Microfluidic Exosome Analysis toward Liquid Biopsy for Cancer

Assessment of a tumor’s molecular makeup using biofluid samples, known as liquid biopsy, is a prominent research topic in precision medicine for cancer, due to its noninvasive property allowing repeat sampling for monitoring molecular changes of tumors over time. Circulating exosomes recently have been recognized as promising tumor surrogates because they deliver enriched biomarkers, such as proteins, RNAs, and DNA. However, purification and characterization of these exosomes are technically challenging. Microfluidic lab-on-a-chip technology effectively addresses these challenges owing to its inherent advantages in integration and automation of multiple functional modules, enhancing sensing performance, and expediting analysis processes. In this article, we review the state-of-the-art development of microfluidic technologies for exosome isolation and molecular characterization with emphasis on their applications toward liquid biopsy–based analysis of cancer. Finally, we share our perspectives on current challenges and future directions of microfluidic exosome analysis

Research on Risk Assessment Technology of the Major Hazard in Harbor Engineering

AbstractThe increased construction of harbor infrastructure has led to distinct safety problems recently. A lack of an efficient risk assessment method to evaluate the major hazard (procedure) in harbor engineering has become a vital reason for frequent grave accidents in harbor engineering area. This work, taking the features of harbor engineering into account and starting from the basic concept of “risk”, sets a risk level evaluation standard for both accident consequence measure index and accident possibility measure index based on the survey of current situation of construction enterprises, thus realizing the quantitative assessment and classification towards major hazard and providing rules for major hazard risk assessment on harbor engineering project in the future

Study and Prospects: Adaptive Planning and Control of Supply Chain in One-of-a-kind Production

Based on the research project titled “Adaptive Planning and Control of Supply Chain in One-of-a-kind Production”, the research group performed a systematic review of supply chain integration, risk prediction and control and trace ability. Studies of a computer-aided and integrated production system for cost-effective OKP systemare included. Our efforts relevant to integration of supply chain in OKP, modeling &control of ripple effects in OKP supply chain and the trace ability of the OKP supply chain are introduced in this paper

Disturbance observer based adaptive sliding mode control for continuous stirred tank reactor

The continuous stirred tank reactor (CSTR) typifies an important class of process control systems. Is is a nonlinear system and is sensitive to both external disturbances and system uncertainty. Given these challenges, a nonsingular terminal sliding mode observer is proposed to estimate any external disturbance. Then, a continuous adaptive sliding mode control method is combined with the proposed disturbance observer. This is found to reduce chattering and improve control accuracy when compared with other methods. A full Lyapunov stability proof of the resulting closed-loop system is performed and the effectiveness of the proposed approach is demonstrated by simulation experiments

BsB_s Semileptonic Decays to DsD_s and Ds∗D_s^* in Bethe-Salpeter Method

Using the relativistic Bethe-Salpeter method, the electron energy spectrum and the semileptonic decay widths of $B^0_s\to D^-_s \ell^+{\nu_\ell}$ and $B^0_s\to D_s^{*-}\ell^+{\nu_\ell}$ are calculated. We obtained large branching ratios, $Br(B_s\to D_se\nu_e)=(2.85\pm0.35)$ and $Br (B_s\to D_s^*e\nu_e)=(7.09\pm0.88)$, which can be easily detected in the future experiment.Comment: 3 pages, 3 figures

A microfluidic ExoSearch chip for multiplexed exosome detection towards blood-based ovarian cancer diagnosis

Citation: Zhao, Z., Yang, Y., Zeng, Y., & He, M. (2016). A microfluidic ExoSearch chip for multiplexed exosome detection towards blood-based ovarian cancer diagnosis. Lab on a Chip, 16(3), 489-496. doi:10.1039/c5lc01117eTumor-derived circulating exosomes, enriched with a group of tumor antigens, have been recognized as a promising biomarker source for cancer diagnosis via a less invasive procedure. Quantitatively pinpointing exosome tumor markers is appealing, yet challenging. In this study, we developed a simple microfluidic approach (ExoSearch) which provides enriched preparation of blood plasma exosomes for in situ, multiplexed detection using immunomagnetic beads. The ExoSearch chip offers a robust, continuous-flow design for quantitative isolation and release of blood plasma exosomes in a wide range of preparation volumes (10 mu L to 10 mL). We employed the ExoSearch chip for blood-based diagnosis of ovarian cancer by multiplexed measurement of three exosomal tumor markers (CA-125, EpCAM, CD24) using a training set of ovarian cancer patient plasma, which showed significant diagnostic power (a. u. c. = 1.0, p = 0.001) and was comparable with the standard Bradford assay. This work provides an essentially needed platform for utilization of exosomes in clinical cancer diagnosis, as well as fundamental exosome research

Quantitative spectroscopic analysis of heterogeneous mixtures: the correction of multiplicative effects caused by variations in physical properties of samples

Spectral measurements of complex heterogeneous types of mixture samples are often affected by significant multiplicative effects resulting from light scattering, due to physical variations (e.g. particle size and shape, sample packing and sample surface, etc.) inherent within the individual samples. Therefore, the separation of the spectral contributions due to variations in chemical compositions from those caused by physical variations is crucial to accurate quantitative spectroscopic analysis of heterogeneous samples. In this work, an improved strategy has been proposed to estimate the multiplicative parameters accounting for multiplicative effects in each measured spectrum, and hence mitigate the detrimental influence of multiplicative effects on the quantitative spectroscopic analysis of heterogeneous samples. The basic assumption of the proposed method is that light scattering due to physical variations has the same effects on the spectral contributions of each of the spectroscopically active chemical component in the same sample mixture. Based on this underlying assumption, the proposed method realizes the efficient estimation of the multiplicative parameters by solving a simple quadratic programming problem. The performance of the proposed method has been tested on two publicly available benchmark data sets (i.e. near-infrared total diffuse transmittance spectra of four-component suspension samples and near infrared spectral data of meat samples) and compared with some empirical approaches designed for the same purpose. It was found that the proposed method provided appreciable improvement in quantitative spectroscopic analysis of heterogeneous mixture samples. The study indicates that accurate quantitative spectroscopic analysis of heterogeneous mixture samples can be achieved through the combination of spectroscopic techniques with smart modeling methodology

Onsite data processing and monitoring for the Daya Bay Experiment

The Daya Bay Reactor Neutrino Experiment started running on September 23, 2011. The offline computing environment, consisting of 11 servers at Daya Bay, was built to process onsite data. With current computing ability, onsite data processing is running smoothly. The Performance Quality Monitoring system (PQM) has been developed to monitor the detector performance and data quality. Its main feature is the ability to efficiently process multi-data-stream from three experimental halls. The PQM processes raw data files from the Daya Bay data acquisition system, generates and publishes histograms via a graphical web interface by executing the user-defined algorithm modules, and saves the histograms for permanent storage. The fact that the whole process takes only around 40 minutes makes it valuable for the shift crew to monitor the running status of all the sub-detectors and the data quality