LINC00667 promotes Wilms’ tumor metastasis and stemness by sponging miR‐200b/c/429 family to regulate IKK‐β

Wilms' tumor, also known as nephroblastoma, is a kind of pediatric renal cancer. Previous studies have indicated that microRNAs (miRNAs) regulate various cancers progression. However, whether miR‐200 family regulated Wilms' tumor progression remains to be elucidated. In our study, miR‐200b/c/429 expression was downregulated in Wilms' tumor tissue samples from 25 patients. And data from three independent analyses of quantitative real‐time polymerase chain reaction revealed that the expression of miR‐200b/c/429 was downregulated in Wilms' tumor cell lines. Functionally, Cell counting kit‐8 assay revealed that cell viability was reduced by overexpressing miR‐200b/c/429. Transwell assay manifested that cell migration and invasion was hindered by miR‐200b/c/429 overexpression. Sphere‐forming and western blot assays demonstrated that miR‐200b/c/429 overexpression suppressed the sphere formation ability. Mechanically, nuclear factor‐κB (NF‐κB) pathway was confirmed to be associated with Wilms' tumor progression; miR‐200b/c/429 overexpression inactivated NF‐κB pathway as miR‐200b/c/429 was identified to target IκB kinase β (IKK‐β), an NF‐κB pathway‐related gene. Moreover, miR‐200b/c/429 was sponged by LINC00667 in Wilms' tumor cells. LINC00667 competitively bound with miR‐200b/c/429 to regulate IKK‐β expression and then activated NF‐κB pathway in Wilms' tumor. Subsequently, rescue assays illustrated that silencing of IKK‐β could reverse the effect of miR‐200b/c/429 inhibition on the progression of sh‐LINC00667‐transfected Wilms' tumor cells. In summary, LINC00667 promoted Wilms' tumor progression by sponging miR‐200b/c/429 family to regulate IKK‐β.     

Rainfall manipulation experiments as simulated by terrestrial biosphere models: Where do we stand?

Changes in rainfall amounts and patterns have been observed and are expected to continue in the near future with potentially significant ecological and societal consequences. Modelling vegetation responses to changes in rainfall is thus crucial to project water and carbon cycles in the future. In this study, we present the results of a new model‐data intercomparison project, where we tested the ability of 10 terrestrial biosphere models to reproduce the observed sensitivity of ecosystem productivity to rainfall changes at 10 sites across the globe, in nine of which, rainfall exclusion and/or irrigation experiments had been performed. The key results are as follows: (a) Inter‐model variation is generally large and model agreement varies with timescales. In severely water‐limited sites, models only agree on the interannual variability of evapotranspiration and to a smaller extent on gross primary productivity. In more mesic sites, model agreement for both water and carbon fluxes is typically higher on fine (daily–monthly) timescales and reduces on longer (seasonal–annual) scales. (b) Models on average overestimate the relationship between ecosystem productivity and mean rainfall amounts across sites (in space) and have a low capacity in reproducing the temporal (interannual) sensitivity of vegetation productivity to annual rainfall at a given site, even though observation uncertainty is comparable to inter‐model variability. (c) Most models reproduced the sign of the observed patterns in productivity changes in rainfall manipulation experiments but had a low capacity in reproducing the observed magnitude of productivity changes. Models better reproduced the observed productivity responses due to rainfall exclusion than addition. (d) All models attribute ecosystem productivity changes to the intensity of vegetation stress and peak leaf area, whereas the impact of the change in growing season length is negligible. The relative contribution of the peak leaf area and vegetation stress intensity was highly variable among models.     

The hybrid bacterial foraging algorithm based on many-objective optimizer

A new multi-objective optimized bacterial foraging algorithm - Hybrid Multi-Objective Optimized Bacterial Foraging Algorithm (HMOBFA) is presented in this article. The proposed algorithm combines the crossover-archives strategy and the life-cycle optimization strategy, look for the best method through research area. The crossover-archive strategy with an external archive and internal archive is assigned to different selection principles to focus on diversity and convergence separately. Additionally, according to the local landscape to satisfy population diversity and variability as well as avoiding redundant local searches, individuals can switch their states periodically throughout the colony lifecycle with the life-cycle optimization strategy. all of which may perform significantly well. The performance of the algorithm was examined with several standard criterion functions and compared with other classical multi-objective majorization methods. The examiner results show that the HMOBFA algorithm can achieve a significant enhancement in performance compare with other method and handles many-objective issues with solid complexity, convergence as well as diversity. The HMOBFA algorithm has been proven to be an excellent alternative to past methods for solving the improvement of many-objective problems.     

Identification of key genes and novel immune infiltration-associated biomarkers of sepsis

Sepsis is the major cause of mortality in the intensive care unit. The aim of this study was to identify the key prognostic biomarkers of abnormal expression and immune infiltration in sepsis. In this study, a total of 36 differentially expressed genes were identified to be mainly involved in a number of immune-related Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways. The hub genes (MMP9 and C3AR1) were significantly related to the prognosis of sepsis patients. The immune infiltration analysis indicated a significant difference in the relative cell content of naive B cells, follicular Th cells, activated NK cells, eosinophils, neutrophils and monocytes between sepsis and normal controls. Weighted gene co-expression network analysis and a de-convolution algorithm that quantifies the cellular composition of immune cells were used to analyse the sepsis expression data from the Gene Expression Omnibus database and to identify modules related to differential immune cells. CEBPB is the key immune-related gene that may be involved in sepsis. Gene set enrichment analysis revealed that CEBPB is involved in the processes of T cell selection, B cell–mediated immunity, NK cell activation and pathways of T cells, B cells and NK cells. Therefore, CEBPB may play a key role in the biological and immunological processes of sepsis.     

Analysis of microRNA expression profiles in porcine PBMCs after LPS stimulation

In the present study, we used microRNA (miRNA) sequencing to discover and explore the expression profiles of known and novel miRNAs in 1000 ng/ml LPS stimulated for 8 h vis-à-vis non-stimulated (i.e. control) PBMCs isolated from the blood of healthy pigs. A total of 291 known miRNAs were bio-computationally identified in porcine PBMCs, and 228 novel miRNAs (not enlisted in the swine mirBase) were identified. Among these miRNAs, ssc-miR-148a-3p, ssc-let-7g, ssc-let-7f, 3_8760, ssc-miR-26a, ssc-miR-451, ssc-miR-21, ssc-miR-30d, ssc-miR-99a and ssc-miR-103 were the top 10 most abundant miRNAs in porcine PBMCs. Through miRNA differential analysis combined with quantitative PCR, we found the expressions of ssc-miR-122, ssc-miR-129b, ssc-miR-17-5p and ssc-miR-152 were significantly changed in porcine PBMCs after LPS stimulation. Furthermore, targets prediction and function analysis indicated a significant enrichment in gene ontology functional categories related to diseases, immunity and inflammation. In conclusion, this study on profiling of miRNAs expressed in LPS-stimulated PBMCs provides an important reference point for future studies on regulatory roles of miRNAs in porcine immune system.     

Chromosome‐level genome assembly of an important pine defoliator,Dendrolimus punctatus (Lepidoptera; Lasiocampidae)

Dendrolimus spp. are important destructive pests of conifer forests, and Dendrolimus punctatus Walker (Lepidoptera; Lasiocampidae) is the most widely distributed Dendrolimus species. During periodic outbreaks, this species is said to make “fire without smoke” because large areas of pine forest can be quickly and heavily damaged. Yet, little is known about the molecular mechanisms that underlie the unique ecological characteristics of this forest insect. Here, we combined Pacific Biosciences (PacBio) RSII single‐molecule long reads and high‐throughput chromosome conformation capture (Hi‐C) genomics‐linked reads to produce a high‐quality, chromosome‐level reference genome for D. punctatus. The final assembly was 614 Mb with contig and scaffold N50 values of 1.39 and 22.15 Mb, respectively, and 96.96% of the contigs anchored onto 30 chromosomes. Based on the prediction, this genome contained 17,593 protein‐coding genes and 56.16% repetitive sequences. Phylogenetic analyses indicated that D. punctatus diverged from the common ancestor of Hyphantria cunea, Spodoptera litura and Thaumetopoea pityocampa ~ 108.91 million years ago. Many gene families that were expanded in the D. punctatus genome were significantly enriched for the xenobiotic biodegradation system, especially the cytochrome P450 gene family. This high‐quality, chromosome‐level reference genome will be a valuable resource for understanding mechanisms of D. punctatus outbreak and host resistance adaption. Because this is the first Lasiocampidae insect genome to be sequenced, it also will serve as a reference for further comparative genomics.     

Introduction to Special Issue on ‘Statistical Methods for Cancer Immunotherapy’

Statistics in Biosciences -