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Introduction Circulating tumour DNA (ctDNA) has potential applications in cancer management. Most previous studies about ctDNA focused on advanced stage cancer patients. We have completed a clinical prospective study (NCT02645318) and showed the feasibility and clinical application of ctDNA detection in early stage non-small cell lung cancer (NSCLC) patients. The aim of this study is to investigate the elimination rate of ctDNA level after surgery. This is the first prospective study to evaluate the perioperative dynamic changes of ctDNA in surgical lung cancer patients. Methods and analysis This is a prospective observational study to determine the elimination rate of circulating tumour DNA after surgery. Consecutive patients with suspected lung cancer who undergo curative-intent lung resection will be enrolled. 10 mL blood samples are taken by intravenous puncture. Plasma samples are obtained before surgery (time A) and at a series of scheduled time-points (2 min to 72 hours, time B to F) after tumour resection. DNA is prepared from 4 mL of purified plasma. A multiplex assay based on circulating single-molecule amplification and resequencing technology (cSMART) is used to simultaneously detect and quantitate hot spot EGFR, KRAS, BRAF, ERBB2, PIK3CA, TP53, ALK, RET and MET plasma DNA variants. Positive plasma mutations are validated in tumour tissue and normal lung tissue by targeted sequencing. Ethics and dissemination Ethical approval has been obtained from the Peking University People's Hospital Medical Ethics Committee (2016PHB156-01). Results will be disseminated through presentations at scientific meetings and publications in peer-reviewed journals. Trial registration number NCT02965391; Pre-results. [ABSTRACT FROM AUTHOR]

A biodegradable poly(lactic-co-glycolic acid) loading atorvastatin calcium (AC) nanoparticles (AC-PLGA-NPs) were prepared by probe ultrasonication and evaporation method aiming at improving the oral bioavailability of AC. The effects of experimental parameters, including stabilizer species, stabilizer concentration and pH of aqueous phase, on particle size were also evaluated. The resultant nanoparticles were in spherical shape with an average diameter of 174.7 nm and a narrow particle size distribution. And the drug loading and encapsulation efficiency were about 8% and 71%, respectively. The particle size and polydispersion were almost unchanged in 10 days. The release curves of AC-PLGA-NPs in vitro displaying sustained release characteristics indicated that its release mechanisms were matrix erosion and diffusion. The pharmacokinetic study in vivo revealed that the Cmax and AUC0-∞ of AC-PLGA-NPs in rats were nearly 3.7-fold and 4.7-fold higher than that of pure atorvastatin calcium suspension. Our results demonstrated that the delivery of AC-PLGANPs could be a promising approach for the oral delivery of AC for enhanced bioavailability. [ABSTRACT FROM AUTHOR]

The aim of this study was to enhance oral bioavailability of itraconazole (ITZ) by developing Liposome containing sodium deoxycholate (ITZ-Lip-NaDC). The liposome, consisting of egg yolk lecithin and sodium deoxycholate, was prepared by thin-film dispersion method. Differential Scanning Calorimetry (DSC) results indicated an amorphous state in the liposome. The physicochemical characteristics including particle size, morphology, entrapment efficiency, dissolution properties were also investigated. The performance of single-pass intestinal infusion exhibited that the transport order of intestinal segment was jejunum, duodenum, colon and ileum, and that all the segments participated in the absorption of ITZ in intestinal tract. The bioavailability study in rats showed that the AUC0-72 of the liposome was nearly 1.67-fold higher than that of commercial capsules (SPORANOX) in terms of oral administration, and the RSD of AUC0-72 of ITZ-Lip-NaDC was also decreased. Our results indicated that ITZ-Lip-NaDC liposome was facilitated to improve dissolution efficiency, augment transmembrane absorption, and then enhance the oral bioavailability of ITZ, successfully. [ABSTRACT FROM AUTHOR]

In this paper, we present design and test of a broadband electrostatic energy harvester with a dual resonant structure, which consists of two cantilever-mass subsystems each with a mass attached at the free edge of a cantilever. Comparing to traditional devices with single resonant frequency, the proposed device with dual resonant structure can resonate at two frequencies. Furthermore, when one of the cantilever-masses is oscillating at resonance, the vibration amplitude is large enough to make it collide with the other mass, which provides strong mechanical coupling between the two subsystems. Therefore, this device can harvest a decent power output from vibration sources at a broad frequency range. During the measurement, continuous power output up to 6.2-9.8 μW can be achieved under external vibration amplitude of 9.3 m/s2 at a frequency range from 36.3 Hz to 48.3 Hz, which means the bandwidth of the device is about 30% of the central frequency. The broad bandwidth of the device provides a promising application for energy harvesting from the scenarios with random vibration sources. The experimental results indicate that with the dual resonant structure, the vibration-to-electricity energy conversion efficiency can be improved by 97% when an external random vibration with a low frequency filter is applied. [ABSTRACT FROM AUTHOR]

The selection of fewer or more representative features from multidimensional features is important when the artificial neural network (ANN) algorithm is used as a classifier. In this paper, a new feature selection method called the mean impact variance (MIVAR)method is proposed to determine the feature that is more suitable for classification. Moreover, this method is constructed on the basis of the training process of the ANN algorithm. To verify the effectiveness of the proposed method, the MIVAR value is used to rank the multidimensional features of the bearing fault diagnosis. In detail, (1) 70-dimensional all waveform features are extracted from a rolling bearing vibration signal with four different operating states, (2) the corresponding MIVAR values of all 70-dimensional features are calculated to rank all features, (3) 14 groups of 10-dimensional features are separately generated according to the ranking results and the principal component analysis (PCA) algorithm and a back propagation (BP) network is constructed, and (4) the validity of the ranking result is proven by training this BP network with these seven groups of 10-dimensional features and by comparing the corresponding recognition rates. The results prove that the features with larger MIVAR value can lead to higher recognition rates. [ABSTRACT FROM AUTHOR]

This paper presents a general framework based on copulas for modeling dependent multivariate uncertainties through the use of a decision tree. The proposed dependent decision tree model allows multiple dependent uncertainties with arbitrary marginal distributions to be represented in a decision tree with a sequence of conditional probability distributions. This general framework could be naturally applied in decision analysis and real options valuations, as well as in more general applications of dependent probability trees. While this approach to modeling dependencies can be based on several popular copula families as we illustrate, we focus on the use of the normal copula and present an efficient computational method for multivariate decision and risk analysis that can be standardized for convenient application. [ABSTRACT FROM AUTHOR]

This paper proposes an approach for solving a multifactor real options problem by approximating the underlying stochastic process with an implied binomial tree. The implied binomial tree is constructed to be consistent with simulated market information. By simulating European option prices as artificial market information, we apply the implied binomial tree method for real options valuation when the options are contingent on the value of market uncertainties that are not traded assets. Compared to the discrete approximations suggested in the current literature, this method offers a more flexible distribution assumption for project values and therefore provides an alternative approach to estimating the value of high-dimensional real options. For risk managers, it serves as a capital budgeting method for projects with managerial flexibility. [ABSTRACT FROM AUTHOR]