsal-like . The resfer risk , 45. Theβ1, and these proteins can be possible indicators for breast cancer in early diagnosis. The level of VEGF, PDGF, and TGF-β1 expression may be associated with cancer prognosis. Further analysis of protein expression in platelets before and after cancer treatment  is needed to evaluate their utility as markers for disease monitoring.In conclusion, we found that circulating platelets in breast cancer sequester higher levels of PF4, VEGF, PDGF-BB, and TGF-


Osmanthus fragrans Lour.). Based on transcriptomic sequencing data from O. fragrans buds at four developmental stages, six reference genes  with stable expression , as well as the commonly used reference gene Of18S, were selected as candidates for gene expression normalization in the RT-qPCR analysis of O. fragrans. For the normalization of RT-qPCR with two dyes, SYBR Green and EvaGreen, the expressional stability of seven candidate reference genes in 43 O. fragrans samples was analyzed using geNorm, NormFinder and BestKeeper. For RT-qPCR using SYBR Green, OfRAN1 and OfUBC2 were the optimal reference genes for all samples and different cultivars, OfACT and OfEF1α were suitable for different floral developmental stages, and OfACT was the optimal reference gene for different temperature treatments. The geometric mean values of the optimal reference gene pairs for the normalization of RT-qPCR are recommended to be used for all samples, different cultivars and different floral developmental stages in O. fragrans. For RT-qPCR using EvaGreen, OfUBC2 was the optimal reference gene for all samples and different cultivars, and OfACT was the optimal reference gene for different floral developmental stages and different temperature treatments. As the worst reference gene, Of18S should not be used as a reference gene in O. fragrans in the future. Our results provide a reference gene application guideline for O. fragrans gene expression characterization using RT-qPCR.Quantitative real-time PCR (RT-qPCR), a sensitive technique for quantifying gene expression, depends on the stability of the reference gene(s) used for data normalization. Several studies examining the selection of reference genes have been performed in ornamental plants but none in sweet osmanthus ( Osmanthus fragrans Lour. is particularly appreciated in China for its aesthetic value, unique scent and cultural significance. O. fragrans cultivars have been divided into 4 groups, Asiaticus, Albus, Luteus, and Aurantiacus [O. fragrans is directly affected by carotenoid composition and content [O. fragrans will help characterize the diverse carotenoid coloration in the flower petals of different O. fragrans cultivars. Moreover, petal color in this species is sensitive to ambient temperature, but how temperature regulates the petal coloration of O. fragrans remains unknown. Therefore, investigating the expression of carotenoid-related genes under different temperature conditions will help gain insight into the regulatory mechanisms of environmental factors in O. fragrans petal coloration.As one of ten Chinese traditional flowers, antiacus , accordi content ,3. HenceACT), beta-tubulin (TUB), elongation factor 1-alpha (EF1a), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), ubiquitin (UBQ) and 18S ribosomal RNA (18S) have been widely used as internal controls for gene expression analysis in many plants [There are several biological techniques for detecting the expression levels of genes, such as semi-quantitative PCR (semi-PCR), northern blotting, RNase protection assays (RPAs), gene chips, RNA sequencing and quantitative real-time RT-PCR (RT-qPCR). Of these techniques, RT-qPCR is presently regarded as the most reliable method because of its sensitivity, accuracy and high throughput –6. Idealy plants –11. Howey plants –14. TherChrysanthemum lavandulifolium [Prunus mume [O. fragrans. To date, Of18S is the most widely used reference gene in the semi-PCR and RT-qPCR analyses of O. fragrans [18S gene performs poorly as a reference gene for RT-qPCR analyses in Salvia miltiorrhiza [Of18S is a suitable reference gene in O. fragrans for gene expression normalization in different cultivars, in different floral development stages or under different temperature treatments. The use of inappropriate reference genes can result in inaccurate measurement of the expression levels of carotenoid-related genes, which may lead to incorrect conclusions with respect to diversified carotenoid coloration in different O. fragrans cultivars. Thus, the systematic exploration and validation of the most stable reference genes is important and requisite in O. fragrans.Studies of optimal reference gene selection for gene expression normalization have been conducted in many ornamental plants, such as petunia , tree pelifolium , cinerarlifolium , rose [1lifolium  and Prunnus mume , in addinus mume –23. Neveiorrhiza , tree peiorrhiza , Chineseiorrhiza , and watiorrhiza . There iOf18S, the commonly used reference gene in O. fragrans, six candidate reference genes with little variation in expression level in four bud transcriptomes were selected for further study: ACT, EF1α, NADP-isocitrate dehydrogenase (IDH), GTP-binding protein (RAN1), TUB and Ubiquitin-conjugating enzyme E2 (UBC2). We then compared the performance of these seven candidate reference genes in different cultivars, different floral developmental stages and under different temperature treatments using RT-qPCR with two dyes, SYBR Green and EvaGreen. Three algorithms, geNorm [O. fragrans.In this study, in addition to , geNorm , NormFin, geNorm  and Best, geNorm , were usO. fragrans orange-red-flowered cultivar ‘Yanhong Gui’ was used for sample collection from different floral development stages and different temperature treatments. Plants were potted and grown in the resource nursery of Zhejiang Agriculture and Forestry University in Lin’an, Zhejiang Province, China. During bud development (from 9 Aug 2014 to 23 Sep 2014), bud samples of O. fragrans ‘Yanhong Gui’ were collected weekly, and floral samples (from 23 Sep Aug 2014 to 25 Sep 2014) were collected daily during flower opening. In total, 10 samples during bud development and flower opening constituted the experimental samples of different floral development stages. To collect samples under different temperature treatments, O. fragrans ‘Yanhong Gui’ plants with globular-shaped buds were treated at 12, 15, 19 and 32°C. To monitor floral development, flower petal samples under four temperature treatments were collected at four developmental stages , as well as petal samples before the treatments, generating 17 petal samples under different temperature treatments. Additionally, petal samples were collected from the fully opened flowers of 16 cultivars, including ‘Hangzhou Huang’, ‘Jinqiu Gui’ and ‘Yuanban Jingui’ from the Luteus group; ‘Xiaoye Sugui’ and ‘Yu Linglong’ from the Albus group; ‘Chenghong Dangui’, ‘Mantiao Hong’, ‘Wuyi Dangui’, ‘Yanhong Gui’, ‘Yingye Dangui’, ‘Zhusha Dangui’ and ‘Zhuangyuan Hong’ from the Aurantiacus group; and ‘Chenghuang Siji Gui’, ‘Ri Xiang Gui’, ‘Tian Nv San Hua’ and ‘Tian Xiang Tai Ge’ from the Asiaticus group. In total, 43 experimental samples comprised 10 at various stages of floral development, 17 exposed to various temperature treatments, and 16 from different cultivars. All samples were immediately frozen in liquid nitrogen after collection and stored at -80°C until use.The Total RNA from all samples was extracted using the RNAprep Pure Plant Kit . All RNA samples were adjusted to the same concentration after measuring the RNA concentration on a NanoDrop ND-1000 spectrophotometer (NanoDrop Technologies). The quality of the RNA was further verified using 1.5% (w/v) agarose gel electrophoresis and ethidium bromide staining. The first strand cDNA was synthesized using 1 μg of total RNA with the Reverse Transcriptase M-MLV  according to the manufacturer’s protocol.O. fragrans ‘Yanhong Gui’ buds at four developmental stages were constructed and sequenced using the Illumina HiSeq2000 platform (unpublished data). A total of 184,860 unigenes were identified, and the relative expression levels of these unigenes were analyzed at four developmental stages. The level of gene expression was determined by calculating the number of unambiguous tags for each gene and then normalizing this to the number of transcripts per million tags (TPM). The difference in gene expression between the samples was determined using the TPM value. Six reference genes  exhibiting stable expression (0.5–2 fold change in expression level) at four developmental stages  contained 10 μL of 2× HRM Analysis PreMix (with EvaGreen) , 0.6 μL of each primer (10 μM), 2 μL of diluted cDNA (~ 50 ng), 0.4 μL of 50× ROX Reference Dye and 6.4 μL of ddH2O. The PCR program was performed as follows: an initial denaturation at 95°C for 2 min, 40 cycles of 95°C for 5 s and 60°C for 30 s, and a melting curve analysis with a temperature ramp from 60°C to 95°C. No-template controls for each primer set were included in every reaction, and the real-time RT-PCR was performed in triplicate.RT-qPCR was performed on an ABI 7300 real-time PCR instrument  using SYBR Green or EvaGreen dyes to detect dsDNA synthesis. For the RT-qPCR with SYBR Green, the reaction mixture  contained 10 μL of SYBR Premix Ex Taq II , 0.8 μL of each primer (10 μM), 2 μL of diluted cDNA (~ 50 ng), 0.4 μL of 50× ROX Reference Dye and 6 μL of ddHO. fragrans.The expression levels of the seven tested reference genes in all samples were determined using cycle threshold values (Ct). geNorm (version 3.5), NormFinder (version 0.953) and BestKeeper (version 1) –28 were The geNorm software is a visual basic application (VBA) for determining the most stable reference genes from a set of tested genes by gene expressional stability measure (M). Stepwise exclusion of the gene with the highest M value allows the ranking of the tested genes according to their expression stabilities. Additionally, the pairwise variation (PV) between the sequential normalization factors was calculated to determine the optimal number of reference genes . The NorOfACT, OfEF1α, OfIDH, OfRAN1, OfTUB, and OfUBC2, were selected as candidate reference genes because they exhibited stable expression (0.5–2 fold change in expression level) during O. fragrans bud development  ranged from 0.9903 to 0.9984, and PCR amplification efficiencies between 97.7 and 109.6% were obtained from the standard curves generated using a ten-fold serial dilution of cDNA. Using EvaGreen, R2 ranged in value from 0.9955 to 1.0000, and PCR amplification efficiencies ranged from 92.8 to 106.0%. These results indicated that each primer set was suitable for gene expression analysis with RT-qPCR using either SYBR Green or EvaGreen.Six reference genes, elopment . In addiOfUBC2 and OfTUB with the highest mean Ct values, whereas Of18S exhibited the highest expression level with the lowest Cq value of all the samples. In addition, each candidate gene exhibited a specific Ct value variation tendency under the applied conditions. Using SYBR Green, OfRAN1 exhibited stable gene expression (below 6 cycles), whereas Of18S had obvious expression variation (above 8 cycles) as shown in OfRAN1 also exhibited stable gene expression (below 5 cycles), whereas Of18S had obvious expression variation (above 9 cycles) using EvaGreen , developmental stages (10 samples), temperature treatments (17 samples), and total (43 samples). We first used geNorm to analyze the expressional stability of the seven candidate reference genes in all the samples and ranked them according to the gene stability index (M): the genes with the lowest M values have the most stable expression . An M vaOfRAN1 and OfUBC2 were the most stably expressed genes with the lowest M value of 0.051 using SYBR Green  was also calculated to determine the optimal number of genes required for normalization. The VEvaGreen , indicatOfUBC2 was the most stable gene for all samples and different cultivars , is widely employed as the internal control for the normalization of target gene expression under cold treatment [Arabidopsis reference genes [UBC (at5g25760) is not always stably expressed in Arabidopsis; the expressional stability of this gene was low in Arabidopsis exposed to cadmium and copper treatments [ tissues . Moreovenditions . In Arabreatment ,44, and ce genes . Howevereatments .ACT is involved in basic cellular processes and has always been considered a potential reference gene in numerous species. In our study, OfACT was the optimal reference gene for different floral developmental stages. In many species, ACT has also been demonstrated to be stably expressed during the development of specific tissues. For example, ACT was stably expressed in the developmental series of soybean [Litchi chinensis [ACT was also stably expressed under various abiotic stresses, including different temperatures, different hormones and wounding [OfACT was also the optimal reference gene for different temperature treatments in O. fragrans.The traditional reference gene  soybean , during  soybean , in diffhinensis  and in thinensis . Moreovewounding ,42,48. AOfEF-1a was the other optimal reference gene using SYBR Green and also performed well with EvaGreen. EF-1a is regarded as one of the most stable genes in the different fruit developmental stages of L. chinensis [EF-1a is also the most stably expressed gene in the six fruit developmental stages of Litsea cubeba [For different floral developmental stages, hinensis . Moreovea cubeba  and in ta cubeba .Of18S had the most obvious expression variation in Ct values in the 43 tested samples (Of18S was ranked the last and regarded as the worst reference gene in all sample sets using either SYBR Green or EvaGreen. Moreover, Of18S exhibited a significantly higher expression level with the lowest Cq value of all genes tested, suggesting that this gene is unsuitable for the normalization of target genes with middle or low expression levels. Similarly, in Salvia miltiorrhiza [18S gene was also found to perform poorly as a reference gene.The widely used reference gene  samples . As expeiorrhiza , tree peiorrhiza , Chineseiorrhiza , and watiorrhiza , the 18SO. fragrans using geNorm, NormFinder and BestKeeper. For RT-qPCR using SYBR Green, OfRAN1 and OfUBC2 were the optimal reference genes for all samples and different cultivars, OfACT and OfEF1α were the optimal reference genes for different floral developmental stages, and OfACT was the optimal reference gene for different temperature treatments. The geometric mean values of the optimal reference gene pairs are recommended to be used for all samples, different cultivars and different floral developmental stages. For RT-qPCR using EvaGreen, OfUBC2 was the optimal reference gene for all samples and different cultivars, and OfACT was the optimal reference gene for different floral developmental stages and different temperature treatments. The use of Of18S as a reference gene should be avoided in O. fragrans. To our knowledge, our study is the first systematic characterization of the expressional stability of reference genes in O. fragrans.In this study, we investigated the expressional stability of seven candidate reference genes for the normalization of RT-qPCR in different sample sets of


Medical students(MS) will face ethical issues throughout their lives as doctors. The present study aims to investigate medical students’ opinions on controversial ethical issues and factors associated with these opinions.SBRAME  is a multicenter study involving 12 Brazilian medical schools with 5950 MS. Participants completed a questionnaire that collected information on socio-demographic data, medical schools characteristics, religious beliefs and opinions on controversial ethical issues. Of all MS, 3630 participated in the survey (61.0%).The sample was 53.8% women and the mean age was 22.5 years. In general, most MS have no objections to prescription of birth control (90.8%), adult stem cell use (87.5%), embryonic stem cell use (82.0%) and abortion for genetic reasons (51.2%). Approximately half of students have no objections to human cloning (47.3%), 45.7% to withdrawal of artificial life support, 41.4% to euthanasia and 23.3% to abortion for failed contraception. Socio-demographic data such as age, gender and income had little influence on MS opinions. On the other hand, medical schools characteristics  and religious aspects  were highly correlated with their opinions. In general, MS with more supportive opinions on controversial ethical issues were less religious and from non-traditional (newer), urban, public and bigger universities.The current study reveals MS have different opinions regarding controversial ethical issues. Noteworthy, these opinions seem to be shaped more by university characteristics and religious beliefs than socio-demographic data. This definition, taken from an ethics book , reflectAccording to Miles et al. , medicalIn fact, MS will face ethical issues throughout their lives as doctors. Feudtner et al.  evaluateMS will also come up against controversial ethical issues , about which they may have moral qualms . Curlin Euthanasia, legal abortion and termination of life-sustaining treatment are some examples of ethical issues that MS and doctors should have knowledge and be trained to deal with it.Among several factors which could have an influence on doctors and MS ethical opinions; religious/cultural issues , undergrReligious beliefs are associated with differing attitudes in the clinical encounter  and diffUndergraduate training is responsible for promoting a significant increase in the growth and development of moral reasoning in medical students  and shouFinally, since there are important differences between medical schools characteristics  such as Hence, understanding MS opinions and what shapes their ethical views could help to provide further evidence to this field and to create new teaching strategies. Therefore, the present study aims to investigate medical students’ opinions on controversial ethical issues and factors associated with these opinions.SBRAME  is a cross-sectional, multicenter study involving 12 Brazilian medical schools that enrolled 5950 medical students (MS) . The preThe following medical schools participated in the study: Universidade Federal de São Paulo (UNIFESP) – São Paulo (570 students) – Public ; Faculdade de Medicina de Marília (FAMEMA) – Marília (460 students) – Public (State); Centro Universitário Lusíadas (Lusíadas) – Santos (460 students) – Private; Faculdade de Medicina de São José do Rio Preto (FAMERP) – São José do Rio Preto (370 students) – Public (State); Pontifícia Universidade Católica de Sorocaba (PUC-SP) – Sorocaba (580 students) – Private; Universidade Metropolitana de Santos (UNIMES) – Santos (480 students) – Private; Universidade Nove de Julho (UNINOVE) – São Paulo (580 students) – Private; Faculdade de Ciências Médicas da Santa Casa de São Paulo (Santa Casa) – São Paulo (570 students) – Private; Faculdade de Medicina do ABC (FMABC) – São Paulo (580 students) – Private; Universidade Federal de Santa Maria (UFSM) – Santa Maria (580 students) – Public ; Universidade Federal do Mato Grosso do Sul (UFMS) – Cuiabá (360 students) – Public  and Faculdade de Medicina de Jundiaí (360 students) – Private.First, a meeting  was held to discuss the objectives and assess each institution’s willingness to participate in this study. Next, research supervisors and interviewers from each medical school were trained using a common manual and supplemented by web-based training.All MS officially registered in the 12 medical schools were invited by the researchers to take part in the study. MS were personally approached before or after classes and during breaks.Participants completed a self-administered, multiple choice 43-item questionnaire, which was adapted and expanded from other pilot studies carried out in Brazil –16 and cSocio-demographic data: gender, age, family income, ethnicity, religious affiliation, undergraduate year and desired medical specialty.Controversial ethical issues: MS were asked about controversial issues in medicine using an instrument adapted from Curlin et al. , 17 in pMedical School characteristics: Number of medical students, type of university (public or private), year of medical School foundation and location of the university .Religiosity and beliefs: For assessing the religious aspects of participants, the Duke Religious Index (DUREL) validated into Portuguese was used . DUREL iHappiness  and SatData were entered into an Excel database and analyzed using Statistical Package for Social Sciences program (SPSS), version 17.0 (SPSS Inc). Descriptive statistics were used to describe the range of responses. For categorical variables, the descriptive statistics are reported as numbers and percentages. For continuous data, the descriptive statistics include mean and standard deviations.Dependent variables : euthanasia, withdrawal of artificial life support, abortion for congenital abnormalities, abortion for failed contraception, prescription of birth control, embryonic stem cell use, adult stem cell use and human cloning.Independent variables: gender, age, undergraduate year, Number of medical students in the university, type of university (public or private), Year of medical School foundation, income, location of the university , intrinsic religiousness, religiousness attendance, non-organizational religiousness, happiness , satisfaction with the course , believe in life after death (Yes or no), believe in soul (Yes or no), religious affiliation and desired medical specialty .For assessing factors associated with MS’ opinions on each ethical issue, a logistic regression was used with the following variables: All independent variables were included in the analysis, and only those identified by the foreward logistic regression model as independently associated with the dependent variable were included in the model. Goodness of fit was evaluated by the Hosmer-Lemeshow test and Nagelkerke R square. All confidence intervals are 95% and p < 0.05 was considered significant.Participants gave written informed consent and the study was approved by the ethics committee of Universidade Federal de São Paulo and all other medical school committees.A total of 3630 medical students participated in the study with a response rate of 61.0%. The most common reasons for not participating were: refused, did not wish to sign the consent form, were interviewers in the study, or were absent at the time of the survey.Most MS were women (53.8%), mean age was 22.5 years (SD: 4.6), 82.2% were white, and 48.9% had an average family income of more than US$3616 per month. Participants were equally distributed in the medical school years: 612 (16.9%) in the first year; 752 (20.7%) in the second year; 559 (15.4%) in the third year; 635 (17.5%) in the fourth year; 579 (15.9%) in the fifth year, and 485 (13.6%) in the sixth year (Table There were 7 (58.3%) private schools and 5 (41.7%) public schools , most institutions (83.3%) were from South-east Brazil  and 5 (41.7%) were from urban centers. The mean year of medical school foundation was 1967.0 (SD: 18.6) varying from 1933 to 2003 and the number of students per medical school was approximately 479.1 (SD: 94.3) varying from 360 to 580. All medical schools have a course on medical ethics.Most MS (66.1%) had a religious affiliation ; believed in God (84.2%); attended religious services less than once a week (81.8%); spend more than once a week in private religious activities (55.8%) and believe that human body included a soul (78.9%). The mean of DUREL intrinsic religiosity was 9.63 (SD: 3.69), which ranged from 3 (low intrinsic religiosity) to 15 (high intrinsic religiosity).Table Tables In relation to other small MS Brazilian studies, we found similar opinions on embryonic stem cell use , less suIn general, the current study reveals that MS opinions on controversial ethical issues are related to religious beliefs and medical school characteristics. In fact, we found religious beliefs were strongly associated with MS opinions on these controversial ethical issues. These findings were in accordance with other studies in this field which evaluated physicians. Baume et al.  investigThe role of medical school characteristics is less established than religious beliefs. It is well known that medical schools differ in their curriculum, structure and missions . AlthougOther characteristics such as number of students, medical school location and year of foundation were also associated with MS opinions on ethical issues. Few studies have assessed this relationship, particularly in medical ethics. There are some studies dealing with number of MS and class sizes with some contradictory results such as changes in students’ satisfaction and test grades . In a fiInterestingly, the year of medical school foundation was also associated with MS opinions on controversial ethical issues, in which MS from newer institutions were more supportive to euthanasia, abortion for congenital reasons and embryonic stem cell use. We can speculate that newer medical schools have a less traditional staff than older institutions. In addition, in public institutions, MS were also more supportive, which could be justified by the secular characteristic of these schools compared to private schools, which could have religious affiliations.Finally, location of the medical school may also impact MS ethical opinions. Rural institutions usually are more conservative and may be less permissive to these controversial ethical issues. Steinauer et al.  investigIn fact, giving the example of the Brazilian scenario, we have some important differences between types of universities. For instance, in the latest “QS University Rankings: Latin America (2014)”, there are 10 Brazilian universities in the top 20 . Likewise, in a recent study in Brazil, Terra et al.  found thTo sum up, our results reveal the importance of medical schools characteristics on MS opinions and give further evidence to this area of research. More studies are needed to replicate our findings and to examine MS attitudes and practical skills in hypothetical controversial ethical situations.Our findings have some limitations that should be highlighted. First, the study was carried out in Brazil and data should be replicated in other cultural contexts. Second, the response rate was 61% and does not include the opinions of over one-third of students who may have had less interest in the topic and so refused to participate. However, this response rate is similar to or better than other multicenter studies in medical education. Third, despite each medical school has a different educational strategy on how to teach medical ethics, we did not evaluate the impact of these strategies on medical students’ ethical opinions.The present study also has a number of strengths. This is one of the most comprehensive studies of the attitudes and experiences of medical students and, to our knowledge, one of the largest studies dealing with ethics in medical education.In conclusion, the current study reveals MS have different opinions regarding controversial ethical issues. Noteworthy, these opinions seem to be shaped more by university characteristics and religious beliefs than socio-demographic data.


Fragaria vesca) is an important model for fruit crops because of several unique characteristics including the small genome size, an ethylene-independent fruit ripening process, and fruit flesh derived from receptacle tissues rather than the ovary wall which is more typical of fruiting plants. Histone methylation is an important factor in gene regulation in higher plants but little is known about its roles in fruit development. We have identified 45 SET methyltransferase, 22 JmjC demethylase and 4 LSD demethylase genes in F. vesca. The analysis of these histone modifiers in eight plant species supports the clustering of those genes into major classes consistent with their functions. We also provide evidence that whole genome duplication and dispersed duplications via retrotransposons may have played pivotal roles in the expansion of histone modifier genes in F. vesca. Furthermore, transcriptome data demonstrated that expression of some SET genes increase as the fruit develops and peaks at the turning stage. Meanwhile, we have observed that expression of those SET genes responds to cold and heat stresses. Our results indicate that regulation of histone methylation may play a critical role in fruit development as well as responses to abiotic stresses in strawberry.The diploid woodland strawberry ( Chromatin is a complex composed of histones, chromosomal proteins, DNAs and small RNAs. The nucleosome is the basic unit of chromatin, consisting of a histone octamer , surrounded by a 146–148 bp DNA wrapping. The post-transcriptional modifications of the N-terminal tails of core histones could affect the nucleosome spacing, higher-order nucleosome interaction, and greatly affect the accessibility of the transcriptional regulatory proteins. Thus, in eukaryotes, post-transcriptional histone modifications are a determinant of the active/silent state of the associated genes, and are of great importance to a variety of important biological processesThe covalent modifications of histones include methylation, acetylation, phosphorylation, ubiquitation and SUMOylation3Suppressor of variegation, Enhancer of zeste and Trithorax in Drosophila) domain mediating the methyltransferase catalytic activity6Histone lysine methylation is dynamic during organ development, and determined by histone modifying proteins including histone lysine methyltransferases (HKMTases), histone demethylases (HDMases) and histone turnovers. The majority of HKMTases have a SET  (Enhancer of Zeste), capable of transferring methyl groups to H3K27. Class II consists of five SET genes homologous to the Drosophila ortholog ASH1, responsible for methylations on H3K4 and/or H3K36. Class III is another group of SET genes responsible for the active mark H3K4me1/2/3, similar to the Drosophila ortholog TRX. Class IV is plant-specific, responsible for monomethylation on H3K27, a silent mark essential for transposon silencingDrosophila SU(VAR)3–9. Similar to their orthologs in animals, class V SET genes in Arabidopsis play an essential role in the establishment of heterochromatic mark H3K9me1/2/3, as well as H4K20me and H3K27me2. Class VI and VII consist of genes having a SET domain with functions to be determined.Based on the amino acid sequence conservation of SET domains, there are seven classes of SET protein encoding genes in Lysine Specific demethylase) type and the JmjC domain-containing HDMasesArabidopsis has four members, being able to demethylate H3K4me1/2 and H3K9me1/2. While JmjC is a much larger gene family consisting of 21 genes in Arabidopsis, and is compatible with trimethylated residuesHistone HDMases consist of two major types of enzymes, the LSD (CURLY LEAF (CLF) and MEDEA (MEA) in Arabidopsis thaliana121The first plant SET genes identified are F. x ananassa) is a young crop species as a model plant considered to be non-climacteric. F. x ananassa has an extremely complex octaploid genome harboring 56 chromosomes (2n = 8x = 56) derived from 4 diploid ancestors. Thus, the sequenced diploid woodland strawberry Fragaria vesca with a small genome  offers substantial advantages for genomic researchF. vesca. Comprehensive studies about the phylogeny, evolutionary history, structure, expression patterns in different stages/organs and in response to abiotic stresses were performed to give an overview of this important group of genes in F. vesca. This study provides the first characterization of the full set of histone lysine methylation modifiers in strawberry, and should greatly facilitate the functional characterization of those epigenetic regulators in this economically important crop species.In spite of the essential roles of histone modifications in cellular processes, little is known about histone modifiers in strawberry. The cultivated strawberry (F. vesca proteome by HMMER toolset (Methods for details). This sequence-based search identified 45 SET domain-containing genes in F. vesca  since thenA.trichopoda (http://chibba.agtec.uga.edu/duplication/)Arabidopsis genes with known functions were named as published, following the standard gene symbol conventions with all capital letters; while genes in other species were named as SET1-62 following the species abbreviation.To identify histone HKMTases, the full alignment of SET domains downloaded from Pfam was searched against the F. vesca . To bettl plants . The basF. vesca SET genes, phylogenetic trees were constructed using the Maximum Likelihood method (see Methods for details) based on amino acid sequences in the conserved SET domains on the SET genes identified in the agiosperms F. vesca, A. thaliana, Z. mays, O. sativa and A. trichopoda ; while class VI and VII consist of relatively shorter genes with no known specificity . In total, there are 7 pairs of such F. vesca SET genes, with 4 pairs in class V and the other 3 in other classes. To study the evolutionary constraints performed on the 7 recent duplicates in F. vesca, dn (nonsynonymous substitutions per site) and ds (synonymous substitutions per site) between each duplicate were calculated. dn of class V duplicated pairs are higher than other classes  in F. vesca has five members . Interestingly, among all the JmjC domain-containing genes, FV_jmjC12 and FV_jmjC21 are the only two genes having a single exon , the anther, and in some tissues in the seed . It suggests that although highly conserved on amino acids sequence, those duplicated genes are differently regulated. Thirdly, LSD and different classes of JmjC HDMases show different expression profiles in different organs/stages as well; and the recent JmjC HDMase duplicates also express differentially , both active and silent mark-related SET genes, LSD and JmjC genes show decreasing expression levels during early-stage fruit development (pollination to big green). Fourthly, overall, genes encoding both HKMTases and HDMases express higher in tissues of developing flowers  than in other tissues. Thus, the different tissues in different developmental stages have diversified expression patterns of histone lysine methylation related genes, indicating the specific regulatory roles of those genes in cellular processes.On the other hand, the different organs/stages have very different combinatorial expression patterns of HKMTase and HDMase genes . FirstlyThe expression profiles shown above reveal that duplicated SET pairs are quite distinct, with one silent in early-stage fruit development, while the other relatively ubiquitously expressed in all tissues, . To inveATX3b and SUVH4a response to both cold and heat shock. Furthermore, the recent duplicated gene pairs response differently. For SUVH4a/b/c/d, the expression level of SUVH4a increases after cold and heat shock, while the other three are not responsive at all. In summary, some SET genes show dynamic expression patterns upon cold and heat shock, which indicates that these genes may be involved in F. vesca’s responses to temperature stresses.Histone modifications are suggested to play an important role in the regulation of gene expression in response to abiotic stresses1F. vesca plus seven other plant species representing the major clades of terrestrial plants. The extensive phylogenetic analysis revealed the evolutionary history of those histone modifiers in F. vesca and also in other angiosperms.Sequence-based searching and phylogenetic analysis proved to be an effective way to identify histone modifiers in a sequenced genome2023242526F. vesca. These phylogenetic studies suggest that those identified SET genes were highly conserved in each class across a wide spectrum of plants, indicating their essential regulatory roles in the plant kingdom. Of the SET genes studied, the most intriguing observation was the expansion of class V in both eudicots and monocots, especially in Z. mays. Class V SET HKMTases are specific for methylations on H3K9, which is involved in transposon silencing and heterochromatin formation2Z. maysZ. mays to protect the genome integrity. In addition, class V genes diverged faster than other classes  showed the least number of genes with active expression, particularly the class V SET genes . The lace.g. overall DNA methylation levels decrease during tomato fruit ripeningAnother interesting phenomenon is that the expression levels of the some active SET genes that we investigated in pith and cortical tissues decreased during early-stage fruit development (from pollination to big green stage), but gradually increased beginning at the white stage and reaching a peak at the turning stage . It has Epigenentic regulation of cellular processes during abiotic stresses has been the subject of several recent investigations that suggest that both DNA modifications and histone modifications play a pivotal role in plant responses to various stresses11433Arabidopsis and rice, strawberry has several distinct characteristics including that “fruits” develop from receptacle tissues and the adaptability of the species to different environments. As essential regulatory factors, how histone modifiers are involved in various cellular process is of great interest. The majority of previous studies about histone modifiers focused on Arabidopsis, which does not have fleshy fruits. Although some work has been published about histone modifiers in tomato, the data are limited. Our identification and characterization of histone modifiers in woodland strawberry is the first comprehensive analysis of HKMTases and HDMases in a non-climacteric fruit species. Our study provides an overview of the histone lysine methylation modifiers in strawberry, and should greatly facilitates molecular, biochemical and physiological characterizations of histone methylations in strawberry and other Rosaceae species.Compared to the well-studied model plants Fragiaria vesca, Arabidopsis thaliana, Vites vinifera, Nelumbo nucifera, Orazy sativa, Zea mays, Amborella trichopoda and Selaginella moellendorffii. The Fragaria vesca and Nelumbo nucifera complete protein sequences and corresponding annotation information were downloaded from NCBI and others were download from Phytozome . See Eight plant genomes were analyzed, http://pfam.xfam.org/search), Conserved Domain Databasehttp://www.ncbi.nlm.nih.gov/Structure/cdd/wrpsb.cgi) available from NCBI, and the Simple Modular Architecture Research Tool databasehttp://smart.embl-heidelberg.de/), with a threshold of e-value < 1e−4. Proteins with both Amino_oxidase domain and SWIRM domain were identified as LSD genes.To identify the genes with the domain(s) of interest, the amino acid sequences of SET domain (PF00856), JmjC domain PF02373), Amino_oxidase domain (PF05193) and SWIRM domain (PF04433) were downloaded from pfam database V27.03, Amino_Protein sequences were aligned using MUSCLE v3.8.31 with default parameters−4 were kept. In addition, motif analyses were performed online by MEME FV-SET13/35 was not identified as an F. vesca lineage-specific duplicated pair by the phylogenetic tree constructed for SET class V  was used for all strawberry material collection. Strawberry flesh at different development stages was collected from plants grown in 10 cm x 10 cm pots in a controlled-environment growth chamber, set at 16 h light/8 h dark cycles, 22 °C, and 65% relative humidity. Strawberry fruits at 12-day old big green stage, big white stage (white flesh with red seeds), pink stage (slight pink flesh and red seeds), and red stage (2–3 days after the pink stage) were collected and immediately put into liquid nitrogen.A 7th generation inbred line of woodland The strawberry seedlings for cold/heat shock were grown in MS media in a growth chamber set at 16 h light/8 h dark cycles, 22 °C. Four-week old seedlings were transferred to a growth chamber set at either 4 °C or 38 °C for cold/heat shock. Cold shocked seedlings were collected at 1 h, 3 h and 8 h; while heat shocked seedlings were collected at 1 h and 3 h, or at 4 h (3 h heat shock and 1 h recovery at 22 °C) and 8 h (3 h heat shock and 5 h recovery at 22 °C). The collected materials were immediately put into liquid nitrogen for RNA processing.Before RNA extraction, the achenes were stripped from the frozen strawberry fruit, and only the de-seeded flesh was processed for RNA isolation. RNA was isolated from either the deseeded flesh or seedlings by a modified CTAB method. After DNase I treatment, RNAs were used for cDNA synthesis by using the Primerscript RT reagent Kit with gDNA Erase (Takara). The cDNAs were used as templates for quantitative RT-PCR to measure the abundance of a certain transcript. Quantitative RT-PCR was performed using SYBR Premix Ex Tag (Takara) on a Bio-rad iQ5. Primers used are listed in How to cite this article: Gu, T. et al. Identification and characterization of histone lysine methylation modifiers in Fragaria vesca. Sci. Rep. 6, 23581; doi: 10.1038/srep23581 (2016).


All these approaches usually lead to DNA damage, gene instability and/or chromatin alterations that primarily affect p53-p21 signaling. Little is known on whether retinoids and rexinoids, which are cell differentiation agents, can also induce CS in vitro and in vivo, and which molecular mechanisms are involved in promoting the senescent phenotype. We reviewed the recent publications on CS induced by retinoids and rexinoids in ER+ and ER− breast cancer cell lines and in corresponding animal models of mammary carcinogenesis which simulate those of human breast cancer. The role of retinoic acid receptors β2 and 5 (RARβ2 and RARβ5) and of receptor independent genes involved in mediating the senescence program of retinoids and rexinoids in ER+ and ER− breast cancer cells is discussed. Potential strategists for clinical implication of CS as biomarker of prognosis and of response to treatment with retinoids, rexinoids and with other cell differentiation and antitumor agents are outlined.Most studies on cellular senescence (CS) have been performed  Most imetinoids . Howeverreported . Most streported ,9. Retin in rats ,12. For  cancers . The ant cancers ,16. Each cancers –19. Over cancers ,21. Incr cancers ,22,23.+ breast cancer cell line retinoids  are more efficacious than rexinoids  in inhibiting cell growth and in inducing CS, whereas rexinoids have very similar effect in both, ER+ and ER− cell lines  in ER+, T47D cells but had opposite effect in resistant to senescence ER−, MDA-MB-231 cells , intercellular matrix protein stromolysin 3 (MMP11) and basal membrane  proteins, which indirectly or by paracrine mechanisms potentiate CS  reaction was employed  and RARβ deficient (−/−) mice were employed. We obtained these mice from the laboratory of Pierre Chambon in Strasburg, France. Mice were cross-bread in our laboratory and RARβ expression was determined by DNA analysis. Mammary gland architecture of RARβ homozygous (−/−) mice did not differ from that of wild-type RARβ mice (+/+). Mice of both genotypes were followed up for more than 12 months and no mammary tumors were identified, suggesting that RARβ deficiency alone does not promote mammary carcinogenesis. Mice of both genotypes were treated with 9cRA at 80 mg/kg for 4 weeks and cell proliferation and apoptosis were determined. No difference in the values of BrdU-labeled and SC was found in mammary terminal end buds (TEBs) and lobules of both genotypes, suggesting that RARβ deficiency alone in normal MECs is not the critical target of retinoids in inhibiting cell proliferation and in inducing CS. Thus, it appears that other transcription factors may contribute to the retinoid-induced CS in normal and tumor MECs.To identify SC employed . The proemployed –14. We semployed ,12. Surpemployed . It has employed . By emplon of CS . By doubon of CS . To furtin vivo, in mammary premalignant lesions  and tumors of rats and mice    and humas (nevi) , furthers (nevi) ,53. Thuss (nevi)  suggestes (nevi) . Recent omote CS . Since, omote CS ,22.Efficacy studies with established and novel cancer prevention and therapy agents are another avenue for potential clinical implication of CS. By employing MNU-, and MMTV-Neu models of mammary carcinogenesis, we found that retinoids (9cRA and 4-HPR), rexinoids (bexarotene), tamoxifen and aromatase inhibitors (vorazole), in addition to inhibition of cell proliferation also induced CS and this correlated with their efficacy to suppress tumor growth ,14. The in vitro cytokines that suppress cell growth by inducing CS it has been suggested also to be employed for selective cytokines in vivo experiments (Development of novel agents that selectively induce CS is another avenue that could be explored in cancer prevention and treatment. These agents apparently need to modulate the activity of genes involved in initiation and maintenance of senescent phenotype. As was shown above, modulation of ER, Her2/New, RAS, RARβ2 signaling may affect the decision of cells to stop proliferating, senesce or die by apoptosis. Since, SC produce eriments ,56. Some