Matrix Production Research Articles

BAD2matrix: Phylogenomic matrix concatenation, indel coding, and more

AbstractPremiseCommon steps in phylogenomic matrix production include biological sequence concatenation, morphological data concatenation, insertion/deletion (indel) coding, gene content (presence/absence) coding, removing uninformative characters for parsimony analysis, recording with reduced amino acid alphabets, and occupancy filtering. Existing software does not accomplish these tasks on a phylogenomic scale using a single program.Methods and ResultsBAD2matrix is a Python script that performs the above‐mentioned steps in phylogenomic matrix construction for DNA or amino acid sequences as well as morphological data. The script works in UNIX‐like environments (e.g., LINUX, MacOS, Windows Subsystem for LINUX).ConclusionsBAD2matrix helps simplify phylogenomic pipelines and can be downloaded from https://github.com/dpl10/BAD2matrix/tree/master under a GNU General Public License v2.

Paramps: Convolutional neural networks based on tensor decomposition for heart sound signal analysis and cardiovascular disease diagnosis

Currently, convolutional neural networks have demonstrated outstanding efficiency in heart sound detection and automatic diagnosis of cardiovascular diseases. However, due to the non-stationary nature and complex data patterns caused by environmental noise and stethoscope differences, traditional neural networks are limited in extracting discriminative features. This article proposes a convolutional neural network based on tensor decomposition to address this issue. This model uses a convolutional neural network with four parallel structures to extract audio features of heart sound signals and introduces a tensor network to use tensor decomposition to perform low-rank approximation on the convolutional kernel, compress model parameters, reduce redundancy, and improve performance. When processing feature data, the model divides large areas of features into locally unordered small areas to achieve feature compression and reorganization, ensuring that crucial information is preserved while compressing parameters. The model can accurately capture spatial structural information and critical features by refining the matrix product state layer. Experiments were conducted on the 2016 PhysioNet/CinC Challenge and the Yaseen heart sound public dataset, the experimental results show that the proposed method has an accuracy of 96.4% and 99.2% on two datasets, specificity of 99.1% and 99.8%, demonstrating its excellent generalization ability and diagnostic accuracy.

Tradeoff relations in open quantum dynamics via Robertson, Maccone–Pati, and Robertson–Schrödinger uncertainty relations

Abstract The Heisenberg uncertainty relation, together with Robertson’s generalisation, serves as a fundamental concept in quantum mechanics, showing that noncommutative pairs of observables cannot be measured precisely. In this study, we explore the Robertson-type uncertainty relations to demonstrate their effectiveness in establishing a series of thermodynamic uncertainty relations and quantum speed limits in open quantum dynamics. The derivation utilises a scaled continuous matrix product state representation that maps the time evolution of the quantum continuous measurement to the time evolution of the system and field. Specifically, we consider the Maccone–Pati uncertainty relation, a refinement of the Robertson uncertainty relation, to derive thermodynamic uncertainty relations and quantum speed limits. These newly derived relations, which use a state orthogonal to the initial state, yield bounds that are tighter than previously known bounds. Moreover, we consider the Robertson–Schrödinger uncertainty, which extends the Robertson uncertainty relation. Our findings not only reinforce the significance of the Robertson-type uncertainty relations, but also expand its applicability in identifying uncertainty relations in open quantum dynamics.

Tensor-network-based variational Monte Carlo approach to the non-equilibrium steady state of open quantum systems

We introduce a novel method of efficiently simulating the non-equilibrium steady state of large many-body open quantum systems with highly non-local interactions, based on a variational Monte Carlo optimization of a matrix product operator ansatz. Our approach outperforms and offers several advantages over comparable algorithms, such as an improved scaling of the computational cost with respect to the bond dimension for periodic systems. We showcase the versatility of our approach by studying the phase diagrams and correlation functions of the dissipative quantum Ising model with collective dephasing and long-ranged power law interactions for spin chains of up to N=100 spins.

Recoverability of zebrafish from decabromodiphenyl ether exposure: The persisted interference with extracellular matrix production and collagen synthesis and the enhancement of arrhythmias

As a widely used brominated flame retardant, the widespread presence of decabromodiphenyl ether (BDE-209) in the natural environment and the toxicity risks it poses are well established, but the recoverability of BDE-209-induced individual injuries remains unknown. Therefore, a 7-day depuration experiment following a 4-day exposure of zebrafish to BDE-209 was conducted to confirm the recoverability and its mode of action. Oxidative stress after depuration was significantly reduced compared with BDE-209 exposure as indicated by the decreased expression level of oxidative stress-related genes and the reduced MDA, Gpx, and GST in zebrafish, indicating a gradual recovery of antioxidant activity. However, BDE-209 inhibition of extracellular matrix (ECM) proteins worsened after depuration. Mechanistically, BDE-209 mediated ECM production and secretion by down-regulating integrin expression. Furthermore, BDE-209 inhibition of collagen synthesis worsened after depuration. Biochemical assays and histopathological observations revealed a same result in zebrafish. Mechanistically, lysine hydroxylation is inhibited thereby affecting collagen synthesis. Interestingly, zebrafish showed arrhythmia after depuration compared to BDE-209 exposure, and abnormal changes in ATPase levels indicated that disturbances in Ca2+ homeostasis contributed to arrhythmia. Collectively, BDE-209-induced interference with ECM production and collagen synthesis persisted after depuration, which will provide new insights for understanding the recovery patterns of individuals under BDE-209 stress.

Identification of novel biomarkers, shared molecular signatures and immune cell infiltration in heart and kidney failure by transcriptomics.

Heart failure (HF) and kidney failure (KF) are closely related conditions that often coexist, posing a complex clinical challenge. Understanding the shared mechanisms between these two conditions is crucial for developing effective therapies. This study employed transcriptomic analysis to unveil molecular signatures and novel biomarkers for both HF and KF. A total of 2869 shared differentially expressed genes (DEGs) were identified in patients with HF and KF compared to healthy controls. Functional enrichment analysis was performed to explore the common mechanisms underlying these conditions. A protein-protein interaction (PPI) network was constructed, and machine learning algorithms, including Random Forest (RF), Support Vector Machine-Recursive Feature Elimination (SVM-RFE), and Least Absolute Shrinkage and Selection Operator (LASSO), were used to identify key signature genes. These genes were further analyzed using Gene Set Variation Analysis (GSVA) and Gene Set Enrichment Analysis (GSEA), with their diagnostic values validated in both training and validation sets. Molecular docking studies were conducted. Additionally, immune cell infiltration and correlation analyses were performed to assess the relationship between immune responses and the identified biomarkers. The functional enrichment analysis indicated that the common mechanisms are associated with cellular homeostasis, cell communication, cellular replication, inflammation, and extracellular matrix (ECM) production, with the PI3K-Akt signaling pathway being notably enriched. The PPI network revealed two key protein clusters related to the cell cycle and inflammation. CDK2 and CCND1 were identified as signature genes for both HF and KF. Their diagnostic value was validated in both training and validation sets. Additionally, docking studies with CDK2 and CCND1 were performed to evaluate potential drug candidates. Immune cell infiltration and correlation analyses highlighted the immune microenvironment, and that CDK2 and CCND1 are associated with immune responses in HF and KF. This study identifies CDK2 and CCND1 as novel biomarkers linking cell cycle regulation and inflammation in heart and kidney failure. These findings offer new insights into the molecular mechanisms of HF and KF and present potential targets for diagnosis and therapy.

MATHEMATICAL APPROACH OF THE BACKPROPAGATION METHOD FOR CONSTRUCTING ARTIFICIAL NEURAL NETWORKS

Backpropagation isthe core part of a neural network. This method is used to efficiently train a network using a chain rule that allows differentiation of complex functions. In other words, after each pass through the network, the backpropagation method performs a backward pass to adjust the model parameters, such as weights and biases. This article highlights the importance of using the backpropagation method from the point of view of mathematical formulas for neural networks. The importance of using the backpropaga-tion learning algorithm to calculate the gradient (gradient descent) and the need to use the activation function to minimize the loss function is mathematically described and calculated by formulas, and also proven by calculating the matrix products of vectors for each layer of parameters - weights and biases and applying complex differential equations.

Comparative Analysis of Commercially Available Extracellular Matrix Soft Tissue Bioscaffolds.

Decellularized extracellular matrix (dECM) products are widely established for soft tissue repair, reconstruction and reinforcement. These regenerative biomaterials mimic native tissue ECM with respect to structure and biology and are produced from a range of tissue sources and species. Optimal source tissue processing requires a balance between removal of cellular material and the preservation of structural and biological properties of tissue ECM. Despite the wide-spread clinical use of dECM products there is a lack of comparative information on these products Structurally, some dECM products showed a well-preserved collagen architecture with a broad porosity distribution, while others showed a significantly altered structure compared with native tissue. Decellularization varied across the products. Some materials surveyed (OFMm, PPN, PPC, OFMo, UBM, SISz, ADM, PADM and BADM) were essentially devoid of nuclear bodies (mean count of <5 cells per high powered field (HPF)), whereas others (SISu and SISb) demonstrated an abundance of nuclear bodies (>50 cells per HPF). Pathology assessment of the products demonstrated that OFMm, OFMo and PADM had the highest qualitative assessment score for collagen fiber orientation and arrangement, matrix porosity, decellularization efficiency, and residual vascular channels scoring 10.5±0.8, 12.8±1.0, and 9.7±0.7 out of a maximum total score of 16, respectively This analysis of commercially available dECM products in terms of their structure and cellularity includes 12 different commercial materials The findings highlight the variability of the products in terms of matrix structure and the efficacy of decellularization.

Correlation functions from tensor network influence functionals: The case of the spin-boson model.

We investigate the application of matrix product state (MPS) representations of the influence functionals (IFs) for the calculation of real-time equilibrium correlation functions in open quantum systems. Focusing specifically on the unbiased spin-boson model, we explore the use of IF-MPSs for complex time propagation, as well as IF-MPSs for constructing correlation functions in the steady state. We examine three different IF approaches: one based on the Kadanoff-Baym contour targeting correlation functions at all times, one based on a complex contour targeting the correlation function at a single time, and a steady state formulation, which avoids imaginary or complex times, while providing access to correlation functions at all times. We show that within the IF language, the steady state formulation provides a powerful approach to evaluate equilibrium correlation functions.

Carrier-Free Nanoagent Interfering with Cancer-Associated Fibroblasts' Metabolism to Promote Tumor Penetration for Boosted Chemotherapy.

Elevated production of extracellular matrix (ECM) in tumor stroma is a critical obstacle for drug penetration. Here we demonstrate that ATP-citrate lyase (ACLY) is significantly upregulated in cancer-associated fibroblasts (CAFs) to produce tumor ECM. Using a self-assembling nanoparticle-design approach, a carrier-free nanoagent (CFNA) is fabricated by simply assembling NDI-091143, a specific ACLY inhibitor, and doxorubicin (DOX) or paclitaxel (PTX), the first-line chemotherapeutic drug, via multiple noncovalent interactions. After arriving at the CAFs-rich tumor site, NDI-091143-mediated ACLY inhibition in CAFs can block the de novo synthesis of fatty acid, thereby dampening the fatty acid-involved energy metabolic process. As the lack of enough energy, the energetic CAFs will be in a dispirited state that is unable to produce abundant ECM, thereby significantly improving drug perfusion in tumors and enhancing the efficacy of chemotherapy. Such a simple drug assembling strategy aimed at CAFs' ACLY-mediated metabolism pathway presents the feasibility of stromal matrix reduction to potentiate chemotherapy.

Bundled matrix product states represent low-energy excitations faithfully

Abstract We consider a set of density matrices. All of which are written in the same orbital basis, but the orbital basis size is less than the total Hilbert space size. We ask how each density matrix is related to each of the others by establishing a norm between density matrices based on the truncation error in a partial trace for a small set of orbitals. We find that states with large energy differences must have large differences in their density matrices. Small energy differences are divided into two groups, one where two density matrices have small differences and another where they are very different, as is the case of symmetry. We extend these ideas to a bundle of matrix product states and show that bond dimension of the wavefunction ansatz for two states with large energy differences are larger. Meanwhile, low energy differences can have nearly the same bond dimensions for similar states.

Quantum computing and tensor networks for laminate design: A novel approach to stacking sequence retrieval

As with many tasks in engineering, structural design frequently involves navigating complex and computationally expensive problems. A prime example is the weight optimization of laminated composite materials, which to this day remains a formidable task, due to an exponentially large configuration space and non-linear constraints. The rapidly developing field of quantum computation may offer novel approaches for addressing these intricate problems. However, before applying any quantum algorithm to a given problem, it must be translated into a form that is compatible with the underlying operations on a quantum computer. Our work specifically targets stacking sequence retrieval with lamination parameters, which is typically the second phase in a common bi-level optimization procedure for minimizing the weight of composite structures. To adapt stacking sequence retrieval for quantum computational methods, we map the possible stacking sequences onto a quantum state space. We further derive a linear operator, the Hamiltonian, within this state space that encapsulates the loss function inherent to the stacking sequence retrieval problem. Additionally, we demonstrate the incorporation of manufacturing constraints on stacking sequences as penalty terms in the Hamiltonian. This quantum representation is suitable for a variety of classical and quantum algorithms for finding the ground state of a quantum Hamiltonian. For a practical demonstration, we performed numerical state-vector simulations of two variational quantum algorithms and additionally chose a classical tensor network algorithm, the DMRG algorithm, to numerically validate our approach. For the DMRG algorithm, we derived a matrix product operator representation of the loss function Hamiltonian and the penalty terms. Although this work primarily concentrates on quantum computation, the application of tensor network algorithms presents a novel quantum-inspired approach for stacking sequence retrieval.

Global quaternion generalized minimal residual method for generalized coupled Sylvester quaternion matrix equations with application to colour image encryption and decryption

ABSTRACT Sylvester matrix equations play important roles in control and system theory. We consider a class of the generalized coupled Sylvester quaternion matrix equations, which includes a lot of special matrix equations such as Stein matrix equation, Lyapunov matrix equation and Sylvester matrix equation on the quaternion skew field. First, the quaternion Krylov subspace and its F-orthogonal basis are constructed via a new quaternion matrix product and the global quaternion Arnoldi process. Then a global quaternion generalized minimal residual (Gl-QGMRES) method is proposed for solving the generalized coupled Sylvester quaternion matrix equations. The convergence of the proposed method is theoretically analysed. Finally, the effectiveness and feasibility of the proposal are verified by some numerical experiments. As an application of Gl-QGMRES method, we establish a kind of colour image encryption and decryption by embedding watermark images.

Identification and characterization of a small molecule BFstatin inhibiting BrpR, the transcriptional regulator for biofilm formation of Vibrio vulnificus.

Many pathogenic bacteria form biofilms that are resistant to not only host immune defenses but also antibiotics, posing a need for the development of strategies to control biofilms. In this study, to prevent biofilm formation of the fulminating foodborne pathogen Vibrio vulnificus, chemical libraries were extensively screened to identify a small molecule inhibiting the activity of BrpR, a transcriptional regulator for biofilm genes. Accordingly, the BrpR inhibitor BFstatin [N1-(2-chloro-5-fluorophenyl)-N3-propylmalonamide], with a half-maximal effective concentration of 8.01 μM, was identified. BFstatin did not interfere with bacterial growth or exhibit cytotoxicity to the human epithelial cell line. BFstatin directly bound to BrpR and interrupted its binding to the target promoter DNAs of the downstream genes. Molecular dynamics simulation of the interaction between BFstatin and BrpR proposed that BFstatin modifies the structure of BrpR, especially the DNA-binding domain. Transcriptomic analyses revealed that BFstatin reduces the expression of the BrpR regulon including the cabABC operon and brp locus which contribute to the production of biofilm matrix of V. vulnificus. Accordingly, BFstatin diminished the biofilm levels of V. vulnificus by inhibiting the matrix development in a concentration-dependent manner. Altogether, BFstatin could be an anti-biofilm agent targeting BrpR, thereby rendering V. vulnificus more susceptible to host immune defenses and antibiotics.

The Clinical Utility of Powdered and Flowable Matrices in Wound Repair and Tissue Regeneration.

Cellular and matrix-like products come in many forms. Among them, powdered and micronized formulations have become increasingly available and popular owing to their unique properties and advantages. Powders have increased tissue contact which many believe can enhance granulation tissue formation, they fill irregular and deep cavities, and they can be used in concert with sheet-like products and skin grafts for improved healing. Despite their advantages, powdered products do have certain limitations that hinder their use, including poor insurance coverage and a lack of CPT coding for adequate reimbursement in an outpatient setting, making their use primarily limited to the operating room. Also, most published data on powdered products consists of smaller case studies and case series, with few reports evaluating the efficacy and utility of powdered formulations compared to their sheet-like progenitors. In this manuscript, we organize available powdered matrix products by type of substrate: xenograft, allograft, placental-based, and synthetic, and review the data in support of various products in specific wound types. This review of the supporting literature provides the current body of evidence on the utility of powdered matrices in wounds.

Exogenous S1P via S1P receptor 2 induces CTGF expression through Src-RhoA-ROCK-YAP pathway in hepatic stellate cells.

Hepatic fibrosis, a prevalent chronic liver condition, involves excessive extracellular matrix production associated with aberrant wound healing. Hepatic stellate cells (HSCs) play a pivotal role in liver fibrosis, activated by inflammatory factors such as sphingosine 1-phosphate (S1P). Despite S1P's involvement in fibrosis, its specific role and downstream pathway in HSCs remain controversial. In this study, we investigated the regulatory role of S1P/S1P receptor (S1PR) in Hippo-YAP activation in both LX-2 cell lines and primary HSCs. Real-time PCR, western blot, pharmacological inhibitors, siRNAs, and Rho activity assays were adopted to address the molecular mechanisms of S1P mediated YAP activation. Serum and exogenous S1P significantly increased the expression of YAP target genes in HSCs. Pharmacologic inhibitors and siRNA-mediated knockdowns of S1P receptors showed S1P receptor 2 (S1PR2) as the primary mediator for S1P-induced CTGF expression in HSCs. Results using siRNA-mediated knockdown, Verteporfin, and Phospho-Tag immunoblots showed that S1P-S1PR2 signaling effectively suppressed the Hippo kinases cascade, thereby activating YAP. Furthermore, S1P increased RhoA activities in cells and ROCK inhibitors effectively blocked CTGF induction. Cytoskeletal-perturbing reagents were shown to greatly modulate CTGF induction, suggesting the important role of actin cytoskeleton in S1P-induced YAP activation. Exogeneous S1P treatment was enough to increase the expression of COL1A1 and α-SMA, that were blocked by YAP specific inhibitor. Our data demonstrate that S1P/S1PR2-Src-RhoA-ROCK axis leads to Hippo-YAP activation, resulting in the up-regulation of CTGF, COL1A1 and α-SMA expression in HSCs. Therefore, S1PR2 may represent a potential therapeutic target for hepatic fibrosis.

Extracellular matrix production and oxygen diffusion regulate chemotherapeutic response in osteosarcoma spheroids.

Osteosarcoma (OS) survival rates and outcome have not improved in 50 years since the advent of modern chemotherapeutics. Thus, there is a critical need for an improved understanding of the tumor microenvironment to identify better therapies. Extracellular matrix (ECM) deposition and hypoxia are known to abrogate the efficacy of various chemical and cell-based therapeutics. Here, we aim to mechanistically investigate the combinatorial effects of hypoxia and matrix deposition with the use of OS spheroids. We use two murine OS cell lines with differential metastatic potential to form spheroids. We form spheroids of two sizes, use ascorbate-2-phosphate supplementation to enhance ECM deposition, and study cell response under standard (21% O2) and physiologic (5% O2) oxygen tensions. Finally, we examine chemotherapeutic responses to doxorubicin treatment. ECM production and oxygen tension are key determinants of spheroid size through cell organization based on nutrient and oxygen distribution. Interestingly, highly metastatic OS is more susceptible to chemotherapeutics compared to less metastatic OS when matrix production increases. Together, these data suggest that dynamic interactions between ECM production and oxygen diffusion may result in distinct chemotherapeutic responses despite inherent tumor aggressiveness. This work establishes OS spheroids as a valuable tool for early OS tumor formation investigation and holds potential for novel therapeutic target and prognostic indicator discovery.

Uremic Toxin Receptor AhR Facilitates Renal Senescence and Fibrosis via Suppressing Mitochondrial Biogenesis.

Retention of metabolic end-products in the bodily fluids of patients with chronic kidney disease (CKD) may lead to uremia. The uremic toxin indoxyl sulfate (IS), a tryptophan metabolite, is an endogenous ligand of aryl hydrocarbon receptor (AhR). It is clarified that the upregulation and activation of AhR by IS in tubular epithelial cells (TECs) promote renal senescence and fibrosis. Renal TEC-specific knockout of AhR attenuates renal senescence and fibrosis, as well as the suppression of PGC1α-mediated mitochondrial biogenesis in ischemia reperfusion (IR)- or IS-treated CKD mice kidneys. Overexpression of peroxisome proliferator-activated receptor gamma coactivator 1-α (PGC1α) attenuates IS-induced cell senescence and extracellular matrix production in cultured TECs. Mechanistically, AhR is able to interact with PGC1α and promotes the ubiquitin degradation of PGC1α via its E3 ubiquitin ligase activity. In summary, the elevation and activation of AhR by the accumulated uremic toxins in the progression of CKD accelerate renal senescence and fibrosis by suppressing mitochondrial biogenesis via promoting ubiquitination and proteasomal degradation of PGC1α.

Assessment of the Mechanical and Microstructural Performance of Waste Kraft Fibre Reinforced Cement Composite Incorporating Sustainable Eco-Friendly Additives

This study investigates the influence of limestone powder and metakaolin as sustainable eco-friendly additives on the properties and behavior of cementitious composite boards, with a focus on mechanical strength, physical properties, and microstructural characteristics. The experimental investigation begins with the characterization of the raw materials, including limestone powder, and metakaolin, to assess their particle sizes, elemental composition, and microstructural features. Cement composite boards were fabricated using an innovatively developed lab-simulated vacuum dewatering process, by varying the proportions of limestone powder and metakaolin as partial replacements for cement, along with waste kraft fibres as reinforcement. Mechanical testing was conducted to evaluate the flexural strength and behaviour of the composite boards according to standardized procedures. A microstructural analysis was performed using scanning electron microscopy (SEM) to examine the effect of additives on the cementitious matrix, fibrematrix interaction, and hydration products. The findings from the experimental study reveal insights into the influence of limestone powder and metakaolin on the mechanical properties and microstructure of waste kraft fibre-reinforced cement composite boards. Our analysis of the results shows that adding 9% limestone powder as partial cement replacement produces a 24% and 50% enhancement in flexural strength at 7 and 28 days of hydration, while that of metakaolin as partial cement replacement was optimum at 6% with an enhancement of 4% and 36%, respectively, at 7 and 28 days of hydration. The implications of these findings for the development of sustainable cementitious composite are discussed, including the potential benefits of using limestone powder and metakaolin as supplementary cementitious materials in waste kraft fibre-reinforced cement composite boards. Finally, recommendations for optimizing additive proportions are also provided to enhance the understanding and application of these materials in the construction and building industries.

Real-time acid production and extracellular matrix formation in mature biofilms of three Streptococcus mutans strains with special reference to xylitol

BackgroundAcidogenicity and production of an extracellular matrix (ECM) are important virulence factors for the dental caries-associated bacteria, such as Streptococcus mutans, that live in biofilms on tooth surface. The ECM protects the bacteria from the flushing and buffering effects of saliva resulting in highly acidic microenvironments inside the biofilm. Materials and methodsIn this in vitro study, we applied real-time assays to follow biofilm formation and pH decrease in a growth medium and saliva by three S. mutans strains, as well as acid neutralization inside the mature biofilm. Results were compared with the biofilm composition. Effects of a non-fermentable polyol, xylitol, on acid production and acid neutralization in mature biofilms were evaluated by real-time pH measurements and confocal microscopy. ResultsCombination of real-time pH measurements with biofilm accumulation assays revealed growth media dependent differences in the pH decrease and biofilm accumulation, as well as strain differences in acid production and biofilm formation but not in the buffer diffusion through ECM. The presence of xylitol reduced the pH drop during biofilm formation of all strains. In addition, with strain Ingbritt xylitol reduced the amount of ECM in biofilm, which increased the rate of acid neutralization inside the biofilm after buffer exposure. ConclusionOur results stress the importance of biofilm matrix in creating the acidic environment inside a S. mutans biofilm, especially in the presence of saliva. In addition, our results suggest a novel mechanism of xylitol action. The observed increase in the permeability of the S. mutans ECM after xylitol exposure may allow acid-neutralizing saliva to reach deeper layer of the biofilms and thus, in part, explain previous clinical observations of reduced plaque acidogenicity after frequent xylitol use.