Ceramic microparticles have great potentials in various fields such as materials engineering, biotechnology, microelectromechanical systems, etc. Morphology of the microparticle performs an important role on their application. To date, it remains difficult to find an effective and controllable way for fabricating nonspherical ceramic microparticles with 3D features. This work demonstrates a method that combines UV light lithography and single emulsion opaque-droplet-templated microfluidic molding to prepare the crescent-shaped ceramic microparticles. By tailoring the intensity of UV light and flow rate of fluid, the shapes of microparticles are accordingly tuned. Therefore, varieties of crescent-shaped microparticles and their variations have been fabricated. After sintering, the crescent-shaped alumina ceramic microparticles were obtained. Benefitting from the light absorption and scattering behavior of most ceramic nanoparticles, this system can serve as a general platform to produce crescent-shaped microparticles made from different materials, and hold great potentials for applications in microrobotics, structural materials in MEMS, and biotechnology. 相似文献
Journal of Materials Science - A green modification method for effectively enhancing toughness of PLA was established. Herein, alkaline lignin (LG) was firstly alkylated with dodecane, and then... 相似文献
Multimedia Systems - The preferences of Web information purchasers are changing. Cost-effectiveness (i.e., an emphasis on performance with respect to price) is becoming less regarded than... 相似文献
Reconstructing gene regulatory networks (GRNs) plays an important role in identifying the complicated regulatory relationships, uncovering regulatory patterns in cells, and gaining a systematic view for biological processes. In order to reconstruct large-scale GRNs accurately, in this paper, we first use fuzzy cognitive maps (FCMs), which are a kind of cognition fuzzy influence graphs based on fuzzy logic and neural networks, to model GRNs. Then, a novel hybrid method is proposed to reconstruct GRNs from time series expression profiles using memetic algorithm (MA) combined with neural network (NN), which is labeled as MANNFCM-GRN. In MANNFCM-GRN, the MA is used to determine regulatory connections in GRNs and the NN is used to determine the interaction strength of the regulatory connections. In the experiments, the performance of MANNFCM-GRN is validated on both synthetic data and the benchmark dataset DREAM3 and DREAM4. The experimental results demonstrate the efficacy of MANNFCM-GRN and show that MANNFCM-GRN can reconstruct GRNs with high accuracy without expert knowledge. The comparison with existing algorithms also shows that MANNFCM-GRN outperforms ant colony optimization, non-linear Hebbian learning, and real-coded genetic algorithms.
Rapid and sensitive point-of-care testing (POCT) is an extremely critical mission in practical applications, especially for rigorous military medicine, home health care, and in the third world. Here, we report a visual POCT method for adenosine triphosphate (ATP) detection based on Taylor rising in the corner of quadratic geometries between two rod surfaces. We discuss the principle of Taylor rising, demonstrating that it is significantly influenced by contact angle, surface tension, and density of the sample, which are controlled by ATP-dependent rolling circle amplification (RCA). In the presence of ATP, RCA reaction effectively suppresses Taylor-rising behavior, due to the increased contact angle, density, and decreased surface tension. Without addition of ATP, untriggered RCA reaction is favorable for Taylor rising, resulting in a significant height. With this proposed method, visual sensitive detection of ATP without the aid of other instruments is realized with only a 5 μL droplet, which has good selectivity and a low detection limit (17 nM). Importantly, this visual method provides a promising POCT tool for user-friendly molecular diagnostics. 相似文献
This study aimed to predict the optimal carbon source for higher production of exopolysaccharides (EPS) by Lactobacillus paracasei TD 062, and to evaluate the effect of this carbon source on the production and monosaccharide composition of EPS. We evaluated the EPS production capacity of 20 strains of L. paracasei under the same conditions. We further investigated L. paracasei TD 062, which showed the highest EPS-producing activity (0.609 g/L), by examining the associated biosynthesis pathways for EPS. Genomics revealed that fructose, mannose, trehalose, glucose, galactose, and lactose were carbon sources that L. paracasei TD 062 could use to produce EPS. We identified an EPS synthesis gene cluster that could participate in transport, export, and sugar chain synthesis, and generate 6 sugar nucleotides. Experimental results showed that the sugar content of the EPS produced using fermentation with the optimized carbon source (fructose, mannose, trehalose, glucose, galactose, and lactose) increased by 115%. Furthermore, use of the optimized carbon source changed the monosaccharide content of the associated EPS. The results of enzyme activity measurements showed significant increases in the activity of 2 key enzymes involved in the glycoside synthesis pathway. Our study revealed that optimizing the carbon source provided for fermentation not only increased the production of EPS, but also affected the composition of the monosaccharides by increasing enzyme activity in the underlying synthesis pathways, suggesting an important role for carbon source in the production of EPS by L. paracasei TD 062. 相似文献