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Labriocimbex sinicus Yan & Wei gen. et sp. nov. of Cimbicidae is described. The new genus is similar to Praia Andre and Trichiosoma Leach. A key to extant Holarctic genera of Cimbicinae is provided. To identify the phylogenetic placement of Cimbicidae, the mitochondrial genome of L. sinicus was annotated and characterized using high-throughput sequencing data. The complete mitochondrial genome of L. sinicus was obtained with a length of 15,405 bp (GenBank: MH136623; SRA: SRR8270383) and a typical set of 37 genes (22 tRNAs, 13 PCGs, and two rRNAs). The results demonstrated that all PCGs were initiated by ATN codon, and ended with TAA or T stop codons. The study reveals that all tRNA genes have a typical clover-leaf secondary structure, except for trnS1. Remarkably, the secondary structures of the rrnS and rrnL of L. sinicus were much different from those of Corynis lateralis. Phylogenetic analyses verified the monophyly and positions of the three Cimbicidae species within the superfamily Tenthredinoidea and demonstrated a relationship as (Tenthredinidae + Cimbicidae) + (Argidae + Pergidae) with strong nodal supports. Furthermore, we found that the generic relationships of Cimbicidae revealed by the phylogenetic analyses based on COI genes agree quite closely with the systematic arrangement of the genera based on the morphological characters. Phylogenetic tree based on two methods shows that L. sinicus is the sister group of Praia with high support values. We suggest that Labriocimbex belongs to the tribe Trichiosomini of Cimbicinae based on adult morphology and molecular data. Besides, we suggest to promote the subgenus Asitrichiosoma to be a valid genus.

The Asian potamid subfamily Potamiscinae is the most species-rich group of primary freshwater crabs in the world, and a large number of these (318 species in 52 genera) are found in China where they exhibit a remarkably high rate of endemism. However, the evolutionary history and phylogenetic relationships of this subfamily is still poorly understood and the hypothesis that the Chinese potamids originated in the Indochina Peninsula has yet to be tested using a modern phylogeographic reconstruction and molecular dating methods. Here we analyze the phylogenetic relationships and biogeographic history of the Chinese potamiscines based on whole mitogenomes of 72 species of Asian freshwater crabs representing 65% of the potamiscine genera found in China, including new mitogenome sequences for 57 species. The mitogenomic phylogeny generated four separate clades: Southwest China (SWC), Indochina-Southwest China (ISWC), Central China (CC), and South China-adjacent Islands (SCI). Our results suggest that the Chinese potamiscine fauna most likely originated in Indochina during the Eocene. The establishment of the East Asian monsoon during the Eocene/Oligocene resulted in major climate changes that coincide with the local diversification of the CC and SCI clades. In addition, diversification of two other clades (ISWC and SWC) may have been driven by past large scale environmental changes taking place at that time such as increased local precipitation and expanding freshwater habitats associated with the uplifting of the Hengduan Mountains. In addition, our phylogenies did not support monophyly for six currently recognized potamiscine genera, highlighting the need for further taxonomic revisions of this fauna. The broad taxonomic sampling and well-supported molecular phylogenies used here allow for the updating of our understanding of the evolutionary origins and diversification of the potamiscine freshwater crabs in China.

Single-cell genomics (SCG) is a recently developed tool to study the genomes of unculturable bacterial species. SCG relies on multiple-strand displacement amplification (MDA), PCR, and next-generation sequencing (NGS); however, obtaining sufficient amounts of high-quality DNA from samples is a major challenge when performing this technique. Here we present an improved bacterial cell lysing procedure that combines incubation in an alkaline buffer with a thermal shock (freezing/heating) treatment to yield highly intact genomic DNA with high efficiency. This procedure is more efficient in lysing Bacillus subtilis and Synechocystis cells compared with two other frequently used lysis methods. Furthermore, 16S ribosomal RNA gene and overall genome recovery were found to be improved by this method using single cells from a Utah desert soil community or Escherichia coli single cells, respectively. The efficiency of genome recovery for E. coli single cells using our procedure is comparable with that of the REPLI-g Single Cell (sc) Kit, but our method is much more economical. By providing high-quality genome templates suitable for downstream applications, our procedure will be a promising improvement for SCG research.

We describe Arge bella Wei & Du sp. nov., a large and beautiful species of Argidae from south China, and report its mitochondrial genome based on high-throughput sequencing data. We present the gene order, nucleotide composition of protein-coding genes (PCGs), and the secondary structures of RNA genes. The nearly complete mitochondrial genome of A. bella has a length of 15,576 bp and a typical set of 37 genes (22 tRNAs, 13 PCGs, and 2 rRNAs). Three tRNAs are rearranged in the A. bella mitochondrial genome as compared to the ancestral type in insects: trnM and trnQ are shuffled, while trnW is translocated from the trnW-trnC-trnY cluster to a location downstream of trnI. All PCGs are initiated by ATN codons, and terminated with TAA, TA or T as stop codons. All tRNAs have a typical cloverleaf secondary structure, except for trnS1. H821 of rrnS and H976 of rrnL are redundant. A phylogenetic analysis based on mitochondrial genome sequences of A. bella, 21 other symphytan species, two apocritan representatives, and four outgroup taxa supports the placement of Argidae as sister to the Pergidae within the symphytan superfamily Tenthredinoidea.

The Chimp Optimization Algorithm (ChOA) is a heuristic algorithm proposed in recent years. It models the cooperative hunting behaviour of chimpanzee populations in nature and can be used to solve numerical as well as practical engineering optimization problems. ChOA has the problems of slow convergence speed and easily falling into local optimum. In order to solve these problems, this paper proposes a novel chimp optimization algorithm with refraction learning (RL-ChOA). In RL-ChOA, the Tent chaotic map is used to initialize the population, which improves the population’s diversity and accelerates the algorithm’s convergence speed. Further, a refraction learning strategy based on the physical principle of light refraction is introduced in ChOA, which is essentially an Opposition-Based Learning, helping the population to jump out of the local optimum. Using 23 widely used benchmark test functions and two engineering design optimization problems proved that RL-ChOA has good optimization performance, fast convergence speed, and satisfactory engineering application optimization performance.

The traditional grey wolf algorithm is widely used for feature selection. However, within complex feature multi-dimensional problems, the grey wolf algorithm is prone to reach locally optimal solutions and premature convergence. In this paper, a threshold binary grey wolf optimizer based on multi-elite interaction for feature selection (MTBGWO) is proposed. Firstly, the multi-population topology is adopted to enhance the population's diversity for improving search space utilization. Secondly, an information interaction learning strategy is adopted for the update of sub-population elite wolf position (optimal position) via learning better position from other elite wolves; in order to improve the local exploitation ability of the sub-population. At the same time, the command of β and δ wolves (second and third best positions) for population position updates is removed. Finally, a threshold approach is employed to convert the continuous position of grey wolf individuals into binary one to apply in the feature selection problem. Further, The MTBGWO algorithm proposed in this paper is compared with the traditional binary grey wolf algorithm (BGWO), binary whale algorithm (BWOA), as well as some recently developed novel algorithms to exhibit its superiority and robustness. Totally 16 classification datasets, from the UCI Machine Learning Repository, are chosen for comparison. The Wilcoxon's rank-sum non-parametric statistical test is carried out at 5% significance level to evaluate whether the results of the proposed algorithms significantly differs from those of the other algorithms. In the experimental results for all datasets, the overall average accuracy of the MTBGWO algorithm is 94.7%, while the highest of the other algorithms is 92.8% and the selected feature subset is 25% of the total dataset, while the GWO and WOA algorithms are twice as high as MTBGWO. In terms of computational efficiency, the overall processing time of MTBGWO is 24.2 seconds, whereas HSGW is 44.1 seconds. The results reveal that the MTBGWO has shown its superiority in solving the feature selection problem.INDEX TERMS Grey wolf optimizer, feature selection, binary optimizer, elite interaction strategy

IntroductionResveratrol, an activator for longevity regulatory genes-sirtuin family (SIRTs) and Sirtuin 2 (SIRT2) is an important factor of SIRTs which demonstrated biological function in cancers, but the underlying mechanism is unrevealed.MethodsWe investigated the mRNA and protein levels of SIRT2 in a variety of cancers and the potential role for clinical prognosis, as well as analysed the association between the gene and immune infiltration in various cancers. And an analysis of two types of lung cancer was conducted to construct a systematic prognostic landscape. Finally, putative binding site of the triacetylresveratrol bound to SIRT2 was built from homology modeling.Results and discussionWe concluded that higher mRNA and protein levels of SIRT2 affected prognosis in various types of cancers, especially in LUAD cohorts. In addition, SIRT2 is linked with a better overall survival (OS) in LUAD patients. Further research suggested a possible explanation for this phenotype might be that SIRT2 mRNA levels are positively correlated with infiltrating status of multiple immunocytes in LU-AD but not LUSC, i.e. SIRT2 expression may contribute to the recruitment of CD8+T cell, CD4+ T cell, T cell CD4+ memory resting, Tregs, T cell NK and positively correlated to the expression of PD-1, also excluding neutrophil, T cell CD8+ naïve and B cell plasma cells in LUAD. We found that triacetyl-resveratrol demonstrated the most potent agonist efficiency to SIRT2 and the EC 50 as low as 142.79 nM. As a result, SIRT2 appears to be a promising novel biomarker for prognosis prediction in patients with LUAD and triacetylresveratrol might be a potential immunomodulator of LUAD to anti-PD-1 based immunotherapy combination therapies.