Proper Matrix Research Articles

Sulfation of glycosaminoglycans depends on the catalytic activity of lithium-inhibited phosphatase BPNT2 in vitro

Golgi-resident bisphosphate nucleotidase 2 (BPNT2) is a member of a family of magnesium-dependent, lithium-inhibited phosphatases that share a three-dimensional structural motif that directly coordinates metal binding to effect phosphate hydrolysis. BPNT2 catalyzes the breakdown of 3′-phosphoadenosine-5′-phosphate, a by-product of glycosaminoglycan (GAG) sulfation. KO of BPNT2 in mice leads to skeletal abnormalities because of impaired GAG sulfation, especially chondroitin-4-sulfation, which is critical for proper extracellular matrix development. Mutations in BPNT2 have also been found to underlie a chondrodysplastic disorder in humans. The precise mechanism by which the loss of BPNT2 impairs sulfation remains unclear. Here, we used mouse embryonic fibroblasts (MEFs) to test the hypothesis that the catalytic activity of BPNT2 is required for GAG sulfation in vitro. We show that a catalytic-dead Bpnt2 construct (D108A) does not rescue impairments in intracellular or secreted sulfated GAGs, including decreased chondroitin-4-sulfate, present in Bpnt2-KO MEFs. We also demonstrate that missense mutations in Bpnt2 adjacent to the catalytic site, which are known to cause chondrodysplasia in humans, recapitulate defects in overall GAG sulfation and chondroitin-4-sulfation in MEF cultures. We further show that treatment of MEFs with lithium (a common psychotropic medication) inhibits GAG sulfation and that this effect depends on the presence of BPNT2. Taken together, this work demonstrates that the catalytic activity of an enzyme potently inhibited by lithium can modulate GAG sulfation and therefore extracellular matrix composition, revealing new insights into lithium pharmacology.

Luminescent lanthanide nanocomposites in thermometry: Chemistry of dopant ions and host matrices

• Current progress on luminescent lanthanide nanocomposites for thermal sensing. • Effect of host matrices on thermometry. • Impact of dopant ions and their emission transition on thermal sensitivity. • Modern challenges in nanothermometry development. Recently, there has been observed huge progress in the advancement of remote optical nanothermometry, as it plays a vital role in remote, noninvasive, and remote temperature sensing, which is especially important for various bio-applications, e.g., in theranostics and photodynamic therapy. This is because the luminescence thermometry technique can accurately identify the temperature distribution in the molecular objectives or the biological body. Especially, the use of temperature-induced change in the luminescence intensity ratio (LIR) of two thermally coupled emission bands of lanthanide (Ln 3+ ) ions, embedded in some inorganic nanoparticles (NPs), allows temperature representing of a single living cell. In this review, we comprehensively summarized the concept of luminescence optical thermometry, photophysical properties of Ln 3+ ions, synthesis process, and various hosts doped with different Ln 3+ ions, in which they act as either sensitizers or activators. Selecting a proper host matrix is an efficient route to achieve the high performance of optical nanothermometers since it takes an important role in determining the luminescent efficiency. Initially, we defined and compared various classes of optical thermometers based on diverse spectroscopic parameters, such as emission intensity, band intensity ratio, bandwidth, band shape, polarization, spectral shift, and luminescence lifetime. Furthermore, we emphasized the most common approach for temperature monitoring, which is based on the thermally coupled levels (TCLs) of Ln 3+ ions, by exploiting the LIR technique, since it can provide a fast response with high accuracy, precision, and resolution. Additionally, this review also discusses the recent progress in diverse strategies to boost thermometric performances, such as changing dopants and utilizing various energy transfer mechanisms. Ultimately, we summed up the recent research achievements through analyzing the current research strategies, discussing future guidelines, as well as exploring the major difficulties for further advancement in the area.

Intrinsic and growth-mediated cell and matrix specialization during murine meniscus tissue assembly.

The incredible mechanical strength and durability of mature fibrous tissues and their extremely limited turnover and regenerative capacity underscores the importance of proper matrix assembly during early postnatal growth. In tissues with composite extracellular matrix (ECM) structures, such as the adult knee meniscus, fibrous (Collagen-I rich), and cartilaginous (Collagen-II, proteoglycan-rich) matrix components are regionally segregated to the outer and inner portions of the tissue, respectively. While this spatial variation in composition is appreciated to be functionally important for resisting complex mechanical loads associated with gait, the establishment of these specialized zones is poorly understood. To address this issue, the following study tracked the growth of the murine meniscus from its embryonic formation through its first month of growth, encompassing the critical time-window during which animals begin to ambulate and weight bear. Using histological analysis, region specific high-throughput qPCR, and Col-1, and Col-2 fluorescent reporter mice, we found that matrix and cellular features defining specific tissue zones were already present at birth, before continuous weight-bearing had occurred. These differences in meniscus zones were further refined with postnatal growth and maturation, resulting in specialization of mature tissue regions. Taken together, this work establishes a detailed timeline of the concurrent spatiotemporal changes that occur at both the cellular and matrix level throughout meniscus maturation. The findings of this study provide a framework for investigating the reciprocal feedback between cells and their evolving microenvironments during assembly of a mechanically robust fibrocartilage tissue, thus providing insight into mechanisms of tissue degeneration and effective regenerative strategies.

Physico-chemical modification of gelatine for the improvement of 3D printability of oxidized alginate-gelatine hydrogels towards cartilage tissue engineering

This work explored 3D printing to mimic the intrinsic hierarchical structure of natural articular cartilage. Alginate di-aldehyde- gelatine (ADA-GEL) hydrogel was used as ink to create hierarchically ordered scaffolds. In comparison to previously reported ADA-GEL compositions, we introduce a modified formulation featuring increased amounts of thermally modified gelatine. Gelatine was degraded by hydrolysis which resulted in tailorable printability characteristics further substantiated by rheological analysis. ADA (3.75 %w/v)-GEL (7.5 %w/v) with gelatine modified at 80 °C for 3 h could be printed in hierarchical complex structures reaching scaffold heights of over 1 cm. The hierarchical structure of the scaffolds was confirmed via µCT analysis. To examine mechanical properties as well as the suitability of the hydrogel as a proper matrix for cell seeding and encapsulation, nanoindentation was performed. Elastic moduli in the range of ~ 5 kPa were measured. Gelatine heat pre-treatment resulted in modifiable mechanical and rheological characteristics of ADA-GEL. In summary, this study demonstrates the possibility to enhance the printability of ADA-GEL hydrogels to fabricate hierarchical scaffold structures with shape stability and fidelity, without the necessity to change the initial hydrogel chemistry by the use of additives or crosslinkers, providing a valuable approach for fabrication of designed scaffolds for cartilage tissue engineering.

Perfusion Decellularization of Extrahepatic Bile Duct Allows Tissue-Engineered Scaffold Generation by Preserving Matrix Architecture and Cytocompatibility

Reconstruction of bile ducts damaged remains a vexing medical problem. Surgeons have few options when it comes to a long segment reconstruction of the bile duct. Biological scaffolds of decellularized biliary origin may offer an approach to support the replace of bile ducts. Our objective was to obtain an extracellular matrix scaffold derived from porcine extrahepatic bile ducts (dECM-BD) and to analyze its biological and biochemical properties. The efficiency of the tailored perfusion decellularization process was assessed through histology stainings. Results from 4’-6-diamidino-2-phenylindole (DAPI), Hematoxylin and Eosin (H&E) stainings, and deoxyribonucleic acid (DNA) quantification showed proper extracellular matrix (ECM) decellularization with an effectiveness of 98%. Immunohistochemistry results indicate an effective decrease in immunogenic marker as human leukocyte antigens (HLA-A) and Cytokeratin 7 (CK7) proteins. The ECM of the bile duct was preserved according to Masson and Herovici stainings. Data derived from scanning electron microscopy (SEM) and thermogravimetric analysis (TGA) showed the preservation of the dECM-BD hierarchical structures. Cytotoxicity of dECM-BD was null, with cells able to infiltrate the scaffold. In this work, we standardized a decellularization method that allows one to obtain a natural bile duct scaffold with hierarchical ultrastructure preservation and adequate cytocompatibility.

A hierarchy of nonlocal nonlinear evolution equations and [formula omitted]-dressing method

Starting from the matrix ∂̄ problem, the dressing method is employed to investigate the nonlocal nonlinear evolution equations. A hierarchy of nonlocal nonlinear evolution equations associated with 2 × 2 matrix problem, which contains the nonlocal extended modified Korteweg–de Vries (emKdV) equation, is derived via using recursive operator for the first time. Finally, via selecting a proper spectral transformation matrix, the N-soliton solutions of the nonlocal emKdV equation are constructed based on the matrix ∂̄ problem.

An inverse optimization approach for a capacitated vehicle routing problem

The capacitated vehicle routing problem studied in this paper stems from an e-commerce company in China. Efficient delivery is crucial for the logistic service of the company. It was observed that experienced drivers (experts) planned better delivery routes than those from optimization tools. This is largely due to the fact that the objectives (or the cost matrices) in real life are highly complicated and the experts use more practical objectives while making decisions. In this paper, we propose an inverse optimization formulation to derive a proper cost matrix by learning from the experts experience. Thus, the routing model with respect to the learned cost matrix could provide solutions as good as those given by experts. A multiplicative weights updates algorithm is applied to achieve a fast and convergent learning process. Experimental analyses based on randomly generated instances and real-world instances demonstrate the effectiveness of the approach.

Early satellite cell communication creates a permissive environment for long-term muscle growth

SummaryUsing in vivo muscle stem cell (satellite cell)-specific extracellular vesicle (EV) tracking, satellite cell depletion, in vitro cell culture, and single-cell RNA sequencing, we show satellite cells communicate with other cells in skeletal muscle during mechanical overload. Early satellite cell EV communication primes the muscle milieu for proper long-term extracellular matrix (ECM) deposition and is sufficient to support sustained hypertrophy in adult mice, even in the absence of fusion to muscle fibers. Satellite cells modulate chemokine gene expression across cell types within the first few days of loading, and EV delivery of miR-206 to fibrogenic cells represses Wisp1 expression required for appropriate ECM remodeling. Late-stage communication from myogenic cells during loading is widespread but may be targeted toward endothelial cells. Satellite cells coordinate adaptation by influencing the phenotype of recipient cells, which extends our understanding of their role in muscle adaptation beyond regeneration and myonuclear donation.

The effect of adding reduced graphene oxide to electrospun polycaprolactone scaffolds on MG-63 cells activity

While providing a proper matrix for cellular responses, bone tissue engineering scaffolds can deal with the shortcomings of conventional treatment methods and enhance bone regeneration. In the current study, graphene oxide (GO) nanoparticles were reduced using L-ascorbic acid, a green reductant. Electrospun polycaprolactone (PCL) and polycaprolactone-reduced graphene oxide (PCL/rGO) scaffolds were fabricated. Fourier transform infrared spectroscopy confirmed the correct synthesis of reduced graphene oxide (rGO). The addition of rGO to electrospun PCL has increased the fiber diameter and surface roughness. Mechanical properties evaluation in a dry environment indicated that elastic modulus and ultimate tensile strength declined in PCL/rGO scaffolds while strain at break improved; however, all mechanical values decreased in wet conditions. Studies on bioactivity suggest that apatite deposition requires time to occur on PCL/rGO scaffolds in vitro. This phenomenon was confirmed by Ca/P ratios obtained from EDX quantitive data. Furthermore, the degradation rate of electrospun PCL accelerated in the scaffolds enriched with rGO. Biological evaluations such as cell viability, cell attachment, and alkaline phosphatase activity were carried out using MG-63 cell lines. A significant difference has been observed in cell viability and alkaline phosphatase activity in the PCL scaffold containing 1 wt% rGO compared to pure PCL (P < 0.05). Overall, results indicated the critical correlation between rGO dosage in electrospun PCL scaffolds and MG-63 cell behavior for bone tissue applications.

Time-and-Frequency Hybrid Multiplexing for Flexible Ambiguity Controls of DFT-coded MIMO OFDM Radar

A time-and-frequency hybrid multiplexing technique for a multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) radar is proposed. Discrete Fourier transform (DFT)-coded OFDM waveforms are introduced, which allow it to be free from range-dependent angle errors. These are readily used to provide both time-domain multiplexing and frequency-domain multiplexing in the MIMO OFDM radar. The DFT- coded frequency-domain multiplexing shortens the maximum unambiguous range, while the DFT- coded time-domain multiplexing lowers the maximum Doppler ambiguity. A hybrid of both domain multiplexing techniques can mitigate the respective limitations by adaptively selecting the proper DFT matrix size in each multiplexing domain. This allows to solve the intrinsic range and Doppler ambiguity problems of MIMO radars by controlling the hybrid ratio of the two kinds of DFT- code based multiplexing methods. Range-Doppler and range-angle maps of four examples with different hybrid multiplexing ratios are simulated with a MIMO OFDM radar numerical platform.

Real-Time Implementation of Extended Kalman Filter Observer With Improved Speed Estimation for Sensorless Control

This work presents an investigation on Improved Extended Kalman Filter (IEKF) performance for induction motor drive without a speed sensor. The performance of a direct sensorless vector-controlled system through simulation and experimental work is tested. The proposed observer focuses on estimating rotor flux and mechanical speed of rotor from the stationary axis components. Extended Kalman Filters’ estimation performance depends on the system matrix’s proper value ( $Q$ ) and measurement error matrix ( $R$ ). These matrices are assumed to be persistent and are calculated by the trial-and-error method. But, the operating environment affects these matrix values. They must be updated based on the prevailing operating conditions to get high speed and accurate estimates. The values of Q and R in the Improved EKF (IEKF) algorithm are obtained using the genetic algorithm. Besides, IEKF is incorporated to reduce in computational burden for real-time applications.

Sparse decision feedback equalization for underwater acoustic channel based on minimum symbol error rate

Abstract Underwater Acoustic Channels (UAC) have inherent sparse characteristics. The traditional adaptive equalization techniques do not utilize this feature to improve the performance. In this paper we consider the Variable Adaptive Subgradient Projection (V-ASPM) method to derive a new sparse equalization algorithm based on the Minimum Symbol Error Rate (MSER) criterion. Compared with the original MSER algorithm, our proposed scheme adds sparse matrix to the iterative formula, which can assign independent step-sizes to the equalizer taps. How to obtain such proper sparse matrix is also analyzed. On this basis, the selection scheme of the sparse matrix is obtained by combining the variable step-sizes and equalizer sparsity measure. We call the new algorithm Sparse-Control Proportional-MSER (SC-PMSER) equalizer. Finally, the proposed SC-PMSER equalizer is embedded into a turbo receiver, which perform turbo decoding, Digital Phase-Locked Loop (DPLL), time-reversal receiving and multi-reception diversity. Simulation and real-field experimental results show that the proposed algorithm has better performance in convergence speed and Bit Error Rate (BER).

Experimental Study On Partially Replaced Concrete With Automobile Industries Wastes

In recent days, the major threat to our environment is waste management. As a contribution to save our environment many research works are happening to utilize waste in their manufacturing process to reduce waste as well as reducing the cost involved in the process. Waste utilization will partially help us to protect our environment. In this paper, for manufacturing concrete with partially replaced fine aggregate is experimented. The objective is to reuse the locally available polypropylene fibre generated as waste by automobile industries. The adhesion between polypropylene fibre and cement matrix is considered as an important factor. To give proper matrix between the fibre and cement, shredded polypropylene fibre is used as partially replaced fine aggregate. The replacement percentages used are 20%, 40% and 60%. The specimens were prepared with water cement ratio 0.5 and tested after 7days and 24 days of curing period. The influences of polypropylene fibre in concrete in fresh and hardened state are compared with conventional concrete properties. The results obtained shows increase in the strength and workability property for 20% replacement of polypropylene fibre as fine aggregate in concrete. Hence the disposal of polypropylene waste from automobile industry can effectively be used in shredded form as partial replacement of fine aggregate in concrete.

Detect Professional Malicious User With Metric Learning in Recommender Systems

In e-commerce, online retailers are usually suffering from professional malicious users (PMUs), who utilize negative reviews and low ratings to their consumed products on purpose to threaten the retailers for illegal profits. PMUs are difficult to be detected because they utilize masking strategies to disguise themselves as normal users. Specifically, there are three challenges for PMU detection: 1) professional malicious users do not conduct any abnormal or illegal interactions (they never concurrently leave too many negative reviews and low ratings at the same time), and they conduct masking strategies to disguise themselves. Therefore, conventional outlier detection methods are confused by their masking strategies. 2) the PMU detection model should take both ratings and reviews into consideration, which makes PMU detection a multi-modal problem. 3) there are no datasets with labels for professional malicious users in public, which makes PMU detection an unsupervised learning problem. To this end, we propose an unsupervised multi-modal learning model: MMD, which employs Metric learning for professional Malicious users Detection with both ratings and reviews. MMD first utilizes a modified RNN to project the informational review into a sentiment score, which jointly considers the ratings and reviews. Then professional malicious user profiling (MUP) is proposed to catch the sentiment gap between sentiment scores and ratings. MUP filters the users and builds a candidate PMU set. We apply a metric learning-based clustering to learn a proper metric matrix for PMU detection. Finally, we can utilize this metric and labeled users to detect PMUs. Specifically, we apply the attention mechanism in metric learning to improve the model’s performance. The extensive experiments in four datasets demonstrate that our proposed method can solve this unsupervised detection problem. Moreover, the performance of the state-of-the-art recommender models is enhanced by taking MMD as a preprocessing stage.

Applications of Decision Theory in Real Life and Business Statistics Problems

The Success or failure for any individual organization experiences depends to large extent on the ability of making positive and acceptable decisions at right time. To obtain such decision in result oriented approach different components of Decision Theory provides the direction to finalize the correct approach in Tree method. We can easily identify the problem and also the events and courses of action available to the decision maker. Provides the proper Payoff matrix through Decision Theory. We will compute the optimum stock to minimize expected cost using decision theory and tree method. It also provides the Under certainty and decision making under risk factors. Decision making under certainty and decision making under uncertainty will also decided in this study of manuscript. Maximax or Minimin Criterion, Pessimism Criterion as Maximin or Minimax also evaluated through Decision Theory approach. The entire Research Manuscript provides the Significance Decision Theory. We can understand the complete scope of Decision Theory in real life problems, we can understand the marginal analysis can solve the uncertainty problems, It also explains the Decision Tree approach in graphic representation of the decision process indicating decision alternatives.

3D Printing Decellularized Extracellular Matrix to Design Biomimetic Scaffolds for Skeletal Muscle Tissue Engineering

Functional engineered muscles are still a critical clinical issue to be addressed, although different strategies have been considered so far for the treatment of severe muscular injuries. Indeed, the regenerative capacity of skeletal muscle (SM) results inadequate for large-scale defects, and currently, SM reconstruction remains a complex and unsolved task. For this aim, tissue engineered muscles should provide a proper biomimetic extracellular matrix (ECM) alternative, characterized by an aligned/microtopographical structure and a myogenic microenvironment, in order to promote muscle regeneration. As a consequence, both materials and fabrication techniques play a key role to plan an effective therapeutic approach. Tissue-specific decellularized ECM (dECM) seems to be one of the most promising material to support muscle regeneration and repair. 3D printing technologies, on the other side, enable the fabrication of scaffolds with a fine and detailed microarchitecture and patient-specific implants with high structural complexity. To identify innovative biomimetic solutions to develop engineered muscular constructs for the treatment of SM loss, the more recent (last 5 years) reports focused on SM dECM-based scaffolds and 3D printing technologies for SM regeneration are herein reviewed. Possible design inputs for 3D printed SM dECM-based scaffolds for muscular regeneration are also suggested.

Incremental Matrix-Based Subspace Method for Matrix-Based Feature Extraction

The matrix-based features can provide valid and interpretable information for matrix-based data such as image. Matrix-based kernel principal component analysis (MKPCA) is a way for extracting matrix-based features. The extracted matrix-based feature is useful to both dimension reduction and spatial statistics analysis for an image. In contrast, the efficiency of MKPCA is highly restricted by the dimension of the given matrix data and the size of the training set. In this paper, an incremental method to extract features of a matrix-based dataset is proposed. The method is methodologically consistent with MKPCA and can improve efficiency through incrementally selecting the proper projection matrix of the MKPCA by rotating the current subspace. The performance of the proposed method is evaluated by performing several experiments on both point and image datasets.

Fast and [formula omitted]-optimal recovery for periodic nonuniformly sampled bandlimited signal

Uniformly-sampled sequence reconstruction from periodic nonuniform samples is addressed. In this problem setting, a bandlimited continuous-time signal is sampled with the same rate and different time offsets to obtain the periodic nonuniform samples, in which time offset information is unknown. We use a modified sequential forward selection algorithm to determine the sampling pattern corresponding to the time offset information, aiming to keep the condition number of the related matrix as small as possible. In our proposed algorithm, the reconstruction is formulated as a L2-norm optimization problem. Besides, proper matrix partition is included to reduce the complexity of large matrix pseudo-inverse. Numerical examples are presented to demonstrate the effectiveness of the derived reconstruction algorithm and its stability problem, even in the presence of noise.

Two constructive proofs on d-majorization and thermo-majorization

Two constructive proofs on d-majorization and thermo-majorization are provided. In the first part, we present a diagrammatic proof of the equivalence between d-majorization and the existence of a proper stochastic matrix. We explicitly construct the desired stochastic matrix by using a graphical argument. In the second part, we present a constructive proof of the equivalence between the Gibbs-preserving map and thermal operation in classical systems. We construct the desired thermal operation and a heat bath which emulates any Gibbs-preserving map with arbitrary accuracy.

Role of collagen XII in skin homeostasis and repair

Skin integrity and function depends to a large extent on the composition of the extracellular matrix, which regulates tissue organization. Collagen XII is a homotrimer with short collagenous domains that confer binding to the surface of collagen I-containing fibrils and extended flexible arms, which bind to non-collagenous matrix components. Thereby, collagen XII helps to maintain collagen suprastructure and to absorb stress. Mutant or absent collagen XII leads to reduced muscle and bone strength and lax skin, whereas increased collagen XII amounts are observed in tumor stroma, scarring and fibrosis.This study aimed at uncovering in vivo mechanisms by which collagen XII may achieve these contrasting outcomes. We analyzed skin as a model tissue that contains abundant fibrils, composed of collagen I, III and V with collagen XII decorating their surface, and which is subject to mechanical stress. The impact of different collagen XII levels was investigated in collagen XII-deficient (Col12-KO) mice and in mice with collagen XII overexpression in the dermis (Col12-OE). Unchallenged skin of these mice was histologically inconspicuous, but at the ultrastructural level revealed distinct aberrations in collagen network suprastructure. Repair of excisional wounds deviated from controls in both models by delayed healing kinetics, which was, however, caused by completely different mechanisms in the two mouse lines. The disorganized matrix in Col12-KO wounds failed to properly sequester TGFβ, resulting in elevated numbers of myofibroblasts. These are, however, unable to contract and remodel the collagen XII-deficient matrix. Excess of collagen XII, in contrast, promotes persistence of M1-like macrophages in the wound bed, thereby stalling the wounds in an early inflammatory stage of the repair process and delaying healing.Taken together, we demonstrate that collagen XII is a key component that assists in orchestrating proper skin matrix structure, controls growth factor availability and regulates cellular composition and function. Together, these functions are pivotal for re-establishing homeostasis after injury.