The vast majority of lepidopterans, about 90%, are moths. Some moths, particularly their caterpillars, are major agricultural and forestry pests in many parts of the world. However, some other members of moths, such as the silkworm Bombyx mori, are famous for their economic value. Fire et al. in 1998 initially found that exogenous double-stranded RNA (dsRNA) can silence the homolog endogenous mRNA in organisms, which is called RNA interference (RNAi). Soon after, the RNAi technique proved to be very promising not only in gene function determination but also in pest control. However, later studies demonstrate that performing RNAi in moths is not as straightforward as shown in other insect taxa. Nevertheless, since 2007, especially after 2010, an increasing number of reports have been published that describe successful RNAi experiments in different moth species either on gene function analysis or on pest management exploration. So far, more than 100 peer-reviewed papers have reported successful RNAi experiments in moths, covering 10 families and 25 species. By using classic and novel dsRNA delivery methods, these studies effectively silence the expression of various target genes and determine their function in larval development, reproduction, immunology, resistance against chemicals, and other biological processes. In addition, a number of laboratory and field trials have demonstrated that RNAi is also a potential strategy for moth pest management. In this review, therefore, we summarize and discuss the mechanisms and applications of the RNAi technique in moths by focusing on recent progresses.

The entomopathogenic fungus Ophiocordyceps sinensis, formerly known as Cordyceps sinensis, has long been used as a traditional Chinese medicine for the treatment of many illnesses. In recent years its usage has increased dramatically because of the improvement of people's living standard and the emphasis on health. Such demands have resulted in over-harvesting of this fungus in the wild. Fortunately, scientists have demonstrated that artificially cultured and fermented mycelial products of O. sinensis have similar pharmacological activities to wild O. sinensis. The availability of laboratory cultures will likely to further expand its usage for the treatment of various illnesses. In this review, we summarize recent results on the pharmacological activities of the components of O. sinensis and their putative mechanisms of actions. Copyright © 2016 John Wiley & Sons, Ltd.

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A number of studies has shown that long non-coding RNAs (lncRNAs), microRNAs (miRNAs) and protein coding genes (PCGs) are involved in various pathophysiological processes and can be used as prognostic biomarkers in cancer patients. The purpose of this study was to find a multidimensional transcriptome signature to predict clinical outcomes in bladder cancer. Using Cox's proportional hazards regression analysis and the random survival forest algorithm, we mined the expression profile data of 239 bladder cancer patients derived from The Cancer Genome Atlas (TCGA) public database. A signature comprised of two PCGs (ACADS and C1QTNF9B), two lncRNAs (RP11‑60L3.1 and CTD‑3195I5.3) and two microRNAs (has‑miR‑3913‑1 and has‑miR‑891a) with highest accuracy prediction (AUC=0.79 in the training dataset and 0.64 in the test dataset) was selected. The signature had an ability to stratify patients into high‑ and low‑risk groups with significantly different survival rates (median 16.9 vs. 54.9 months, log‑rank test P<0.001) in the training dataset, and its performance was validated for risk stratification in the test dataset (median 18.2 vs. 58.9 months, log‑rank test P=0.002). Multivariable Cox regression analysis revealed that the signature was an independent prognostic factor for patients with bladder urothelial carcinoma (BLCA). A comparison of tumour node metastasis (TNM) stage and the signature indicated that the signature had better survival prediction power (AUCsignature=0.79/0.64 vs. AUCTNM=0.67/0.60, P<0.05). Functional analyses indicated that these prognostic genes from the signature may be involved in tumourigenesis‑related biological processes and pathways. In conclusion, the multidimensional PCG‑lncRNA‑microRNA signature can be a novel prognostic marker to predict the survival of bladder cancer patients.

BACKGROUND: Helicoverpa armigera and Aphis gossypii are two important insect species that feed on cotton plants. These insects have distinct abilities to induce plant resistance and tolerate plant toxins, which results in interspecific competition imbalance that may be fatal to the low-tolerance A. gossypii and force these insects to develop avoidance behaviors and subsequently separate from their niche. We implemented ecological experiments to test the effects of H. armigera-induced plant resistance and behavioral avoidance in A. gossypii, and employed transcriptomics and metabolomics analyses to reveal changes in resistance genes and metabolites in plants.RESULTS: Our results demonstrate that cotton plants induced by H. armigera cause significant inhibitory and avoidance effects on A. gossypii insect populations. Electrical penetration graph (EPG) analysis showed changes in plant resistance induced by H. armigera leading to a decreased feeding efficiency of A. gossypii. In addition, genes associated with jasmonic acid and ethylene signaling pathways were significantly up-regulated in cotton plants after H. armigera induction, which led to a significant up-regulation of metabolites inducing plant resistance. These observations were corroborated by bioactivity analysis on metabolites, which showed that jasmonic acid, gossypol and tannins have significant inhibitory effects on A. gossypii populations. In contrast, methylparaben is associated with avoidance behaviors on A. gossypii populations.CONCLUSION: Our study suggests that the differences in the ability to induce plant resistance and tolerance between two non-predatory insects were lethal to low-tolerance A. gossypii insects, which might be a major factor determining their niche differentiation. This was further demonstrated by screening anti-insect and bio-hormonal metabolites. Our study provides a reference for investigating the evolutionary relationship between non-predatory insects and insights to implement effective insect biocontrol.