Analysis of the Tragedy of Vila Socóin Cubatão (São Paulo, Brazil) Using the Haddon Matrix: A Comprehensive Examination of Socio-Environmental Factors and Risk Mitigation Strategies

The tragedy of Vila Socó epitomizes the socio-environmental repercussions of rapid industrialization in Cubatão. Beginning in the 1940s with the construction of the Anchieta highway, the city experienced an influx of migrants drawn by burgeoning industries, leading to unplanned urban growth and the emergence of vulnerable communities like Vila Socó. This article examines the interconnected factors—such as demographic shifts, inadequate planning, and regulatory oversight—that culminated in the devastating fire of 1984, claiming numerous lives and highlighting systemic failures. Utilizing the Haddon Matrix, this study dissects the Vila Socó incident, emphasizing the roles of human error, infrastructure integrity, and socio-economic disparities in disaster causation. By contextualizing the tragedy within Cubatão’s industrial trajectory, it underscores the urgent need for comprehensive risk assessment and proactive mitigation strategies in rapidly developing regions globally. Beyond its immediate focus, this work offers broader insights into the dynamics of industrial disasters and their socio-economic implications. As pipelines continue to play a vital role in global energy infrastructure, the lessons drawn from Vila Socó’s tragedy resonate deeply, emphasizing the imperative of robust safety protocols and accountable governance to prevent similar catastrophes in the future.

Biofabrication of nanocomposite-based scaffolds containing human bone extracellularmatrix for the differentiation of skeletal stem and progenitor cells

Autograft or metal implants are routinely used in skeletal repair.However,they fail to provide long-term clinical resolution,necessitating a functional biomimetic tissue engineering alternative.The use of native human bone tissue for synthesizing a biomimeticmaterial inkfor three-dimensional(3D)bioprintingof skeletal tissueis anattractivestrategyfor tissueregeneration.Thus,human bone extracellular matrix(bone-ECM)offers an exciting potential for the development of an appropriate microenvironment for human bone marrow stromal cells(HBMSCs)to proliferate and differentiate along the osteogenic lineage.In this study,we engineered a novel material ink(LAB)by blending human bone-ECM(B)with nanoclay(L,Laponite®)and alginate(A)polymers using extrusion-based deposition.The inclusion of the nanofiller and polymeric material increased the rheology,printability,and drug retention properties and,critically,the preservation of HBMSCs viability upon printing.The composite of human bone-ECM-based 3D constructs containing vascular endothelial growth factor(VEGF)enhanced vascularization after implantation in an ex vivo chick chorioallantoic membrane(CAM)model.The inclusion of bone morphogenetic protein-2(BMP-2)with the HBMSCs further enhanced vascularization and mineralization after only seven days.This study demonstrates the synergistic combination of nanoclay with biomimetic materials(alginate and bone-ECM)to support the formation of osteogenic tissue both in vitro and ex vivo and offers a promising novel 3D bioprinting approach to personalized skeletal tissue repair.

Non-Linear Matrix Completion

Current methods for predicting missing values in datasets often rely on simplistic approaches such as taking median value of attributes, limiting their applicability. Real-world observations can be diverse, taking stock price as example, ranging from prices post-IPO to values before a company’s collapse, or instances where certain data points are missing due to stock suspension. In this paper, we propose a novel approach using Nonlinear Matrix Completion (NIMC) and Deep Matrix Completion (DIMC) to predict associations, and conduct experiment on financial data between dates and stocks. Our method leverages various types of stock observations to capture latent factors explaining the observed date-stock associations. Notably, our approach is nonlinear, making it suitable for datasets with nonlinear structures, such as the Russell 3000. Unlike traditional methods that may suffer from information loss, NIMC and DIMC maintain nearly complete information, especially in high-dimensional parameters. We compared our approach with state-of-the-art linear methods, including Inductive Matrix Completion, Nonlinear Inductive Matrix Completion, and Deep Inductive Matrix Completion. Our findings show that the nonlinear matrix completion method is particularly effective for handling nonlinear structured data, as exemplified by the Russell 3000. Additionally, we validate the information loss of the three methods across different dimensionalities.

Amino-functionalized UiO-66-doped mixed matrix membranes with high permeation performance and fouling resistance

For the reduction of bovine serum proteins from wastewater,a novel mixed matrix membrane was prepared by functionalizing the substrate material polyaryletherketone(PAEK),followed by carboxyl groups(C-SPAEKS),and then adding amino-functionalized UiO-66-NH_(2)(Am-UiO-66-NH_(2)).Aminofunctionalization of UiO-66 was accomplished by melamine,followed by an amidation reaction to immobilize Am-UiO-66-NH_(2),which was immobilized on the surface of the membrane as well as in the pore channels,which enhanced the hydrophilicity of the membrane surface while increasing the negative potential of the membrane surface.This nanoparticle-loaded ultrafiltration membrane has good permeation performance,with a pure water flux of up to 482.3 L·m^(-2)·h^(-1) for C-SPAEKS/AmUiO-66-NH_(2) and a retention rate of up to 98.7%for bovine serum albumin(BSA)-contaminated solutions.Meanwhile,after several hydrophilic modifications,the flux recovery of BSA contaminants by this series of membranes increased from 56.2%to 80.55%of pure membranes.The results of ultra-filtration flux time tests performed at room temperature showed that the series of ultrafiltration membranes remained relatively stable over a test time of 300 min.Thus,the newly developed mixed matrix membrane showed potential for high efficiency and stability in wastewater treatment containing bovine serum proteins.

Low-Complexity Reconstruction of Covariance Matrix in Hybrid Uniform Circular Array

Spatial covariance matrix(SCM) is essential in many multi-antenna systems such as massive multiple-input multiple-output(MIMO). For multi-antenna systems operating at millimeter-wave bands, hybrid analog-digital structure has been widely adopted to reduce the cost of radio frequency chains.In this situation, signals received at the antennas are unavailable to the digital receiver, and as a consequence, traditional sample average approach cannot be used for SCM reconstruction in hybrid multi-antenna systems. To address this issue, beam sweeping algorithm(BSA) which can reconstruct the SCM effectively for a hybrid uniform linear array, has been proposed in our previous works. However, direct extension of BSA to a hybrid uniform circular array(UCA)will result in a huge computational burden. To this end, a low-complexity approach is proposed in this paper. By exploiting the symmetry features of SCM for the UCA, the number of unknowns can be reduced significantly and thus the complexity of reconstruction can be saved accordingly. Furthermore, an insightful analysis is also presented in this paper, showing that the reduction of the number of unknowns can also improve the accuracy of the reconstructed SCM. Simulation results are also shown to demonstrate the proposed approach.

Long noncoding RNAs HAND2-AS1 ultrasound microbubbles suppress hepatocellular carcinoma progression by regulating the miR-873-5p/tissue inhibitor of matrix metalloproteinase-2 axis

BACKGROUND Increasing data indicated that long noncoding RNAs(lncRNAs)were directly or indirectly involved in the occurrence and development of tumors,including hepatocellular carcinoma(HCC).Recent studies had found that the expression of lncRNA HAND2-AS1 was downregulated in HCC tissues,but its role in HCC progression is unclear.Ultrasound targeted microbubble destruction mediated gene transfection is a new method to overexpress genes.AIM To study the role of ultrasound microbubbles(UTMBs)mediated HAND2-AS1 in the progression of HCC,in order to provide a new reference for the treatment of HCC.METHODS In vitro,we transfected HAND2-AS1 siRNA into HepG2 cells by UTMBs,and detected cell proliferation,apoptosis,invasion and epithelial-mesenchymal transition(EMT)by cell counting kit-8 assay,flow cytometry,Transwell invasion assay and Western blotting,respectively.In addition,we transfected miR-837-5p mimic into UTMBs treated cells and observed the changes of cell behavior.Next,the UTMBs treated HepG2 cells were transfected together with miR-837-5p mimic and tissue inhibitor of matrix metalloproteinase-2(TIMP2)overexpression vector,and we detected cell proliferation,apoptosis,invasion and EMT.In vivo,we established a mouse model of subcutaneous transplantation of HepG2 cells and observed the effect of HAND2-AS1 silencing on tumor formation ability.RESULTS We found that UTMBs carrying HAND2-AS1 restricted cell proliferation,invasion,and EMT,encouraged apoptosis,and HAND2-AS1 silencing eliminated the effect of UTMBs.Additionally,miR-873-5p targets the gene HAND2-AS1,which also targets the 3’UTR of TIMP2.And miR-873-5p mimic counteracted the impact of HAND2-AS1.Further,miR-873-5p mimic solely or in combination with pcDNA-TIMP2 had been transformed into HepG2 cells exposed to UTMBs.We discovered that TIMP2 reversed the effect of miR-873-5p mimic caused by the blocked signalling cascade for matrix metalloproteinase(MMP)2/MMP9.In vivo results showed that HAND2-AS1 silencing significantly inhibited tumor formation in mice.CONCLUSION LncRNA HAND2-AS1 promotes TIMP2 expression by targeting miR-873-5p to inhibit HepG2 cell growth and delay HCC progression.

Association between Gene Polymorphisms and SNP-SNP Interactions of the Matrix Metalloproteinase 2 Signaling Pathway and the Risk of Vascular Senescence

Objective This study aimed to explore the association of single nucleotide polymorphisms(SNP)in the matrix metalloproteinase 2(MMP-2)signaling pathway and the risk of vascular senescence(VS).Methods In this cross-sectional study,between May and November 2022,peripheral venous blood of151 VS patients(case group)and 233 volunteers(control group)were collected.Fourteen SNPs were identified in five genes encoding the components of the MMP-2 signaling pathway,assessed through carotid-femoral pulse wave velocity(cf PWV),and analyzed using multivariate logistic regression.The multigene influence on the risk of VS was assessed using multifactor dimensionality reduction(MDR)and generalized multifactor dimensionality regression(GMDR)modeling.Results Within the multivariate logistic regression models,four SNPs were screened to have significant associations with VS:chemokine(C-C motif)ligand 2(CCL2)rs4586,MMP2 rs14070,MMP2rs7201,and MMP2 rs1053605.Carriers of the T/C genotype of MMP2 rs14070 had a 2.17-fold increased risk of developing VS compared with those of the C/C genotype,and those of the T/T genotype had a19.375-fold increased risk.CCL2 rs4586 and MMP-2 rs14070 exhibited the most significant interactions.Conclusion CCL2 rs4586,MMP-2 rs14070,MMP-2 rs7201,and MMP-2 rs1053605 polymorphisms were significantly associated with the risk of VS.

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.

An Eight Component Integrable Hamiltonian Hierarchy from a Reduced Seventh-Order Matrix Spectral Problem

We present an eight component integrable Hamiltonian hierarchy, based on a reduced seventh order matrix spectral problem, with the aim of aiding the study and classification of multicomponent integrable models and their underlying mathematical structures. The zero-curvature formulation is the tool to construct a recursion operator from the spatial matrix problem. The second and third set of integrable equations present integrable nonlinear Schrödinger and modified Korteweg-de Vries type equations, respectively. The trace identity is used to construct Hamiltonian structures, and the first three Hamiltonian functionals so generated are computed.

A Perturbation Analysis of Low-Rank Matrix Recovery by Schatten p-Minimization

A number of previous papers have studied the problem of recovering low-rank matrices with noise, further combining the noisy and perturbed cases, we propose a nonconvex Schatten p-norm minimization method to deal with the recovery of fully perturbed low-rank matrices. By utilizing the p-null space property (p-NSP) and the p-restricted isometry property (p-RIP) of the matrix, sufficient conditions to ensure that the stable and accurate reconstruction for low-rank matrix in the case of full perturbation are derived, and two upper bound recovery error estimation ns are given. These estimations are characterized by two vital aspects, one involving the best r-approximation error and the other concerning the overall noise. Specifically, this paper obtains two new error upper bounds based on the fact that p-RIP and p-NSP are able to recover accurately and stably low-rank matrix, and to some extent improve the conditions corresponding to RIP.

Placenta-derived mesenchymal stem cells attenuate secondary brain injury after controlled cortical impact in rats by inhibiting matrix metalloproteinases

Background:As a form of biological therapy,placenta-derived mesenchymal stem cells(PDMSCs)exhibit considerable promise in addressing the complex pathological processes of traumaticbrain injury(TBI)due to their multi-target and multi-pathway mode of action.Material&Methods:This study investigates the protective mechanisms and benefits of PDMSCs in mitigating the effects of controlled cortical impact(CCI)in rats and glutamate-induced oxidative stress injury in HT22 cells in vitro.Our primary objective is to provide evidence supporting the clinical application of PDMSCs.Results:In the in vivo arm of our investigation,we observed a swift elevation of matrix metalloproteinase-9(MMP-9)in the proximal cortex of injured brain tissues after CCI.PDMSCs,distinguished by their heightened expression of metalloproteinase tissue inhibitors-1 and-2(TIMP-1 and TIMP-2):were intravenously administered via the caudal vein.This intervention yielded significant reductions in the permeability of the blood-brain barrier(BBB):the extent of brain edema,the levels of inflammatory cytokines IL-1βand TNF-αin damaged brain tissue,and the activation status of microglia in CCI-afflicted rats.In the realm of in vitro experiments,PDMSC-conditioned media demonstrated substantial reductions in mortality rates and cleaved caspase-3 levels in glutamate-induced HT22 cells compared with conventional media.Notably,this advantage was negated upon the introduction of neutralizing antibodies targeting TIMP-1 and TIMP-2.Conclusion:Collectively,our findings underscore the potential of PDMSCs in alleviating oxidative stress injury and secondary brain injury in the pathological process of TBI.

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.

Automatic modulation recognition of radiation source signals based on two-dimensional data matrix and improved residual neural network

Automatic modulation recognition(AMR)of radiation source signals is a research focus in the field of cognitive radio.However,the AMR of radiation source signals at low SNRs still faces a great challenge.Therefore,the AMR method of radiation source signals based on two-dimensional data matrix and improved residual neural network is proposed in this paper.First,the time series of the radiation source signals are reconstructed into two-dimensional data matrix,which greatly simplifies the signal preprocessing process.Second,the depthwise convolution and large-size convolutional kernels based residual neural network(DLRNet)is proposed to improve the feature extraction capability of the AMR model.Finally,the model performs feature extraction and classification on the two-dimensional data matrix to obtain the recognition vector that represents the signal modulation type.Theoretical analysis and simulation results show that the AMR method based on two-dimensional data matrix and improved residual network can significantly improve the accuracy of the AMR method.The recognition accuracy of the proposed method maintains a high level greater than 90% even at -14 dB SNR.

先锋女性主义者的建筑实验--英国Matrix的女性主义建筑观念与实践研究

英国的Matrix是西方第一个明确以女性主义为主张的女性建筑事务所。在特定的时代背景下,她们试图挑战父权制下的建筑体系并发展一种女性主义的设计方法,是西方将女性主义理论运用到建筑空间实践中的先锋者。本文回溯了Matrix组建时的政治与社会背景,分析她们以建筑师的身份采取集体合作工作模式、以女性为主体的参与式机制、以技能培训为辅助的女性建筑教育介入的方法来促进女性解放并重构建筑的空间生产。基于女性主义社会建构论的观念,解读Matrix是如何以性别批判的视角来看待和认知城市空间与女性主义建筑,并结合具体建筑案例分析女性视角下的包容性建筑设计。最后本文探讨了以Matrix为代表的女性建筑师及其女性主义建筑观念与实践对于当下建筑学科研究的价值与意义。

Transfer matrix method for free and forced vibrations of multi-level functionally graded material stepped beams with different boundary conditions

Functionally graded materials(FGMs)are a novel class of composite materials that have attracted significant attention in the field of engineering due to their unique mechanical properties.This study aims to explore the dynamic behaviors of an FGM stepped beam with different boundary conditions based on an efficient solving method.Under the assumptions of the Euler-Bernoulli beam theory,the governing differential equations of an individual FGM beam are derived with Hamilton’s principle and decoupled via the separation-of-variable approach.Then,the free and forced vibrations of the FGM stepped beam are solved with the transfer matrix method(TMM).Two models,i.e.,a three-level FGM stepped beam and a five-level FGM stepped beam,are considered,and their natural frequencies and mode shapes are presented.To demonstrate the validity of the method in this paper,the simulation results by ABAQUS are also given.On this basis,the detailed parametric analyses on the frequencies and dynamic responses of the three-level FGM stepped beam are carried out.The results show the accuracy and efficiency of the TMM.

Recent advances in flat sheet mixed matrix membrane modified by Mg-based layered double hydroxides(LDHs)for salt and organic compound separations

Magnesium(Mg)is a widely used and attractive metal,known for its unique physical and chemical properties,and it has been employed in the manufacture of many practical materials.Layered Double Hydroxides(LDHs),particularly Mg-based LDHs,rank among the most prevalent two-dimensional materials utilized in separation processes,which include adsorption,extraction,and membrane technology.The high popularity of Mg-based LDHs in separation applications can be attributed to their properties,such as excellent hydrophilicity,high surface area,ion exchangeability,and adjustable interlayer space.Currently,polymer membranes play a pivotal role in semi-industrial and industrial separation processes.Consequently,the development of polymer membranes and the mitigation of their limitations have emerged as compelling topics for researchers.Several methods exist to enhance the separation performance and anti-fouling properties of polymer membranes.Among these,incorporating additives into the membrane polymer matrix stands out as a cost-effective,straightforward,readily available,and efficient approach.The use of Mg-based LDHs,either in combination with other materials or as a standalone additive in the polymer membrane matrix,represents a promising strategy to bolster the separation and anti-fouling efficacy of flat sheet mixed matrix polymer membranes.This review highlights Mg-based LDHs as high-potential additives designed to refine flat sheet mixed matrix polymer membranes for applications in wastewater treatment and brackish water desalination.

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.

新风胶囊抑制软骨细胞炎症和细胞外基质降解:基于调控miR-502-5p/TRAF2/NF-κB轴

目的探讨新风胶囊(XFC)对白介素(IL)-1β诱导的软骨细胞功能的影响及作用机制。方法构建IL-1β诱导的软骨细胞炎症模型;SD大鼠灌胃制备XFC含药血清。细胞增殖实验(CCK-8)和流式细胞术筛选最佳XFC含药血清浓度;双荧光素酶报告分析miR-502-5p和TRAF2的靶向关系。构建miR-502-5p抑制表达质粒(inhibitor)及阴性对照组,转染至软骨细胞中。分为对照组(NC),IL-1β组,XFC组,IL-1β+NC-inhibitor,IL-1β+miR-502-5pinhibitor,IL-1β+miR-502-5pinhibitor+XFC最佳含药血清组,酶联免疫吸附试验(ELASA)检测IL-1β、肿瘤坏死因子-α(TNF-α)、IL-4、IL-10的水平。逆转录PCR(RT-PCR)、蛋白质免疫印迹实验(WB)、免疫荧光法检测Ⅱ型胶原α1(COL2A1)、基质金属蛋白酶13(MMP13)、软骨蛋白聚糖抗体(ADAMTS5)和miR-502-5p/TRAF2/NF-κB基因的表达。结果与NC组相比,IL-1β组中软骨细胞活力下降,细胞凋亡率升高,且miR-502-5p、IL-4、IL-10和COL2A1表达下降,IL-1β、TNF-α和ADAMTS5、MMP13、TRAF2、NF-κB p65表达升高(P<0.05)。筛选得出20%XFC为最佳含药血清浓度。与IL-1β组相比,XFC含药血清干预后,软骨细胞活力升高,细胞凋亡率下降,IL-1β、TNF-α、ADAMTS5、MMP13、TRAF2、NF-κBp65表达下降,miR-502-5p、IL-4、IL-10和COL2A1表达升高(P<0.05)。与NC-inhibitor相比,转染miR-502-5p inhibitor后,IL-1β、TNF-α、ADAMTS5、MMP13、TRAF2、NF-κB p65表达升高,miR-502-5p、IL-4、IL-10和COL2A1表达下降;与miR-502-5pinhibitor相比,将miR-502-5pinhibitor转染的软骨细胞和最佳XFC含药血清共培养后,XFC含药血清能逆转miR-502-5p抑制状态对软骨细胞炎症和ECM的影响。结论XFC抑制软骨细胞炎症、细胞外基质降解,减轻IL-1β诱导的软骨细胞损伤,其机制可能是通过调节miR-502-5p/TRAF2/NF-κB轴。

基于无差拍预测算法的双向隔离型AC-DC矩阵变换器高动态电流控制策略

针对双向隔离型AC-DC矩阵变换器采用传统双闭环控制策略存在的控制参数多、整定困难等问题,提出了一种基于无差拍预测算法的高动态电流控制策略,通过引入无差拍预测算法对网侧电流进行控制,以减少控制器参数,消除数字控制时延。考虑到算法中电压电流检测量众多,故采用输入电压观测器以降低检测成本,减小采样误差的影响。变换器采用后级单重移相的调制方法来协调配合无差拍预测算法,其中参考输入电流指令与移相角为双射函数关系,简单易实现。仿真和实验结果表明:采用所提控制策略可以实现网侧电流正弦,功率因数接近于1;直流侧电压稳定,电流纹波率小于1%;直流电流在参考值突变时,跟踪快速且无超调、无振荡;同时,在变换器功率正向传输、反向传输以及正反向切换过程中,采用所提控制策略相比于传统的双闭环控制策略,电流动态调节时间分别缩短了69%、85%、67%。由此证明所提控制策略可以保证变换器良好的输入输出性能,并且相比于传统的双闭环控制策略在切换过程中动态性能得到显著提升。

组织中MMP-9、E-cadherin与子宫内膜样癌伴MELF浸润方式及肿瘤侵袭程度的关系

目的分析子宫内膜样癌组织中基质金属蛋白酶(matrix metalloproteinase,MMP)-9、E-钙黏蛋白(E-cadherin)与微囊性、伸长及碎片状(microcystic,elongation,and fragmentation,MELF)浸润方式及肿瘤侵袭程度之间的关系,探讨能够识别子宫内膜样癌伴MELF浸润的指标,抑制肿瘤侵袭能力。方法回顾性分析在河北北方学院附属第一医院接受手术治疗的112例子宫内膜样癌患者临床资料,全部患者均顺利完成改良根治性子宫切除术,并获得肿瘤标准,根据病理检查结果对112例患者进行分组,分为MELF组和N-MELF组。统计112例患者一般临床资料,血液检查项目包括肿瘤标志物,免疫组织化学检查项目包括组织中MMP-9、E-cadherin,根据检查结果,构建Logistic回归模型,分析组织中MMP-9、E-cadherin及相关指标与子宫内膜样癌MELF浸润方式及肿瘤侵袭程度的关系。结果研究中112例子宫内膜样癌患者,评估为MELF浸润患者21例(18.75%);MELF浸润患者病理等级低级别,国际妇产科联盟(International Federation of Gynecology and Obstetrics,FIGO)ⅣA期,淋巴脉管间隙浸润(lymphatic vascular space,LVSI)、组织中MMP-9阳性患者占比多于N-MELF浸润患者,E-cadherin阳性患者占比少于N-MELF浸润患者,人附睾蛋白(humanepididymisprotein 4,HE4),甲壳质酶蛋白(human cartilageglycopmtein,YKL-40)水平高于N-MELF患者,差异有统计学意义(P<0.05)。多元Logistic回归分析提示,组织中E-cadherin表达率低、MMP-9表达率高,MELF浸润与子宫内膜样癌FIGO分期进展有关(P<0.05)。结论子宫内膜样癌发生MELF浸润与组织中MMP-9、E-cadherin有关,MMP-9表达率高和E-cadherin表达率低能够通过导致MELF浸润发生,从而增强肿瘤侵袭能力。