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BackgroundColon cancer is one of the common cancers, and its prognosis remains to be improved. The role of cuproptosis as a newly discovered form of cell death in the development of colon cancer has not been determined.MethodsBased on 983 colon cancer samples in the TCGA database and the GEO database, we performed a comprehensive genomic analysis to explore the molecular subtypes mediated by cuproptosis-related genes. Single-sample gene set enrichment analysis (ssGSEA) was utilized to quantify the relative abundance of each cell infiltrate in the TME. A risk score was established using least absolute shrinkage and selection operator regression (LASSO), and its predictive ability for colon cancer patients was verified to explore its guiding value for treatment.ResultsWe identified two distinct cuproptosis-related molecular subtypes in colon cancer. These two distinct molecular subtypes can predict clinicopathological features, prognosis, TME activity, and immune-infiltrating cells. A risk model was developed and its predictive ability was verified. Compared with patients in the high-risk score group, patients in the low-risk score group were characterized by lower tumor microenvironment score, higher stem cell activity, lower tumor mutational burden, lower microsatellite instability, higher sensitivity to chemotherapeutics, and better immunotherapy efficacy.ConclusionThis study contributes to understanding the molecular characteristics of cuproptosis-related subtypes. We demonstrate a critical role for cuproptosis genes in colon cancer s in the TME. Our study contributes to the development of individualized treatment regimens for colon cancer.

Abstract CHK1 is a crucial DNA damage checkpoint kinase and its activation, which requires ATR and RAD17, leads to inhibition of DNA replication and cell cycle progression. Recently, we reported that SMG7 stabilizes and activates p53 to induce G1 arrest upon DNA damage; here we show that SMG7 plays a critical role in the activation of the ATR-CHK1 axis. Following genotoxic stress, SMG7-null cells exhibit deficient ATR signaling, indicated by the attenuated phosphorylation of CHK1 and RPA32, and importantly, unhindered DNA replication and fork progression. Through its 14-3-3 domain, SMG7 interacts directly with the Ser635-phosphorylated RAD17 and promotes chromatin retention of the 9-1-1 complex by the RAD17-RFC, an essential step to CHK1 activation. Furthermore, through maintenance of CHK1 activity, SMG7 controls G2-M transition and facilitates orderly cell cycle progression during recovery from replication stress. Taken together, our data reveals SMG7 as an indispensable signaling component in the ATR-CHK1 pathway during genotoxic stress response.

The southwestern margin of the South China Craton preserves a Late Permian to Early Triassic sedimentary succession, the provenance of which helps to constrain the magmatic history and tectonic evolution of the Paleo-Tethyan Orogen. In this study, we present new detrital zircon U-Pb age, trace element, Hf isotope and whole-rock geochemical composition analyses from the Lower Triassic Qingtianbao Formation, to distinguish the provenance of clastic rocks. The results show that the detrital zircons of the Qingtianbao Formation are characterized by an age spectrum of unimodal, with an age peak of ∼260 Ma, and have a geochemical affinity to within-plate sources. Most of these zircons have positive εHf(t) values (+1.6 to +5.9), similar to those of the Emeishan rhyolites. The whole-rock geochemistry of most clastic samples shows no Nb–Ta anomalies on primitive mantle-normalized elemental diagrams. These features imply a source related to the Emeishan volcanic rocks. Integration of the geologic and provenance records in the southwestern margin of the South China Craton, we suggest that the Paleo-Tethyan Ocean may undergo a unidirectional subduction westward beneath the Indochina Block during the Late Permian–Early Triassic.

Coastal lagoon is an important productive ecosystem on the Earth. In this study, we compared microbial community in the sediments between lagoon and surrounding areas, and explored mechanism for the variation of microbial community. As a result, the sediment of surrounding area showed significantly higher organic matter and total nitrogen than that of the lagoon. The linear regression analysis revealed that organic matter and total nitrogen are positively correlated with Xenococcus. Bacterial and fungal PCoA1 showed significantly positive relationships with the relative abundance of Xenococcus, indicating that Xenococcus affects the bacterial and fungal community in the sediments of both the lagoon and surrounding area. ANOSIM analysis demonstrated that there were significant differences in bacterial and fungal community structure in the sediments between the lagoon and surrounding areas. Therefore, organic matter and total nitrogen affect the microbial community structure in the sediments of lagoon and surrounding areas by regulating the abundance of Xenococcus.

Long non-coding RNAs (lncRNAs) play vital roles in the metastasis and invasion of cancer cells. Systematic analysis of ovarian cancer (OvCa) expression profiles suggests that deregulation of lncRNA AC004988.1, designated promoting transition-associated lncRNA (PTAL), is involved in OvCa progression. However, the underlying mechanism of PTAL in OvCa remains unknown. In this study, we showed that PTAL was significantly upregulated in mesenchymal subtype samples compared with epithelial subtype samples from TCGA serous OvCa datasets. PTAL expression was positively correlated with the expression of fibronectin1 (FN1), whereas PTAL and FN1 were negatively correlated with miR-101 expression in the mesenchymal OvCa samples. In addition, knockdown of PTAL inhibited cell migration and invasion and blunted the progression of metastasis in vitro. Meanwhile, knockdown of PTAL increased the expression of miR-101 and subsequently inhibited the expression of FN1. Importantly, PTAL positively regulated the expression of FN1 through sponging of miR-101 and promoted OvCa cell metastasis by regulating epithelial-mesenchymal transition. Overall, our study demonstrates the role of PTAL as a miRNA sponge in OvCa and suggests that PTAL may be a potential target for preventing OvCa metastasis. Keywords: ovarian cancer, epithelial-mesenchymal transition, lncRNA PTAL, miR-101, FN1

The mobile ad hoc network (MANET) is a kind of dynamic, easy to construct and universal network, which has been widely concerned by a large number of researchers. Graph theory provides an effective theoretical tool for MANETs modeling and analysis. Clustering is one of the most effective methods to measure network performance with different attributes. This paper gives the basic concept of graph kernel and discusses the principle of optimizing graph kernel and multi-graph kernel. In this paper, we propose a Graph Kernel based Clustering Algorithm in MANETs (GKCA). The GKCA algorithm gives the basic concept of graph kernel, discusses the principle of optimizing graph kernel and multi-graph kernel, and proposes the basic principle based on $d$ -hop graph kernel. GKCA algorithm uses shortest path (SP) to connect different cluster head nodes for packet transmission. The performance of GKCA algorithm, such as the control packets ratio, packets loss ratio, and average end-to-end delay are experimentally evaluated using network simulation (NS2) software. Experimental analysis shows that the proposed approach is efficient, and its performance advantage in dynamic mobile networks is promising.

Background: The abnormal expression of RNA-binding proteins (RBPs) in various malignant tumors is closely related to the occurrence and development of tumors. However, the role of RBPs in acute myeloid leukemia (AML) is unclear.Methods: We downloaded harmonized RNA-seq count data and clinical data for AML from UCSC Xena, including The Cancer Genome Atlas (TCGA), The Genotype-Tissue Expression (GTEx), and Therapeutically Applicable Research to Generate Effective Treatments (TARGET) cohorts. R package edgeR was used for differential expression analysis of 337 whole-blood data and 173 AML data. The prognostic value of these RBPs was systematically investigated by using univariate Cox regression analysis, least absolute shrinkage and selection operator (LASSO)–Cox regression analysis, and multivariate Cox regression analysis. C-index and calibration diagram were used to judge the accuracy of the model, and decision curve analysis (DCA) was used to judge the net benefit. The biological pathways involved were revealed by gene set enrichment analysis (GSEA). The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and the protein–protein interaction (PPI) network performed lateral verification on the selected gene set and LASSO results.Results: A prognostic model of 12-RBP signature was established. In addition, the net benefit and prediction accuracy of the prognostic model and the mixed model based on it were significantly higher than that of cytogenetics. It is verified in the TARGET cohort and shows good prediction effect. Both the selection of our gene set and the LASSO results have high credibility. Most of these pathways are involved in the development of the disease, and they also accumulate in leukemia and RNA-related pathways.Conclusion: The prognosis model of the 12-RBP signature found in this study is an optimized biomarker that can effectively stratify the risk of AML patients. Nomogram based on this prognostic model is a reliable method to predict the median survival time of patients. This study expands our current understanding of the role of RBPs in the occurrence of AML and may lay the foundation for future treatment of the disease.

Polymorphonuclear neutrophils (PMNs) are the most important determinants in the acute inflammatory response. Pathologically increased numbers of PMNs in the circulation or specific tissues (or both) lead to neutrophilia. However, the genes expressed and pathways involved in neutrophilia have yet to be elucidated. By analysis of three public microarray datasets related to neutrophilia (GSE64457, GSE54644, and GSE94923) and evaluation by gene ontology, pathway enrichment, protein–protein interaction networks, and hub genes analysis using multiple methods (DAVID, PATHER, Reactome, STRING, Reactome FI Plugin, and CytoHubba in Cytoscape), we identified the commonly up-regulated and down-regulated different expressed genes. We also discovered that multiple signaling pathways (IL-mediated, LPS-mediated, TNF-α, TLR cascades, MAPK, and PI3K-Akt) were involved in PMN regulation. Our findings suggest that the commonly expressed genes involved in regulation of multiple pathways were the underlying molecular mechanisms in the development of inflammatory, autoimmune, and hematologic diseases that share the common phenotypic characteristics of increased numbers of PMNs. Taken together, these data suggest that these genes are involved in the regulation of neutrophilia and that the corresponding gene products could serve as potential biomarkers and/or therapeutic targets for neutrophilia.

In applications as in wireless communication, computer graphics and digital signal processing, a massive of complex matrix operations is often performed. Reciprocal is computed in large quantities in these matrix operations. To obtain high performance, efficient algorithm and hardware architecture are important in terms of low cost, low computation time and high precision. Second order first sub-function and squaring shrunk method have been proposed to build efficient hardware architecture for reciprocal using field programmable gate array. Second order first sub-function in harmonized parabolic synthesis is presented to improve the approximating precision and decrease the memory usage at the cost of additional multipliers. To further reduce the complexity, squaring shrunk method is proposed to decrease the expensive cost of multipliers. The combination of these techniques yields good performance trade-off. Precision simulation and hardware implementation result has shown that hardware reciprocal of high precision, low memory and low multiplier usage has been obtained compared to traditional first order first sub-function harmonized parabolic synthesis method. DOI: http://dx.doi.org/10.5755/j01.eie.24.2.20635

In order to remove the strong noise with complex shapes and high density in nuclear radiation scenes, a lightweight network composed of a Noise Learning Unit (NLU) and Texture Learning Unit (TLU) was designed. The NLU is bilinearly composed of a Multi-scale Kernel Module (MKM) and a Residual Module (RM), which learn non-local information and high-level features, respectively. Both the MKM and RM have receptive field blocks and attention blocks to enlarge receptive fields and enhance features. The TLU is at the bottom of the NLU and learns textures through an independent loss. The entire network adopts a Mish activation function and asymmetric convolutions to improve the overall performance. Compared with 12 denoising methods on our nuclear radiation dataset, the proposed method has the fewest model parameters, the highest quantitative metrics, and the best perceptual satisfaction, indicating its high denoising efficiency and rich texture retention.

A PI hydroturbine governing system with saturation and double delays is generated in small perturbation. The nonlinear dynamic behavior of the system is investigated. More precisely, at first, we analyze the stability and Hopf bifurcation of the PI hydroturbine governing system with double delays under the four different cases. Corresponding stability theorem and Hopf bifurcation theorem of the system are obtained at equilibrium points. And then the stability of periodic solution and the direction of the Hopf bifurcation are illustrated by using the normal form method and center manifold theorem. We find out that the stability and direction of the Hopf bifurcation are determined by three parameters. The results have great realistic significance to guarantee the power system frequency stability and improve the stability of the hydropower system. At last, some numerical examples are given to verify the correctness of the theoretical results.

We introduce a discretization process to discretize a modified fractional-order optically injected semiconductor lasers model and investigate its dynamical behaviors. More precisely, a sufficient condition for the existence and uniqueness of the solution is obtained, and the necessary and sufficient conditions of stability of the discrete system are investigated. The results show that the system’s fractional parameter has an effect on the stability of the discrete system, and the system has rich dynamic characteristics such as Hopf bifurcation, attractor crisis, and chaotic attractors.