A method using high-speed capillary micellar electrokinetic chromatography and a microbial fuel cell was applied to determine the metabolite of the peptides released by Bacillus licheniformis. Two peptides, l-carnosine and l-alanyl-l-glutamine were used as the substrate to feed Bacillus licheniformis in a microbial fuel cell. The metabolism process of the bacterium was monitored by analyzing the voltage outputs of the microbial fuel cell. A home-made spontaneous injection device was applied to perform high-speed capillary micellar electrokinetic chromatography. Under the optimized conditions, tryptophan, glycine, valine, tyrosine and the two peptides could be rapidly separated within 2.5 min with micellar electrokinetic chromatography mode. Then the method was applied to analyze the solutions sampled from the microbial fuel cell. After 92 h running, valine, as the metabolite, was successfully detected with concentration 3.90 × 10 M. The results demonstrated that Bacillus licheniformis could convert l-carnosine and l-alanyl-l-glutamine into valine. The method employed in this work was proved to have great potential in analysis of metabolites, such as amino acids, for microorganisms.

In this work, high-speed capillary sieving electrophoresis with laser-induced fluorescence detection was applied to simultaneously determine three microRNAs. A developed manual sample introduction device for the high-speed capillary electrophoresis system was applied to perform sample injection. Strategies, including field-amplified sample injection and electrokinetic injection, were studied to improve the detection sensitivity. Under the optimal conditions, the limit of detection for DNA-159 could be lowered to 5.10 × 10 mol/L. In order to achieve enough separation resolution, two DNA probes were designed to have extra sequences that acted as the drag tails. Under the optimized conditions, the three DNA probes and the complexes of microRNA-156, microRNA-159, and microRNA-166 could be completely separated within 3.2 min in background electrolyte (pH 8.7) containing 2.0% m/m polyvinyl pyrrolidone and 0.4% m/m hydroxyethyl cellulose. The limits of detection for the three microRNAs were 0.051, 0.11, and 0.25 nmol/L, respectively. Then the method was applied to analyze the microRNAs spiked in the samples extracted from banana leaves. The recoveries ranged from 114.3 to 121.1% (n = 3). The results showed that the method developed in this work was an effective means for microRNA assay.

Corynebacterium glutamicum (C. glutamicum) is a well‐known workhorse for the industrial production of amino acids. Different carbon, nitrogen, and sulfur source may force the bacterium to produce specific metabolites. In this work, a method of high‐speed MEKC with LIF detection was developed to rapidly analyze the amino acid metabolites released by C. glutamicum, which is fed with different culture mediums. Corynebacterium glutamicum was cultured in microbial fuel cells to monitor its metabolism process and collect its metabolites. In the CE system, a microliter‐scale sample reservoir was designed and applied to perform tiny volume sample injection. With the assistance of microwave, the derivatization time for amino acids with FITC was greatly shortened to 6 min. Under the optimized condition, the eight candidate amino acids of metabolites could be rapidly separated within 2 min. The whole analysis process for real samples, from sampling to determination, could be shortened to less than 10 min. The results showed that C. glutamicum could produce additional l‐lysine and l‐valine as the metabolites when fed with glucose and l‐methionine, respectively. The method proved that culture mediums used to feed C. glutamicum had great effect on the bacterium's metabolites.

Cooperative targets assignment of multiple Unmanned Combat Aerial Vehicles (UCAVs) is the basis and key issue of multi-UCAVs cooperative combat. The kill probability is taken into consideration in cooperative targets assignment problem, for which a multi-objective MIP model is proposed. The objectives include minimizing the number of launch points taking part in a mission and minimizing the launch time range. An improved efficacy coefficient method is developed to transform the problem to a single-objective MILP model. Numerical experiments show the effectiveness of the proposed approach.