Non-negative Matrix Factorization (NMF) has been an ideal tool for machine learning. Non-negative Matrix Tri-Factorization (NMTF) is a generalization of NMF that incorporates a third non-negative factorization matrix,...Non-negative Matrix Factorization (NMF) has been an ideal tool for machine learning. Non-negative Matrix Tri-Factorization (NMTF) is a generalization of NMF that incorporates a third non-negative factorization matrix, and has shown impressive clustering performance by imposing simultaneous orthogonality constraints on both sample and feature spaces. However, the performance of NMTF dramatically degrades if the data are contaminated with noises and outliers. Furthermore, the high-order geometric information is rarely considered. In this paper, a Robust NMTF with Dual Hyper-graph regularization (namely RDHNMTF) is introduced. Firstly, to enhance the robustness of NMTF, an improvement is made by utilizing the l_(2,1)-norm to evaluate the reconstruction error. Secondly, a dual hyper-graph is established to uncover the higher-order inherent information within sample space and feature spaces for clustering. Furthermore, an alternating iteration algorithm is devised, and its convergence is thoroughly analyzed. Additionally, computational complexity is analyzed among comparison algorithms. The effectiveness of RDHNMTF is verified by benchmarking against ten cutting-edge algorithms across seven datasets corrupted with four types of noise.展开更多
Heterogeneous Information Networks(HINs)contain multiple types of nodes and edges;therefore,they can preserve the semantic information and structure information.Cluster analysis using an HIN has obvious advantages ove...Heterogeneous Information Networks(HINs)contain multiple types of nodes and edges;therefore,they can preserve the semantic information and structure information.Cluster analysis using an HIN has obvious advantages over a transformation into a homogenous information network,which can promote the clustering results of different types of nodes.In our study,we applied a Nonnegative Matrix Tri-Factorization(NMTF)in a cluster analysis of multiple metapaths in HIN.Unlike the parameter estimation method of the probability distribution in previous studies,NMTF can obtain several dependent latent variables simultaneously,and each latent variable in NMTF is associated with the cluster of the corresponding node in the HIN.The method is suited to co-clustering leveraging multiple metapaths in HIN,because NMTF is employed for multiple nonnegative matrix factorizations simultaneously in our study.Experimental results on the real dataset show that the validity and correctness of our method,and the clustering result are better than that of the existing similar clustering algorithm.展开更多
The World Wide Web generates more and more data with links and node contents,which are always modeled as attributed networks.The identification of network communities plays an important role for people to understand a...The World Wide Web generates more and more data with links and node contents,which are always modeled as attributed networks.The identification of network communities plays an important role for people to understand and utilize the semantic functions of the data.A few methods based on non-negative matrix factorization(NMF)have been proposed to detect community structure with semantic information in attributed networks.However,previous methods have not modeled some key factors(which affect the link generating process together),including prior information,the heterogeneity of node degree,as well as the interactions among communities.The three factors have been demonstrated to primarily affect the results.In this paper,we propose a semi-supervised community detection method on attributed networks by simultaneously considering these three factors.First,a semi-supervised non-negative matrix tri-factorization model with node popularity(i.e.,PSSNMTF)is designed to detect communities on the topology of the network.And then node contents are integrated into the PSSNMTF model to find the semantic communities more accurately,namely PSSNMTFC.Parameters of the PSSNMTFC model is estimated by using the gradient descent method.Experiments on some real and artificial networks illustrate that our new method is superior over some related stateof-the-art methods in terms of accuracy.展开更多
In this paper,we consider the maximal positive definite solution of the nonlinear matrix equation.By using the idea of Algorithm 2.1 in ZHANG(2013),a new inversion-free method with a stepsize parameter is proposed to ...In this paper,we consider the maximal positive definite solution of the nonlinear matrix equation.By using the idea of Algorithm 2.1 in ZHANG(2013),a new inversion-free method with a stepsize parameter is proposed to obtain the maximal positive definite solution of nonlinear matrix equation X+A^(*)X|^(-α)A=Q with the case 0<α≤1.Based on this method,a new iterative algorithm is developed,and its convergence proof is given.Finally,two numerical examples are provided to show the effectiveness of the proposed method.展开更多
Driven by advancements in mobile internet technology,images have become a crucial data medium.Ensuring the security of image information during transmission has thus emerged as an urgent challenge.This study proposes ...Driven by advancements in mobile internet technology,images have become a crucial data medium.Ensuring the security of image information during transmission has thus emerged as an urgent challenge.This study proposes a novel image encryption algorithm specifically designed for grayscale image security.This research introduces a new Cantor diagonal matrix permutation method.The proposed permutation method uses row and column index sequences to control the Cantor diagonal matrix,where the row and column index sequences are generated by a spatiotemporal chaotic system named coupled map lattice(CML).The high initial value sensitivity of the CML system makes the permutation method highly sensitive and secure.Additionally,leveraging fractal theory,this study introduces a chaotic fractal matrix and applies this matrix in the diffusion process.This chaotic fractal matrix exhibits selfsimilarity and irregularity.Using the Cantor diagonal matrix and chaotic fractal matrix,this paper introduces a fast image encryption algorithm involving two diffusion steps and one permutation step.Moreover,the algorithm achieves robust security with only a single encryption round,ensuring high operational efficiency.Experimental results show that the proposed algorithm features an expansive key space,robust security,high sensitivity,high efficiency,and superior statistical properties for the ciphered images.Thus,the proposed algorithm not only provides a practical solution for secure image transmission but also bridges fractal theory with image encryption techniques,thereby opening new research avenues in chaotic cryptography and advancing the development of information security technology.展开更多
We read with the great interest the study by Ababneh et al in which inducedmesenchymal stem cell-derived exosomes were shown to exhibit a stronger andmore sustained anti-proliferative effect by inducing a senescence-l...We read with the great interest the study by Ababneh et al in which inducedmesenchymal stem cell-derived exosomes were shown to exhibit a stronger andmore sustained anti-proliferative effect by inducing a senescence-like state withoutapoptosis.The results obtained by the authors highlight the features of theeffects of senescent drift induction in surrounding tissues.In the light of thesefindings,the role of the properties of extracellular matrix and cellular glycocalyxin responses of human tumors to therapy remain uninvestigated.These extracellularbarriers appear to be significant obstacles to effective cancer therapy,especiallyin relation to the use of unique properties of tumor microenvironment forthe immunotherapy-resistant cancer treatment.展开更多
Peripheral nerve injury causes severe neuroinflammation and has become a global medical challenge.Previous research has demonstrated that porcine decellularized nerve matrix hydrogel exhibits excellent biological prop...Peripheral nerve injury causes severe neuroinflammation and has become a global medical challenge.Previous research has demonstrated that porcine decellularized nerve matrix hydrogel exhibits excellent biological properties and tissue specificity,highlighting its potential as a biomedical material for the repair of severe peripheral nerve injury;however,its role in modulating neuroinflammation post-peripheral nerve injury remains unknown.Here,we aimed to characterize the anti-inflammatory properties of porcine decellularized nerve matrix hydrogel and their underlying molecular mechanisms.Using peripheral nerve injury model rats treated with porcine decellularized nerve matrix hydrogel,we evaluated structural and functional recovery,macrophage phenotype alteration,specific cytokine expression,and changes in related signaling molecules in vivo.Similar parameters were evaluated in vitro using monocyte/macrophage cell lines stimulated with lipopolysaccharide and cultured on porcine decellularized nerve matrix hydrogel-coated plates in complete medium.These comprehensive analyses revealed that porcine decellularized nerve matrix hydrogel attenuated the activation of excessive inflammation at the early stage of peripheral nerve injury and increased the proportion of the M2 subtype in monocytes/macrophages.Additionally,porcine decellularized nerve matrix hydrogel negatively regulated the Toll-like receptor 4/myeloid differentiation factor 88/nuclear factor-κB axis both in vivo and in vitro.Our findings suggest that the efficacious anti-inflammatory properties of porcine decellularized nerve matrix hydrogel induce M2 macrophage polarization via suppression of the Toll-like receptor 4/myeloid differentiation factor 88/nuclear factor-κB pathway,providing new insights into the therapeutic mechanism of porcine decellularized nerve matrix hydrogel in peripheral nerve injury.展开更多
Objectives:High-grade serous ovarian cancer(HGSOC),the most common subtype of epithelial ovarian cancer(EOC),exhibits a mesenchymal phenotype characterized by fibrotic stroma and poor prognosis.Human epididymis protei...Objectives:High-grade serous ovarian cancer(HGSOC),the most common subtype of epithelial ovarian cancer(EOC),exhibits a mesenchymal phenotype characterized by fibrotic stroma and poor prognosis.Human epididymis protein 4(HE4),a key diagnostic biomarker for ovarian cancer,is involved in fibrotic processes in several non-malignant diseases.Given the clinical significance of stromal fibrosis in HGSOC and the potential link between HE4 and fibrosis,this study aimed to investigate the role of HE4 in the formation of stromal fibrosis in HGSOC.Methods:A total of 126 patients with gynecological conditions were included and divided into normal,benign,and EOC groups.Tissue stiffness was quantitatively measured and analyzed for its correlation with clinicopathological features.We further investigated the correlation between tumor stiffness and the expression levels of HE4 and fibroblast activation markers(α-smooth muscle actin(α-SMA)and fibroblast activation protein(FAP))in tumor tissues from 22 HGSOC patients.In vitro,primary fibroblasts were treated with recombinant HE4(rHE4)or conditioned media from HE4-knockdown ovarian cancer cells to assess fibroblasts activation and matrix contractility(Collagen gel contraction assays).In vivo,a subcutaneous xenograft model using HE4-knockdown cells was established to evaluate the effects of HE4 suppression on tumor growth and extensive extracellular matrix(ECM)remodeling.Results:Ovarian cancer tissues showed significantly increased stiffness compared to benign/normal groups,showing positive correlation with serum HE4 levels.High-stiffness HGSOC tumors exhibited upregulated expression of HE4,α-SMA,FAP,and collagen I.rHE4 stimulated fibroblast activation and enhanced matrix contractility,whereas HE4 knockdown in cancer cells abrogated these pro-fibrotic effects.In vivo,HE4-silenced xenografts displayed restricted tumor growth accompanied by reduced stromal expression ofα-SMA,FAP,and collagen I.Conclusion:Our findings suggest that HE4 may facilitate ECM remodeling in HGSOC through promoting fibroblast activation and increasing collagen deposition.展开更多
Intestinal ischemia-reperfusion injury(IIRI)is a complex and severe pathophysiological process characterized by oxidative stress,inflammation,and apoptosis.In recent years,the critical roles of extracellular matrix(EC...Intestinal ischemia-reperfusion injury(IIRI)is a complex and severe pathophysiological process characterized by oxidative stress,inflammation,and apoptosis.In recent years,the critical roles of extracellular matrix(ECM)genes and microRNAs(miRNAs)in IIRI have garnered widespread attention.This review aims to systematically summarize the diagnostic and therapeutic potential of ECM gene sets and miRNA regulatory networks in IIRI.First,we review the molecular mechanisms of IIRI,focusing on the dual role of the ECM in tissue injury and repair processes.The expression changes and functions of ECM components such as collagen,elastin,and matrix metalloproteinases during IIRI progression are deeply analyzed.Second,we systematically summarize the regulatory roles of miRNAs in IIRI,particularly the mechanisms and functions of miRNAs such as miR-125b and miR-200a in regulating inflammation,apoptosis,and ECM remodeling.Additionally,this review discusses potential diagnostic biomarkers and treatment strategies based on ECM genes and miRNAs.We extensively evaluate the prospects of miRNA-targeted therapy and ECM component modulation in preventing and treating IIRI,emphasizing the clinical translational potential of these emerging therapies.In conclusion,the diagnostic and therapeutic potential of ECM gene sets and miRNA regulatory networks in IIRI provides new directions for further research,necessitating additional clinical and basic studies to validate and expand these findings for improving clinical outcomes in IIRI patients.展开更多
BACKGROUND One of the main characteristics of oral squamous cell carcinoma(OSCC)is that it metastasizes to cervical lymph nodes frequently with a high degree of local invasiveness.A primary feature of malignant tumors...BACKGROUND One of the main characteristics of oral squamous cell carcinoma(OSCC)is that it metastasizes to cervical lymph nodes frequently with a high degree of local invasiveness.A primary feature of malignant tumors is their penetration of neighboring tissues,such as lymphatic and blood arteries,due to the tumor cells'capacity to break down the extracellular matrix(ECM).Matrix metalloproteinases(MMPs)constitute a family of proteolytic enzymes that facilitate tissue remodeling and the degradation of the ECM.MMP-9 and MMP-13 belong to the group of extracellular matrix degrading enzymes and their expression has been studied in OSCC because of their specific functions.MMP-13,a collagenase family member,is thought to play an essential role in the MMP activation cascade by breaking down the fibrillar collagens,whereas MMP-9 is thought to accelerate the growth of tumors.Elevated MMP-13 expression has been associated with tumor behavior and patient prognosis in a number of malignant cases.AIM To assess the immunohistochemical expression of MMP-9 and MMP-13 in OSCC.METHODS A total of 40 cases with histologically confirmed OSCC by incisional biopsy were included in this cross-sectional retrospective study.The protocols for both MMP-9 and MMP-13 immunohistochemical staining were performed according to the manufacturer’s recommendations along with the normal gingival epithelium as a positive control.All the observations were recorded and Pearson’sχ²test with Fisher exact test was used for statistical analysis.RESULTS Our study showed no significant correlation between MMP-9 and MMP-13 staining intensity and tumor size.The majority of the patients were in advanced TNM stages(III and IV),and showed intense expression of MMP-9 and MMP-13.CONCLUSION The present study suggests that both MMP-9 and MMP-13 play an important and independent role in OSCC progression and invasiveness.Intense expression of MMP-9 and MMP-13,irrespective of histological grade of OSCC,correlates well with TNM stage.Consequently,it is evident that MMP-9 and MMP-13 are important for the invasiveness and progression of tumors.The findings may facilitate the development of new approaches for evaluating lymph node metastases and interventional therapy techniques,hence enhancing the prognosis of patients diagnosed with OSCC.展开更多
The brain's extracellular matrix(ECM),which is comprised of protein and glycosaminoglycan(GAG)scaffolds,constitutes 20%-40% of the human brain and is considered one of the largest influencers on brain cell functio...The brain's extracellular matrix(ECM),which is comprised of protein and glycosaminoglycan(GAG)scaffolds,constitutes 20%-40% of the human brain and is considered one of the largest influencers on brain cell functioning(Soles et al.,2023).Synthesized by neural and glial cells,the brain's ECM regulates a myriad of homeostatic cellular processes,including neuronal plasticity and firing(Miyata et al.,2012),cation buffering(Moraws ki et al.,2015),and glia-neuron interactions(Anderson et al.,2016).Considering the diversity of functions,dynamic remodeling of the brain's ECM indicates that this understudied medium is an active participant in both normal physiology and neurological diseases.展开更多
Increased matrix stiffness of nucleus pulposus(NP)tissue is a main feature of intervertebral disc degeneration(IVDD)and affects various functions of nucleus pulposus cells(NPCs).Glycolysis is the main energy source fo...Increased matrix stiffness of nucleus pulposus(NP)tissue is a main feature of intervertebral disc degeneration(IVDD)and affects various functions of nucleus pulposus cells(NPCs).Glycolysis is the main energy source for NPC survival,but the effects and underlying mechanisms of increased extracellular matrix(ECM)stiffness on NPC glycolysis remain unknown.In this study,hydrogels with different stiffness were established to mimic the mechanical environment of NPCs.Notably,increased matrix stiffness in degenerated NP tissues from IVDD patients was accompanied with impaired glycolysis,and NPCs cultured on rigid substrates exhibited a reduction in glycolysis.展开更多
Quantum dot(QD)-based infrared photodetector is a promising technology that can implement current monitoring,imaging and optical communication in the infrared region. However, the photodetection performance of self-po...Quantum dot(QD)-based infrared photodetector is a promising technology that can implement current monitoring,imaging and optical communication in the infrared region. However, the photodetection performance of self-powered QD devices is still limited by their unfavorable charge carrier dynamics due to their intrinsically discrete charge carrier transport process. Herein, we strategically constructed semiconducting matrix in QD film to achieve efficient charge transfer and extraction.The p-type semiconducting CuSCN was selected as energy-aligned matrix to match the n-type colloidal PbS QDs that was used as proof-of-concept. Note that the PbS QD/CuSCN matrix not only enables efficient charge carrier separation and transfer at nano-interfaces but also provides continuous charge carrier transport pathways that are different from the hoping process in neat QD film, resulting in improved charge mobility and derived collection efficiency. As a result, the target structure delivers high specific detectivity of 4.38 × 10^(12)Jones and responsivity of 782 mA/W at 808 nm, which is superior than that of the PbS QD-only photodetector(4.66 × 10^(11)Jones and 338 mA/W). This work provides a new structure candidate for efficient colloidal QD based optoelectronic devices.展开更多
Neuronal growth, extension, branching, and formation of neural networks are markedly influenced by the extracellular matrix—a complex network composed of proteins and carbohydrates secreted by cells. In addition to p...Neuronal growth, extension, branching, and formation of neural networks are markedly influenced by the extracellular matrix—a complex network composed of proteins and carbohydrates secreted by cells. In addition to providing physical support for cells, the extracellular matrix also conveys critical mechanical stiffness cues. During the development of the nervous system, extracellular matrix stiffness plays a central role in guiding neuronal growth, particularly in the context of axonal extension, which is crucial for the formation of neural networks. In neural tissue engineering, manipulation of biomaterial stiffness is a promising strategy to provide a permissive environment for the repair and regeneration of injured nervous tissue. Recent research has fine-tuned synthetic biomaterials to fabricate scaffolds that closely replicate the stiffness profiles observed in the nervous system. In this review, we highlight the molecular mechanisms by which extracellular matrix stiffness regulates axonal growth and regeneration. We highlight the progress made in the development of stiffness-tunable biomaterials to emulate in vivo extracellular matrix environments, with an emphasis on their application in neural repair and regeneration, along with a discussion of the current limitations and future prospects. The exploration and optimization of the stiffness-tunable biomaterials has the potential to markedly advance the development of neural tissue engineering.展开更多
This paper studies the problem of the spectral radius of the uniform hypergraph determined by the signless Laplacian matrix.The upper bound of the spectral radius of a uniform hypergraph is obtained by using Rayleigh ...This paper studies the problem of the spectral radius of the uniform hypergraph determined by the signless Laplacian matrix.The upper bound of the spectral radius of a uniform hypergraph is obtained by using Rayleigh principle and the perturbation of the spectral radius under moving the edge operation,and the extremal hypergraphs are characterized for both supertree and unicyclic hypergraphs.The spectral radius of the graph is generalized.展开更多
Mixed matrix membranes(MMMs)have demonstrated significant promise in energy-intensive gas separations by amalgamating the unique properties of fillers with the facile processability of polymers.However,achieving a sim...Mixed matrix membranes(MMMs)have demonstrated significant promise in energy-intensive gas separations by amalgamating the unique properties of fillers with the facile processability of polymers.However,achieving a simultaneous enhancement of permeability and selectivity remains a formidable challenge,due to the difficulty of achieving an optimal match between polymers and fillers.In this study,we incorporate a porous carbon-based zinc oxide composite(C@ZnO)into high-permeability polymers of intrinsic microporosity(PIMs)to fabricate MMMs.The dipole–dipole interaction between C@ZnO and PIMs ensures their exceptional compatibility,mitigating the formation of non-selective voids in the resulting MMMs.Concurrently,C@ZnO with abundant interconnected pores can provide additional low-resistance pathways for gas transport in MMMs.As a result,the CO_(2) permeability of the optimized C@ZnO/PIM-1 MMMs is elevated to 13,215 barrer,while the CO_(2)/N_(2) and CO_(2)/CH_(4) selectivity reached 21.5 and 14.4,respectively,substantially surpassing the 2008 Robeson upper bound.Additionally,molecular simulation results further corroborate that the augmented membrane gas selectivity is attributed to the superior CO_(2) affinity of C@ZnO.In summary,we believe that this work not only expands the application of MMMs for gas separation but also heralds a paradigm shift in the application of porous carbon materials.展开更多
Analysis and design of linear periodic control systems are closely related to the periodic matrix equations.The biconjugate residual method(BCR for short)have been introduced by Vespucci and Broyden for efficiently so...Analysis and design of linear periodic control systems are closely related to the periodic matrix equations.The biconjugate residual method(BCR for short)have been introduced by Vespucci and Broyden for efficiently solving linear systems Aα=b.The objective of this paper is to provide one new iterative algorithm based on BCR method to find the symmetric periodic solutions of linear periodic matrix equations.This kind of periodic matrix equations has not been dealt with yet.This iterative method is guaranteed to converge in a finite number of steps in the absence of round-off errors.Some numerical results are performed to illustrate the efficiency and feasibility of new method.展开更多
Capacitive voltage transformers (CVTs) are essential in high-voltage systems. An accurate error assessment is crucial for precise energy metering. However, tracking real-time quantitative changes in capacitive voltage...Capacitive voltage transformers (CVTs) are essential in high-voltage systems. An accurate error assessment is crucial for precise energy metering. However, tracking real-time quantitative changes in capacitive voltage transformer errors, particularly minor variations in multi-channel setups, remains challenging. This paper proposes a method for online error tracking of multi-channel capacitive voltage transformers using a Co-Prediction Matrix. The approach leverages the strong correlation between in-phase channels, particularly the invariance of the signal proportions among them. By establishing a co-prediction matrix based on these proportional relationships, The influence of voltage changes on the primary measurements is mitigated. Analyzing the relationships between the co-prediction matrices over time allows for inferring true measurement errors. Experimental validation with real-world data confirms the effectiveness of the method, demonstrating its capability to continuously track capacitive voltage transformer measurement errors online with precision over extended durations.展开更多
基金supported by the National Natural Science Foundation of China(No.62003281)the Natural Science Foundation of Chongqing,China(No.cstc2021jcyjmsxmX1169)the Science and Technology Research Program of Chongqing Municipal Education Commission(No.KJQN202200207).
文摘Non-negative Matrix Factorization (NMF) has been an ideal tool for machine learning. Non-negative Matrix Tri-Factorization (NMTF) is a generalization of NMF that incorporates a third non-negative factorization matrix, and has shown impressive clustering performance by imposing simultaneous orthogonality constraints on both sample and feature spaces. However, the performance of NMTF dramatically degrades if the data are contaminated with noises and outliers. Furthermore, the high-order geometric information is rarely considered. In this paper, a Robust NMTF with Dual Hyper-graph regularization (namely RDHNMTF) is introduced. Firstly, to enhance the robustness of NMTF, an improvement is made by utilizing the l_(2,1)-norm to evaluate the reconstruction error. Secondly, a dual hyper-graph is established to uncover the higher-order inherent information within sample space and feature spaces for clustering. Furthermore, an alternating iteration algorithm is devised, and its convergence is thoroughly analyzed. Additionally, computational complexity is analyzed among comparison algorithms. The effectiveness of RDHNMTF is verified by benchmarking against ten cutting-edge algorithms across seven datasets corrupted with four types of noise.
基金supported in part by the National Natural Science Foundation of China(No.61701190)the Youth Science Foundation of Jilin Province of China(No.20180520021JH)+4 种基金the National Key Research and Development Plan of China(No.2017YFA0604500)the Key Scientific and Technological Research and Development Plan of Jilin Province of China(No.20180201103GX)the China Postdoctoral Science Foundation(No.2018M631873)the Project of Jilin Province Development and Reform Commission(No.2019FGWTZC001)the Key Technology Innovation Cooperation Project of Government and University for the Whole Industry Demonstration(No.SXGJSF2017-4)。
文摘Heterogeneous Information Networks(HINs)contain multiple types of nodes and edges;therefore,they can preserve the semantic information and structure information.Cluster analysis using an HIN has obvious advantages over a transformation into a homogenous information network,which can promote the clustering results of different types of nodes.In our study,we applied a Nonnegative Matrix Tri-Factorization(NMTF)in a cluster analysis of multiple metapaths in HIN.Unlike the parameter estimation method of the probability distribution in previous studies,NMTF can obtain several dependent latent variables simultaneously,and each latent variable in NMTF is associated with the cluster of the corresponding node in the HIN.The method is suited to co-clustering leveraging multiple metapaths in HIN,because NMTF is employed for multiple nonnegative matrix factorizations simultaneously in our study.Experimental results on the real dataset show that the validity and correctness of our method,and the clustering result are better than that of the existing similar clustering algorithm.
基金This work was partly supported by the National Natural Science Foundation of China(Grant Nos.61876128,61772361)the National Science Foundation of Hebei(F2019403070)the science and technology research project for universities of Hebei(ZD2020175).
文摘The World Wide Web generates more and more data with links and node contents,which are always modeled as attributed networks.The identification of network communities plays an important role for people to understand and utilize the semantic functions of the data.A few methods based on non-negative matrix factorization(NMF)have been proposed to detect community structure with semantic information in attributed networks.However,previous methods have not modeled some key factors(which affect the link generating process together),including prior information,the heterogeneity of node degree,as well as the interactions among communities.The three factors have been demonstrated to primarily affect the results.In this paper,we propose a semi-supervised community detection method on attributed networks by simultaneously considering these three factors.First,a semi-supervised non-negative matrix tri-factorization model with node popularity(i.e.,PSSNMTF)is designed to detect communities on the topology of the network.And then node contents are integrated into the PSSNMTF model to find the semantic communities more accurately,namely PSSNMTFC.Parameters of the PSSNMTFC model is estimated by using the gradient descent method.Experiments on some real and artificial networks illustrate that our new method is superior over some related stateof-the-art methods in terms of accuracy.
基金Supported in part by Natural Science Foundation of Guangxi(2023GXNSFAA026246)in part by the Central Government's Guide to Local Science and Technology Development Fund(GuikeZY23055044)in part by the National Natural Science Foundation of China(62363003)。
文摘In this paper,we consider the maximal positive definite solution of the nonlinear matrix equation.By using the idea of Algorithm 2.1 in ZHANG(2013),a new inversion-free method with a stepsize parameter is proposed to obtain the maximal positive definite solution of nonlinear matrix equation X+A^(*)X|^(-α)A=Q with the case 0<α≤1.Based on this method,a new iterative algorithm is developed,and its convergence proof is given.Finally,two numerical examples are provided to show the effectiveness of the proposed method.
基金supported by the National Natural Science Foundation of China(62376106)The Science and Technology Development Plan of Jilin Province(20250102212JC).
文摘Driven by advancements in mobile internet technology,images have become a crucial data medium.Ensuring the security of image information during transmission has thus emerged as an urgent challenge.This study proposes a novel image encryption algorithm specifically designed for grayscale image security.This research introduces a new Cantor diagonal matrix permutation method.The proposed permutation method uses row and column index sequences to control the Cantor diagonal matrix,where the row and column index sequences are generated by a spatiotemporal chaotic system named coupled map lattice(CML).The high initial value sensitivity of the CML system makes the permutation method highly sensitive and secure.Additionally,leveraging fractal theory,this study introduces a chaotic fractal matrix and applies this matrix in the diffusion process.This chaotic fractal matrix exhibits selfsimilarity and irregularity.Using the Cantor diagonal matrix and chaotic fractal matrix,this paper introduces a fast image encryption algorithm involving two diffusion steps and one permutation step.Moreover,the algorithm achieves robust security with only a single encryption round,ensuring high operational efficiency.Experimental results show that the proposed algorithm features an expansive key space,robust security,high sensitivity,high efficiency,and superior statistical properties for the ciphered images.Thus,the proposed algorithm not only provides a practical solution for secure image transmission but also bridges fractal theory with image encryption techniques,thereby opening new research avenues in chaotic cryptography and advancing the development of information security technology.
文摘We read with the great interest the study by Ababneh et al in which inducedmesenchymal stem cell-derived exosomes were shown to exhibit a stronger andmore sustained anti-proliferative effect by inducing a senescence-like state withoutapoptosis.The results obtained by the authors highlight the features of theeffects of senescent drift induction in surrounding tissues.In the light of thesefindings,the role of the properties of extracellular matrix and cellular glycocalyxin responses of human tumors to therapy remain uninvestigated.These extracellularbarriers appear to be significant obstacles to effective cancer therapy,especiallyin relation to the use of unique properties of tumor microenvironment forthe immunotherapy-resistant cancer treatment.
基金supported by the Shenzhen Hong Kong Joint Funding Project,No.SGDX20230116093645007(to LY)the Shenzhen Science and Technology Innovation Committee International Cooperation Project,No.GJHZ20200731095608025(to LY)+7 种基金Shenzhen Development and Reform Commission’s Intelligent Diagnosis,Treatment and Prevention of Adolescent Spinal Health Public Service Platform,No.S2002Q84500835(to LY)Shenzhen Medical Research Fund,No.B2303005(to LY)Team-based Medical Science Research Program,No.2024YZZ02(to LY)Zhejiang Provincial Natural Science Foundation of China,No.LWQ20H170001(to RL)Basic Research Project of Shenzhen Science and Technology from Shenzhen Science and Technology Innovation Commission,No.JCYJ20210324103010029(to BY)Shenzhen Second People’s Hospital Clinical Research Fund of Guangdong Province High-level Hospital Construction Project,Nos.2023yjlcyj029(to BY),2023yjlcyj021(to LL)Guangdong Basic and Applied Basic Research Foundation,No.2022A1515110679(to LL)China Postdoctoral Science Foundation,No.2022M722203(to GL).
文摘Peripheral nerve injury causes severe neuroinflammation and has become a global medical challenge.Previous research has demonstrated that porcine decellularized nerve matrix hydrogel exhibits excellent biological properties and tissue specificity,highlighting its potential as a biomedical material for the repair of severe peripheral nerve injury;however,its role in modulating neuroinflammation post-peripheral nerve injury remains unknown.Here,we aimed to characterize the anti-inflammatory properties of porcine decellularized nerve matrix hydrogel and their underlying molecular mechanisms.Using peripheral nerve injury model rats treated with porcine decellularized nerve matrix hydrogel,we evaluated structural and functional recovery,macrophage phenotype alteration,specific cytokine expression,and changes in related signaling molecules in vivo.Similar parameters were evaluated in vitro using monocyte/macrophage cell lines stimulated with lipopolysaccharide and cultured on porcine decellularized nerve matrix hydrogel-coated plates in complete medium.These comprehensive analyses revealed that porcine decellularized nerve matrix hydrogel attenuated the activation of excessive inflammation at the early stage of peripheral nerve injury and increased the proportion of the M2 subtype in monocytes/macrophages.Additionally,porcine decellularized nerve matrix hydrogel negatively regulated the Toll-like receptor 4/myeloid differentiation factor 88/nuclear factor-κB axis both in vivo and in vitro.Our findings suggest that the efficacious anti-inflammatory properties of porcine decellularized nerve matrix hydrogel induce M2 macrophage polarization via suppression of the Toll-like receptor 4/myeloid differentiation factor 88/nuclear factor-κB pathway,providing new insights into the therapeutic mechanism of porcine decellularized nerve matrix hydrogel in peripheral nerve injury.
文摘Objectives:High-grade serous ovarian cancer(HGSOC),the most common subtype of epithelial ovarian cancer(EOC),exhibits a mesenchymal phenotype characterized by fibrotic stroma and poor prognosis.Human epididymis protein 4(HE4),a key diagnostic biomarker for ovarian cancer,is involved in fibrotic processes in several non-malignant diseases.Given the clinical significance of stromal fibrosis in HGSOC and the potential link between HE4 and fibrosis,this study aimed to investigate the role of HE4 in the formation of stromal fibrosis in HGSOC.Methods:A total of 126 patients with gynecological conditions were included and divided into normal,benign,and EOC groups.Tissue stiffness was quantitatively measured and analyzed for its correlation with clinicopathological features.We further investigated the correlation between tumor stiffness and the expression levels of HE4 and fibroblast activation markers(α-smooth muscle actin(α-SMA)and fibroblast activation protein(FAP))in tumor tissues from 22 HGSOC patients.In vitro,primary fibroblasts were treated with recombinant HE4(rHE4)or conditioned media from HE4-knockdown ovarian cancer cells to assess fibroblasts activation and matrix contractility(Collagen gel contraction assays).In vivo,a subcutaneous xenograft model using HE4-knockdown cells was established to evaluate the effects of HE4 suppression on tumor growth and extensive extracellular matrix(ECM)remodeling.Results:Ovarian cancer tissues showed significantly increased stiffness compared to benign/normal groups,showing positive correlation with serum HE4 levels.High-stiffness HGSOC tumors exhibited upregulated expression of HE4,α-SMA,FAP,and collagen I.rHE4 stimulated fibroblast activation and enhanced matrix contractility,whereas HE4 knockdown in cancer cells abrogated these pro-fibrotic effects.In vivo,HE4-silenced xenografts displayed restricted tumor growth accompanied by reduced stromal expression ofα-SMA,FAP,and collagen I.Conclusion:Our findings suggest that HE4 may facilitate ECM remodeling in HGSOC through promoting fibroblast activation and increasing collagen deposition.
基金Supported by Health Science and Technology Programme of Zhejiang Province,No.2022KY1391.
文摘Intestinal ischemia-reperfusion injury(IIRI)is a complex and severe pathophysiological process characterized by oxidative stress,inflammation,and apoptosis.In recent years,the critical roles of extracellular matrix(ECM)genes and microRNAs(miRNAs)in IIRI have garnered widespread attention.This review aims to systematically summarize the diagnostic and therapeutic potential of ECM gene sets and miRNA regulatory networks in IIRI.First,we review the molecular mechanisms of IIRI,focusing on the dual role of the ECM in tissue injury and repair processes.The expression changes and functions of ECM components such as collagen,elastin,and matrix metalloproteinases during IIRI progression are deeply analyzed.Second,we systematically summarize the regulatory roles of miRNAs in IIRI,particularly the mechanisms and functions of miRNAs such as miR-125b and miR-200a in regulating inflammation,apoptosis,and ECM remodeling.Additionally,this review discusses potential diagnostic biomarkers and treatment strategies based on ECM genes and miRNAs.We extensively evaluate the prospects of miRNA-targeted therapy and ECM component modulation in preventing and treating IIRI,emphasizing the clinical translational potential of these emerging therapies.In conclusion,the diagnostic and therapeutic potential of ECM gene sets and miRNA regulatory networks in IIRI provides new directions for further research,necessitating additional clinical and basic studies to validate and expand these findings for improving clinical outcomes in IIRI patients.
文摘BACKGROUND One of the main characteristics of oral squamous cell carcinoma(OSCC)is that it metastasizes to cervical lymph nodes frequently with a high degree of local invasiveness.A primary feature of malignant tumors is their penetration of neighboring tissues,such as lymphatic and blood arteries,due to the tumor cells'capacity to break down the extracellular matrix(ECM).Matrix metalloproteinases(MMPs)constitute a family of proteolytic enzymes that facilitate tissue remodeling and the degradation of the ECM.MMP-9 and MMP-13 belong to the group of extracellular matrix degrading enzymes and their expression has been studied in OSCC because of their specific functions.MMP-13,a collagenase family member,is thought to play an essential role in the MMP activation cascade by breaking down the fibrillar collagens,whereas MMP-9 is thought to accelerate the growth of tumors.Elevated MMP-13 expression has been associated with tumor behavior and patient prognosis in a number of malignant cases.AIM To assess the immunohistochemical expression of MMP-9 and MMP-13 in OSCC.METHODS A total of 40 cases with histologically confirmed OSCC by incisional biopsy were included in this cross-sectional retrospective study.The protocols for both MMP-9 and MMP-13 immunohistochemical staining were performed according to the manufacturer’s recommendations along with the normal gingival epithelium as a positive control.All the observations were recorded and Pearson’sχ²test with Fisher exact test was used for statistical analysis.RESULTS Our study showed no significant correlation between MMP-9 and MMP-13 staining intensity and tumor size.The majority of the patients were in advanced TNM stages(III and IV),and showed intense expression of MMP-9 and MMP-13.CONCLUSION The present study suggests that both MMP-9 and MMP-13 play an important and independent role in OSCC progression and invasiveness.Intense expression of MMP-9 and MMP-13,irrespective of histological grade of OSCC,correlates well with TNM stage.Consequently,it is evident that MMP-9 and MMP-13 are important for the invasiveness and progression of tumors.The findings may facilitate the development of new approaches for evaluating lymph node metastases and interventional therapy techniques,hence enhancing the prognosis of patients diagnosed with OSCC.
基金supported by National Institute on Aging(NIH-NIA)R21 AG074152(to KMA)National Institute of Allergy and Infectious Diseases(NIAID)grant DP2 AI171150(to KMA)Department of Defense(DoD)grant AZ210089(to KMA)。
文摘The brain's extracellular matrix(ECM),which is comprised of protein and glycosaminoglycan(GAG)scaffolds,constitutes 20%-40% of the human brain and is considered one of the largest influencers on brain cell functioning(Soles et al.,2023).Synthesized by neural and glial cells,the brain's ECM regulates a myriad of homeostatic cellular processes,including neuronal plasticity and firing(Miyata et al.,2012),cation buffering(Moraws ki et al.,2015),and glia-neuron interactions(Anderson et al.,2016).Considering the diversity of functions,dynamic remodeling of the brain's ECM indicates that this understudied medium is an active participant in both normal physiology and neurological diseases.
基金supported by the National Nature Science Foundation of China(No.82002345 to J.D and 81902179 to L.S)the Gusu Talent Program(No.Qngg2022008 and GSWS2021027 to J.D)the Preliminary Research Project of the Second Affiliated Hospital of Soochow University(No.SDFEYBS1905 to J.D).
文摘Increased matrix stiffness of nucleus pulposus(NP)tissue is a main feature of intervertebral disc degeneration(IVDD)and affects various functions of nucleus pulposus cells(NPCs).Glycolysis is the main energy source for NPC survival,but the effects and underlying mechanisms of increased extracellular matrix(ECM)stiffness on NPC glycolysis remain unknown.In this study,hydrogels with different stiffness were established to mimic the mechanical environment of NPCs.Notably,increased matrix stiffness in degenerated NP tissues from IVDD patients was accompanied with impaired glycolysis,and NPCs cultured on rigid substrates exhibited a reduction in glycolysis.
基金supported by the National Natural Science Foundation of China (No. 62204079)the Science and Technology Development Project of Henan Province (Nos.202300410048, 202300410057)+2 种基金the China Postdoctoral Science Foundation (No. 2022M711037)the Intelligence Introduction Plan of Henan Province in 2021 (No. CXJD2021008)Henan University Fund。
文摘Quantum dot(QD)-based infrared photodetector is a promising technology that can implement current monitoring,imaging and optical communication in the infrared region. However, the photodetection performance of self-powered QD devices is still limited by their unfavorable charge carrier dynamics due to their intrinsically discrete charge carrier transport process. Herein, we strategically constructed semiconducting matrix in QD film to achieve efficient charge transfer and extraction.The p-type semiconducting CuSCN was selected as energy-aligned matrix to match the n-type colloidal PbS QDs that was used as proof-of-concept. Note that the PbS QD/CuSCN matrix not only enables efficient charge carrier separation and transfer at nano-interfaces but also provides continuous charge carrier transport pathways that are different from the hoping process in neat QD film, resulting in improved charge mobility and derived collection efficiency. As a result, the target structure delivers high specific detectivity of 4.38 × 10^(12)Jones and responsivity of 782 mA/W at 808 nm, which is superior than that of the PbS QD-only photodetector(4.66 × 10^(11)Jones and 338 mA/W). This work provides a new structure candidate for efficient colloidal QD based optoelectronic devices.
基金supported by the Natio`nal Natural Science Foundation of China,No. 81801241a grant from Sichuan Science and Technology Program,No. 2023NSFSC1578Scientific Research Projects of Southwest Medical University,No. 2022ZD002 (all to JX)。
文摘Neuronal growth, extension, branching, and formation of neural networks are markedly influenced by the extracellular matrix—a complex network composed of proteins and carbohydrates secreted by cells. In addition to providing physical support for cells, the extracellular matrix also conveys critical mechanical stiffness cues. During the development of the nervous system, extracellular matrix stiffness plays a central role in guiding neuronal growth, particularly in the context of axonal extension, which is crucial for the formation of neural networks. In neural tissue engineering, manipulation of biomaterial stiffness is a promising strategy to provide a permissive environment for the repair and regeneration of injured nervous tissue. Recent research has fine-tuned synthetic biomaterials to fabricate scaffolds that closely replicate the stiffness profiles observed in the nervous system. In this review, we highlight the molecular mechanisms by which extracellular matrix stiffness regulates axonal growth and regeneration. We highlight the progress made in the development of stiffness-tunable biomaterials to emulate in vivo extracellular matrix environments, with an emphasis on their application in neural repair and regeneration, along with a discussion of the current limitations and future prospects. The exploration and optimization of the stiffness-tunable biomaterials has the potential to markedly advance the development of neural tissue engineering.
基金Supported by Natural Science Foundation of HuBei Province(2022CFB299).
文摘This paper studies the problem of the spectral radius of the uniform hypergraph determined by the signless Laplacian matrix.The upper bound of the spectral radius of a uniform hypergraph is obtained by using Rayleigh principle and the perturbation of the spectral radius under moving the edge operation,and the extremal hypergraphs are characterized for both supertree and unicyclic hypergraphs.The spectral radius of the graph is generalized.
基金financial support from the National Natural Science Foundation of China(Nos.22108258 and 52003251)Program for Science&Technology Innovation Talents in Universities of Henan Province(24HASTIT004)+1 种基金Outstanding Youth Fund of Henan Scientific Committee(222300420085)Science and Technology Joint Project of Henan Province(222301420041)。
文摘Mixed matrix membranes(MMMs)have demonstrated significant promise in energy-intensive gas separations by amalgamating the unique properties of fillers with the facile processability of polymers.However,achieving a simultaneous enhancement of permeability and selectivity remains a formidable challenge,due to the difficulty of achieving an optimal match between polymers and fillers.In this study,we incorporate a porous carbon-based zinc oxide composite(C@ZnO)into high-permeability polymers of intrinsic microporosity(PIMs)to fabricate MMMs.The dipole–dipole interaction between C@ZnO and PIMs ensures their exceptional compatibility,mitigating the formation of non-selective voids in the resulting MMMs.Concurrently,C@ZnO with abundant interconnected pores can provide additional low-resistance pathways for gas transport in MMMs.As a result,the CO_(2) permeability of the optimized C@ZnO/PIM-1 MMMs is elevated to 13,215 barrer,while the CO_(2)/N_(2) and CO_(2)/CH_(4) selectivity reached 21.5 and 14.4,respectively,substantially surpassing the 2008 Robeson upper bound.Additionally,molecular simulation results further corroborate that the augmented membrane gas selectivity is attributed to the superior CO_(2) affinity of C@ZnO.In summary,we believe that this work not only expands the application of MMMs for gas separation but also heralds a paradigm shift in the application of porous carbon materials.
基金Supported by NSFC (No.12371378)NSF of Fujian Province (Nos.2024J01980,2023J01955)。
文摘Analysis and design of linear periodic control systems are closely related to the periodic matrix equations.The biconjugate residual method(BCR for short)have been introduced by Vespucci and Broyden for efficiently solving linear systems Aα=b.The objective of this paper is to provide one new iterative algorithm based on BCR method to find the symmetric periodic solutions of linear periodic matrix equations.This kind of periodic matrix equations has not been dealt with yet.This iterative method is guaranteed to converge in a finite number of steps in the absence of round-off errors.Some numerical results are performed to illustrate the efficiency and feasibility of new method.
文摘Capacitive voltage transformers (CVTs) are essential in high-voltage systems. An accurate error assessment is crucial for precise energy metering. However, tracking real-time quantitative changes in capacitive voltage transformer errors, particularly minor variations in multi-channel setups, remains challenging. This paper proposes a method for online error tracking of multi-channel capacitive voltage transformers using a Co-Prediction Matrix. The approach leverages the strong correlation between in-phase channels, particularly the invariance of the signal proportions among them. By establishing a co-prediction matrix based on these proportional relationships, The influence of voltage changes on the primary measurements is mitigated. Analyzing the relationships between the co-prediction matrices over time allows for inferring true measurement errors. Experimental validation with real-world data confirms the effectiveness of the method, demonstrating its capability to continuously track capacitive voltage transformer measurement errors online with precision over extended durations.
