Gestational Diabetes Mellitus (GDM) has a high incidence of pregnancy, which seriously affects the life quality of pregnant women and fetal health. DNA methylation is one of the most important epigenetic modification that can regulate the gene expression level, and thus affect the occurrence of various diseases. Increasing evidence has shown that gene expression changes caused by DNA methylation play an important role in metabolic diseases. Here we explored the mechanisms and biological processes that affect the occurrence and development of GDM through analyzing the gene expression profiles and DNA methylation data of GDM. We detected 24,577 differential CpG sites mapping to 9339 genes (DMGs, differential methylation gene) and 931 differential expressed genes (DEGs) between normal samples and GDM samples. GO (gene ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway analysis of 326 overlapping genes between DMGs and DEGs showed obvious enrichment in terms related to metabolic disorders and immune responses. We identified Oas1, Ppie, Polr2g as possible pathogenic target genes of GDM by combining protein-protein interaction analysis. Our study provides possible targets for early diagnosis of GDM and information for clinical prevention of abnormal fetal development and type 2 diabetes.
As a non-coding and endogenous small RNA, MicroRNA (miRNA) takes a vital regulatory role in plant growth and development. Long-term storage and processing of many fruits and vegetables, including Luffa, are subject to influences from browning, a common post-harvest problem that adversely affects flavor, aroma, and nutritional value. The browning regulatory networks mediated by miRNA, however, remain largely unexplored. For a systematic identification of browning-responsive miRNAs and the targets, we built two RNA libraries from Luffa pulps of near-isogenic line, with resistant and sensitive browning characteristics respectively, and then sequenced them using Solexa high-throughput technology. We consequently identified 179 known miRNAs that represent 17 non-conserved miRNA families and 24 conserved families, as well as 84 potential novel miRNAs, among which 16 miRNAs (eight known and eight novel miRNAs) were found to exhibit significant differential expressions and were thus identified as browning-related miRNAs. We then studied those browning-responsive miRNAs and the corresponding targets with RT-qPCR and finally validated their expression patterns. The results revealed that the expression patterns are specific to plant development stages and the miRNAs are identified with 39 target transcripts, which involve in plant development, defense response, transcriptional regulation, and signal transduction. After characterizing these miRNAs and their targets, we propose a browning regulatory network model of miRNA-mediatation in this paper. The findings of the work are helpful for the understanding of miRNA-mediated regulatory mechanisms of browning in Luffa, and will facilitate genetic improvement of pulp characteristics in Luffa.
DNA N6-methyladenine (6mA) modifications expand the information capacity of DNA and have long been known to exist in bacterial genomes. Xanthomonas oryzae pv. Oryzicola (Xoc) is the causative agent of bacterial leaf streak, an emerging and destructive disease in rice worldwide. However, the genome-wide distribution patterns and potential functions of 6mA in Xoc are largely unknown. In this study, we analyzed the levels and global distribution patterns of 6mA modification in genomic DNA of seven Xoc strains (BLS256, BLS279, CFBP2286, CFBP7331, CFBP7341, L8 and RS105). The 6mA modification was found to be widely distributed across the seven Xoc genomes, accounting for percent of 3.80, 3.10, 3.70, 4.20, 3.40, 2.10, and 3.10 of the total adenines in BLS256, BLS279, CFBP2286, CFBP7331, CFBP7341, L8, and RS105, respectively. Notably, more than 82% of 6mA sites were located within gene bodies in all seven strains. Two specific motifs for 6 mA modification, ARGT and AVCG, were prevalent in all seven strains. Comparison of putative DNA methylation motifs from the seven strains reveals that Xoc have a specific DNA methylation system. Furthermore, the 6 mA modification of rpfC dramatically decreased during Xoc infection indicates the important role for Xoc adaption to environment.
Salinity is one of the major abiotic factors that affect productivity in oat. Here, we report a comparison of the transcriptomes of two hexaploid oat cultivars, 'Hanyou-5' and 'Huazao-2', which differ with respect to salt tolerance, in seedlings exposed to salt stress. Analysis of the assembled unigenes from the osmotically stressed and control libraries of 'Hanyou-5' and 'Huazao-2' showed that the expression of 21.92% (36,462/166,326) of the assembled unigenes was differentially regulated in the two cultivars after different durations of salt stress. Bioinformatics analysis showed that the main functional categories enriched in these DEGs were "metabolic process", "response to stresses", "plant hormone signal transduction", "MAPK signalling", "oxidative phosphorylation", and the plant-pathogen interaction pathway. Some regulatory genes, such as those encoding MYB, WRKY, bHLH, and zinc finger proteins, were also found to be differentially expressed under salt stress. Physiological measurements also detected significant differences in the activities of POD (76.24 +/- 1.07 Vs 81.53 +/- 1.47 U/g FW) in the two genotypes in response to osmotic stress. Furthermore, differential expression of 18 of these genes was successfully validated using RNA-seq and qRT-PCR analyses. A number of stress-responsive genes were identified in both cultivars, and candidate genes with potential roles in the adaptation to salinity were proposed.
Totally asymmetric simple exclusion process (namely, TASEP) is one of the most vital driven diffusive systems, which depicts stochastic dynamics of self-driven particles unidirectional updating along one-dimensional discrete lattices controlled by hard-core exclusions. Different with pre-existing results, driven diffusive system composed by multiple TASEPs with asymmetric heterogeneous interactions under two-dimensional periodic boundaries is investigated. By using detailed balance principle, particle configurations are extensively studied to obtain universal laws of characteristic order parameters of such stochastic dynamic system. By performing analytical analyses and Monte-Carlo simulations, local densities are found to be monotone increase with global density and spatially homogeneous to site locations. Oppositely, local currents are found to be non-monotonically increasing against global density and proportional to forward rate. Additionally, by calculating different cases of topologies, changing transition rates are found to have greater effects on particle configurations in adjacent subsystems. By intuitively comparing with pre-existing results, the improvement of our work also shows that introducing and considering totally heterogeneous interactions can improve the total current in such multiple TASEPs and optimize the overall transport of such driven-diffusive system. Our research will be helpful to understand microscopic dynamics and non-equilibrium dynamical behaviors of interacting particle systems.
The options of traditional self-report rating-scale, like the PTSD Checklist Civilian (PCL-C) scale, have no clear boundaries which might cause considerable biases and low effectiveness. This research aimed to explore the feasibility of using fuzzy set in the data processing to promote the screening effectiveness of PCL-C in real-life practical settings. The sensitivity, specificity, Youden's index etc., of PCL-C at different cutoff lines (38, 44 and 50 respectively) were analyzed and compared with those of fuzzy set approach processing. In practice, no matter the cutoff line of the PCL-C was set at 50, 44 or 38, the PCL-C showed good specificity, but failed to exhibit good sensitivity and screening effectiveness. The highest sensitivity was at 65.22%, with Youden's index being 0.64. After fuzzy processing, the fuzzy-PCL-C's sensitivity increased to 91.30%, Youden's index rose to 0.91, having seen marked augmentation. In conclusion, this study indicates that fuzzy set can be used in the data processing of psychiatric scales which have no clear definition standard of the options to improve the effectiveness of the scales.
Homeobox (HB) genes are crucial for plant growth and development processes. They encode transcription factors and responses to various stresses, as reported by recent emerging evidence. In this study, a total of 113 BraHB genes were identified in Brassica rapa. On the basis of domain organization and phylogenetic analysis, the BraHBs were grouped into nine subclasses, in which homeobox leucine-zipper (HB LZP-III) showed the highest number of genes (28) compared to other subclasses. The BraHBs exhibited similarities in exon-intron organization and motif composition among the members of the same subclasses. The analysis revealed that HB-Knotted was more preferentially retained than any other subclass of BraHB. Furthermore, we evaluated the impact of whole-genome triplication on the evolution of BraHBs. In order to analyze the subgenomes of B. rapa, we identified 39 paralogous pairs for which synonymous substitution values were lower than 1.00 for further purifying selection. Finally, the expression patterns of BraHBs across six tissues expressed dynamic variations combined with their responses against multiple stresses. The current study provides brief information on the homeobox gene family in B. rapa. Our findings can serve as a reference for further functional analysis of BraHBs.
With most city dwellers in China subjected to air pollution, forecasting extreme air pollution spells is of paramount significance in both scheduling outdoor activities and ameliorating air pollution. In this paper, we integrate the autoregressive conditional duration model (ACD) with the recurrence interval analysis (RIA) and also extend the ACD model to a spatially autoregressive conditional duration (SACD) model by adding a spatially reviewed term to quantitatively explain and predict extreme air pollution recurrence intervals. Using the hourly data of six pollutants and the air quality index (AQI) during 2013-2016 collected from 12 national air quality monitoring stations in Beijing as our test samples, we attest that the spatially reviewed recurrence intervals have some general explanatory power over the recurrence intervals in the neighbouring air quality monitoring stations. We also conduct a one-step forecast using the RIA-ACD(1,1) and RIA-SACD(1,1,1) models and find that 90% of the predicted recurrence intervals are smaller than 72 hours, which justifies the predictive power of the proposed models. When applied to more time lags and neighbouring stations, the models are found to yield results that are consistent with reality, which evinces the feasibility of predicting extreme air pollution events through a recurrence-interval-analysis-based autoregressive conditional duration model. Moreover, the addition of a spatial term has proved effective in enhancing the predictive power.
Poleroviruses are widely distributed and often of great economic importance because they cause a variety of symptoms, such as the rolling of young leaves, leaf color changes, and plant decline, in infected plants. However, the molecular mechanism behind these viral-induced symptoms is still unknown. Here, we verified the pathogenicity of the polerovirus Brassica yellows virus (BrYV) by transforming its full-length amplicon into Arabidopsis thaliana, which resulted in many abnormal phenotypes. To better understand the interactions between BrYV and its host, global transcriptome profiles of the transgenic plants were compared with that of non-transgenic Arabidopsis plants. An association between the BrYV-induced purple leaf symptoms and the activation of anthocyanin biosynthesis was noted. Using the transgenic approach, we found that movement protein of BrYV was responsible for the induction of these coloration symptoms. Collectively, our findings demonstrate the BrYV' pathogenicity and show that the BrYV-induced purple leaf symptom resulted from its movement protein stimulating anthocyanin accumulation.
Treating an abdominal aortic aneurysm (AAA) with a stent graft (SG) and a multilayer stent (MS) is a key technology in isolating flow fields. Clinically, dual stents (an SG in the proximal and an MS in the distal of AAA) are used for treatment of AAA, but only a few studies have examined the relationship between SG coverage and treatment effects. Through numerical simulation of the hemodynamics after SG and MS implantation, the SG coverage and position were simulated at 0% (0 mm), 25% (13.75 mm), 50% (27.5 mm), and 75% (41.25 mm). With increasing SG coverage, the pressure on the aneurysm sac wall and the flow of branch vessels gradually decreased, and the lower wall shear stress (WSS) gradually increased. The changes in pressure, lower WSS, and the mass flow rate of the branch vessels did not change significantly. The coverage of the SG has a nonsignificant effect on hemodynamics in the treatment of AAA; the implantation position need not be very precise. This research can provide theoretic support for clinicians' decision-making.
Human carboxylesterases has been proven to be age and race-related and a sound basis of clinical medication. PLE involve in signal transduction and highly catalyze hydrolysis. Therefore, the expression level of PLE most probably exist age and breed difference and lead to significant differences of pharmacology and physiology. Four age groups of Tongcheng (TC) and Large White (LW) pigs were selected to explore PLE breed and age differences, and it was found that PLE mRNA was most abundant in liver in both breeds. In liver, PLE levels and hydrolytic activities increased with age, and PLE levels (except for 3 month) and the hydrolytic activities were higher in LW than in TC across all age groups. Abundance of PLE isoenzymes was obvious different between breeds and among age groups. The most abundant PLE isoenzyme in LW and TC pigs was PLE-A1 (all age groups) and PLE-B9 (three early age groups) or PLE-G3 (adult groups), respectively. 103 new PLE isoenzymes were found, and 55 high-frequency PLE isoenzymes were accordingly classified into seven categories (A-G). The results of this research provide a necessary basis not only for clinical medication of pigs but also for pig breeding purposes.
Amplification and sequencing of 16S amplicons are widely used for profiling the structure of oral microbiota. However, it remains not clear whether and to what degree DNA extraction and targeted 16S rRNA hypervariable regions influence the analysis. Based on a mock community consisting of five oral bacterial species in equal abundance, we compared the 16S amplicon sequencing results on the Illumina MiSeq platform from six frequently employed DNA extraction procedures and three pairs of widely used 16S rRNA hypervariable primers targeting different 16S rRNA regions. Technical reproducibility of selected 16S regions was also assessed. DNA extraction method exerted considerable influence on the observed bacterial diversity while hypervariable regions had a relatively minor effect. Protocols with beads added to the enzyme-mediated DNA extraction reaction produced more accurate bacterial community structure than those without either beads or enzymes. Hypervariable regions targeting V3-V4 and V4-V5 seemed to produce more reproducible results than V1-V3. Neither sequencing batch nor change of operator affected the reproducibility of bacterial diversity profiles. Therefore, DNA extraction strategy and 16S rDNA hypervariable regions both influenced the results of oral microbiota biodiversity profiling, thus should be carefully considered in study design and data interpretation.
So far, the development of a unique strategy for specific biomolecules activity monitoring and precise drugs release in cancerous cells is still challenging. Here, we designed a conformation-switchable smart nanoprobe to monitor telomerase activity and to enable activity-triggered drug release in cancerous cells. The straightforward nanoprobe contained a gold nanoparticle (AuNP) core and a dense layer of 5-carboxyfluorescein (FAM)-labeled hairpin DNA shell. The 3' region of hairpin DNA sequence could function as the telomerase primer to be elongated in the presence of telomerase, resulting in the conformational switch of hairpin DNA. As a result, the FAM fluorescence was activated and the anticancer drug doxorubicin (Dox) molecules which intercalated into the stem region of the hairpin DNA sequence were released into cancerous cells simultaneously. The smart method could specifically distinguish cancerous cells from normal cells based on telomerase activity. It also showed a good performance for monitoring telomerase activity in the cytoplasm by molecular imaging and precise release of Dox triggered by telomerase activity in cancerous cells. These advantages may offer a great potential of this method for monitoring telomerase activity in cancer progression and estimating therapeutic effect.
We show that both single-component and two-component Bose-Einstein condensates' (BECs) ground states can be simulated by a deep convolutional neural network. We trained the neural network via inputting the parameters in the dimensionless Gross-Pitaevskii equation (GPE) and outputting the ground-state wave function. After the training, the neural network generates ground-state wave functions with high precision. We benchmark the neural network for either inputting different coupling strength in the GPE or inputting an arbitrary potential under the infinite double walls trapping potential, and it is found that the ground state wave function generated by the neural network gives the relative chemical potential error magnitude below 10(-3). Furthermore, the neural network trained with random potentials shows prediction ability on other types of potentials. Therefore, the BEC ground states, which are continuous wave functions, can be represented by deep convolutional neural networks.
For the evacuation crowd of social agents, environment plays a big effect on the behavior and decision of the agents. When facing the uncertain environment, the behavior and decision of agents depend heavily on the perception of environment. Therefore, the cooperation between agents and their perception of environment may coexist during evacuation. Here we establish a mechanism to analyze the coevolution between the cooperation of agents and the perception of environment. In detail, we use a regular square lattice with periodic boundaries, where two payoff matrices are used to describe two kinds of games between neighbors in the safe and dangerous environments. For individual agent, its perception can be adjusted by interacting with neighboring agents. When the environment is generally considered dangerous, the fraction of cooperative agents keeps at a high level, even if the value of b is very large. When all the agents think that the environment is safe, the fraction of cooperation will decrease as the value of b increases.