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The ability to accurately quantify the protein coverage on nanoparticles is critical for assessing the quality of the surface chemistry and the success of the functionalization process of protein-nanoparticle conjugates. Surface coverage determination is therefore an integral part in the quality control of protein-modified nanoparticles in industrial nanotechnology. In this work, a novel and conventional method was established for direct quantification of the protein surface coverage on metallic nanoparticles. Different concentrations of pepsin were conjugated to gold nanoparticles (GNPs) by a straightforward adsorptive immobilization process as a model system, and a protein quantitation methodology based on the amino acid analysis of the hydrolysate of the protein-GNP conjugates was established. For this purpose, pepsin functionalized GNPs (pepsin-GNP bioconjugates) were processed via in situ hydrolysis with 6N HCl and subsequent derivatization with 6-aminoquinolyl- N -hydroxysuccinimidyl carbamate (AQC reagent). Direct quantitative amino acid analysis was performed based on measuring the intensity of AQC-glycine derivative by high-performance liquid chromatography with fluorescence detection (HPLC-FLD). The method allows for detection of surface coverages as low as 0.1 μg mL −1 pepsin (corresponding to 2.89 × 10 −9 mol L −1 ) in the colloidal solution. Method imprecision for replicated surface coverage determinations was

Long non-coding RNAs (lncRNAs) have been demonstrated to play essential roles in diverse cellular processes and biological functions. Exploring the functions associated with lncRNAs may help provide insight into their underlying biological mechanisms. The current methods primarily focus on investigating the functions of individual lncRNAs; however, essential biological functions may be affected by the combinatorial effects of multiple lncRNAs. Here, we have developed a novel computational method, LncRNAs2Pathways, to identify the functional pathways influenced by the combinatorial effects of a set of lncRNAs of interest based on a global network propagation algorithm. A new Kolmogorov–Smirnov-like statistical measure weighted by the network propagation score, which considers the expression correlation among lncRNAs and coding genes, was used to evaluate the biological pathways influenced by the lncRNAs of interest. We have described the LncRNAs2Pathways methodology and illustrated its effectiveness by analyzing three lncRNA sets associated with glioma, prostate and pancreatic cancers. We further analyzed the reproducibility and robustness and compared our results with those of two other methods. Based on these analyses, we showed that LncRNAs2Pathways can effectively identify the functional pathways associated with lncRNA sets. Finally, we implemented this method as a freely available R-based tool.

Grafting robots have been developed in the world, but some auxiliary works such as gap-inspecting for grafted seedlings still need to be done by human. An machine-vision system of gap inspection for grafted muskmelon seedlings was developed in this study. The image acquiring system consists of a CCD camera, a lens and a front white lighting source. The image of inspected gap was processed and analyzed by software of HALCON 12.0. The recognition algorithm for the system is based on principle of deformable template matching. A template should be created from an image of qualified grafted seedling gap. Then the gap image of the grafted seedling will be compared with the created template to determine their matching degree. Based on the similarity between the gap image of grafted seedling and the template, the matching degree will be 0 to 1. The less similar for the grafted seedling gap with the template the smaller of matching degree. Thirdly, the gap will be output as qualified or unqualified. If the matching degree of grafted seedling gap and the template is less than 0.58, or there is no match is found, the gap will be judged as unqualified; otherwise the gap will be qualified. Finally, 100 muskmelon seedlings were grafted and inspected to test the gap inspection system. Results showed that the gap inspection machine-vision system could recognize the gap qualification correctly as 98% of human vision. And the inspection speed of this system can reach 15 seedlings·min-1. The gap inspection process in grafting can be fully automated with this developed machine-vision system, and the gap inspection system will be a key step of a fully-automatic grafting robots.

Surface-modified gold nanoparticles (GNPs) were synthesized via layer-by-layer process with alternating cationic polyallylamine and anionic poly(acrylic acid) polyelectrolyte layers leading to a highly hydrophilic biocompatible shell supporting colloidal stability. Afterwards, papain was covalently immobilized on the modified GNPs via amide coupling between the amino groups on papain and the terminal carboxylic groups of the modified GNPs by using N-(3-dimethylaminopropyl)-N'-ethylcarbodiimide and N-hydroxysulfosuccinimide sodium as coupling agents. The resultant papain-functionalized gold nanoparticles were characterized by surface plasmon resonance, dynamic light scattering and zeta potential measurements. The new technology resonant mass measurement was applied for determining the average number of papain molecules immobilized per GNP by measurement of the single nanoparticle buoyant mass in the range of femtograms. The activity of the immobilized enzyme was estimated by determination of the kinetic parameters (Km, Vmax and kcat) with the standard chromogenic substrate Nα-benzoyl-dl-arginine-4-nitroanilide hydrochloride. It was found that Km of immobilized and free enzyme are in the same order of magnitude. On contrary, turnover numbers kcat were significantly higher for GNP-conjugated papain. Further, the gold nanobiocatalyst was applied for digestion of polyclonal human immunoglobulin G to yield protein fragments. The resultant fragment mixture was further analyzed by high-performance liquid chromatography-microelectrospray ionization-quadrupole-time-of-flight mass spectrometry, which demonstrated the applicability of the bioreactor based on papain functionalized GNPs. The immobilized papain not only has higher catalytic activity and better stability, but also can be easily isolated from the reaction medium by straightforward centrifugation steps for reuse.

In many cases, the correlation between time series has a certain lag effect. To study the lag correlation between two time series variables, we select London Metal Exchange (LME) nickel futures and spot prices from 3 January 2008 to 29 December 2017 as sample data to carry out stationarity tests, cointegration tests and Granger causality tests to determine the stationarity and correlation of two time series. Then, we use the method of combining the distributed lag model and sliding window method to construct a network. We select the best sliding window length through a sensitivity test. The time series is reconstructed into a complex network by taking the types of patterns as the nodes and the conduction relationship between the patterns as the edges. The number of transitions between patterns is defined as the weight of the edge. The results show that the spot price changes are caused by the change in nickel futures price and that the optimal sliding window length is 64. Additionally, 12 types of patterns account for a large proportion of the patterns in the network. Six patterns are the main intermediaries of pattern transmission and appear centrally with the change in the market environment. Therefore, the relationship model between these futures and spot prices has remained stable for a long time. Combining the positive and negative news of the market, we identify the timing of the change in the relationship model and can use this approach to improve the accuracy of early warning methods. This study provides a method to construct a complex network using a distributed lag model, which can help analyze two real time series variables with lag correlation.

In this paper, as applications of singularity theory, we study the singularities of several worldsheets generated by null Cartan curves in Lorentz–Minkowski space–time. Using the approach of the unfolding theory in singularity theory, we establish the relationships between these worldsheets and invariants such that the cuspidal edge type of singularity and the swallowtail type of singularity can be characterized by these invariants, respectively. Meanwhile, the contact of the tangent curve of a null Cartan curve with some model surfaces are discussed in detail. In addition, we also describe the dual relationships between the tangent curve of a null Cartan curve and these worldsheets. Finally, some concrete examples are provided to explain our theoretical results.

The use of conductive polymer composites (CPCs) as strain sensors has been widely investigated and various resistivity-strain sensitivities are desirable for different applications. In this study, the use of mixed carbon fillers and functionalized carbon nanotubes was demonstrated to be vital for preparing thermoplastic polyurethane (TPU)-based strain sensors with tunable sensitivity. To understand the strain sensing behavior, we carried out scanning electron microscopy (SEM), Raman spectroscopy, wide-angle X-ray diffraction (WAXD), mechanical test, and rheology-electrical measurement. Hybrid fillers of multi-walled carbon nanotubes (MWNTs) and carbon black (CB) could reduce the entanglement in conductive network structure, thus increase the resistivity-strain sensitivity. Furthermore, incorporation of additional functionalized MWNTs in the CPCs could enhance the interfacial interaction between nanofillers and TPU, leading to further increase in sensitivity. Through such a simple method, strain sensors could be efficiently fabricated with large strain-sensing capability (strain as large as 200%) and a wide range of strain sensitivity (gauge factor ranging from 5 to 140238). Finally, the exponential revolution of resistive response to strain was fitted with a model based on tunneling theory by Simmons. It was observed that the change in tunneling distance and the number of conductive pathways could be accelerated significantly by adjusting conductive network structure and interfacial interaction. This study provides a guideline for the preparation of high-performance CPC strain sensors with a large range of resistivity-strain sensitivity.

Stretchable conductors, which can keep their excellent electrical conductivity while highly stretched, have been investigated extensively due to their wide range of applications in flexible and stretchable electronics, wearable displays, etc.; however, their preparation is often complicated and expensive. Herein, an efficient method to prepare high performance stretchable conductors through morphological control of conductive networks formed with carbon nanotubes (CNTs) in an elastomer matrix is reported. It is observed that an interface-mediated method could be used to align randomly oriented filler during stretching and to induce buckling of CNTs during relaxation. Further morphological studies indicate the possible formation of a wavy CNT structure induced by cyclic pre-straining. Subsequent thermal annealing is observed to collapse the oriented network and improve the local contacts between conductive networks. Through such a simple procedure, a conductivity of nearly 1000 S m(-1) and a stretchability of 200% can be achieved for composites containing 20 wt% CNTs. CNTs are observed to buckle over a large area in polymer bulk, and the combination of pre-straining and thermal annealing modifies the conductive network in the elastomer matrix. As a general method, this could be used for easy fabrication of high-performance stretchable conductors for arbitrary-shaped objects on a large scale.

Aim: Peripheral blood-derived endothelial cells (pBD-ECs) are an attractive tool for cell therapies and tissue engineering, but have been limited by their low isolation yield. We increase pBD-EC yield via administration of the chemokine receptor type 4 antagonist AMD3100, as well as via a diluted whole blood incubation (DWBI). Materials & Methods: Porcine pBD-ECs were isolated using AMD3100 and DWBI and tested for EC markers, acetylated LDL uptake, growth kinetics, metabolic activity, flow-mediated nitric oxide production and seeded onto titanium tubes implanted into vessels of pigs. Results: DWBI increased the yield of porcine pBD-ECs 6.6-fold, and AMD3100 increased the yield 4.5-fold. AMD3100-mobilized ECs were phenotypically indistinguishable from nonmobilized ECs. In porcine implants, the cells expressed endothelial nitric oxide synthase, reduced thrombin-antithrombin complex systemically and prevented thrombosis. Conclusion: Administration of AMD3100 and the DWBI method both increase pBD-EC yield.

Virtual Reality Technology was born to have the potentiality of constructing an effective learning environment due to its 3I characteristics: Interaction, Immersion and Imagination. It is now applied in education in a more profound way along with the development of Virtual Reality Technology. Virtual Culture Museum is one of the applications. The Virtual Culture Museum is based on the VRML technology, and extensibility is the most important factor. A Forum based on PHP and ASP technology is also been created in order to make the Virtual Culture Museum an interactive learning environment.