Application of serum SELDI proteomic patterns in diagnosis of lung cancer

BACKGROUND: Currently, no satisfactory biomarkers are available to screen for lung cancer. Surface-Enhanced Laser Desorption/ionization Time-of- Flight Mass Spectrometry ProteinChip system (SELDI-TOF-MS) is one of the currently used techniques to identify biomarkers for cancers. The aim of this study is to explore the application of serum SELDI proteomic patterns to distinguish lung cancer patients from healthy individuals. METHODS: A total of 208 serum samples, including 158 lung cancer patients and 50 healthy individuals, were randomly divided into a training set (including 11 sera from patients with stages I/II lung cancer, 63 from patients with stages III/IV lung cancer and 20 from healthy controls) and a blinded test set (including 43 sera from patients with stages I/II lung cancer, 41 from patients with stages III/IV lung cancer and 30 from healthy controls). All samples were analyzed by SELDI technology. The spectra were generated on weak cation exchange (WCX2) chips, and protein peaks clustering and classification analyses were made using Ciphergen Biomarker Wizard and Biomarker Pattern software, respectively. We additionally determined Cyfra21-1 and NSE in the 208 serum samples included in this study using an electrochemiluminescent immunoassay. RESULTS: Five protein peaks at 11493, 6429, 8245, 5335 and 2538 Da were automatically chosen as a biomarker pattern in the training set. When the SELDI marker pattern was tested with the blinded test set, it yielded a sensitivity of 86.9%, a specificity of 80.0% and a positive predictive value of 92.4%. The sensitivities provided by Cyfra21-1 and NSE used individually or in combination were significantly lower than that of the SELDI marker pattern (P < 0.005 or 0.05, respectively). Based on the results of the test set, we found that the SELDI marker pattern showed a sensitivity of 91.4% in the detection of non-small cell lung cancers (NSCLC), which was significantly higher than that in the detection of small cell lung cancers (P < 0.05); The pattern also had a sensitivity of 79.1% in the detection of lung cancers in stages I/II. CONCLUSION: These results suggest that serum SELDI protein profiling can distinguish lung cancer patients, especially NSCLC patients, from normal subjects with relatively high sensitivity and specificity, and the SELDI-TOF-MS is a potential tool for the screening of lung cancer

A Bioinformatics Filtering Strategy for Identifying Radiation Response Biomarker Candidates

The number of biomarker candidates is often much larger than the number of clinical patient data points available, which motivates the use of a rational candidate variable filtering methodology. The goal of this paper is to apply such a bioinformatics filtering process to isolate a modest number (<10) of key interacting genes and their associated single nucleotide polymorphisms involved in radiation response, and to ultimately serve as a basis for using clinical datasets to identify new biomarkers. In step 1, we surveyed the literature on genetic and protein correlates to radiation response, in vivo or in vitro, across cellular, animal, and human studies. In step 2, we analyzed two publicly available microarray datasets and identified genes in which mRNA expression changed in response to radiation. Combining results from Step 1 and Step 2, we identified 20 genes that were common to all three sources. As a final step, a curated database of protein interactions was used to generate the most statistically reliable protein interaction network among any subset of the 20 genes resulting from Steps 1 and 2, resulting in identification of a small, tightly interacting network with 7 out of 20 input genes. We further ranked the genes in terms of likely importance, based on their location within the network using a graph-based scoring function. The resulting core interacting network provides an attractive set of genes likely to be important to radiation response

The Influence of Subjective Socioeconomic Status on Life Satisfaction: The Chain Mediating Role of Social Equity and Social Trust

Life satisfaction is significantly influenced by social capital, a key sociological term that links people to their social surroundings. Through a survey of 17,217 Chinese residents, this study investigated the probable processes of how subjective socioeconomic status affects life satisfaction within the framework of social capital. The results indicate that there is a positive correlation between subjective socioeconomic status and life satisfaction. Subjective socioeconomic status influences citizens’ life satisfaction not only through the independent mediating effects of perceived social equity and social trust, but also through the chain mediation of perceived social equity and social trust. This research advances our knowledge of the mechanisms behind the association between subjective socioeconomic status and life satisfaction. In improving citizens’ life satisfaction, we should not only provide sufficient subjective socioeconomic status to improve it, but also focus on the improvement of their social equity perceptions and social trust

Regular Tennis Exercise May Improve the Vascular Endothelial Function in Postmenopausal Women: The Influence of Hemodynamics

Physical inactivity plays a role in the incidence of cardiovascular disease (CVD). Although the current guidelines for physical activity, such as the prescription of exercise, seek to combat CVD, attaining the recommended targets remains challenging. Tennis exercise has been proven to have a unique advantage in reducing the mortality of CVD, but little is known about the influence of playing tennis on impaired vascular endothelial function (VEF), which initiates CVD. Thus, this study aimed to investigate whether regular tennis participation could protect the VEF better than merely meeting the physical activity recommended by the current guidelines. A cross-sectional design was performed based on a sample of 38 healthy postmenopausal women who were matched for physical activity, of which 17 subjects had long-term tennis experience and 21 age-matched subjects regularly exercised but did not play tennis. The cardiovascular function and the body composition of all subjects were measured. We used cluster analysis to assess the overall health status. The modeling results showed that the tennis players performed better in terms of VEF than the nonplayers (10.55 &plusmn; 0.58 vs. 8.69 &plusmn; 0.52, p &lt; 0.01, R2ad = 0.367), while the wall shear stress positively correlated with VEF (r = 0.505, p &lt; 0.05), after controlling for age and physical activity levels. Regular tennis exercise may be a protective factor for VEF, and further study should be performed to research the role of hemodynamics in tennis exercise

A hierarchical game theoretic framework for cognitive radio networks

We consider OFDMA-based cognitive radio (CR) networks where multiple secondary users (SUs) compete for the available sub-bands in the spectrum of multiple primary users (PUs). We focus on maximizing the payoff of both SUs and PUs by jointly optimizing transmit powers of SUs, sub-band allocations of SUs, and the prices charged by PUs. To further improve the performance of SUs, we allow SUs who share the same sub-band to cooperate with each other to send and receive signals. To help us understand the interaction among SUs and PUs, we study the proposed network model from a game theoretic perspective. More specifically, we first formulate a coalition formation game to study the sub-band allocation problem of SUs and then integrate the coalition formation game into a Stackelberg game-based hierarchical framework. We propose a simple distributed algorithm for SUs to search for the optimal sub-bands. We prove that the transmit power and sub-band allocation of SUs and the price charged by PUs are interrelated by the pricing function of PUs. This makes the joint optimization possible. More importantly, we prove that if the pricing coefficients of PUs have a fixed linear relationship, the sub-band allocation of SUs will be stable and the Stackelberg equilibrium of the hierarchical game framework will be unique and optimal. We propose a simple distributed algorithm to achieve the Stackelberg equilibrium of the hierarchical game. Our proposed algorithm does not require SUs to know the interference temperature limit of each PU, and has low communication overheads between SUs and PUs

An effective LFM signal reconstruction method for signal denoising

One of the main challenges in signal denoising is to accurately restore useful signals in low signal-to-noise ratio (SNR) scenarios. In this paper, we investigate the signal denoising problem for multi-component linear frequency modulated (LFM) signals. An effective time-frequency (TF) analysis-based approach is proposed. Compared to the existing approaches, our proposed one can further increase the noise suppressing performance and improve the quality of the reconstructed signal. Experimental results are presented to show that the proposed denoising approach is able to effectively separate the multi-component LFM signal from the strong noise environments

Guidelines for Installation of Sensors in Smart Sensing Platforms in Underground Spaces

The purpose of this study is to propose guidelines for sensor installation in different types of underground space smart sensing platforms. Firstly, we classify the underground space, analyze the scene requirements according to the classification of underground space, and sort out the requirements for sensors in various types of underground space. Secondly, according to the requirements of underground space scenes for sensors, the types of sensors and corresponding parameters are clarified. After that, the system design and sensor installation guidelines of the underground space smart sensing platform are proposed by sorting out the data acquired by the sensor