959 resultados para MOLECULAR ASSOCIATION
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Background Ras-related nuclear protein (Ran) is required for cancer cell survival in vitro and human cancer progression, but the molecular mechanisms are largely unknown. Methods We investigated the effect of the v-myc myelocytomatosis viral oncogene homolog (Myc) on Ran expression by Western blot, chromatin immunoprecipitation, and luciferase reporter assays and the effects of Myc and Ran expression in cancer cells by soft-agar, cell adhesion, and invasion assays. The correlation between Myc and Ran and the association with patient survival were investigated in 14 independent patient cohorts (n = 2430) and analyzed with Spearman's rank correlation and Kaplan-Meier plots coupled with Wilcoxon-Gehan tests, respectively. All statistical tests were two-sided. Results Myc binds to the upstream sequence of Ran and transactivates Ran promoter activity. Overexpression of Myc upregulates Ran expression, whereas knockdown of Myc downregulates Ran expression. Myc or Ran overexpression in breast cancer cells is associated with cancer progression and metastasis. Knockdown of Ran reverses the effect induced by Myc overexpression in breast cancer cells. In clinical data, a positive association between Myc and Ran expression was revealed in 288 breast cancer and 102 lung cancer specimens. Moreover, Ran expression levels differentiate better or poorer survival in Myc overexpressing breast (χ2 = 24.1; relative risk [RR] = 9.1, 95% confidence interval [CI] = 3.3 to 24.7, P <. 001) and lung (χ2 = 6.04; RR = 2.8, 95% CI = 1.2 to 6.3; P =. 01) cancer cohorts. Conclusions Our results suggest that Ran is required for and is a potential therapeutic target of Myc-driven cancer progression in both breast and lung cancers. © 2013 The Author.
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To investigate the correlation between postmenopausal osteoporosis (PMO) and the pathogenesis of periodontitis, ovariectomized rats were generated and the experimental periodontitis was induced using a silk ligature. The inflammatory factors and bone metabolic markers were measured in the serum and periodontal tissues of ovariectomized rats using an automatic chemistry analyzer, enzyme-linked immunosorbent assays, and immunohistochemistry. The bone mineral density of whole body, pelvis, and spine was analyzed using dual-energy X-ray absorptiometry and image analysis. All data were analyzed using SPSS 13.0 statistical software. It was found that ovariectomy could upregulate the expression of interleukin- (IL-)6, the receptor activator of nuclear factor-κB ligand (RANKL), and osteoprotegerin (OPG) and downregulate IL-10 expression in periodontal tissues, which resulted in progressive alveolar bone loss in experimental periodontitis. This study indicates that changes of cytokines and bone turnover markers in the periodontal tissues of ovariectomized rats contribute to the damage of periodontal tissues.
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We report here that the expression of endogenous microRNAs (miRNAs) can be efficiently silenced in Arabidopsis thaliana (Arabidopsis) using artificial miRNA (amiRNA) technology. We demonstrate that an amiRNA designed to target a mature miRNA directs silencing against all miRNA family members, whereas an amiRNA designed to target the stem-loop region of a miRNA precursor transcript directs silencing against only the individual family member targeted. Furthermore, our results indicate that amiRNAs targeting both the mature miRNA and stem-loop sequence direct RNA silencing through cleavage of the miRNA precursor transcript, which presumably occurs in the nucleus of a plant cell during the initial stages of miRNA biogenesis. This suggests that small RNA (sRNA)-guided RNA cleavage in plants occurs not only in the cytoplasm, but also in the nucleus. Many plant miRNA gene families have been identified via sequencing and bioinformatic analysis, but, to date, only a small tranche of these have been functionally characterized due to a lack of effective forward or reverse genetic tools. Our findings therefore provide a new and powerful reverse-genetic tool for the analysis of miRNA function in plants. © The Author 2010. Published by the Molecular Plant Shanghai Editorial Office in association with Oxford University Press on behalf of CSPP and IPPE, SIBS, CAS.
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This study examined the prevalence of depressive symptoms and elucidated the causal pathway between socioeconomic status and depression in a community in the central region of Vietnam. The study used a combination of qualitative and quantitative research methods. Indepth interviews were applied with two local psychiatric experts and ten residents for qualitative research. A cross sectional survey with structured interview technique was implemented with 100 residents in the pilot quantitative survey. The Center for Epidemiological Studies-Depression Scale (CES-D) was applied to valuate depressive symptoms ( CES-D score over 21) and depression ( CESD core over 25). Ordinary Least Squares Regression following the three steps of Baron and Kenny’s framework was employed for testing mediation models. There was a strong social gradient with respect to depressive symptoms. People with higher education levels reported fewer depressive symptoms (lower CES-D scores). Incomes were also inversely associated with depressive symptoms, but only the ones at the bottom of the quartile income. Low level and unstable individuals in terms of occupation were associated with higher depressive symptoms compared with the highest occupation group. Employment status showed the strongest gradient with respect to its impact on the burden of depressive symptoms compared with other indicators of SES. Findings from this pilot study suggest a pattern on the negative association between socioeconomic status and depression in Vietnamese adults.
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Association rule mining is one technique that is widely used when querying databases, especially those that are transactional, in order to obtain useful associations or correlations among sets of items. Much work has been done focusing on efficiency, effectiveness and redundancy. There has also been a focusing on the quality of rules from single level datasets with many interestingness measures proposed. However, with multi-level datasets now being common there is a lack of interestingness measures developed for multi-level and cross-level rules. Single level measures do not take into account the hierarchy found in a multi-level dataset. This leaves the Support-Confidence approach, which does not consider the hierarchy anyway and has other drawbacks, as one of the few measures available. In this chapter we propose two approaches which measure multi-level association rules to help evaluate their interestingness by considering the database’s underlying taxonomy. These measures of diversity and peculiarity can be used to help identify those rules from multi-level datasets that are potentially useful.
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Lycopene is a phytochemical that belongs to a group of pigments known as carotenoids. It is red, lipophilic and naturally occurring in many fruits and vegetables, with tomatoes and tomato-based products containing the highest concentrations of bioavailable lycopene. Several epidemiological studies have linked increased lycopene consumption with decreased prostate cancer risk. These findings are supported by in vitro and in vivo experiments showing that lycopene not only enhances the antioxidant response of prostate cells, but that it is even able to inhibit proliferation, induce apoptosis and decrease the metastatic capacity of prostate cancer cells. However, there is still no clearly proven clinical evidence supporting the use of lycopene in the prevention or treatment of prostate cancer, due to the only limited number of published randomized clinical trials and the varying quality of existing studies. The scope of this article is to discuss the potential impact of lycopene on prostate cancer by giving an overview about its molecular mechanisms and clinical effects. © 2013 by the authors; licensee MDPI, Basel, Switzerland.
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Kallikrein-related peptidases, in particular KLK4, 5, 6 and 7 (4-7), often have elevated expression levels in ovarian cancer. In OV-MZ-6 ovarian cancer cells, combined expression of KLK4-7 reduces cell adhesion and increases cell invasion and resistance to paclitaxel. The present work investigates how KLK4-7 shape the secreted proteome ("secretome") and proteolytic profile ("degradome") of ovarian cancer cells. The secretome comparison consistently identified >900 proteins in three replicate analyses. Expression of KLK4-7 predominantly affected the abundance of proteins involved in cell-cell communication. Among others, this includes increased levels of transforming growth factor β-1 (TGFβ-1). KLK4-7 co-transfected OV-MZ-6 cells share prominent features of elevated TGFβ-1 signaling, including increased abundance of neural cell adhesion molecule L1 (L1CAM). Augmented levels of TGFβ-1 and L1CAM upon expression of KLK4-7 were corroborated in vivo by an ovarian cancer xenograft model. The degradomic analysis showed that KLK4-7 expression mostly affected cleavage sites C-terminal to arginine, corresponding to the preference of kallikreins 4, 5 and 6. Putative kallikrein substrates include chemokines, such as growth differentiation factor 15 (GDF 15) and macrophage migration inhibitory factor (MIF). Proteolytic maturation of TGFβ-1 was also elevated. KLK4-7 have a pronounced, yet non-degrading impact on the secreted proteome, with a strong association between these proteases and TGFβ-1 signaling in tumor biology. © 2013 Federation of European Biochemical Societies.
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Bone, a hard biological material, possesses a combination of high stiffness and toughness, even though the main basic building blocks of bone are simply mineral platelets and protein molecules. Bone has a very complex microstructure with at least seven hierachical levels. This unique material characteristic attracts great attention, but the deformation mechanisms in bone have not been well understood. Simulation at nano-length scale such as molecular dynamics (MD) is proven to be a powerful tool to investigate bone nanomechanics for developing new artificial biological materials. This study focuses on the ultra large and thin layer of extrafibrillar protein matrix (thickness = ~ 1 nm) located between mineralized collagen fibrils (MCF). Non-collagenous proteins such as osteopontin (OPN) can be found in this protein matrix, while MCF consists mainly of hydroxyapatite (HA) nanoplatelets (thickness = 1.5 – 4.5 nm). By using molecular dynamics method, an OPN peptide was pulled between two HA mineral platelets with water in presence. Periodic boundary condition (PBC) was applied. The results indicate that the mechanical response of OPN peptide greatly depends on the attractive electrostatics interaction between the acidic residues in OPN peptide and HA mineral surfaces. These bonds restrict the movement of OPN peptide, leading to a high energy dissipation under shear loading.
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Although at present, there is a high incidence of prostate cancer, particularly in the Western world, mortality from this disease is declining and occurs primarily only from clinically significant late stage tumors with a poor prognosis. A major current focus of this field is the identification of new biomarkers which can detect earlier, and more effectively, clinically significant tumors from those deemed “low risk”, as well as predict the prognostic course of a particular cancer. This strategy can in turn offer novel avenues for targeted therapies. The large family of Receptor Tyrosine Kinases, the Ephs, and their binding partners, the ephrins, has been implicated in many cancers of epithelial origin through stimulation of oncogenic transformation, tumor angiogenesis, and promotion of increased cell survival, invasion and migration. They also show promise as both biomarkers of diagnostic and prognostic value and as targeted therapies in cancer. This review will briefly discuss the complex roles and biological mechanisms of action of these receptors and ligands and, with regard to prostate cancer, highlight their potential as biomarkers for both diagnosis and prognosis, their application as imaging agents, and current approaches to assessing them as therapeutic targets. This review demonstrates the need for future studies into those particular family members that will prove helpful in understanding the biology and potential as targets for treatment of prostate cancer.
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The last four decades have seen a significant increase in the incidence of non-Hodgkin's lymphoma (NHL) as a possible result of increasing environmental carcinogen exposure, particularly pesticides and solvents. Based on the increasing evidence for an association between carcinogen exposure-related cancer risk and xenobiotic gene polymorphisms, we have undertaken a case-control study of xenobiotic gene polymorphisms in individuals with a diagnosis of NHL. Polymorphisms of six xenobiotic genes (CYP1A1, GSTT1, GSTM1, PON1, NAT1, NAT2) were characterized in 169 individuals with NHL and 205 normal controls using polymerase chain reaction-based methods. Polymorphic frequencies were compared using Fisher's exact tests, and odds ratios for NHL risk were calculated. Among the NHL group, the incidence of GSTT1 null and PON1 BB genotypes were significantly increased compared with controls, 34% vs 14%, and 24% vs 11% respectively. Adjusted odds ratios calculated from multivariate analyses demonstrated that GSTT1 null conferred a fourfold increase in NHL risk (OR = 4.27; 95% CI, 2.40-7.61, P < 0.001) and PON1 BB a 2.9-fold increase (OR = 2.92; 95% CI, 1.49-5.72, P = 0.002). Furthermore, GSTT1 null combined with PON1 BB or GSTM1 null conferred an additional risk of NHL. This is the first time that a PON1 gene polymorphism has been shown to be associated with cancer risk. We conclude that the two polymorphisms, GSTT1 null and PON1 BB, are common genetic traits that pose low individual risk but may be important determinants of overall population NHL risk, particularly among groups exposed to NHL-related carcinogens.
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Background Transmission of Plasmodium vivax malaria is dependent on vector availability, biting rates and parasite development. In turn, each of these is influenced by climatic conditions. Correlations have previously been detected between seasonal rainfall, temperature and malaria incidence patterns in various settings. An understanding of seasonal patterns of malaria, and their weather drivers, can provide vital information for control and elimination activities. This research aimed to describe temporal patterns in malaria, rainfall and temperature, and to examine the relationships between these variables within four counties of Yunnan Province, China. Methods Plasmodium vivax malaria surveillance data (1991–2006), and average monthly temperature and rainfall were acquired. Seasonal trend decomposition was used to examine secular trends and seasonal patterns in malaria. Distributed lag non-linear models were used to estimate the weather drivers of malaria seasonality, including the lag periods between weather conditions and malaria incidence. Results There was a declining trend in malaria incidence in all four counties. Increasing temperature resulted in increased malaria risk in all four areas and increasing rainfall resulted in increased malaria risk in one area and decreased malaria risk in one area. The lag times for these associations varied between areas. Conclusions The differences detected between the four counties highlight the need for local understanding of seasonal patterns of malaria and its climatic drivers.
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As of today, opinion mining has been widely used to iden- tify the strength and weakness of products (e.g., cameras) or services (e.g., services in medical clinics or hospitals) based upon people's feed- back such as user reviews. Feature extraction is a crucial step for opinion mining which has been used to collect useful information from user reviews. Most existing approaches only find individual features of a product without the structural relationships between the features which usually exists. In this paper, we propose an approach to extract features and feature relationship, represented as tree structure called a feature hi- erarchy, based on frequent patterns and associations between patterns derived from user reviews. The generated feature hierarchy profiles the product at multiple levels and provides more detailed information about the product. Our experiment results based on some popularly used review datasets show that the proposed feature extraction approach can identify more correct features than the baseline model. Even though the datasets used in the experiment are about cameras, our work can be ap- plied to generate features about a service such as the services in hospitals or clinics.
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BACKGROUND: Variations in 'slope' (how steep or flat the ground is) may be good for health. As walking up hills is a physiologically vigorous physical activity and can contribute to weight control, greater neighbourhood slopes may provide a protective barrier to weight gain, and help prevent Type 2 diabetes onset. We explored whether living in 'hilly' neighbourhoods was associated with diabetes prevalence among the Australian adult population. METHODS: Participants ([greater than or equal to]25years; n=11,406) who completed the Western Australian Health and Wellbeing Surveillance System Survey (2003-2009) were asked whether or not they had medically-diagnosed diabetes. Geographic Information Systems (GIS) software was used to calculate a neighbourhood mean slope score, and other built environment measures at 1600m around each participant's home. Logistic regression models were used to predict the odds of self-reported diabetes after progressive adjustment for individual measures (i.e., age, sex), socioeconomic status (i.e., education, income), built environment, destinations, nutrition, and amount of walking. RESULTS: After full adjustment, the odds of self-reported diabetes was 0.72 (95% CI 0.55-0.95) and 0.52 (95% CI 0.39-0.69) for adults living in neighbourhoods with moderate and higher levels of slope, respectively, compared with adults living in neighbourhoods with the lowest levels of slope. The odds of having diabetes was 13% lower (odds ratio 0.87; 95% CI 0.80-0.94) for each increase of one percent in mean slope. CONCLUSIONS: Living in a hilly neighbourhood may be protective of diabetes onset or this finding is spurious. Nevertheless, the results are promising and have implications for future research and the practice of flattening land in new housing developments.