Matrix mechanics regulates epithelial defence against cancer by tuning dynamic localization of filamin

In epithelia, normal cells recognize and extrude out newly emerged transformed cells by competition. This process is the most fundamental epithelial defence against cancer, whose occasional failure promotes oncogenesis. However, little is known about what factors determine the success or failure of this defence. Here we report that mechanical stiffening of extracellular matrix attenuates the epithelial defence against HRasV12-transformed cells. Using photoconversion labelling, protein tracking, and loss-of-function mutations, we attribute this attenuation to stiffening-induced perinuclear sequestration of a cytoskeletal protein, filamin. On soft matrix mimicking healthy epithelium, filamin exists as a dynamically single population, which moves to the normal cell-transformed cell interface to initiate the extrusion of transformed cells. However, on stiff matrix mimicking fibrotic epithelium, filamin redistributes into two dynamically distinct populations, including a new perinuclear pool that cannot move to the cell-cell interface. A matrix stiffness-dependent differential between filamin-Cdc42 and filamin-perinuclear cytoskeleton interaction controls this distinctive filamin localization and hence, determines the success or failure of epithelial defence on soft versus stiff matrix. Together, our study reveals how pathological matrix stiffening leads to a failed epithelial defence at the initial stage of oncogenesis.

FORC analysis of magnetically soft microparticles embedded in a polymeric elastic environment

First-order reversal curve (FORC) analysis allows one to investigate composite magnetic materials by decomposing the magnetic response of a whole sample into individual responses of the elementary objects comprising the sample. In this work, we apply this technique to analysing silicone elastomer composites reinforced with ferromagnetic microparticles possessing low intrinsic coercivity. Even though the material of such particles does not demonstrate significant magnetic hysteresis, the soft matrix of the elastomers allows for the translational mobility of the particles and enables their magnetomechanical hysteresis which renders into a wasp-waisted major magnetization loop of the whole sample. It is demonstrated that the FORC diagrams of the composites contain characteristic wing features arising from the collective hysteretic magnetization of the magnetically soft particles. The influence of the matrix elasticity and particle concentration on the shape of the wing feature is investigated, and an approach to interpreting experimental FORC diagrams of the magnetically soft magnetoactive elastomers is proposed. The experimental data are in qualitative agreement with the results of the simulation of the particle magnetization process obtained using a model comprised of two magnetically soft particles embedded in an elastic environment.

Stiffness is associated with hepatic stellate cell heterogeneity during liver fibrosis

The fibrogenic wound-healing response in liver increases stiffness. Stiffness mechano-transduction in turn amplifies fibrogenesis. Here, we aimed to understand the distribution of stiffness in fibrotic liver, how it impacts hepatic stellate cell (HSC) heterogeneity and identify mechanisms by which stiffness amplifies fibrogenic responses. Magnetic resonance elastography and atomic force microscopy demonstrated a heterogenous distribution of liver stiffness at macroscopic and microscopic levels, respectively, in a carbon tetrachloride (CCl4) mouse model of liver fibrosis as compared to controls. High stiffness was mainly attributed to extracellular matrix dense areas. To identify a stiffness-sensitive HSC sub-population, we performed scRNA-seq on primary HSCs derived from healthy versus CCl4-treated mice. A sub-cluster of HSCs was matrix-associated with the most upregulated pathway in this sub-population being focal adhesion signaling, including a specific protein termed four and a half LIM domains protein 2 (FHL2). In vitro, FHL2 expression was increased in primary human HSCs cultured on stiff matrix as compared to HSCs on soft matrix. Moreover, FHL2 knockdown inhibited fibronectin and collagen 1 expression, whereas its overexpression promoted matrix production. In summary, we demonstrate stiffness heterogeneity at the whole organ, lobular, and cellular level which drives an amplification loop of fibrogenesis through specific focal adhesion molecular pathways.

Subtraction of soft matrices

In this paper, we introduce subtraction operation notation on the soft matrix of size m×n with its entry on the set {0, 1}. In addition, we studied the characteristics of subtraction operations over intersection and union operations on soft matrices. The result shows the distributive law of subtraction operations over intersection and union operations on the soft matrix. Finally, we discuss the characteristics of De Morgan’s law analogous to set theory.

Decision-Making with Fuzzy Soft Matrix Using a Revised Method: A Case of Medical Diagnosis of Diseases

In this paper, we study the matrix representation of fuzzy soft sets, complement of fuzzy soft sets, product of fuzzy soft matrices and the application of fuzzy soft matrices in medical diagnosis presented by Lavanya and Akila. Additionally, a new method (max-min average) based on fuzzy reference function is introduced instead of the max-product method by Lavanya and Akila to extend Sanchez’s technique for decision making problems in medical diagnosis. Using the same data by Lavanya and Akila, the result shows that the new method gives more information about the medical status of the patients being considered in relation to a set of diseases.

Application of Picture Fuzzy Soft Relations in Multi- altribute Decision Making

In this paper, we rst dene picture fuzzy soft sets (PFSS) and study some of their relevant operations such as subset, equal, complement, AND,OR… and so on. we investigate some theorems on picture fuzzy soft sets based on union and intersection with counter examples. Also we proved a necessary and sufficient condition for the dual laws of PFSS theory. Finaly, we then introduce an algorithum based on relational picture fuzzy soft matrix to solve decision making problems.

Soft-ANN based correlation for air-water two-phase flow pressure drop estimation in a vertical mini-channel

In this paper, an Artificial Neural Network soft matrix correlation to estimate the pressure drop of air-water two-phase flow is developed. The applicability of the model is extended by using dimensionless physical numbers as inputs (Air-Reynolds number, Water-Reynolds number, and the ratio of Air Inertial Forces to Water Inertial Forces), so the model can be implemented for vertical pipes with the proper combination of diameter-velocity-density-viscosity allowing estimations of dimensional numbers within the range of: Air-Reynolds numbers (430–6100), Water-Reynolds number (2400–7200), and Air-Water-Inertial forces ratio (1.6–1834), including the diameter range from 3 to 28 mm. Experimental measurements of frictional pressure drop of water-air mixtures are determined at different conditions. A search of the most suitable density, viscosity, and friction models was conducted and used in the model. The performance of the proposed ANN correlation is compared against published expressions showing good approximation to experimental data; results indicate that the most used correlations are within a mean relative error ( mre) of 23.9–30.7%, while the proposed ANN has a mre = 0.9%. Two additional features are discussed: i) the applicability and generality of the ANN using untrained data, ii) the applicability in laminar, transitional, and turbulent flow regimen. To take the approach beyond a robust performance mapping, the methodology to translate the ANN into a programmable equation is presented.

Neutrosophic Hypersoft Matrices with Application to Solve Multiattributive Decision-Making Problems

The concept of the neutrosophic hypersoft set (NHSS) is a parameterized family that deals with the subattributes of the parameters and is a proper extension of the neutrosophic soft set to accurately assess the deficiencies, anxiety, and uncertainty in decision-making. Compared with existing research, NHSS can accommodate more uncertainty, which is the most significant technique for describing fuzzy information in the decision-making process. The main objective of the follow-up study is to develop the theory of neutrosophic hypersoft matrix (NHSM). The NHSM is the generalized form of a neutrosophic soft matrix (NSM). Some fundamental operations and score function for NHSMs have been introduced with their desirable properties. Furthermore, we introduce the logical operators such as OR-operator and AND-operator with their fundamental properties in the following research. The necessity and possibility operations for NHSMs have been established. Utilizing the developed score function, a decision-making methodology has been developed to solve the multiattribute decision-making (MADM) problem. To ensure the validity of the proposed approach, a numerical illustration has been described for the selection of competent faculty member. The practicality and effectiveness of the current approach are proved through comparative analysis with the assistance of some existing studies.