Predicting and explaining nonlinear material response using deep Physically Guided Neural Networks with Internal Variables

Nonlinear materials are often difficult to model with classical state model theory because they have a complex and sometimes inaccurate physical and mathematical description or we simply do not know how to describe such materials in terms of relations between external and internal variables. In many disciplines, Neural Network methods have arisen as powerful tools to identify very complex and non-linear correlations. In this work, we use the very recently developed concept of Physically Guided Neural Networks with Internal Variables (PGNNIV) to discover constitutive laws using a model-free approach and training solely with measured force-displacement data. PGNNIVs make a particular use of the physics of the problem to enforce constraints on specific hidden layers and are able to make predictions without internal variable data. We demonstrate that PGNNIVs are capable of predicting both internal and external variables under unseen load scenarios, regardless of the nature of the material considered (linear, with hardening or softening behavior and hyperelastic), unravelling the constitutive law of the material hence explaining its nature altogether, placing the method in what is known as eXplainable Artificial Intelligence (XAI).Comment: Main text: 25 pages, 6 figures. Appendices: 13 pages, 12 figure

Altered Mechano-Electrochemical Behavior of Articular Cartilage in Populations with Obesity

Obesity, one of the major problems in modern society, adversely affects people’s health and increases the risk of suffering degeneration in supportive tissues such as cartilage, which loses its ability to support and distribute loads. However, no specific research regarding obesity-associated alterations in the mechano-electrochemical cartilage environment has been developed. Such studies could help us to understand the first signs of cartilage degeneration when body weight increases and to establish preventive treatments to avoid cartilage deterioration. In this work, a previous mechano-electrochemical computational model has been further developed and employed to analyze and quantify the effects of obesity on the articular cartilage of the femoral hip. A comparison between the obtained results of the healthy and osteoarthritic cartilage has been made. It shows that behavioral patterns of cartilage, such as ion fluxes and cation distribution, have considerable similarities with those obtained for the early stages of osteoarthritis. Thus, an increment in the outgoing ion fluxes is produced, resulting in lower cation concentrations in all the cartilage layers. These results suggest that people with obesity, i.e. a body mass index greater than 30 kg/m2, should undergo preventive treatments for osteoarthritis to avoid homeostatic alterations and, subsequent, tissue deterioration

Analysis and Curation of the Database of a Colo-Rectal Cancer Screening Program

Data collection in health programs databases is prone to errors that might hinder its use to identify risk indicators and to support optimal decision making in health services. This is the case, in colo-rectal cancer (CRC) screening programs, when trying to optimize the cut-off point to select the patients who will undergo a colonoscopy, especially when having insufficient offer of colonoscopies or temporary excessive demand. It is necessary therefore to establish “good practice” guidelines for data collection, management and analysis. With the aim of improving the redesign of a regional CRC screening program platform, we performed an exhaustive analysis of the data collected, proposing a set of recommendations for its correct maintenance. We also carried out the curation of the available data in order to finally have a clean source of information that would allow proper future analyses. We present here the result of such study, showing the importance of the design of the database and of the user interface to avoid redundancies keeping consistency and checking known correlations, with the final aim of providing quality data that permit to take correct decisions

Inhomogeneous response of articular cartilage:a three-1 dimensional multiphasic heterogeneous study

Articular cartilage exhibits complex mechano-electrochemical behaviour due to its anisotropy, inhomogeneity and material non-linearity. In this work, the thickness and radial dependence of cartilage properties are incorporated into a 3D mechano-electrochemical model to explore the relevance of heterogeneity in the behaviour of the tissue. The model considers four essential phenomena: (i) osmotic pressure, (ii) convective and diffusive processes, (iii) chemical expansion and (iv) three-dimensional through-the-thickness heterogeneity of the tissue. The need to consider heterogeneity in computational simulations of cartilage behaviour and in manufacturing biomaterials mimicking this tissue is discussed. To this end, healthy tibial plateaus from pigs were mechanically and biochemically tested in-vitro. Heterogeneous properties were included in the mechano-electrochemical computational model to simulate tissue swelling. The simulation results demonstrated that swelling of the heterogeneous samples was significantly lower than swelling under homogeneous and isotropic conditions. Furthermore, there was a significant reduction in the flux of water and ions in the former samples. In conclusion, the computational model presented here can be considered as a valuable tool for predicting how the variation of cartilage properties affects its behaviour, opening up possibilities for exploring the requirements of cartilage-mimicking biomaterials for tissue engineering. Besides, the model also allows the establishment of behavioural patterns of swelling and of water and ion fluxes in articular cartilage

Glioblastoma on a microfluidic chip: Generating pseudopalisades and enhancing aggressiveness through blood vessel obstruction events

Background: Glioblastoma (GBM) is one of the most lethal tumor types. Hypercellular regions, named pseudo- palisades, are characteristic in these tumors and have been hypothesized to be waves of migrating glioblastoma cells.These “waves” of cells are thought to be induced by oxygen and nutrient depletion caused by tumor-induced blood vessel occlusion. Although the universal presence of these structures in GBM tumors suggests that they may play an instrumental role in GBM’s spread and invasion, the recreation of these structures in vitro has remained challenging. Methods: Here we present a new microfluidic model of GBM that mimics the dynamics of pseudopalisade forma- tion.To do this, we embedded U-251 MG cells within a collagen hydrogel in a custom-designed microfluidic device. By controlling the medium flow through lateral microchannels, we can mimic and control blood-vessel obstruction events associated with this disease. Results: Through the use of this new system, we show that nutrient and oxygen starvation triggers a strong migratory process leading to pseudopalisade generation in vitro.These results validate the hypothesis of pseudo- palisade formation and show an excellent agreement with a systems-biology model based on a hypoxia-driven phenomenon. Conclusions: This paper shows the potential of microfluidic devices as advanced artificial systems capable of mod- eling in vivo nutrient and oxygen gradients during tumor evolution

Finite element implementation of a stochastic three dimensional finite-strain damage model for fibrous soft tissue

A fully three dimensional finite-strain damage model for fibrous soft tissue is here presented. The model assumes uncoupled contributions for the matrix and collagen fibers, and uncoupled bulk and deviatoric response over any range of deformations. A simple isotropic damage mechanism within the framework of continuum damage mechanics has been used to describe the softening behavior under deformation for the matrix. On the other hand, statistical aspects related to the length distribution of the reinforcing fibers lead to a damage model for the reinforcing material. As a result, a general theoretical framework for constitutive modeling of biological soft tissue with continuum damage is obtained. The formulation has been implemented in a finite element framework and the capabilities of the model tested in three computer simulations of inhomogeneous boundary value problems. The results show the quadratic rate of convergence of the implementation and the ability to describe typical stress-strain behavior of fiber reinforced soft tissues. © 2007 Elsevier B.V. All rights reserved

Towards a natural element Lagrangian strategy in fluid-structure interaction

International audienceMany efforts of research have been made in the Fluid-Structure Interaction (FSI) field in order to couple Eulerian (or ALE) formulations in the fluid domain with Lagrangian formulations in the solid domain. See, for instance, [8][16], just to cite a few. In some cases, however, the employ of Lagrangian formulations for both domains seems to be interesting. These cases include—but they are not restricted to—the presence of free surfaces in the fluid, for instance, whose accurate description requires an additional technique (ALE, VoF, level set, among them) in order to capture the position of the free surface. The development of meshless techniques in the nineties opened the possibility of employing Lagrangian formulations for both the solid and fluid domains. This is so since meshless methods are less sensible to “mesh” distortion (i.e., relative nodal displacement) than finite element methods are. Thus, it is possible to employ an updated Lagrangian strategy for the fluid domain, while employing a total or updated Lagrangian strategy for the solid. This approach is very convenient for some classes of problems, especially those involving drastic changes in the fluid domain geometry

Understanding glioblastoma invasion using physically-guided neural networks with internal variables.

Microfluidic capacities for both recreating and monitoring cell cultures have opened the door to the use of Data Science and Machine Learning tools for understanding and simulating tumor evolution under controlled conditions. In this work, we show how these techniques could be applied to study Glioblastoma, the deadliest and most frequent primary brain tumor. In particular, we study Glioblastoma invasion using the recent concept of Physically-Guided Neural Networks with Internal Variables (PGNNIV), able to combine data obtained from microfluidic devices and some physical knowledge governing the tumor evolution. The physics is introduced in the network structure by means of a nonlinear advection-diffusion-reaction partial differential equation that models the Glioblastoma evolution. On the other hand, multilayer perceptrons combined with a nodal deconvolution technique are used for learning the go or grow metabolic behavior which characterises the Glioblastoma invasion. The PGNNIV is here trained using synthetic data obtained from in silico tests created under different oxygenation conditions, using a previously validated model. The unravelling capacity of PGNNIV enables discovering complex metabolic processes in a non-parametric way, thus giving explanatory capacity to the networks, and, as a consequence, surpassing the predictive power of any parametric approach and for any kind of stimulus. Besides, the possibility of working, for a particular tumor, with different boundary and initial conditions, permits the use of PGNNIV for defining virtual therapies and for drug design, thus making the first steps towards in silico personalised medicine

Influence of the macro and micro-porous structure on the mechanical behavior of poly(L-lactic acid) scaffolds

The development of macroporous biodegradable polymeric materials with three-dimensional pore structure is an important research field in tissue engineering. Structural scaffolds not only provide the cells with a mechanical support, but also perform an interactive physico-chemical role in tissue regeneration, thus it becomes important to be able to tune their mechanical properties to deliver appropriate mechanical signals to adhered cells for proper tissue regeneration. This work presents two series of poly(L-lactic acid) (PLLA) scaffolds in which we modulated the mechanical properties by systematically changing two synthesis parameters: polymer/solvent ratio and polymer-solution/porogen percentage. The peculiarity of the constructs is the presence of a double porosity: micropores generated by dioxane solvent using a freeze extraction technique and macropores produced by the leaching of macroporogen spheres. An increase in the PLLA/dioxane ratio decreases the micropores size and also influences to some extent the macropores size, due to the ability of dioxane to swell macroporogen particles. On the other hand, an increase in the amount of macroporogen increases the porosity by increasing the dimension of pore the throats connecting the macropores. Consequently, the increase in the PLLA/dioxane ratio produces a significant decrease in the permeability, and an increase in the apparent compression Young's modulus and aggregate modulus. When increasing the amount of macroporogen the permeability significantly increases and a decrease in the mechanical properties of the scaffolds is observed. Summarizing, with a systematic change of two fabrication parameters (amount of dioxane and macroporogen) the structural characteristics of the scaffolds were modulated and thereby their mechanical and transport properties were controlled.The authors gratefully acknowledge research support from the Spanish Ministry of Science and Innovation through research project DPI2010-20399-C04-00. CIBER-BBN is an initiative funded by the VI National R&D&D&i Plan 2008-2011, Iniciativa Ingenio 2010, and Consolider Program. CIBER Actions are financed by the Instituto de Salud Carlos III with assistance from the European Regional Development Fund.Acosta Santamaria, V.; Deplaine, H.; Mariggio, D.; Villanueva Molines, AR.; Garcia Aznar, JM.; Gómez Ribelles, JL.; Doblare Castellano, M.... (2012). Influence of the macro and micro-porous structure on the mechanical behavior of poly(L-lactic acid) scaffolds. Journal of Non-Crystalline Solids. 358(23):3141-3149. https://doi.org/10.1016/j.jnoncrysol.2012.08.001S314131493582