Linc01232 promotes the metastasis of pancreatic cancer by suppressing the ubiquitin-mediated degradation of HNRNPA2B1 and activating the A-Raf-induced MAPK/ERK signaling pathway

Pancreatic cancer (PC) is a malignant cancer with high mortality and poor prognosis. In this study, we found that Linc01232 was significantly upregulated in PC tissues and cells and higher Linc01232 expression was associated with poorer prognosis. Linc01232 overexpression promoted and Linc01232 knockdown inhibited the migration and invasion of PC cells. The results of RNA pull-down, RNA Binding Protein Immunoprecipitation (RIP) assays revealed that Linc01232 physically interacted with Heterogeneous Nuclear Ribonucleoprotein A2/B1 (HNRNPA2B1) (680-890 nt fragment with the RNA recognition motif 2 domain) to inhibit its ubiquitin-mediated degradation in PC cells. RNA sequencing was performed to obtain the transcriptional profiles regulated by Linc01232 and we further demonstrated that Linc01232 participated in the alternative splicing of A-Raf by stabilizing HNRNPA2B1 and subsequently regulated the MAPK/ERK signaling pathway. Collected, our study showed that Linc01232/HNRNPA2B1/A-Raf/MAPK axis participated in the progression of PC and provided a potential therapeutic target for PC.

Two Variations of Peer Intermediaries for Key Establishment in Sensor Networks

Recently, the issue pertinent to sensor network security is a popular topic. Especially, due to the restriction of energy supplied by battery power of the sensors, symmetric cryptography is one of the suitable choices for the secret communication between sensors, while asymmetric cryptography is not appropriate because of its heavy loading on computation should consume a lot of energy. As a result of using symmetric cryptography, there are numerous research papers focusing on designing efficient key management scheme in sensor networks. PIKE designed by Chan and Perrig is a scheme using peer intermediaries and their pre-installed keys to deliver secret message from one sensor to another. However, they did not consider the case that the sensors are scattered in nonuniform way. Moreover, O(logn) is enough for sensor networks to achieve expander topology while PIKE has O(√n) storage overhead. This article gives generalizations of PIKE to offer more choices for developers under different requirements. The Constant Storage Protocol, abbreviated as CSP, costs constant memory storage and is more suitable for group-based deployment.

Correction to: Common metabolic networks contribute to carbon sink strength of sorghum internodes: implications for bioenergy improvement

[This corrects the article DOI: 10.1186/s13068-019-1612-7.].

Common metabolic networks contribute to carbon sink strength of sorghum internodes: implications for bioenergy improvement

BACKGROUND

Sorghum bicolor (L.) is an important bioenergy source. The stems of sweet sorghum function as carbon sinks and accumulate large amounts of sugars and lignocellulosic biomass and considerable amounts of starch, therefore providing a model of carbon allocation and accumulation for other bioenergy crops. While omics data sets for sugar accumulation have been reported in different genotypes, the common features of primary metabolism in sweet genotypes remain unclear. To obtain a cohesive and comparative picture of carbohydrate metabolism between sorghum genotypes, we compared the phenotypes and transcriptome dynamics of sugar-accumulating internodes among three different sweet genotypes (Della, Rio, and SIL-05) and two non-sweet genotypes (BTx406 and R9188).

RESULTS

Field experiments showed that Della and Rio had similar dynamics and internode patterns of sugar concentration, albeit distinct other phenotypes. Interestingly, cellulose synthases for primary cell wall and key genes in starch synthesis and degradation were coordinately upregulated in sweet genotypes. Sweet sorghums maintained active monolignol biosynthesis compared to the non-sweet genotypes. Comparative RNA-seq results support the role of candidate Tonoplast Sugar Transporter gene (TST), but not the Sugars Will Eventually be Exported Transporter genes (SWEETs) in the different sugar accumulations between sweet and non-sweet genotypes.

CONCLUSIONS

Comparisons of the expression dynamics of carbon metabolic genes across the RNA-seq data sets identify several candidate genes with contrasting expression patterns between sweet and non-sweet sorghum lines, including genes required for cellulose and monolignol synthesis (CesA, PTAL, and CCR), starch metabolism (AGPase, SS, SBE, and G6P-translocator SbGPT2), and sucrose metabolism and transport (TPP and TST2). The common transcriptome features of primary metabolism identified here suggest the metabolic networks contributing to carbon sink strength in sorghum internodes, prioritize the candidate genes for manipulating carbon allocation with bioenergy purposes, and provide a comparative and cohesive picture of the complexity of carbon sink strength in sorghum stem.

Large Scale Profiling of Protein Isoforms Using Label-Free Quantitative Proteomics Revealed the Regulation of Nonsense-Mediated Decay in Moso Bamboo (Phyllostachys edulis)

Moso bamboo is an important forest species with a variety of ecological, economic, and cultural values. However, the gene annotation information of moso bamboo is only based on the transcriptome sequencing, lacking the evidence of proteome. The lignification and fiber in moso bamboo leads to a difficulty in the extraction of protein using conventional methods, which seriously hinders research on the proteomics of moso bamboo. The purpose of this study is to establish efficient methods for extracting the total proteins from moso bamboo for following mass spectrometry-based quantitative proteome identification. Here, we have successfully established a set of efficient methods for extracting total proteins of moso bamboo followed by mass spectrometry-based label-free quantitative proteome identification, which further improved the protein annotation of moso bamboo genes. In this study, 10,376 predicted coding genes were confirmed by quantitative proteomics, accounting for 35.8% of all annotated protein-coding genes. Proteome analysis also revealed the protein-coding potential of 1015 predicted long noncoding RNA (lncRNA), accounting for 51.03% of annotated lncRNAs. Thus, mass spectrometry-based proteomics provides a reliable method for gene annotation. Especially, quantitative proteomics revealed the translation patterns of proteins in moso bamboo. In addition, the 3284 transcript isoforms from 2663 genes identified by Pacific BioSciences (PacBio) single-molecule real-time long-read isoform sequencing (Iso-Seq) was confirmed on the protein level by mass spectrometry. Furthermore, domain analysis of mass spectrometry-identified proteins encoded in the same genomic locus revealed variations in domain composition pointing towards a functional diversification of protein isoform. Finally, we found that part transcripts targeted by nonsense-mediated mRNA decay (NMD) could also be translated into proteins. In summary, proteomic analysis in this study improves the proteomics-assisted genome annotation of moso bamboo and is valuable to the large-scale research of functional genomics in moso bamboo. In summary, this study provided a theoretical basis and technical support for directional gene function analysis at the proteomics level in moso bamboo.

Post-transcriptional adaptation of the aquatic plant Spirodela polyrhiza under stress and hormonal stimuli

The Lemnaceae family comprises aquatic plants of angiosperms gaining attention due to their utility in wastewater treatment, and rapid production of biomass that can be used as feed, fuel, or food. Moreover, it can serve as a model species for neotenous growth and environmental adaptation. The latter properties are subject to post-transcriptional regulation of gene expression, meriting investigation of how miRNAs in Spirodela polyrhiza, the most basal and most thoroughly sequenced member of the family, are expressed under different growth conditions. To further scientific understanding of its capacity to adapt to environmental cues, we measured miRNA expression and processing of their target sequences under different temperatures, and in the presence of abscisic acid, copper, kinetin, nitrate, and sucrose. Using two small RNA sequencing experiments and one degradome sequencing experiment, we provide evidence for 108 miRNAs. Sequencing cleaved mRNAs validated 42 conserved miRNAs with 83 targets and 24 novel miRNAs regulating 66 targets and created a list of 575 predicted and verified targets. These analyses revealed condition-induced changes in miRNA expression and cleavage activity, and resulted in the addition of stringently reviewed miRNAs to miRBase. This combination of small RNA and degradome sequencing provided not only high confidence predictions of conserved and novel miRNAs and targets, but also a view of the post-transcriptional regulation of adaptations. A unique aspect is the role of miR156 and miR172 expression and activity in its clonal propagation and neoteny. Additionally, low levels of 24 nt sRNAs were observed, despite the lack of recent retrotransposition.

Transcriptome and metabolome reveal distinct carbon allocation patterns during internode sugar accumulation in different sorghum genotypes

Sweet sorghum accumulates large amounts of soluble sugar in its stem. However, a system-based understanding of this carbohydrate allocation process is lacking. Here, we compared the dynamic transcriptome and metabolome between the conversion line R9188 and its two parents, sweet sorghum RIO and grain sorghum BTx406 that have contrasting sugar-accumulating phenotypes. We identified two features of sucrose metabolism, stable concentrations of sugar phosphates in RIO and opposite trend of trehalose-6-phosphate (T6P) between RIO vs R9188/BTx406. Integration of transcriptome and metabolome revealed R9188 is partially active in starch metabolism together with medium sucrose level, whereas sweet sorghum had the highest sucrose concentration and remained highly active in sucrose, starch, and cell wall metabolism post-anthesis. Similar expression pattern of genes involved in sucrose degradation decreased the pool of sugar phosphates for precursors of starch and cell wall synthesis in R9188 and BTx406. Differential T6P signal between RIO vs R9188/BTx406 is associated with introgression of T6P regulators from BTx406 into R9188, including C-group bZIP and trehalose 6-phosphate phosphatase (TPP). The inverted T6P signalling in R9188 appears to down-regulate sucrose and starch metabolism partly through transcriptome reprogramming, whereas introgressed metabolic genes could be related to reduced cell wall metabolism. Our results show that coordinated primary metabolic pathways lead to high sucrose demand and accumulation in sweet sorghum, providing us with targets for genetic improvements of carbohydrate allocation in bioenergy crops.

Candidate gene identification of existing or induced mutations with pipelines applicable to large genomes

Bulked segregant analysis (BSA) is used to identify existing or induced variants that are linked to phenotypes. Although it is widely used in Arabidopsis and rice, it remains challenging for crops with large genomes, such as maize. Moreover, analysis of huge data sets can present a bottleneck linking phenotypes to their molecular basis, especially for geneticists without programming experience. Here, we identified two genes of maize defective kernel mutants with newly developed analysis pipelines that require no programing skills and should be applicable to any large genome. In the 1970s, Neuffer and Sheridan generated a chemically induced defective kernel (dek) mutant collection with the potential to uncover critical genes for seed development. To locate such mutations, the dek phenotypes were introgressed into two inbred lines to take advantage of maize haplotype variations and their sequenced genomes. We generated two pipelines that take fastq files derived from next-generation (nextGen) paired-end DNA and cDNA sequencing as input, call on several well established and freely available genomic analysis tools to call SNPs and INDELs, and generate lists of the most likely causal mutations together with variant index plots to locate the mutation to a specific sequence position on a chromosome. The pipelines were validated with a known strawberry mutation before cloning the dek mutants, thereby enabling phenotypic analysis of large genomes by next-generation sequencing.

Tracking the Process of a Solvothermal Domino Reaction Leading to a Stable Triheteroarylmethyl Radical: A Combined Crystallographic and Mass-Spectrometric Study

A new free carbon radical was obtained in a microwave-assisted solvothermal reaction of the primary amine (1-methyl-1H-benzo[d]imidazol-2-yl)methanamine with FeCl₃ ⋅6 H₂ O in methanol at 140 °C. Through a combination of crystallography and electrospray ionization mass spectrometry, the reaction process was studied. The longest domino reaction includes 14 steps and forms up to 12 new covalent bonds (9 C-N and 3 C-C bonds) and 3 five-membered heterocycles. For the first time, the homolytic cleavage of a C-O bond was used to synthesize a triarylmethyl radical.

An Adiponectin Receptor Agonist Reduces Type 2 Diabetic Periodontitis

Periodontitis is twice as prevalent in diabetics as in nondiabetics, and type 2 diabetes (T2D)-associated periodontitis is severe in many cases due to the altered and aberrant functions of bone cells in hyperglycemic conditions. Therefore, developing an effective method to halt the disease process, as well as restore and regenerate lost alveolar bone to reserve the natural teeth in diabetics, is critically important. In the current study, we applied a newly discovered adiponectin receptor agonist AdipoRon (APR) in experimental periodontitis in diabetic animal models and demonstrated the underlying molecular mechanisms. We found that when APR systemically quenched the blood sugar level in diet-induced obesity (DIO) diabetic mice, it reduced osteoclast numbers and alveolar bone loss significantly due to APR's inhibition on osteoclast differentiation shown in our in vitro studies. APR also decreased the production of proinflammatory molecules CC chemokine ligand 2 and interleukin 6 in diseased gingival tissues. On the other hand, APR promoted alveolar bone regeneration through enhancing osteogenic differentiation and decreasing stromal cell-derived factor 1 in the bone marrow that facilitates stem cell migration. Same results were achieved by APR treatment of periodontitis induced in adiponectin (APN) knockout mice, indicating the ability of APR to activate the endogenous APN receptors to exert osteoanabolic effects. In summary, our study supports the notion that APR could be used as an effective multipronged approach to target T2D-associated periodontitis.

Construction of expression vectors of capsid proteins from goose parvovirus and investigation of the immunogenicity

Goose parvovirus (GPV) is a highly contagious and lethal disease in goslings and Muscovy ducklings, and is of concern to the waterfowl industry. With the aim of comparing the cellular immunogenicity of three capsid proteins of GPV, plasmids of pcDNA3.1(+)-VP1, pcDNA3.1(+)-VP2, and pcDNA3.1(+)-VP3 were constructed, and the recombinant protein VPs were expressed using an eukaryotic expression system. We detected the levels of immune-related genes (CD4, CD8α, IL-1β, IL-6, IFNα, IFNγ, and IFNλ) in both goose embryo fibroblasts (GEF) and goose peripheral blood mononuclear cells (PBMCs) cellular models. The immune response conferred by a VP2 DNA vaccine in vivo was observed in a time course. Our data suggested that the cellular immune response to VP2 and VP3 was stronger than that to VP1, while VP2 and VP3 shared similar cellular immune reactivity. In addition, vaccination with VP2 plasmid can induce high level of IgY antibody that continued to increase through 28 days post vaccination. Therefore, our findings shed light on the host cellular immune response against GPV capsid proteins. Keywords: GPV; capsid proteins; cellular immune response; humoral immunity.

HHLA2 is a novel immune checkpoint protein in pancreatic ductal adenocarcinoma and predicts post-surgical survival

HHLA2 is a newly identified member of the B7 immune checkpoint family, but its function and crosstalk with immune cells is not fully understood. To gain insights into the HHLA2 expression profile and to determine the clinical significance and function of HHLA2 in pancreatic cancer, we performed immunohistochemistry (IHC) analyses on tissue microarrays (TMAs) of pancreatic ductal adenocarcinoma (PDAC, n = 92) with matched peritumoral tissues as well as in cohorts of precancerous lesions: pancreatic intraepithelial neoplasia (PanIN) and intraductal papillary mucinous neoplasm (IPMN). We found that HHLA2 was rarely detected in normal acinar, islet, and ductal cells but widely expressed from early pancreatic precancerous lesions to invasive PDAC. The overall HHLA2 positivity was 95% (19/20) in low grade PanIN and 70.73% (29/41) in IPMN. HHLA2 expression was detected in 77.17% (71/92) of the PDAC cases and was significantly associated with better prognosis in this cohort. Our findings suggest that HHLA2 may behave as a costimulatory ligand in pancreatic cancer, which differs from other B7 family members that are largely characterized as checkpoint inhibitors. Further investigation of the HHLA2 signaling pathway and its receptors is warranted by our data and may lead to novel therapeutic interventions.

Asthma and the risk of prostate cancer

Objective

The association between asthma and the risk of prostate cancer remains elusive. We aimed to evaluate the relationship between asthma and the onset of prostate cancer.

Methods

We searched PubMed, Embase, and Cochrane databases for articles that assessed the association of asthma with the risk of prostate cancer through October 2015. We extracted odds ratio (OR) and calculated the corresponding 95% confidence interval (CI). We used random-effects models to calculate a pooled association between asthma and the risk of prostate cancer.

Results

Fourteen studies were involved in the assessment of the association between asthma and prostate cancer risk. Asthma was not associated with the risk of prostate cancer in overall populations (OR 0.994, 95% CI 0.836-1.182), Caucasians (OR 0.922, 95% CI 0.825-1.030), and Asians (OR 5.022, 95% CI 0.415-60.793). The cumulative analysis also suggested a lack association between asthma and the risk of prostate cancer. Exclusion of any single study did not change the results significantly. No evidence of marked publication bias was observed.

Conclusions

Our investigation indicated that asthma was not associated with prostate cancer risk in overall populations, Caucasians, and Asians.

Evaluation Method of Public Transportation System Based on Fuzzy Cloud Model

This article describes how the public traffic system evaluation is an important measure to strengthen the management of urban transportation. Many scholars have evaluated the public transportation system, but lack research on different index weights of it. In past models, although the fuzzy assessment method was integrated into an evaluation methodology, its randomness was reflected unclearly. To solve the problems, a fuzzy evaluation of a cloud model is researched. Firstly, the corresponding weights of all indexes are calculated by analytic hierarchy process (AHP) and a clustering method. Then, the principal component of the indexes is extracted by the principal component analysis. According to the distribution of a principal component and processed with the cloud model, a subordinate degree function was established. Finally, scoring cities by combining the principal component weight and membership cloud matrix and evaluating the public transportation system. Comparing the matter-element analysis and the AHP gray model method, this proposed model in this article can evaluate the performance of different urban traffic systems more practically.

Using Weighted Similarity to Assess Risk of Illegal Fund Raising in Online P2P Lending

Peer-to-peer (P2P) lending is an important internet financial mode, which has a greater risk of illegal fund raising. From the risk research on P2P lending platforms has focused on policy and law, and the existing risk assessment is mainly aimed at borrowers' credit. Since it cannot meet the needs of effective supervision, this article proposes a risk alarm model from the perspective of illegal fund raising based on similarity weighted case. Through the investigation of P2P illegal fundraising cases, this article has extracted the risk features to build a risk feature matrix. A case to be evaluated needs to be transformed into a feature vector in the data preprocessing stage. Then, the similarity vector can be obtained by comparing a feature vector with the vectors in the risk feature matrix. The following selected the TOP K similarity to calculate the risk value by weighting. The experiments show that under the condition of even a small sample, it can reasonably evaluate the risk of the P2P lending platform, to achieve a certain risk alarm effect, and has a good feasibility.