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Caffeic acid O-methyltransferase from Ligusticum chuanxiong (LcCOMT) showed strict regiospecificity despite a relative degree of preference. Compared with caffeic acid, methyl caffeate was the preferential substrate by its low Km and high Kcat. In this study, we obtained the SAM binary (1.80 A) and SAH binary (1.95 A) complex LcCOMT crystal structures, and established the ternary complex structure with methyl caffeate by molecular docking. The active site of LcCOMT included phenolic substrate pocket, SAM/SAH ligand pocket and conserved catalytic residues as well. The regiospecificity of LcCOMT that permitted only 3-hydroxyl group to be methylated arise from the interactions between the active site and the phenyl ring. However, the propanoid tail governed the relative preference of LcCOMT. The ester group in methyl caffeate stabilized the anionic intermediate caused by His268-Asp269 pair, whereas caffeic acid was unable to stabilize the anionic intermediate due to the adjacent carboxylate anion in the propanoid tail. Ser183 residue formed an additional hydrogen bond with SAH and its role was identified by S183A mutation. Ile318 residue might be a potential site for determination of substrate preference, and its mutation led to the change of tertiary conformation. The results supported the selective mechanism of LcCOMT.

Objectives Recent genomic studies suggest the biological significance of the cylindromatosis (CYLD) gene in thymic epithelial tumors (TETs). CYLD is a crucial regulator of immune response, and we previously reported that CYLD mutation is associated with high PD-L1 expression in thymic carcinoma. Therefore, we wanted to explore the role and mechanism of CYLD in regulating PD-L1 expression in TETs. Materials and methods The role of CYLD in PD-L1 expression was assessed by knockdown of CYLD in TET cells upon stimulation with interferon gamma (IFN-γ), tumor necrosis factor-α (TNF-α) or polyinosinic-polycytidylic acid (poly I:C). The molecular mechanism was investigated through analysis of downstream molecules in the STAT1/IRF1 pathway. Moreover, the clinical correlation between low CYLD and high PD-L1 expression, and the clinical impact of CYLD expression were evaluated in tissue microarrays of 105 TET cases. Results CYLD knockdown significantly enhanced the expression of PD-L1 in presence of IFN-γ stimulation in most TET cell lines. However, this phenomenon was not observed in presence of TNF-α stimulation. CYLD knockdown upregulated IFN-γ mediated activation of the STAT1/IRF1 axis, which in turn induced PD-L1 expression. Interestingly, we found a significant association between low CYLD expression and ≥ 50 % PD-L1 expression (p = 0.001). In addition, the average proportion of tumor cells exhibiting PD-L1 staining was significantly higher in the low CYLD expression group (24.7 %) than in the high CYLD expression group (5.2 %) (p = 0.005). There was no correlation between CYLD expression and the frequency of pre-existing paraneoplastic auto-immune diseases. In advanced stages (III/IV), the low CYLD expressing group had numerically worse survival than the high CYLD group (log-rank p = 0.089). Conclusions Our findings provide insight into the mechanism of regulation of PD-L1 expression by CYLD in TET cells. Tumors with low CYLD expression could be potential targets for PD-1/PD-L1 inhibitors.

Although digestive resistance of Kunitz protease inhibitors has been reported extensively, the molecular mechanism is not well established. In the present study, the first X-ray structure of Cassia obtusifolia trypsin inhibitor (COTI), a member of Kunitz protease inhibitors, was solved at a resolution of 1.9 Å. The structure adopted a classic β-trefoil fold with the inhibitory loop protruding from the hydrophobic core. The role of Phe139, a unique residue in Kunitz protease inhibitors, and Arg63 in the COTI structure was verified by F139A and R63E mutants. COTI was a specific inhibitor of bovine trypsin and the result was also verified by COTI-trypsin complex formation. Meanwhile, COTI showed equivalent inhibitory activity with that of soybean trypsin inhibitor against bovine trypsin and midgut trypsin from Pieris rapae. The F139 and R63E mutants further indicated that inhibitory specificity and efficiency of COTI were closely related to the global framework, the conformation and the amino acid composition of reactive loop. Finally, a midgut trypsin from P. rapae (PrSP40), which might be involve in the food digestion, was proposed to be a potential target of COTI and might be a promising target for future crop-protection strategy. The results supported the digestive resistance of COTI.

Dynamic energy management (DEM) is being recognized as an important tool for the economical and efficient operation of microgrid. This paper proposes an expected-cost realization-probability (ECRP) optimization approach for the DEM of microgrid. In the model, the expected cost is taken as an economic goal to find the schedule with the maximum ECRP (i.e., the maximum probability of obtaining an actual operation cost which is lower than this economic goal). It is a stochastic mixed-integer nonlinear programming (MINLP) problem composed of the AC power flow, battery operation characters and logical variables. To solve this NP-hard problem, an ECRP-based approximate dynamic programming is proposed. The original MINLP problem is decomposed into small nonlinear programming subproblems to facilitate the solution. And the ECRP-based value function is formed to describe the relationship among the decisions of subproblems, which helps to obtain the near-optimal decision in a decomposed manner. Simulation examples presented on a real microgrid indicate that the ECRP of the proposed method is higher than those of the other two comparison algorithms.

Plug-in electric buses have great potential to enhance the profits of operators in multiple-microgrid systems via the use of vehicle-to-grid technology. In contrast to stationary energy storage units, a plug-in electric bus can move among different microgrids to provide not only passenger transportation service but also energy transportation service. In this paper, a single-leader and multiple-follower model based on the Stackelberg game method is proposed for the look-ahead dispatch of bus routes and power allocation in microgrids. First, a time-space trip model for a fleet of plug-in electric buses was established, and the total costs of the plug-in electric bus operator were optimized as a leader-level problem. Then a rolling energy management strategy was formulated as a follower-level problem to optimize the total costs of each microgrid operator and to deal with the prediction error of the distributed energy resources and loads. Next, the proposed bi-level optimization problem was transformed into a single-level mixed-integer linear programming problem. Finally, case studies were carried out on three real microgrids in China and on BYD-K9 plug-in electric buses. The simulation results indicated that the costs for a plug-in electric bus operator would decrease by 33.35% in the proposed bi-level model compared with the fixed charging model, and the costs for an isolated MG would decrease by 24.16% compared with the model regardless of the plug-in electric buses.

In this paper, we present a spatiotemporal decomposition solution approach to the fully decentralized dynamic economic dispatch (DED) problem in a microgrid. Our approach divides the centralized DED problem into a series of sub-problems in the spatiotemporal dimensions and relies on multiple agents to solve those sub-problems. The proposed method requires no central operator intervention, preserving the decision independence and information privacy of each unit. Approximate value functions are used to describe the interaction among those sub-problems. With the approximate value functions, one agent not only knows the impact of its decision on the decisions of other agents in the same period, but also knows the impact of this decision on the decisions of its subsequent periods. Unlike the existing value function update strategy, which updates the state variables and value functions in one direction, we update the state variables and value functions in two directions based on a forward-push-back strategy. In this manner, the time-delayed problem can be solved, and the iteration speed of the algorithm is greatly improved. Moreover, the proposed algorithm does not require parameter tuning and has good accuracy and adaptability. Numerical simulations for multiple cases demonstrate the effectiveness of the proposed algorithm.