Identification and characterization of lymph organ microRNAs in red swamp crayfish, Procambarus clarkii infected with white spot syndrome virus.

MicroRNAs (miRNAs) were important post-transcriptional regulators and played vital roles in innate immunity system of invertebrates, especially in the aspect of antivirus. In this study, using high-throughput small RNAs Illumina sequencing system, differentially expressed miRNAs (DEMs) from lymph organs in red swamp crayfish, Procambarus clarkii, infected with white spot syndrome virus, were identified. As a result, 32 known miRNAs and 7 novel miRNAs were identified in crayfish lymph organ small RNAs library of NG and WG. Among them, 7 differentially expressed miRNAs (DEMs) were predicted to be involved in the lymph organ antiviral innate immunity of P. clarkii. Besides, the results showed that putative target genes of these DEMs were related with tight junction, RNA transport, regulation of actin cytoskeleton, focal adhesion, vascular smooth muscle contraction, mRNA surveillance pathway, NOD-like receptor signaling pathway, leukocyte transendothelial migration, and protein processing in endoplasmic reticulum. These results might provide the guiding theoretical foundation for future studies about crustaceans' antiviral innate immunity.

Artificial neural network-genetic algorithm-based optimization of aerobic composting process parameters of Ganoderma lucidum residue.

The rapid development of traditional Chinese medicine enterprises has put forward higher requirements for the resource utilization of traditional Chinese medicine residues (TCMR). Aerobic composting of TCMR to prepare bio-organic fertilizer is an effective resource utilization method. In this study, a back-propagation artificial neural network (BPNN) model using composting factors as inputs (C/N, initial moisture content, type of inoculant, composting days) and the humic acid content as the output was constructed based on the orthogonal test data. BPNN-GA (a genetic algorithm) was used for extreme value optimization, and the optimal composting process parameter combination was obtained and verified. The results show that the combination of orthogonal testing and BPNN can effectively establish the relationship between the composting process parameters and humic acid content. The R2 value was 0. 9064. The optimized parameter combination is as follows: C/N,37.42; moisture content,69.76%; bacteria,no; and composting time,50 d.