Immunohistochemical expression of matrix metalloproteinase-9 and 13 in oral squamous cell carcinoma and their role in predicting lymph node metastasis

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 remo-deling 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.The authors wish to thank Jadhav KB for his valuable opinion during the preparation of the manuscript.

Health risk assessment of trace metal(loid)s in agricultural soils based on Monte Carlo simulation coupled with positive matrix factorization model in Chongqing, southwest China

This study aimed to investigate the pollution characteristics, source apportionment, and health risks associated with trace metal(loid)s(TMs) in the major agricultural producing areas in Chongqing, China. We analyzed the source apportionment and assessed the health risk of TMs in agricultural soils by using positive matrix factorization(PMF) model and health risk assessment(HRA) model based on Monte Carlo simulation. Meanwhile, we combined PMF and HRA models to explore the health risks of TMs in agricultural soils by different pollution sources to determine the priority control factors. Results showed that the average contents of cadmium(Cd), arsenic (As), lead(Pb), chromium(Cr), copper(Cu), nickel(Ni), and zinc(Zn) in the soil were found to be 0.26, 5.93, 27.14, 61.32, 23.81, 32.45, and 78.65 mg/kg, respectively. Spatial analysis and source apportionment analysis revealed that urban and industrial sources, agricultural sources, and natural sources accounted for 33.0%, 27.7%, and 39.3% of TM accumulation in the soil, respectively. In the HRA model based on Monte Carlo simulation, noncarcinogenic risks were deemed negligible(hazard index <1), the carcinogenic risks were at acceptable level(10^(-6)<total carcinogenic risk ≤ 10^(-4)), with higher risks observed for children compared to adults. The relationship between TMs, their sources, and health risks indicated that urban and industrial sources were primarily associated with As, contributing to 75.1% of carcinogenic risks and 55.7% of non-carcinogenic risks, making them the primary control factors. Meanwhile, agricultural sources were primarily linked to Cd and Pb, contributing to 13.1% of carcinogenic risks and 21.8% of non-carcinogenic risks, designating them as secondary control factors.

High quality repair of osteochondral defects in rats using the extracellular matrix of antler stem cells

BACKGROUND Cartilage defects are some of the most common causes of arthritis.Cartilage lesions caused by inflammation,trauma or degenerative disease normally result in osteochondral defects.Previous studies have shown that decellularized extracellular matrix(ECM)derived from autologous,allogenic,or xenogeneic mesenchymal stromal cells(MSCs)can effectively restore osteochondral integrity.AIM To determine whether the decellularized ECM of antler reserve mesenchymal cells(RMCs),a xenogeneic material from antler stem cells,is superior to the currently available treatments for osteochondral defects.METHODS We isolated the RMCs from a 60-d-old sika deer antler and cultured them in vitro to 70%confluence;50 mg/mL L-ascorbic acid was then added to the medium to stimulate ECM deposition.Decellularized sheets of adipocyte-derived MSCs(aMSCs)and antlerogenic periosteal cells(another type of antler stem cells)were used as the controls.Three weeks after ascorbic acid stimulation,the ECM sheets were harvested and applied to the osteochondral defects in rat knee joints.RESULTS The defects were successfully repaired by applying the ECM-sheets.The highest quality of repair was achieved in the RMC-ECM group both in vitro(including cell attachment and proliferation),and in vivo(including the simultaneous regeneration of well-vascularized subchondral bone and avascular articular hyaline cartilage integrated with surrounding native tissues).Notably,the antler-stem-cell-derived ECM(xenogeneic)performed better than the aMSC-ECM(allogenic),while the ECM of the active antler stem cells was superior to that of the quiescent antler stem cells.CONCLUSION Decellularized xenogeneic ECM derived from the antler stem cell,particularly the active form(RMC-ECM),can achieve high quality repair/reconstruction of osteochondral defects,suggesting that selection of decellularized ECM for such repair should be focused more on bioactivity rather than kinship.

Matrix Riccati Equations in Optimal Control

In this paper, the matrix Riccati equation is considered. There is no general way for solving the matrix Riccati equation despite the many fields to which it applies. While scalar Riccati equation has been studied thoroughly, matrix Riccati equation of which scalar Riccati equations is a particular case, is much less investigated. This article proposes a change of variable that allows to find explicit solution of the Matrix Riccati equation. We then apply this solution to Optimal Control.

Collaborative Optimization of a Matrix Manufacturing System Based on Overall Equipment Effectiveness

When several traditional flow-shop lines operate in parallel,the operation mode with no communication between production lines will no longer be the optimal production paradigm.This paper describes matrix manufacturing systems(MMS)in a general manner from the perspective of related works,comparing different manufacturing organizational forms and their characteristics.Subsequently,MMS are extracted during the parallel production of multiple surface mount technology(SMT)lines.An overall equipment effectiveness(OEE)online calculation model and a collaborative optimization method are proposed based on the OEE of the MMS.The innovative idea of this study is to divide existing multiple parallel SMT lines into MMS.The efficiency of each matrix unit(MU)was calculated,and a collaborative optimization method was proposed based on an indicator(OEE).In this paper,an example of eight SMT lines is presented.The partitioning of MUs,OEE calculation of each MU,and the low OEE unit collaborative optimization method are described in detail.Through a case study,the architecture of the collaborative optimization model for the MMS was constructed and discussed.Finally,the improvement in the OEE proved the effectiveness and usability of the proposed architecture.

Numerical Methods for a Class of Quadratic Matrix Equations

Quadratic matrix equations arise in many elds of scienti c computing and engineering applications.In this paper,we consider a class of quadratic matrix equations.Under a certain condition,we rst prove the existence of minimal nonnegative solution for this quadratic matrix equation,and then propose some numerical methods for solving it.Convergence analysis and numerical examples are given to verify the theories and the numerical methods of this paper.

Working condition recognition of sucker rod pumping system based on 4-segment time-frequency signature matrix and deep learning

High-precision and real-time diagnosis of sucker rod pumping system(SRPS)is important for quickly mastering oil well operations.Deep learning-based method for classifying the dynamometer card(DC)of oil wells is an efficient diagnosis method.However,the input of the DC as a two-dimensional image into the deep learning framework suffers from low feature utilization and high computational effort.Additionally,different SRPSs in an oil field have various system parameters,and the same SRPS generates different DCs at different moments.Thus,there is heterogeneity in field data,which can dramatically impair the diagnostic accuracy.To solve the above problems,a working condition recognition method based on 4-segment time-frequency signature matrix(4S-TFSM)and deep learning is presented in this paper.First,the 4-segment time-frequency signature(4S-TFS)method that can reduce the computing power requirements is proposed for feature extraction of DC data.Subsequently,the 4S-TFSM is constructed by relative normalization and matrix calculation to synthesize the features of multiple data and solve the problem of data heterogeneity.Finally,a convolutional neural network(CNN),one of the deep learning frameworks,is used to determine the functioning conditions based on the 4S-TFSM.Experiments on field data verify that the proposed diagnostic method based on 4S-TFSM and CNN(4S-TFSM-CNN)can significantly improve the accuracy of working condition recognition with lower computational cost.To the best of our knowledge,this is the first work to discuss the effect of data heterogeneity on the working condition recognition performance of SRPS.

基于改进APF-QRRT^(*)策略的移动机器人路径规划

针对Q-RRT^(*)算法在路径规划过程中无法兼顾可达性和安全性的问题,提出一种改进APF-QRRT^(*)(IAPF-QRRT^(*))路径规划策略。IAPF-QRRT^(*)策略通过Q-RRT^(*)算法获得一组连接起点到终点的离散关键路径点,较传统的快速搜索随机树(RRT^(*))算法具备更好的初始解和更快的收敛速度。改进传统人工势场(APF)方法获得一种新的无势正交向量场,在一定条件下使整体排斥向量场与吸引向量场正交,并将其作用于关键路径点,从而提高路径的安全性。将IAPF-QRRT^(*)策略与其他算法比较,通过数值模拟实验证明了所提策略的有效性。

加强型Q460C方钢管间隙N型节点承载力研究

为考察加强构造对N型节点失效机理和承载力的影响规律,对加强节点和基本节点进行了主管轴压静力加载试验,试验结果表明:基本节点的破坏模式为主管上翼缘受拉鼓曲开裂,加强节点破坏模式为加劲板屈曲和覆板焊缝受拉开裂;加强节点的承载力较基本节点提高了9.4%~36.5%;增加覆板厚度,可明显提高节点承载力。采用ABAQUS软件对覆板和加劲板加强的Q460C方钢管间隙N型节点进行了有限元参数研究,考察了主管宽厚比γ、主支管厚度比η、主支管宽度比β、受拉支管与主管夹角θ、支管间距与主管宽度比ξ对节点破坏模式、应力分布、主管荷载-位移曲线和覆板焊缝断裂指数I f的影响规律。根据试验和数值模拟结果,提出了覆板和加劲板加强的Q460C方钢管间隙N型节点承载力计算式和构造设计建议。

Solution of the Matrix Second Semi-Tensor Product Equation A ∘ l X ∘ l B=C

In this paper, the solution of the matrix second semi-tensor product equation A∘lX∘lB=Cis studied. Firstly, the solvability of the matrix-vector second semi-tensor product equation is investigated. At the same time, the compatibility conditions, the sufficient and necessary conditions and the specific solution methods for the matrix solution are given. Secondly, we further consider the solvability of the second semi-tensor product equation of the matrix. For each part, several examples are given to illustrate the validity of the results.

Neurocircuit regeneration by extracellular matrix reprogramming

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.

Stiffness-tunable biomaterials provide a good extracellular matrix environment for axon growth and regeneration

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.

THE SPECTRAL RADIUS OF UNIFORM HYPERGRAPH DETERMINED BY THE SIGNLESS LAPLACIAN MATRIX

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.

A matrix metalloproteinase-responsive hydrogel system controls angiogenic peptide release for repair of cerebral ischemia/reperfusion injury

Vascular endothelial growth factor and its mimic peptide KLTWQELYQLKYKGI(QK)are widely used as the most potent angiogenic factors for the treatment of multiple ischemic diseases.However,conventional topical drug delivery often results in a burst release of the drug,leading to transient retention(inefficacy)and undesirable diffusion(toxicity)in vivo.Therefore,a drug delivery system that responds to changes in the microenvironment of tissue regeneration and controls vascular endothelial growth factor release is crucial to improve the treatment of ischemic stroke.Matrix metalloproteinase-2(MMP-2)is gradually upregulated after cerebral ischemia.Herein,vascular endothelial growth factor mimic peptide QK was self-assembled with MMP-2-cleaved peptide PLGLAG(TIMP)and customizable peptide amphiphilic(PA)molecules to construct nanofiber hydrogel PA-TIMP-QK.PA-TIMP-QK was found to control the delivery of QK by MMP-2 upregulation after cerebral ischemia/reperfusion and had a similar biological activity with vascular endothelial growth factor in vitro.The results indicated that PA-TIMP-QK promoted neuronal survival,restored local blood circulation,reduced blood-brain barrier permeability,and restored motor function.These findings suggest that the self-assembling nanofiber hydrogel PA-TIMP-QK may provide an intelligent drug delivery system that responds to the microenvironment and promotes regeneration and repair after cerebral ischemia/reperfusion injury.

Q550E高强钢及焊接接头的疲劳裂纹扩展研究

焊接构造是钢桥的薄弱部位,在反复车辆荷载作用下,疲劳损伤正逐步成为影响桥梁服役安全的关键问题之一。以Q550E高强钢为研究对象,开展母材和对接焊缝接头的静力拉伸和疲劳裂纹扩展试验,建立母材及焊接连接件的疲劳裂纹增长模型,揭示了应力比对高强钢焊接节点疲劳裂纹扩展速率的影响规律;开展基于FRANC3D和ABAQUS的联合仿真模拟分析,通过敏感性分析明确关键影响参数。结果表明:随着应力比的增大,疲劳裂纹扩展速率参数m增大、lg C减小,应力强度因子门槛值减小;对接焊缝m值约为母材的2倍,对接焊缝裂纹门槛值大于母材,且对应力比更敏感;联合仿真方法可准确预测高强钢焊接接头疲劳寿命,高应力比下试件厚度和初始裂纹深度对疲劳扩展影响显著。

基于UPLC-Q-TOF/MS^(E)结合UNIFI质谱数据平台快速表征鉴定天南星中的化学成分

目的:建立天南星中化学成分快速表征的分析方法,并用于该药材的质量控制。方法:采用超高效液相色谱联用四级杆串联飞行时间质谱(UPLC-Q-TOF/MS)结合UNIFI质谱数据分析平台,选择Waters Acquity UPLC HSS T 3 C 18色谱柱,以0.1%甲酸水和0.1%甲酸乙腈为流动相进行梯度洗脱,流速为0.35 mL/min,进样量5μL;选择电喷雾离子源,以MS^(E)模式采集正、负离子下天南星化学成分的质谱数据;通过UNIFI平台自带数据库结合文献检索建立天南星化学成分数据库,并根据化合物的精准分子质量、二级碎片离子信息及与对照品和文献数据等比对进化学成分的鉴定。结果:在正离子模式下鉴定出49个化合物,负离子模式下鉴定16个化合物,主要以有机酸、氨基酸及黄酮苷类化合物为主。其中,35个化合物可能首次从天南星中发现。结论:采用UPLC-Q-TOF/MS结合UNIFI平台的分析方法可快速鉴定天南星的化学成分,该研究结果可为天南星药效物质基础的研究以及质量控制体系建立和产品开发等提供科学依据。

Effect of applied pressure on microstructure and mechanical properties of Mg-Zn-Y quasicrystal-reinforced AZ91D magnesium matrix composites prepared by squeeze casting

The Mg-Zn-Y quasicrystal-reinforced AZ91 D magnesium matrix composites were prepared by squeeze casting process. The effects of applied pressure on microstructure and mechanical properties of the composites were investigated. The results show that squeeze casting process is an effective method to refine the grain. The composites are mainly composed of α-Mg, β-Mg17Al12 and Mg3Zn6Y icosahedral quasicrystal phase（I-phase）. With the increase of applied pressure, the contents of β-Mg17Al12 phase and Mg3Zn6 Y quasicrystal particles increase, further matrix grain refinement occurs and coarse dendritic α-Mg transforms into equiaxed grain structure. The composite exhibits the maximum ultimate tensile strength and elongation of 194.3 MPa and 9.2% respectively when the applied pressure is 100 MPa, and a lot of dimples appear on the tensile fractography. Strengthening mechanisms of quasicrystal-reinforced AZ91 D magnesium matrix composites are chiefly fine-grain strengthening and quasicrystal particles strengthening.

INCREMENTAL AUGMENT ALGORITHM BASED ON REDUCED Q-MATRIX

Reduced Q-matrix （Qr matrix） plays an important role in the rule space model （RSM） and the attribute hierarchy method （AHM）. Based on the attribute hierarchy, a valid/invalid item is defined. The judgment method of the valid/invalid item is developed on the relation between reachability matrix and valid items. And valid items are explained from the perspective of graph theory. An incremental augment algorithm for constructing Qr matrix is proposed based on the idea of incremental forward regression, and its validity is theoretically considered. Results of empirical tests are given in order to compare the performance of the incremental augment algo-rithm and the Tatsuoka algorithm upon the running time. Empirical evidence shows that the algorithm outper-forms the Tatsuoka algorithm, and the analysis of the two algorithms also show linear growth with respect to the number of valid items. Mathematical models with 10 attributes are built for the two algorithms by the linear regression analysis.

Optimization of AZ80 magnesium alloy squeeze cast process parameters using morphological matrix

The squeeze cast process parameters of AZ80 magnesium alloy were optimized by morphological matrix. Experiments were conducted by varying squeeze pressure, die pre-heat temperature and pressure duration using L9（33） orthogonal array of Taguchi method. In Taguchi method, a 3-level orthogonal array was used to determine the signal/noise ratio. Analysis of variance was used to determine the most significant process parameters affecting the mechanical properties. Mechanical properties such as ultimate tensile strength, elongation and hardness of the components were ascertained using multi variable linear regression analysis. Optimal squeeze cast process parameters were obtained.

EFFECT OF FIBER FAILURE ON QUASI-STATIC UNLOADING/RELOADING HYSTERESIS LOOPS OF CERAMIC MATRIX COMPOSITES

The two-parameter Weibull model is used to describe the fiber strength distribution.The stress carried by the intact and fracture fibers on the matrix crack plane during unloading/reloading is determined based on the global load sharing criterion.The axial stress distribution of intact fibers upon unloading and reloading is determined based on the mechanisms of fiber sliding relative to matrix in the interface debonded region.The interface debonded length,unloading interface counter slip length,and reloading interface new slip length are obtained by the fracture mechanics approach.The hysteresis loops corresponding to different stresses considering fiber failure are compared with the cases without considering fiber failure.The effects of fiber characteristic strength and fiber Weibull modulus on the fiber failure,the shape,and the area of the hysteresis loops are analyzed.The predicted quasi-static unloading/reloading hysteresis loops agree well with experimental data.