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Abstract System state plays an important role in cyber-physical systems (CPSs). Ensuring the security of the CPSs is a key issue that can be widely applied. The confidentiality of system state is a fundamental feature of the CPSs security. This paper studies the distributed fusion estimation problem in the presence of eavesdropper, where local sensors send their estimates to a remote fusion center (FC). To prevent eavesdropping, the event triggered scheduling strategy was adopted on each sensor. Some sufficient conditions on the triggers’ threshold were derived to make the eavesdropping expected covariance unbounded while the expected error covariance for the user remains bounded. Moreover, the distributed confidentiality fusion estimation algorithm is provided to achieve perfect expected secrecy. Finally, simulations of different trigger levels for two local systems are employed to show the effectiveness of the proposed methods.

Abstract Background Glioblastoma multiforme (GBM) is the most aggressive form of brain cancer, and chemoresistance poses a significant challenge to the survival and prognosis of GBM. Although numerous regulatory mechanisms that contribute to chemoresistance have been identified, many questions remain unanswered. This study aims to identify the mechanism of temozolomide (TMZ) resistance in GBM. Methods Bioinformatics and antibody-based protein detection were used to examine the expression of E2F7 in gliomas and its correlation with prognosis. Additionally, IC50, cell viability, colony formation, apoptosis, doxorubicin (Dox) uptake, and intracranial transplantation were used to confirm the role of E2F7 in TMZ resistance, using our established TMZ-resistance (TMZ-R) model. Western blot and ChIP experiments provided confirmation of p53-driven regulation of E2F7. Results Elevated levels of E2F7 were detected in GBM tissue and were correlated with a poor prognosis for patients. E2F7 was found to be upregulated in TMZ-R tumors, and its high levels were linked to increased chemotherapy resistance by limiting drug uptake and decreasing DNA damage. The expression of E2F7 was also found to be regulated by the activation of p53. Conclusions The high expression of E2F7, regulated by activated p53, confers chemoresistance to GBM cells by inhibiting drug uptake and DNA damage. These findings highlight the significant connection between sustained p53 activation and GBM chemoresistance, offering the potential for new strategies to overcome this resistance.

Some haplotypes of the sucrose synthase gene TaSus1 are associated with thousand-grain weight (TGW) in wheat (Triticum aestivum L.). However, no mutations have been identified within the gene to test this association. The effects of TaSus1 on grain number per spike (GNS) also are largely unknown. Our previous genome-wide association study identified TaSus-A1 as a candidate gene controlling fertile spikelet number per spike (FSN). In the present study, we generated two independent mutants for the three TaSus1 homoeologs by CRISPR/Cas9-mediated genome editing. The triple mutants displayed lower FSN, GNS, grain number per spikelet (GNST), and TGW than wild-type plants. In 306 hexaploid wheat accessions, two single-nucleotide polymorphisms in TaSus-A1 contributed differently to GNS. Introgression of the two alleles into a wheat genetic background confirmed their effects. The alleles differed in geographical distribution among the accessions.

Abstract Background Large-scale genotype–phenotype association studies of crop germplasm are important for identifying alleles associated with favorable traits. The limited number of single-nucleotide polymorphisms (SNPs) in most wheat genome-wide association studies (GWASs) restricts their power to detect marker-trait associations. Additionally, only a few genes regulating grain number per spikelet have been reported due to sensitivity of this trait to variable environments. Results We perform a large-scale GWAS using approximately 40 million filtered SNPs for 27 spike morphology traits. We detect 132,086 significant marker-trait associations and the associated SNP markers are located within 590 associated peaks. We detect additional and stronger peaks by dividing spike morphology into sub-traits relative to GWAS results of spike morphology traits. We propose that the genetic dissection of spike morphology is a powerful strategy to detect signals for grain yield traits in wheat. The GWAS results reveal that TaSPL17 positively controls grain size and number by regulating spikelet and floret meristem development, which in turn leads to enhanced grain yield per plant. The haplotypes at TaSPL17 indicate geographical differentiation, domestication effects, and breeding selection. Conclusion Our study provides valuable resources for genetic improvement of spike morphology and a fast-forward genetic solution for candidate gene detection and cloning in wheat.

Abstract Background Plant architecture associated with increased grain yield and adaptation to the local environments is selected during wheat (Triticum aestivum) breeding. The internode length of individual stems and tiller length of individual plants are important for the determination of plant architecture. However, few studies have explored the genetic basis of these traits. Results Here, we conduct a genome-wide association study (GWAS) to dissect the genetic basis of geographical differentiation of these traits in 306 worldwide wheat accessions including both landraces and traditional varieties. We determine the changes of haplotypes for the associated genomic regions in frequency in 831 wheat accessions that are either introduced from other countries or developed in China from last two decades. We identify 83 loci that are associated with one trait, while the remaining 247 loci are pleiotropic. We also find 163 associated loci are under strong selective sweep. GWAS results demonstrate independent regulation of internode length of individual stems and consistent regulation of tiller length of individual plants. This makes it possible to obtain ideal haplotype combinations of the length of four internodes. We also find that the geographical distribution of the haplotypes explains the observed differences in internode length among the worldwide wheat accessions. Conclusion This study provides insights into the genetic basis of plant architecture. It will facilitate gene functional analysis and molecular design of plant architecture for breeding.

Summary: TP53 mutations are ubiquitous with tumorigenesis in non-small cell lung cancers (NSCLC). By analyzing the TCGA database, we reported that TP53 missense mutations are correlated with chromosomal instability and tumor mutation burden in NSCLC. The inability of wild-type nor mutant p53 expression can't predict survival in lung cancer cohorts, however, an examination of primary NSCLC tissues found that acetylated p53 did yield an association with improved survival outcomes. Molecularly, we demonstrated that acetylation drove the ubiquitination and degradation of mutant p53 but enhanced stability of wild-type p53. Moreover, acetylation of a missense p53 mutation prevented the gain of oncogenic function observed in typical TP53 mutant-expressing cells and enhanced tumor suppressor functions. Consequently, acetylation inducer targeting of missense mutant p53 may be a viable therapeutic goal for NSCLC treatment and may improve the accuracy of current efforts to utilize p53 mutations in a prognostic manner.

Objective(s): Hyperuricemia is a risk for cardiovascular and metabolic diseases, but the mechanism is ambiguous. Increased intestinal permeability is correlated with metabolic syndrome risk factors. Intestinal epithelial cells play a pivotal role in maintaining intestinal permeability. Uric acid is directly eliminated into intestinal lumen, however, the mechanism and effect of uric acid on intestinal epithelial cells is poorly explored. Here we carried out an analysis to identify the effect and mechanism of uric acid on intestinal epithelial cells.Materials and Methods: IEC-6 was exposed to different concentrations of uric acid to simulate the effect of uric acid on intestinal epithelial cells. Cell viability was determined by MTS assay. Protein content and mRNA were assessed using Western blotting and Q-PCR, respectively. Intracellular ROS was determined using flow-cytometry and fluorescence microscopy. Mitochondrial membrane potential was detected by immunofluorescence using a mitochondrial membrane potential assay kit with JC-1. Small interfering RNA transfection was used to suppress the expression of TLR4.Results: We found soluble uric acid alone increased the release of ROS, depolarized the mitochondrial membrane potential, up-regulated TSPO, increased the expression of TLR4 and NLRP3, and then activated NLRP3 inflammasome and NF-κB signaling, which further resulted in lower expression of tight junction protein and exerted adverse effects on intestinal epithelial cells. Furthermore, the elevated IL-1β could be restored by silencing of TLR4, indicating soluble uric acid induces inflammation via the TLR4/NLRP3 pathway.Conclusion: Soluble uric acid exerted detrimental effect on intestinal epithelial cells through the TLR4/NLRP3 pathway.

Stem elongation is a critical phase for yield determination and, as a major trait, is targeted for manipulation for improvement in bread wheat (Triticum aestivum L.). In a previous study, we characterized a mutant showing rapid stem elongation but with no effect on plant height at maturity. The present study aimed to finely map the underlying mutated gene, qd1, in this mutant. By analyzing an F2 segregating population consisting of 606 individuals, we found that the qd1 gene behaved in a dominant manner. Moreover, by using the bulked segregant RNA sequencing (BSR-seq)-based linkage analysis method, we initially mapped the qd1 gene to a 13.55 Mb region on chromosome 4B (from 15.41 to 28.96 Mb). This result was further confirmed in F2 and BC3F2 segregating populations. Furthermore, by using transcriptome sequencing data, we developed 14 Kompetitive Allele-Specific PCR (KASP) markers and then mapped the qd1 gene to a smaller and more precise 5.08 Mb interval from 26.80 to 31.88 Mb. To develop additional markers to finely map the qd1 gene, a total of 4,481 single-nucleotide polymorphisms (SNPs) within the 5.08 Mb interval were screened, and 25 KASP markers were developed based on 10x-depth genome resequencing data from both wild-type (WT) and mutant plants. The qd1 gene was finally mapped to a 1.33 Mb interval from 28.86 to 30.19 Mb on chromosome 4B. Four candidate genes were identified in this region. Among them, the expression pattern of only TraesCS4B02G042300 in the stems was concurrent with the stem development of the mutant and WT. The qd1 gene could be used in conjunction with molecular markers to manipulate stem development in the future.

The stems of cereal crops provide both mechanical support for lodging resistance and a nutrient supply for reproductive organs. Elongation, which is considered a critical phase for yield determination in winter wheat (Triticum aestivum L.), begins from the first node detectable to anthesis. Previously, we characterized a heavy ion beam triggered wheat mutant qd, which exhibited an altered stem elongation pattern without affecting mature plant height. In this study, we further analyzed mutant stem developmental characteristics by using transcriptome data. More than 40.87 Mb of clean reads including at least 36.61 Mb of unique mapped reads were obtained for each biological sample in this project. We utilized our transcriptome data to identify 124,971 genes. Among these genes, 4,340 differentially expressed genes (DEG) were identified between the qd and wild-type (WT) plants. Compared to their WT counterparts, qd plants expressed 2,462 DEGs with downregulated expression levels and 1878 DEGs with upregulated expression levels. Using DEXSeq, we identified 2,391 counting bins corresponding to 1,148 genes, and 289 of them were also found in the DEG analysis, demonstrating differences between qd and WT. The 5,199 differentially expressed genes between qd and WT were employed for GO and KEGG analyses. Biological processes, including protein-DNA complex subunit organization, protein-DNA complex assembly, nucleosome organization, nucleosome assembly, and chromatin assembly, were significantly enriched by GO analysis. However, only benzoxazinoid biosynthesis pathway-associated genes were enriched by KEGG analysis. Genes encoding the benzoxazinoid biosynthesis enzymes Bx1, Bx3, Bx4, Bx5, and Bx8_9 were confirmed to be differentially expressed between qd and WT. Our results suggest that benzoxazinoids could play critical roles in regulating the stem elongation phenotype of qd.

With the development of the industry, the physical model of controlled object tends to be complicated and unknown. It is particularly important to estimate the state variables of a nonlinear system when the model is unknown. This paper proposes a state estimation method based on adaptive fusion of multiple kernel functions to improve the accuracy of system state estimation. First, a dynamic neural network is used to build the system state model, where the kernel function node is constructed by a weighted linear combination of multiple local kernel functions and global kernel functions. Then, the state of the system and the weight of the kernel functions are put together to form an augmented state vector, which can be estimated in real time by using high-degree cubature Kalman filter. The high-degree cubature Kalman filter performs adaptive fusion of the kernel function weights according to specific samples, which makes the neural network function approximate the real system model, and the state estimate follows the real value. Finally, the simulation results verify the feasibility and effectiveness of the proposed algorithm.

BackgroundMore than 30–40% of uric acid is excreted via the intestine, and the dysfunction of intestinal epithelium disrupts uric acid excretion. The involvement of gut microbiota in hyperuricemia has been reported in previous studies, but the changes and mechanisms of intestinal immunity in hyperuricemia are still unknown.MethodsThis study developed a urate oxidase (Uox)-knockout (Uox–/–) mouse model for hyperuricemia using CRISPR/Cas9 technology. The lipometabolism was assessed by measuring changes in biochemical indicators. Furthermore, 4-kDa fluorescein isothiocyanate–labeled dextran was used to assess gut barrier function. Also, 16S rRNA sequencing was performed to examine the changes in gut microbiota in mouse feces. RNA sequencing, Western blot, Q-PCR, ELISA, and immunohistochemical analysis were used for measuring gene transcription, the number of immune cells, and the levels of cytokines in intestinal tissues, serum, kidney, liver, pancreas, and vascellum.ResultsThis study showed that the abundance of inflammation-related microbiota increased in hyperuricemic mice. The microbial pattern recognition–associated Toll-like receptor pathway and inflammation-associated TNF and NF-kappa B signaling pathways were significantly enriched. The increased abundance of inflammation-related microbiota resulted in immune disorders and intestinal barrier dysfunction by upregulating TLR2/4/5 and promoting the release of IL-1β and TNF-α. The levels of epithelial tight junction proteins occludin and claudin-1 decreased. The expression of the pro-apoptotic gene Bax increased. The levels of LPS and TNF-α in systemic circulation increased in hyperuricemic mice. A positive correlation was observed between the increase in intestinal permeability and serum levels of uric acid.ConclusionHyperuricemia was characterized by dysregulated intestinal immunity, compromised intestinal barrier, and systemic inflammation. These findings might serve as a basis for future novel therapeutic interventions for hyperuricemia.

Some studies on the hyperuricemia (HUA) have focused on intestinal bacteria. To better understand the correlation between gut microbiota and HUA, we established a HUA rat model with high-purine diet, and used 16S rRNA genes sequencing to analyze gut microbiota changes in HUA rats. To analyze the potential role played by gut microbiota in HUA, we altered the gut microbiota of HUA rats with antibiotics, and compared the degree of uric acid elevation between HUA and antibiotic-fed HUA rats (Ab+HUA). Finally, we established a recipient rat model, in which we transplanted fecal microbiota of HUA and normal rats into recipient rats. Three weeks later, we compared the uric acid content of recipient rats. As a result, the diversity and abundance of the gut microbiota had changed in HUA rats. The Ab-fed HUA rats had significantly lower uric acid content compared to the HUA rats, and gut microbiota from HUA rats increased uric acid content of recipient rats. The genera Vallitalea, Christensenella and Insolitispirillum may associate with HUA. Our findings highlight the association between gut microbiota and HUA, and the potential role played by gut microbiota in HUA. We hope that this finding will promote the isolation and culture of HUA-related bacteria and orient HUA-related studies from being correlational to mechanistic. These steps will therefore make it possible for us to treat HUA using gut microbiota as the target.

Support vector regression algorithm is widely used in fault diagnosis of rolling bearing. A new model parameter selection method for support vector regression based on adaptive fusion of the mixed kernel function is proposed in this paper. We choose the mixed kernel function as the kernel function of support vector regression. The mixed kernel function of the fusion coefficients, kernel function parameters, and regression parameters are combined together as the parameters of the state vector. Thus, the model selection problem is transformed into a nonlinear system state estimation problem. We use a 5th-degree cubature Kalman filter to estimate the parameters. In this way, we realize the adaptive selection of mixed kernel function weighted coefficients and the kernel parameters, the regression parameters. Compared with a single kernel function, unscented Kalman filter (UKF) support vector regression algorithms, and genetic algorithms, the decision regression function obtained by the proposed method has better generalization ability and higher prediction accuracy.

The molecular mechanism underlying hyperuricemia-induced lipid metabolism disorders is not clear. The purpose of the current study was to investigate the mechanism of lipid disturbances in a hyperuricemia mice model. RNA-Seq showed that differentially expressed genes (DEGs) in the fatty acid synthesis signaling pathway were mainly enriched and CXCL-13 was significantly enriched in protein-protein interaction networks. Western blotting, Q-PCR, and immunofluorescence results further showed that hyperuricemia upregulated CXCL-13 and disturbed lipid metabolism in vivo and in vitro. Furthermore, CXCL-13 alone also promoted the accumulation of lipid droplets and upregulated the expression of FAS and SREBP1, blocking AMPK signaling and activating the PKC and P38 signaling pathways. Silencing CXCL-13 reversed uric-acid-induced lipid droplet accumulation, which further downregulated FAS and SREBP1 expression, inhibited the p38 and PKC signaling, and activated AMPK signaling. In conclusion, hyperuricemia induces lipid metabolism disorders via the CXCL-13 pathway, making CXCL-13 a key regulatory factor linking hyperuricemia and lipid metabolism disorders. These results may provide novel insights for the treatment of hyperuricemia. NEW & NOTEWORTHY The underlying molecular mechanism of hyperuricemia-induced lipid metabolism disorders is still unclear. The study aimed to investigate the mechanism of lipid disturbance in hyperuricemia mice model. To our knowledge, we proposed for the first time that CXCL-13 may be a key regulator of hyperuricemia and lipid metabolism disorders. These results may provide new insights for the clinical treatment of hyperuricemia. [ABSTRACT FROM AUTHOR]

Water quality estimation is a basic task in regional water environment planning, evaluation, and management. This paper studies the water quality state estimation problem of the nonlinear system with an unknown state model. The existing algorithms based on nonlinear filtering and neural networks have limited accuracy in state estimation. To solve this problem, a new estimation method based on high-degree cubature Kalman filtering and neural networks is proposed. First, neural network is used to establish the state-space model for the nonlinear system. Then, the weights of the neural network and the system state variables are combined as a new state variable. Meanwhile, the real-time state update is performed by high-degree cubature Kalman. Moreover, the neural network can achieve the true approximation of the nonlinear system model and the accurate estimation of the state value. Finally, water quality estimation simulation shows the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Hyperuricemia is associated with many metabolic diseases. However, the underlying mechanism remains unknown. The gut microbiota has been demonstrated to play significant roles in the immunity and metabolism of the host. In the present study, we constructed a hyperuricemic mouse model to investigate whether the metabolic disorder caused by hyperuricemia is related to intestinal dysbiosis. A significantly increased intestinal permeability was detected in hyperuricemic mice. The difference in microflora between wild-type and hyperuricemic mice accompanies the translocation of gut microbiota to the extraintestinal tissues. Such a process is followed by an increase in innate immune system activation. We observed increased LPS and TNF-α levels in the hyperuricemic mice, indicating that hyperuricemic mice were in a state of low-grade systemic inflammation. In addition, hyperuricemic mice presented early injury of parenteral tissue and disordered lipid metabolism. These findings suggest that intestinal dysbiosis due to an impaired intestinal barrier may be the key cause of metabolic disorders in hyperuricemic mice. Our findings should aid in paving a new way of preventing and treating hyperuricemia and its complications. NEW & NOTEWORTHY Hyperuricemia is associated with many metabolic diseases. However, the underlying mechanism remains unknown. We constructed a hyperuricemic mouse model to explore the relationship between intestinal dysbiosis and metabolic disorder caused by hyperuricemia. [ABSTRACT FROM AUTHOR]