Search

To balance the relationship between current THD and switching loss, an optimal predictive control method using single and double vector hybrid modulation of NPC-3L inverter is proposed. Firstly, the relationship of the THD of output current and the Aoc&rc(the Area enclosed by output current and reference current) is built. Secondly, the current threshold is defined to control the switching time of single/double vectors, which is used to balance the current THD and switching loss and determined by the target current THD value. Thirdly, the output of single vector or double vector is determined by comparing the output real-time current value with the set current threshold. That is, when the output current is greater than the current threshold, a single vector is used to reduce the switching loss. When the output current is less than the current threshold, the THD of the output current is raised by using output double vectors. At the same time, by using this control method, the disadvantages of single/dual vector independent operation are mutually offset. Finally, a simulation model is built to verify the proposed control method. Compared with traditional methods, the simulation results show that the proposed method is correct and effective.

An increasing number of studies have reported that microbiome can affect drug response by altering pharmacokinetics and pharmacodynamics of formation of toxic metabolites. With the development of metagenomic sequencing, gut microbial composition as well as the metabolic function are drawing more and more attention for the patient stratification. The established microbiota databases provide useful information about the gut microbe-drug interactions. However, these databases generally lacked the detailed effects on substance and the metabolites, which are helpful in elucidating the mechanisms underlying drug biotransformation and personalized medicine. To address these issues, in this study, we developed Metabolic action of gut Microbiota to Drugs (MagMD), a database and a web-service covering 32, 678 records of interactions between 2,146 gut microbes, 36 enzymes and 219 substrates (mainly drugs). The detailed annotations for each entry, including the taxonomic level of microbes, the molecular form and PubChem ID of drugs from PubChem Compound Database, types of microbial secreted enzymes and the original reference links can also be accessed from the web service. Availability and implementation: MagMD is a publicly available resource, constantly updated. It has an intuitive web interface and can be freely accessed at http://www.unimd.org/magmd.

Decapod iridescent virus 1 (DIV1) results in severe economic losses in shrimp aquaculture. However, little is known about the physiological effect of DIV1 infection on the host. In this study, we found that the lethal dose 50 of DIV1-infected Litopenaeus vannamei after 48, 72, 96, and 156 h were 4.86 × 106, 5.07 × 105, 2.13 × 105, and 2.38 × 104 copies/μg DNA, respectively. In order to investigate the mechanisms of DIV1 infection, a comparative transcriptome analysis of hemocytes from L. vannamei, infected or not with DIV1, was conducted. The BUSCO analysis showed that the transcriptome was with high completeness (complete single-copy BUSCOs: 57.3%, complete duplicated BUSCOs: 41.1%, fragmentation: 0.8%, missing: 0.8%). A total of 168,854 unigenes were assembled, with an average length of 601 bp. Based on homology searches, Kyoto Encyclopedia of Genes and Genomes (KEGG), gene ontology (GO), and cluster of orthologous groups of proteins (KOG) analysis, 62,270 (36.88%) unigenes were annotated. Among them, 1,112 differentially expressed genes (DEGs) were identified, of which 889 genes were up-regulated and 223 genes were down-regulated after DIV1 infection. These genes were mainly annotated to the major metabolic processes such as fructose and mannose metabolism, carbon metabolism, and inositol phosphate metabolism. Among these metabolic pathways, the triosephosphate isomerase (TPI) family was the most eye-catching DEG as it participates in several metabolic processes. Three types of TPI, LvTPI-like, LvTPI-Blike, and LvTPI-Blike1, were obtained for gene silencing by RNA interference. The results showed that LvTPI-like and LvTPI-Blike1 silencing caused a high mortality rate among L. vannamei. However, LvTPI-like and LvTPI-Blike silencing reduced DIV1 replication in DIV1-infected L. vannamei. All the results indicated that TPI-like genes play an important role during DIV1 infection, which provides valuable insight into the infection mechanism of DIV1 in shrimp and may aid in preventing viral diseases in shrimp culture.