Search results for "Matrix"

Biofabrication of 3D tumor models in cancer research

2020

Abstract Tumors are complex tissues in which cancer cells are interwoven with fibroblasts, endothelial cells, pericytes, and inflammatory cells; these cells and the extracellular matrix constitute the tumor microenvironment (TME). The TME can modulate the behavior of tumor cells in terms of capacity to invade neighboring or distant tissues and drug resistance, by secreting tumor-promoting growth factors and cytokines. The poor efficacy of many anticancer drugs in clinical trials can be partly justified by the lack of predictive preclinical models. Prior to in vivo testing, biofabrication of tools for investigation in three-dimensional (3D) could be useful. Indeed, cells grown in 3D matrices…

P–543 Inhibition of cell proliferation and extracellular matrix formation in human uterine leiomyomas by 5-aza–2’-deoxycitidine via Wnt/ β-catenin pa…

2021

Abstract Study question Is DNA methylation reversion through DNA methyltransferases (DNMT) inhibitors, such as 5-aza–2’-deoxycitidine, a potential therapeutic option for treatment of patients with uterine leiomyomas (UL)? Summary answer 5-aza–2’-deoxycitidine reduces proliferation and extracellular matrix (ECM) formation by inhibition of Wnt/ β-catenin pathway on UL cells, suggesting DNMT inhibitors as an option to treat UL. What is known already: UL is a multifactorial disease with an unclear pathogenesis and inaccurate treatment. Aberrant DNA methylation have been found in UL compared to myometrium (MM) tissue, showing hypermethylation of tumor suppressor genes, which contributes to the d…

Yeast Cell Wall Glycoproteins

1991

In higher cells, glycoproteins play a variety of functions as surface receptors, cell-cell mediators, carriers of enzyme activities, components of the extracellular matrix, etc. In most glycoproteins, the protein moiety will be the functional part whereas the carbohydrate moiety would contribute to the attainment of an adequate tertiary structure, modify the glycoprotein molecule making it more resistant to degradation, and facilitate its secretion.

Glycoconjugate expression in the extracellular matrix of the mouse lung (87.7)

2014

Biochemical composition of muscle extracellular matrix: the effect of loading

2000

Collagen plays an important role in skeletal muscle both during muscle differentiation and normal muscle growth, and also serves a role as a supportive structure. It is the most abundant protein of the extracellular matrix and of the 19 distinct collagen types, types I, III, IV and V are the dominating ones in skeletal muscle. Both collagen synthesis as well as degradation is influenced by either physical loading or immobilization in skeletal muscle, and recent methods have allowed for greater understanding of the posttranslational processing of collagen.

Using Hankel matrices for dynamics-based facial emotion recognition and pain detection

2015

This paper proposes a new approach to model the temporal dynamics of a sequence of facial expressions. To this purpose, a sequence of Face Image Descriptors (FID) is regarded as the output of a Linear Time Invariant (LTI) system. The temporal dynamics of such sequence of descriptors are represented by means of a Hankel matrix. The paper presents different strategies to compute dynamics-based representation of a sequence of FID, and reports classification accuracy values of the proposed representations within different standard classification frameworks. The representations have been validated in two very challenging application domains: emotion recognition and pain detection. Experiments on…

A General Framework for Complex Network-Based Image Segmentation

2019

International audience; With the recent advances in complex networks theory, graph-based techniques for image segmentation has attracted great attention recently. In order to segment the image into meaningful connected components, this paper proposes an image segmentation general framework using complex networks based community detection algorithms. If we consider regions as communities, using community detection algorithms directly can lead to an over-segmented image. To address this problem, we start by splitting the image into small regions using an initial segmentation. The obtained regions are used for building the complex network. To produce meaningful connected components and detect …

Cyclic Complexity of Words

2014

We introduce and study a complexity function on words $c_x(n),$ called \emph{cyclic complexity}, which counts the number of conjugacy classes of factors of length $n$ of an infinite word $x.$ We extend the well-known Morse-Hedlund theorem to the setting of cyclic complexity by showing that a word is ultimately periodic if and only if it has bounded cyclic complexity. Unlike most complexity functions, cyclic complexity distinguishes between Sturmian words of different slopes. We prove that if $x$ is a Sturmian word and $y$ is a word having the same cyclic complexity of $x,$ then up to renaming letters, $x$ and $y$ have the same set of factors. In particular, $y$ is also Sturmian of slope equ…

CLEAR: Covariant LEAst-Square Refitting with Applications to Image Restoration

2017

International audience; In this paper, we propose a new framework to remove parts of the systematic errors affecting popular restoration algorithms, with a special focus for image processing tasks. Generalizing ideas that emerged for $\ell_1$ regularization, we develop an approach re-fitting the results of standard methods towards the input data. Total variation regularizations and non-local means are special cases of interest. We identify important covariant information that should be preserved by the re-fitting method, and emphasize the importance of preserving the Jacobian (w.r.t. the observed signal) of the original estimator. Then, we provide an approach that has a ``twicing'' flavor a…

Extending the Unmixing methods to Multispectral Images

2021

In the past few decades, there has been intensive research concerning the Unmixing of hyperspectral images. Some methods such as NMF, VCA, and N-FINDR have become standards since they show robustness in dealing with the unmixing of hyperspectral images. However, the research concerning the unmixing of multispectral images is relatively scarce. Thus, we extend some unmixing methods to the multispectral images. In this paper, we have created two simulated multispectral datasets from two hyperspectral datasets whose ground truths are given. Then we apply the unmixing methods (VCA, NMF, N-FINDR) to these two datasets. By comparing and analyzing the results, we have been able to demonstrate some…