Anti-Tumor Effect of Cactus Polysaccharides on Lung Squamous Carcinoma Cells (SK-MES-1)

Background: Cactus polysaccharides are the active components of Opuntia dillenii which have been used extensively in folk medicine. In thisstudy, we investigate the anti-tumor effect of cactus polysaccharides on lung squamous carcinoma cells SK-MES-1.Materials and Methods: The inhibitory effect of Cactus polysaccharides on lung squamous carcinoma cells were detected by MTT assay. Cellcycle was determined by flow cytometry and cell apoptosis was determined by AnnexinV assay. Western-blotting was applied to detect P53 andPTEN protein expression in the cells treated with cactus polysaccharides.Results: Results showed that different concentrations of wild cactus polysaccharides prevent SK-MES-1 cells growth and induces S phase arrest.The data also revealed that cactus polysaccharides cause apoptosis in SK-MES-1 cells determined by Annexin-V assay. Furthermore, cactuspolysaccharides induced growth arrest and apoptosis may be due to the increase of P53 and phosphatase and tension homolog deleted onchromosome ten (PTEN) protein.Conclusion: Cactus polysaccharides have anti-tumor activity on lung squamous carcinoma cells.Key words: Cactus polysaccharides, Lung squamous carcinoma, Anti-tumor effect, P53, PTEN Abbreviations: PTEN :phosphatase and tension homolog deleted on chromosome ten; NSCLC: Non-small-cell lung cancer; FBS :Phosphate buffered saline; MTT:3-(4, 5-Dimethylthiazol-2-yl)-2, 5-diphenyltetrazolium bromide; PBS: Phosphate buffered saline; DMSO:Dimethyl sulfoxide; PI: Propidium iodide

WNT signaling regulates self-renewal and differentiation of prostate cancer cells with stem cell characteristics

Prostate cancer cells with stem cell characteristics were identified in human prostate cancer cell lines by their ability to form from single cells self-renewing prostaspheres in non-adherent cultures. Prostaspheres exhibited heterogeneous expression of proliferation, differentiation and stem cell-associated makers CD44, ABCG2 and CD133. Treatment with WNT inhibitors reduced both prostasphere size and self-renewal. In contrast, addition of Wnt3a caused increased prostasphere size and self-renewal, which was associated with a significant increase in nuclear Β-catenin, keratin 18, CD133 and CD44 expression. As a high proportion of LNCaP and C4-2B cancer cells express androgen receptor we determined the effect of the androgen receptor antagonist bicalutamide. Androgen receptor inhibition reduced prostasphere size and expression of PSA, but did not inhibit prostasphere formation. These effects are consistent with the androgen-independent self-renewal of cells with stem cell characteristics and the androgen-dependent proliferation of transit amplifying cells. As the canonical WNT signaling effector Β-catenin can also associate with the androgen receptor, we propose a model for tumour propagation involving a balance between WNT and androgen receptor activity. That would affect the self-renewal of a cancer cell with stem cell characteristics and drive transit amplifying cell proliferation and differentiation. In conclusion, we provide evidence that WNT activity regulates the self-renewal of prostate cancer cells with stem cell characteristics independently of androgen receptor activity. Inhibition of WNT signaling therefore has the potential to reduce the self-renewal of prostate cancer cells with stem cell characteristics and improve the therapeutic outcome.Peer reviewe

The Escherichia coli transcriptome mostly consists of independently regulated modules

Underlying cellular responses is a transcriptional regulatory network (TRN) that modulates gene expression. A useful description of the TRN would decompose the transcriptome into targeted effects of individual transcriptional regulators. Here, we apply unsupervised machine learning to a diverse compendium of over 250 high-quality Escherichia coli RNA-seq datasets to identify 92 statistically independent signals that modulate the expression of specific gene sets. We show that 61 of these transcriptomic signals represent the effects of currently characterized transcriptional regulators. Condition-specific activation of signals is validated by exposure of E. coli to new environmental conditions. The resulting decomposition of the transcriptome provides: a mechanistic, systems-level, network-based explanation of responses to environmental and genetic perturbations; a guide to gene and regulator function discovery; and a basis for characterizing transcriptomic differences in multiple strains. Taken together, our results show that signal summation describes the composition of a model prokaryotic transcriptome

Externalizing behavior in early childhood and body mass index from age 2 to 12 years: longitudinal analyses of a prospective cohort study

Background: Some evidence suggests that obesity and behavior problems are related in children, but studies have been conflicting and have rarely included children under age 4. An association between behavior problems in early childhood and risk for obesity could suggest that a common set of factors contribute to both. Our research objectives were to determine the extent to which externalizing behavior in early childhood is related to body mass index (BMI) in early childhood and through age 12, and to evaluate whether these associations differ by sex and race. Methods: Data from the NICHD Study of Early Child Care and Youth Development were analyzed. Externalizing behaviors at 24 months were assessed by mothers using the Child Behavior Checklist. BMI was calculated from measured height and weight assessed 7 times between age 2 and 12 years. Linear mixed effects models were used to assess associations between 24 month externalizing behavior and BMI from 2 to 12 years, calculate predicted differences in BMI, and evaluate effect modification. Results: Externalizing behavior at 24 months was associated with a higher BMI at 24 months and through age 12. Results from a linear mixed effects model, controlling for confounding variables and internalizing behavior, predicted a difference in BMI of approximately 3/4 of a unit at 24 months of age comparing children with high levels of externalizing behavior to children with low levels of externalizing behavior. There was some evidence of effect modification by race; among white children, the average BMI difference remained stable through age 12, but it doubled to 1.5 BMI units among children who were black or another race. Conclusions: Our analyses suggest that externalizing behaviors in early childhood are associated with children's weight status early in childhood and throughout the elementary school years, though the magnitude of the effect is modest.https://doi.org/10.1186/1471-2431-10-4

MicroRNAs in pulmonary arterial remodeling

Pulmonary arterial remodeling is a presently irreversible pathologic hallmark of pulmonary arterial hypertension (PAH). This complex disease involves pathogenic dysregulation of all cell types within the small pulmonary arteries contributing to vascular remodeling leading to intimal lesions, resulting in elevated pulmonary vascular resistance and right heart dysfunction. Mutations within the bone morphogenetic protein receptor 2 gene, leading to dysregulated proliferation of pulmonary artery smooth muscle cells, have been identified as being responsible for heritable PAH. Indeed, the disease is characterized by excessive cellular proliferation and resistance to apoptosis of smooth muscle and endothelial cells. Significant gene dysregulation at the transcriptional and signaling level has been identified. MicroRNAs are small non-coding RNA molecules that negatively regulate gene expression and have the ability to target numerous genes, therefore potentially controlling a host of gene regulatory and signaling pathways. The major role of miRNAs in pulmonary arterial remodeling is still relatively unknown although research data is emerging apace. Modulation of miRNAs represents a possible therapeutic target for altering the remodeling phenotype in the pulmonary vasculature. This review will focus on the role of miRNAs in regulating smooth muscle and endothelial cell phenotypes and their influence on pulmonary remodeling in the setting of PAH

Cyclic AMP-Dependent Protein Kinase A Regulates the Alternative Splicing of CaMKIIδ

Ca2+/calmodulin-dependent protein kinase (CaMK) IIδ is predominantly expressed in the heart. There are three isoforms of CaMKIIδ resulting from the alternative splicing of exons 14, 15, and 16 of its pre-mRNA, which is regulated by the splicing factor SF2/ASF. Inclusion of exons 15 and 16 or of exon 14 generates δA or δB isoform. The exclusion of all three exons gives rise to δC isoform, which is selectively increased in pressure-overload-induced hypertrophy. Overexpression of either δB or δC induces hypertrophy and heart failure, suggesting their specific role in the pathogenesis of hypertrophy and heart failure. It is well known that the β-adrenergic-cyclic AMP-dependent protein kinase A (PKA) pathway is implicated in heart failure. To determine the role of PKA in the alternative splicing of CaMKIIδ, we constructed mini-CaMKIIδ genes and used these genes to investigate the regulation of the alternative splicing of CaMKIIδ by PKA in cultured cells. We found that PKA promoted the exclusion of exons 14, 15, and 16 of CaMKIIδ, resulting in an increase in δC isoform. PKA interacted with and phosphorylated SF2/ASF, and enhanced SF2/ASF's activity to promote the exclusion of exons 14, 15, and 16 of CaMKIIδ, leading to a further increase in the expression of δC isoform. These findings suggest that abnormality in β-adrenergic-PKA signaling may contribute to cardiomyopathy and heart failure through dysregulation in the alternative splicing of CaMKIIδ exons 14, 15, and 16 and up-regulation of CaMKIIδC

Kernel-imbedded Gaussian processes for disease classification using microarray gene expression data

BACKGROUND: Designing appropriate machine learning methods for identifying genes that have a significant discriminating power for disease outcomes has become more and more important for our understanding of diseases at genomic level. Although many machine learning methods have been developed and applied to the area of microarray gene expression data analysis, the majority of them are based on linear models, which however are not necessarily appropriate for the underlying connection between the target disease and its associated explanatory genes. Linear model based methods usually also bring in false positive significant features more easily. Furthermore, linear model based algorithms often involve calculating the inverse of a matrix that is possibly singular when the number of potentially important genes is relatively large. This leads to problems of numerical instability. To overcome these limitations, a few non-linear methods have recently been introduced to the area. Many of the existing non-linear methods have a couple of critical problems, the model selection problem and the model parameter tuning problem, that remain unsolved or even untouched. In general, a unified framework that allows model parameters of both linear and non-linear models to be easily tuned is always preferred in real-world applications. Kernel-induced learning methods form a class of approaches that show promising potentials to achieve this goal. RESULTS: A hierarchical statistical model named kernel-imbedded Gaussian process (KIGP) is developed under a unified Bayesian framework for binary disease classification problems using microarray gene expression data. In particular, based on a probit regression setting, an adaptive algorithm with a cascading structure is designed to find the appropriate kernel, to discover the potentially significant genes, and to make the optimal class prediction accordingly. A Gibbs sampler is built as the core of the algorithm to make Bayesian inferences. Simulation studies showed that, even without any knowledge of the underlying generative model, the KIGP performed very close to the theoretical Bayesian bound not only in the case with a linear Bayesian classifier but also in the case with a very non-linear Bayesian classifier. This sheds light on its broader usability to microarray data analysis problems, especially to those that linear methods work awkwardly. The KIGP was also applied to four published microarray datasets, and the results showed that the KIGP performed better than or at least as well as any of the referred state-of-the-art methods did in all of these cases. CONCLUSION: Mathematically built on the kernel-induced feature space concept under a Bayesian framework, the KIGP method presented in this paper provides a unified machine learning approach to explore both the linear and the possibly non-linear underlying relationship between the target features of a given binary disease classification problem and the related explanatory gene expression data. More importantly, it incorporates the model parameter tuning into the framework. The model selection problem is addressed in the form of selecting a proper kernel type. The KIGP method also gives Bayesian probabilistic predictions for disease classification. These properties and features are beneficial to most real-world applications. The algorithm is naturally robust in numerical computation. The simulation studies and the published data studies demonstrated that the proposed KIGP performs satisfactorily and consistently

A positive role for PEA3 in HER2-mediated breast tumour progression

Overexpression of HER2 is associated with an adverse prognosis in breast cancer. Despite this, the mechanism of its transcriptional regulation remains poorly understood. PEA3, a MAP kinase (MAPK)-activated member of the Ets transcription factor family has been implicated in the transcriptional regulation of HER2. The direction of its modulation remains controversial. We assessed relative levels of PEA3 expression and DNA binding in primary breast cultures derived from patient tumours (n=18) in the presence of an activated MAPK pathway using Western blotting and shift analysis. Expression of PEA3 in breast tumours from patients of known HER2 status (n=107) was examined by immunohistochemistry. In primary breast cancer cell cultures, growth factors induced interaction between PEA3 and its DNA response element. Upregulation of PEA3 expression in the presence of growth factors associated with HER2 positivity and axillary lymph node metastasis (P=0.034 and 0.049, respectively). PEA3 expression in breast cancer tissue associated with reduced disease-free survival (P<0.001), Grade III tumours (P<0.0001) and axillary lymph node metastasis (P=0.026). Co-expression of PEA3 and HER2 significantly associated with rate of recurrence compared to patients who expressed HER2 alone (P=0.0039). These data support a positive role for PEA3 in HER2-mediated oncogenesis in breast cancer

Determinants of subject visit participation in a prospective cohort study of HTLV infection

<p>Abstract</p> <p>Background</p> <p>Understanding participation in a prospective study is crucial to maintaining and improving retention rates. In 1990–92, following attempted blood donation at five blood centers, we enrolled 155 HTLV-I, 387 HTLV-II and 799 HTLV seronegative persons in a long-term prospective cohort.</p> <p>Methods</p> <p>Health questionnaires and physical exams were administered at enrollment and 2-year intervals through 2004. To examine factors influencing attendance at study visits of the cohort participants we calculated odds ratios (ORs) with generalized estimated equations (GEE) to analyze fixed and time-varying predictors of study visit participation.</p> <p>Results</p> <p>There were significant independent associations between better visit attendance and female gender (OR = 1.31), graduate education (OR = 1.86) and income > $75,000 (OR = 2.68). Participants at two centers (OR = 0.47, 0.67) and of Black race/ethnicity (OR = 0.61) were less likely to continue. Higher subject reimbursement for interview was associated with better visit attendance (OR = 1.84 for$25 vs. $10). None of the health related variables (HTLV status, perceived health status and referral to specialty diagnostic exam for potential adverse health outcomes) significantly affected participation after controlling for demographic variables.</p> <p>Conclusion</p> <p>Increasing and maintaining participation by minority and lower socioeconomic status participants is an ongoing challenge in the study of chronic disease outcomes. Future studies should include methods to evaluate attrition and retention, in addition to primary study outcomes, including qualitative analysis of reasons for participation or withdrawal.</p