Association of promoter methylation with histologic type and pleural indentation in non-small cell lung cancer (NSCLC)

<p>Abstract</p> <p>Background</p> <p>Lung cancer is a major cause of death worldwide. Gene promoter methylation is a major inactivation mechanism of tumor-related genes, some of which can be served as a biomarker for early diagnosis and prognosis evaluation of lung cancer.</p> <p>Methods</p> <p>We determined the promoter methylation of 6 genes using quantitative methylation-specific PCR (Q-MSP) technique in 96 clinically well-characterized non-small cell lung cancer (NSCLC).</p> <p>Results</p> <p>Highly frequent promoter methylation was found in NSCLC. With 100% diagnostic specificity, high sensitivity, ranging from 44.9 to 84.1%, was found for each of the 6 genes. Our data also showed that promoter methylation was closely associated with histologic type. Most of genes were more frequently methylated in squamous cell carcinomas (SCC) compared to adenocarcinomas (ADC). Moreover, promoter methylation significantly increased the risk of pleural indentation in NSCLC.</p> <p>Conclusion</p> <p>Our findings provided evidences that multiple genes were aberrantly methylated in lung tumorigenesis, and demonstrated the promoter methylation was closely associated with clinicopathologic characteristics of NSCLC. More importantly, we first revealed promoter methylation may be served as a potentially increased risk factor for pleural indentation of NSCLC patients.</p

Aberrant DNA methylation of drug metabolism and transport genes in nodular goiter

The genes encoding drug-metabolizing enzymes and transporters play an important role in maintaining the normal life processes of human body. Their disorder or defect will lead to the occurrence and development of various diseases. Currently, most of studies have focused on genetic variations in these genes, however, in the present study, we analyzed promoter methylation of 11 drug metabolism and transport genes in a cohort of nodular goiter and normal thyroid tissues using methylation-specific PCR (MSP). Our data first revealed a distinct methylation profiling in drug metabolism and transport genes between nodular goiter and normal thyroid tissues, particularly ABCB4, CYP1B1 and CYP24A1 and SLC1A2. Given these genes contribute to the development and progression of various diseases, such as multidrug resistance and tumorigenesis, these epigenetic events may thus play a critical role in the pathogenesis of nodular goiter

Bis{μ-1-[(2-oxidophen­yl)imino­meth­yl]-2-naphtholato}bis­[pyridine­copper(II)]

The dinuclear title complex, [Cu2(C17H11NO2)2(C5H5N)2], consists of centrosymmetric dimers in which the CuII atom displays an elongated square-pyramidal coordination geometry. The conformation of the dimer is stabilized by inter­molecular C—H⋯O hydrogen bonds and by π–π aromatic stacking inter­actions involving the pyridine and benzene rings with centroid–centroid separations of 3.624 (3) Å

Oil metal particles Detection Algorithm Based on Wavelet Transform

In order to observe the real-time abrasion status of the aero-engine, we need to monitor the lubrication system online. As the aero-engine operating time and running state changes, the concentration, composition, size and other parameters of the metal debris can show different changes. They can be used as an important indicator to reflect the state of the aero-engine fault. However, due to the influence of electromagnetic, vibration disturbance and random noise signal introduced by the processing unit itself, the metal particles signal tend to comprise noise. Oil metal particles detection algorithm based on wavelet transform, utilizes the optimized localized nature in time domain and frequency domain of wavelet transform and the characteristics of multi-resolution analysis, combined with the signal characteristics in actual aero-engine condition to realize noise reduction and detection, while validating the algorithm using real experimental data. The result shows that noise can be effectively decreased and signal characteristics can be detected correctly

Elevated Foxp3+ double-negative T cells are associated with disease progression during HIV infection

Persistent immune activation, which occurs during the whole course of HIV infection, plays a pivotal role in CD4+ T cells depletion and AIDS progression. Furthermore, immune activation is a key factor that leads to impaired immune reconstitution after long-term effective antiretroviral therapy (ART), and is even responsible for the increased risk of developing non-AIDS co-morbidities. Therefore, it’s imperative to identify an effective intervention targeting HIV-associated immune activation to improve disease management. Double negative T cells (DNT) were reported to provide immunosuppression during HIV infection, but the related mechanisms remained puzzled. Foxp3 endows Tregs with potent suppressive function to maintain immune homeostasis. However, whether DNT cells expressed Foxp3 and the accurate function of these cells urgently needed to be investigated. Here, we found that Foxp3+ DNT cells accumulated in untreated people living with HIV (PLWH) with CD4+ T cell count less than 200 cells/µl. Moreover, the frequency of Foxp3+ DNT cells was negatively correlated with CD4+ T cell count and CD4/CD8 ratio, and positively correlated with immune activation and systemic inflammation in PLWH. Of note, Foxp3+ DNT cells might exert suppressive regulation by increased expression of CD39, CD25, or vigorous proliferation (high levels of GITR and ki67) in ART-naive PLWH. Our study underlined the importance of Foxp3+ DNT cells in the HIV disease progression, and suggest that Foxp3+ DNT may be a potential target for clinical intervention for the control of immune activation during HIV infection

Frequent Gene Amplification Predicts Poor Prognosis in Gastric Cancer

Gastric cancer is one of the most common malignancies worldwide. However, genetic alterations leading to this disease are largely unknown. Gene amplification is one of the most frequent genetic alterations, which is believed to play a major role in the development and progression of gastric cancer. In the present study, we identified three frequently amplified genes from 30 candidate genes using real-time quantitative PCR method, including ERBB4, C-MET and CD44, and further explored their association with clinicopathological characteristics and poor survival in a cohort of gastric cancers. Our data showed amplification of these genes was significantly associated with certain clinicopathological characteristics, particularly tumor differentiation and cancer-related death. More importantly, amplification of these genes was significantly related to worse survival, suggesting that these amplified genes may be significant predictors of poor prognosis and potential therapeutic targets in gastric cancer. Targeting these genes may thus provide new possibilities in the treatment of gastric cancer

Highly frequent PIK3CA amplification is associated with poor prognosis in gastric cancer

<p>Abstract</p> <p>Background</p> <p>The phosphoinositide 3-kinase (PI3K)/Akt pathway plays a fundamental role in cell proliferation and survival in human tumorigenesis, including gastric cancer. <it>PIK3CA </it>mutations and amplification are two major causes of overactivation of this pathway in human cancers. However, until this work, there was no sound investigation on the association of <it>PIK3CA </it>mutations and amplification with clinical outcome in gastric cancer, particularly the latter.</p> <p>Methods</p> <p>Using direct sequencing and real-time quantitative PCR, we examined <it>PIK3CA </it>mutations and amplification, and their association with clinicopathological characteristics and clinical outcome of gastric cancer patients.</p> <p>Results</p> <p><it>PIK3CA </it>mutations and amplification were found in 8/113 (7.1%) and 88/131 (67%) gastric cancer patients, respectively. <it>PIK3CA </it>amplification was closely associated with increased phosphorylated Akt (p-Akt) level. No relationship was found between <it>PIK3CA </it>mutations and clinicopathological characteristics and clinical outcome in gastric cancer. <it>PIK3CA </it>amplification was significantly positively associated with cancer-related death. Importantly, Kaplan-Meier survival curves revealed that the patients with <it>PIK3CA </it>amplification had significantly shorter survival times than the patients without <it>PIK3CA </it>amplification.</p> <p>Conclusions</p> <p>Our data showed that <it>PIK3CA </it>mutations were not common, but its amplification was very common in gastric cancer and may be a major mechanism in activating the PI3K/Akt pathway in gastric cancer. Importantly, Kaplan-Meier survival curves revealed that <it>PIK3CA </it>amplification was significantly positively associated with poor survival of gastric cancer patients. Collectively, the PI3K/Akt signaling pathway may be an effective therapeutic target in gastric cancer.</p

Smoothing sample average approximation method for solving stochastic second-order-cone complementarity problems

Abstract In this paper, we consider stochastic second-order-cone complementarity problems (SSOCCP). We first use the so-called second-order-cone complementarity function to present an expected residual minimization (ERM) model for giving reasonable solutions of SSOCCP. Then, we introduce a smoothing function, by which we obtain a smoothing approximate ERM model. We further show that the global solution sequence and weak stationary point sequence of this smoothing approximate ERM model converge to the global solution and the weak stationary point of the original ERM model as the smoothing parameter tends to zero respectively. Moreover, since the ERM formulation contains an expectation, we employ a sample average approximate method for solving the smoothing ERM model. As the convergence analysis, we first show that the global optimal solution of this smoothing sample average approximate problem converges to the global optimal solution of the ERM problem with probability one. Subsequently, we consider the weak stationary points’ convergence results of this smoothing sample average approximate problem of ERM model. Finally, some numerical examples are given to explain that the proposed methods are feasible