Remodeling of extracellular matrix by normal and tumor-associated fibroblasts promotes cervical cancer progression

Background: Comparison of tissue microarray results of 29 cervical cancer and 27 normal cervix tissue samples using immunohistochemistry revealed considerable reorganization of the fibrillar stroma of these tumors. Preliminary densitometry analysis of laminin-1, α -smooth muscle actin (SMA) and fibronectin immunostaining demonstrated 3.8-fold upregulation of laminin-1 and 5.2-fold increase of SMA in the interstitial stroma, indicating that these proteins and the activated fibroblasts play important role in the pathogenesis of cervical cancer. In the present work we investigated the role of normal and tumor-associated fibroblasts. Methods: In vitro models were used to throw light on the multifactorial process of tumor-stroma interaction, by means of studying the cooperation between tumor cells and fibroblasts. Fibroblasts from normal cervix and cervical cancers were grown either separately or in co-culture with CSCC7 cervical cancer cell line. Changes manifest in secreted glycoproteins, integrins and matrix metallo-proteases (MMPs) were explored. Results: While normal fibroblasts produced components of interstitial matrix and TGF- β 1 that promoted cell proliferation, cancer-associated fibroblasts (CAFs) synthesized ample amounts of laminin-1. The following results support the significance of laminin-1 in the invasion of CSCC7 cells: 1.) Tumor-associated fibroblasts produced more laminin-1 and less components of fibrillar ECM than normal cells; 2.) The production of laminin chains was further increased when CSCC7 cells were grown in co-culture with fibroblasts; 3.) CSCC7 cells were capable of increasing their laminin production; 4.) Tumor cells predominantly expressed integrin α 6 β 4 laminin receptors and migrated towards laminin. The integrin profile of both normal and tumor-associated fibroblasts was similar, expressing receptors for fibronectin, vitronectin and osteopontin. MMP-7 secreted by CSCC7 cells was upregulated by the presence of normal fibroblasts, whereas MMP-2 produced mainly by fibroblasts was activated in the presence of CSCC7 cells. Conclusions: Our results indicate that in addition to degradation of the basement membrane, invasion of cervical cancer is accomplished by the remodeling of the interstitial stroma, which process includes decrease and partial replacement of fibronectin and collagens by a laminin-rich matrix

Mechanics and thermodynamics of a new minimal model of the atmosphere

The understanding of the fundamental properties of the climate system has long benefitted from the use of simple numerical models able to parsimoniously represent the essential ingredients of its processes. Here, we introduce a new model for the atmosphere that is constructed by supplementing the now-classic Lorenz ’96 one-dimensional lattice model with temperature-like variables. The model features an energy cycle that allows for energy to be converted between the kinetic form and the potential form and for introducing a notion of efficiency. The model’s evolution is controlled by two contributions—a quasi-symplectic and a gradient one, which resemble (yet not conforming to) a metriplectic structure. After investigating the linear stability of the symmetric fixed point, we perform a systematic parametric investigation that allows us to define regions in the parameters space where at steady-state stationary, quasi-periodic, and chaotic motions are realised, and study how the terms responsible for defining the energy budget of the system depend on the external forcing injecting energy in the kinetic and in the potential energy reservoirs. Finally, we find preliminary evidence that the model features extensive chaos. We also introduce a more complex version of the model that is able to accommodate for multiscale dynamics and that features an energy cycle that more closely mimics the one of the Earth’s atmosphere

Analysis of a bistable climate toy model with physics-based machine learning methods

We propose a comprehensive framework able to address both the predictability of the first and of the second kind for high-dimensional chaotic models. For this purpose, we analyse the properties of a newly introduced multistable climate toy model constructed by coupling the Lorenz ’96 model with a zero-dimensional energy balance model. First, the attractors of the system are identified with Monte Carlo Basin Bifurcation Analysis. Additionally, we are able to detect the Melancholia state separating the two attractors. Then, Neural Ordinary Differential Equations are applied to predict the future state of the system in both of the identified attractors