Morphological and molecular identification of Xylocoris flavipes(Hemiptera:Anthocoridae)in southern China

During the investigation of natural enemy insects in grain depots,we've found an Anthocoridae insect accounted for a high proportion of natural enemy insects.We identify the enemy insects from morphology and molecular biology,so as to realize more accurate and effective control of storage pests by using the enemy insect.The images of the insects under the ultra-depth microscope(VHX-5000)showed that the insect adults were black brown in colour;the antennas of both the female and male had four segments,which increase in length sequentially from the base to the end,and had a length of 756.2μm for the female and 741.1μm for the male.The rostrums of both the female and the male insects were composed of three segments,the male's rostrum(596.8μm)were shorter than the female's(734.6μm),and the former two segments of the female's rostrum were significantly longer than the male's.The abdomen of the insect was bilaterally symmetrical,the female's abdomen was wider than the male,and the male insect had a dent between its eighth and ninth segments of the left abdomen,in which its male genitalia was located.In addition,the nymphs as a whole were tangerine in colour,and the eggs were elliptic with creamy white gloss and gridding patterns on the surface.The cytochrome C oxidase I(COI)gene sequences of the insects were identified by DNA barcoding technique,and the determined COI sequences were then submitted to the Genbank database for Blast alignment,and the results showed that the COI gene sequences had a high degree of similarity(99%)with X.flavipes records in the Genbank database.Therefore,we could determine that the insect was X.flavipes.In addition,the neighbor joining(NJ)was used to construct the evolutionary tree,and 1,000 repeated tests were conducted on the confidence levels of each branch.Based on the phylogenetic tree,we've found that X.flavipes belongs to Xylocoris genus.Based on morphology and COI sequence identification,we confidentiy determined that the collected natural enemy insect was X.flavipes.This is the first time that the identification of X.flavipes is being investigated from morphology and molecular biology.The research results are helpful to identify and distinguish the species of flower bugs,and beneficial for the better application of X.flavipes in biological control.

Interface structure prediction via CALYPSO method

The atomistic structures of solid–solid interfaces are of fundamental interests for understanding physical properties of interfacial materials. However, determination of interface structures faces a substantial challenge, both experimentally and theoretically. Here, we propose an efficient method for predicting interface structures via the generalization of our in-house developed CALYPSO method for structure prediction. We devised a lattice match toolkit that allows us to automatically search for the optimal latticematched superlattice for construction of the interface structures. In addition, bonding constraints(e.g.,constraints on interatomic distances and coordination numbers of atoms) are imposed to generate better starting interface structures by taking advantages of the known bonding environment derived from the stable bulk phases. The interface structures evolve by following interfacially confined swarm intelligence algorithm, which is known to be efficient for exploration of potential energy surface. The method was validated by correctly predicting a number of known interface structures with only given information of two parent solids. The application of the developed method leads to prediction of two unknown grain boundary(GB) structures(r-GB and p-GB) of rutile TiO_2 ∑5(2 1 0) under an O reducing atmosphere that contained Ti^(3+)as the result of O defects. Further calculations revealed that the intrinsic band gap of p-GB is reduced to 0.7 eV owing to substantial broadening of the Ti-3 d interfacial levels from Ti^(3+)centers.Our results demonstrated that introduction of grain boundaries is an effective strategy to engineer the electronic properties and thus enhance the visible-light photoactivity of TiO_2.

Understanding the proteome encoded by “non-coding RNAs”:new insights into human genome

A great number of non-coding RNAs(ncRNAs) account for the majority of the genome. The translation of these ncRNAs has been noted but seriously underestimated due to both technological and theoretical limitations. Based on the development of ribosome profiling(Ribo-seq), full length translating RNA analysis(RNC-seq) and mass spectrometry technology, more and more ncRNAs are being found to be translated in different organism, and some of them can produce functional peptides. While recently, not only individual new functional proteins, but also a new proteome have been experimentally discovered to be encoded by endogenous lncRNAs and circRNAs. These new proteins are of biological significance, suggesting the connection of the translation of ncRNAs to human physiology and diseases. Therefore, an in-depth and systematic understanding of the coding capabilities of ncRNAs is necessary for basic biology and medicine. In this review, we summarize the advances in the field of discovering this new proteome, i.e. "ncRNA-coded" proteins.

Structure search of two-dimensional systems using CALYPSO methodology

The dimensionality of structures allows materials to be classified into zero-, one-, two-, and threedimensional systems. Two-dimensional (2D) systems have attracted a great deal of attention andtypically include surfaces, interfaces, and layered materials. Due to their varied properties, 2D systemshold promise for applications such as electronics, optoelectronics, magnetronics, and valleytronics.The design of 2D systems is an area of intensive research because of the rapid development of abinitio structure-searching methods. In this paper, we highlight recent research progress on acceleratingthe design of 2D systems using the CALYPSO methodology. Challenges and perspectives for futuredevelopments in 2D structure prediction methods are also presented.