Manuel doblaré

• Doctor of Philosophy
• Professor at University of Zaragoza

Predictive physics has been historically based upon the development of mathematical models that describe the evolution of a system under certain external stimuli and constraints. The structure of such mathematical models relies on a set of physical hypotheses that are assumed to be fulfilled by the system within a certain range of environmental con...

A bstract Mathematical models are invaluable tools for understanding the mechanisms and interactions that control the behavior of complex systems. Modeling a problem as cancer evolution includes many coupled phenomena being therefore impossible to obtain sufficient experimental results to fully evaluate all possible conditions. In this work, we foc...

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 emerged...

Este estudio combina algoritmos de aprendizaje automático con principios físicos para resolver la ecuación de calor estacionaria, mejorando la capacidad predictiva de los modelos con respecto a las redes neuronales clásicas, y aportando capacidad explicativa, descubriendo modelos de estado no lineales y revelando la microestructura heterogénea de u...

Los modelos matemáticos o in silico han demostrado ser de gran utilidad en la investigación del cáncer. En este trabajo, se presenta un modelo híbrido para la simulación del entorno del glioblastoma. El objetivo es señalar las ventajas que ofrecen estos modelos para abordar este problema con respecto a los modelos continuos y discretos.

Se ha llevado a cabo una caracterización biaxial de las propiedades mecánicas pasivas del miocardio tras dos modelos de infarto distintos (LCfx y LDes). Se observó que la rigidez del tejido infartado aumenta proporcionalmente al grado de infarto, con valores similares entre LCfx y LDes. Se observó una respuesta anisótropa en LCfx y una respuesta pr...

En este trabajo se desarrollan distintos métodos de aprendizaje automático para estimar parámetros de modelos matemáticos de evolución de células tumorales de glioblastoma, así como para calcular la equivalencia entre los parámetros de distintos modelos. Esto facilita el desarrollo de modelos paciente específico y su calibración.

La Fecundación In Vitro es una técnica ampliamente utilizada por parejas infértiles que buscan formar una familia. Decidir qué embriones se implantan es crucial pero incierto. A fin de brindar herramientas que ayuden en esta decisión, realizamos una segmentación automática del blastocisto mediante técnicas de visión por computador, obteniéndose res...

A novel methodology utilizing plasma surface treatment enables the construction of cell culture chambers featuring abutment-free patterns, facilitating the precise distribution of shear stress.

Drug resistance is one of the biggest challenges in the fight against cancer. In particular, in the case of glioblastoma, the most lethal brain tumour, resistance to temozolomide (the standard of care drug for chemotherapy in this tumour), is one of the main reasons behind treatment failure and hence responsible for the poor prognosis of patients d...

As motivated by studies of cellular motility driven by spatiotemporal chemotactic gradients in microdevices, we develop a framework for constructing approximate analytical solutions for the location, speed and cellular densities for cell chemotaxis waves in heterogeneous fields of chemoattractant from the underlying partial differential equation mo...

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 a...

Cellular adaptation is the ability of cells to change in response to different stimuli and environmental conditions. It occurs via phenotypic plasticity, that is, changes in gene expression derived from changes in the physiological environment. This phenomenon is important in many biological processes, in particular in cancer evolution and its trea...

La plasticidad fenotípica fue incluida en 2022 entre los Hallmarks del Cáncer. En particular, es crucial en la adaptación del glioblastoma a la hipoxia, principal causante de su agresividad. Desarrollamos un modelo matemático basado en variables internas que permite reproducir cualitativamente las tendencias observadas en la evolución de este tumor...

Mechanical interactions between cells and their microenvironment play an important role in determining cell fate, which is particularly relevant in metastasis, a process where cells invade tissue matrices with different mechanical properties. In vitro, type I collagen hydrogels have been commonly used for modeling the microenvironment due to its ub...

A bstract Cellular adaptation is the ability of cells to change in response to different stimuli and environmental conditions. It occurs via phenotypic plasticity, that is, changes in gene expression derived from changes in the physiological environment. This phenomenon is important in many biological processes, in particular in cancer evolution an...

Background: Spheroids are in vitro quasi-spherical structures of cell aggregates, eventually cultured within a hydrogel matrix, that are used, among other applications, as a technological platform to investigate tumor formation and evolution. Several interesting features can be replicated using this methodology, such as cell communication mechanis...

As motivated by studies of cellular motility driven by spatiotemporal chemotactic gradients in microdevices, we develop a framework for constructing approximate analytical solutions for the location, speed and cellular densities for cell chemotaxis waves in heterogeneous fields of chemoattractant from the underlying partial differential equation mo...

Biofabrication of human tissues has seen a meteoric growth triggered by recent technical advancements such as human induced pluripotent stem cells (hiPSCs) and additive manufacturing. However, generation of cardiac tissue is still hampered by lack of addequate mechanical properties and crucially by the often unpredictable post-fabrication evolution...

Este estudio se centra en el diseño de un dispositivo de asistencia ventricular, formado por una malla rellena de un hidrogel celularizado. Para estudiar su comportamiento mecánico, se han realiado ensayos en prototipos de malla y en tejido cardiaco y se ha desarrollado un entorno computacional basado en los resultados obtenidos.

In the field of microtechnologies applied to the simulation of controlled biological environments are the so-called organ-on-a-chip, microfluidic cell culture devices. The gradient model plays an indispensable role in this technology. Here, we present a novel microfabrication process for pillarless microfluidic platforms which enables the creation...

The increased life expectancy has boomed the demand of dental implants in the elderly. As a consequence, considering the effect of poorer bone quality, due to aging or associated diseases such as osteoporosis, on the success of dental restoration is becoming increasingly important. Bisphosphonates are one of the most used drugs to overcome the effe...

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 b...

Las numerosas posibilidades que ofrece la microfluídica a nivel de obtención y monitorización de grandes cantidades de datos abren la puerta a la aplicación de técnicas de aprendizaje profundo al análisis de la evolución cultivos celulares, un campo poco explorado hasta la fecha. En este trabajo, se desarrolla una red neuronal para identificar, a p...

Los cardiomiocitos derivados de células madre pluripotentes inducidas humanas (hiPSC-CMs) que se cultivan en matrices bioimpresas han mostrado resultados prometedores en el campo de la medicina regenerativa. El trasplante de estos cultivos en áreas dañadas del ventrículo puede contribuir a restaurar la función cardíaca. Sin embargo, la arritmicidad...

La combinación de medidas en dispositivos microfluídicos con técnicas de inteligencia artificial permite estudiar fenómenos celulares complejos difíciles de encarar con los métodos tradicionales. En este trabajo se usan redes neuronales guiadas por la física para explicar los cambios metabólicos celulares y predecir el comportamiento de cultivos de...

En este trabajo se presenta el uso y las ventajas de los modelos basados en agentes (ABMs) como herramienta para validar hipótesis biológicas y entender procesos celulares fundamentales que permitan posteriormente simular sistemas más complejos. Mediante este tipo de modelos se estudiarán algunos procesos involucrados en la evolución del glioblasto...

Con el objetivo de caracterizar mecánicamente el tejido cardiaco porcino, se han llevado a cabo diferentes ensayos mecánicos sobre siete animales. Se han realizado ensayos biaxiales y tangenciales, elásticos y viscoelásticos. El procedimiento utilizado permite caracterizar el comportamiento del tejido con cualquier modelo de material existente en l...

State-of-the-art solvers for in silico cardiac electro-physiology employ the Finite Element Method to solve complex anatomical models. While this is a robust and accurate tech-nique, it requires a high-quality mesh to prevent its accuracy from being severely deteriorated. The generation of a good quality mesh for realistic anatomical models can be...

Spheroids are in vitro spherical structures of cell aggregates, eventually cultured within a hydrogel matrix, that are used, among other applications, as a technological platform to investigate tumor formation and evolution. Several interesting features can be replicated using this methodology, such as cell communication mechanisms, the effect of g...

Substitution of well-grounded theoretical models by data-driven predictions is not as simple in engineering and sciences as it is in social and economic fields. Scientific problems suffer many times from paucity of data, while they may involve a large number of variables and parameters that interact in complex and non-stationary ways, obeying certa...

Background: The COVID pandemic has forced the closure of many colorectal cancer (CRC) screening programs. Resuming these programs is a priority, but fewer colonoscopies may be available. We developed an evidence-based tool for decision-making in CRC screening programs, based on a fecal hemoglobin immunological test (FIT), to optimize the strategy f...

The broad possibilities offered by microfluidic devices in relation to massive data monitoring and acquisition open the door to the use of deep learning technologies in a very promising field: cell culture monitoring. In this work, we develop a methodology for parameter identification in cell culture from fluorescence images using Convolutional Neu...

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...

Bone remodeling identifies the process of permanent bone change with new bone formation and old bone resorption. Understanding this process is essential in many applications, such as optimizing the treatment of diseases like osteoporosis, maintaining bone density in long-term periods of disuse, or assessing the long-term evolution of the bone surro...

An artistic representation of our workflow, including atomic force microscopy characterization and a custom-made microfluidic compression experiment, is presented. This workflow has been applied to the characterization of the effects of graphene oxide in the mechanical stability and surface properties of hybrid alginate microspheres destined to cel...

Modeling and simulation are essential tools for better understanding complex biological processes, such as cancer evolution. However, the resulting mathematical models are often highly non-linear and include many parameters, which, in many cases, are difficult to estimate and present strong correlations. Therefore, a proper parametric analysis is m...

Se presenta una metodología hibrida que combina el aprendizaje de las redes neuronales y la incorporación de la física sobre ciertas capas internas de la red. La herramienta tiene poder predictivo y explicativo, mejora a las redes clásicas en velocidad, necesidad de datos, capacidad de filtrado y poder de extrapolación.

La epigenética juega un papel crucial en el desarrollo tumoral, en particular en la adquisición de resistencia. Se presenta un enfoque novedoso en la comunidad científica, utilizando un modelo matemático con variables internas, inspirado en la teoría de la plasticidad para describir este fenómeno.

Cell encapsulation in hydrogel-based microspheres has demonstrated successes in regenerative cell therapy. We developed a workflow based on Atomic Force Microscopy (AFM) and a microfluidic constriction system to characterize stiffness and surface properties of microcapsules.

Microencapsulation of cells in hydrogel-based porous matrices is an approach that has demonstrated great success in regenerative cell therapy. These microcapsules work by concealing the exogenous cells and materials in a robust biomaterial that prevents their recognition by the immune system. A vast number of formulations and additives are continuo...

In silico models and computer simulation are invaluable tools to better understand complex biological processes such as cancer evolution. However, the complexity of the biological environment, with many cell mechanisms in response to changing physical and chemical external stimuli, makes the associated mathematical models highly non-linear and mult...

Bone remodeling is a fundamental biological process that develops in bone tissue along its whole lifetime. It refers to a continuous bone transformation with new bone formation and old bone resorption that changes the internal microstructure and composition of the tissue. The main objectives of bone remodeling are: repair of the internal microcrack...

Predictive Physics has been historically based upon the development of mathematical models that describe the evolution of a system under certain external stimuli and constraints. The structure of such mathematical models relies on a set of hysical hypotheses that are assumed to be fulfilled by the system within a certain range of environmental cond...

Bones can replace old and damaged tissue with healthy new tissue in a process called bone remodeling. This process is biologically described by coordinated activity between bone formation (osteoblasts) and bone resorption (osteoclasts) by following stages of activation, resorption, and formation. From a mechanical point of view, there is formation...

Substitution of well-grounded theoretical models by data-driven predictions is not as simple in engineering and sciences as it is in social and economic fields. Scientific problems suffer most times from paucity of data, while they may involve a large number of variables and parameters that interact in complex and non-stationary ways, obeying certa...

The data-driven approach was formally introduced in the field of computational mechanics just a few years ago, but it has gained increasing interest and application as disruptive technology in many other fields of physics and engineering. Although the fundamental bases of the method have been already settled, there are still many challenges to solv...

The data-driven methodology with application to continuum mechanics relies in two main pillars, namely, (i) experimental characterization of stress-strain pairs associated to different loading states, and (ii) numerical development of the elasticity equations as an optimization (searching) algorithm using compatibility and equilibrium as constraint...

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Cell-laden hydrogel microspheres have shown encouraging outcomes in the fields of drug delivery, tissue engineering or regenerative medicine. Beyond the classical single coating with polycations, many other different coating designs have been reported with the aim of improving mechanical properties and in vivo performance of the microspheres. Among...

Featured Application Multiscale analysis is widely applied in the field of mechanics of heterogeneous materials, as a numerical tool, to simulate both microstructure evolution and macroscopic response to loads. The potential of this technique is applied in this work to the micro- and macro-mechanical study of the cortical bone tissue, using a mixed...

Despite the high success rate achieved in current dental implantation, there are still important problems to solve like incomplete early osteointegration, bone damage, and long‐term implant loosening. Highly compliant stress absorbers are a possible solution to these problems. Although several works examined the stress‐strain distribution in bone w...

In this chapter, we review the fundamental concepts and formulation of the thermomechanics of continuous media. First, we revise the expressions of the two first laws of thermodynamics for thermomechanical processes, that is, those with changes in temperature and strains as state-independent variables. These equations constitute the generalization...

Multi phenotypical cellular microenvironments (organ-on-chip devices) are extremely challenging biological systems to be modeled. For different phenotype populations, chemical interactions with nutrients or other biochemical signals, physical driving factors, proliferation, migration, differentiation and cell death should be considered. Mathematica...

The tumour microenvironment (TME) has recently drawn much attention due to its profound impact on tumour development, drug resistance and patient outcome. There is an increasing interest in new therapies that target the TME. Nonetheless, most established in vitro models fail to include essential cues of the TME. Microfluidics can be used to reprodu...

Multi phenotype cellular microenvironments are extremely challenging biological systems to be modeled. In such a case, many factors should be taken into account such as chemical interactions with nutrients or other biochemical signals, physical driving factors such as electrical or thermal cues, cell proliferation, migration, differentiation, and a...

Data-driven methods are an innovative model-free approach for engineering and sciences, still in process of maturation. The idea behind is the combination of data analytics techniques, to handle the huge amount of data derived from continuous monitoring or experimental measurements, and of the constraints imposed by universal physical laws, particu...

Computational multiscale analyses are currently ubiquitous in science and technology. Different problems of interest—e.g., mechanical, fluid, thermal, or electromagnetic—involving a domain with two or more clearly distinguished spatial or temporal scales, are candidates to be solved by using this technique. Moreover, the predictable capability and...

Data-driven methods are an innovative model-free approach for engineering and sciences, still in process of maturation. The idea behind is the combination of data analytics techniques, to handle the huge amount of data derived from continuous monitoring or experimental measurements, and of the constraints imposed by universal physical laws, particu...

We present a continuum-based mathematical approach to the interacting cellular population’s problem and a numerical formulation based on FE spatial discretization. Governing equations are advection-diffusion-reaction transport equations for the cell populations and the involved chemical species. In addition, chemotaxis, mechanotaxis, proliferation...

The high temperatures required for efficient operation of solar thermal power plants constitutes one of the major challenges of this technology. Gaining insight into materials behavior at very high temperatures is critical to improve their techno-economic feasibility. Standard material characterization approaches become inefficient, as extensive te...

Los microentornos celulares multi fenotípicos que se reproducen en dispositivos microfluídicos Organ-On-Chip son sistemas biológicos extremadamente complejos de modelar. Para diferentes poblaciones celulares, se deben considerar las interacciones químicas con nutrientes u otras señales, la disposición espacial, la rigidez y características del sust...

The finite element method (FEM) is the most widely used numerical method for solving complex problems mathematically represented by one or several coupled field equations in continuum physics. The main power of the FEM appears in coupled, nonlinear, and heterogeneous problems where several physical fields interact pointwise in a nonlinear way. This...

Background: The first metatarsal bone is a viable source for autologous bone grafting in foot and ankle surgery and may serve as another convenient graft site to correct a flail toe deformity. We aimed to determine how progressive bone removal from the first metatarsal affects the mechanical redistribution of the foot and whether this bone removal...

The tumour microenvironment is very complex, and essential in tumour development and drug resistance. The endothelium is critical in the tumour microenvironment: it provides nutrients and oxygen to the tumour and is essential for systemic drug delivery. Therefore, we report a simple, user-friendly microfluidic device for co-culture of a 3D breast t...

Data Science has burst into simulation-based engineering sciences with an impressive impulse. However, data are never uncertainty-free and a suitable approach is needed to face data measurement errors and their intrinsic randomness in problems with well-established physical constraints. As in previous works, this problem is here faced by hybridizin...

Cardiovascular diseases are the number one of death globally. According to the World Health organization 17.7 million people died from cardiovascular diseases in 2015, representing 31% of all global deaths. In these diseases the cardiac homeostasis is disrupted by a non-appropriate myocardium remodelling. The cardiac extracellular matrix (ECM) prov...

A new anidolic parametric trough solar collector (PmTC) having 8.12m net width aperture has been recently proposed for a commercial evacuated receiver tube with an absorber diameter of 70 mm. Since the collector was designed ignoring transmission, absorption, and reflection optical losses, calculations of the optical efficiency and the incidence an...

Solar selective coatings can be multi-layered materials that optimize the solar absorption while reducing thermal radiation losses, granting the material long-term stability. These layers are deposited on structural materials (e.g., stainless steel, Inconel) in order to enhance the optical and thermal properties of the heat transfer system. However...

Background There is compelling evidence demonstrating that the tumor microenvironment (TME) plays a key role in tumor initiation, development and response to therapy. This contributes to a high heterogeneity within the same cancer type, and hinders the process of finding effective treatments. In this context, microfluidics has proven capable of cre...

Data Science has burst into Simulation-Based Engineering Sciences. However, data around us is never risk-free and a suitable approach is needed in order to face measure- ment error and uncertainty. A new Data-Driven solver accounting for uncertainty of input data is introduced. This solver presents an ideal meeting point between theoretical and exp...

GBM on chip: Mimicking the gliobastoma microenvironment within microfluidic devices

Background: Glioblastoma (GBM) is one of the most lethal tumor types. Hypercellular regions, named pseudopalisades, 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 occlusi...

The physical microenvironment of tumours is characterized by heterotypic cell interactions and physiological gradients of nutrients, waste products and oxygen. This tumour microenvironment has a major impact on the biology of cancer cells and their response to chemotherapeutic agents. Despite this, most in vitro cancer research still relies primari...

Two new symmetric Non Imaging Parametric Trough Collectors (PmTC) with circular and flat evacuated receivers have been recently proposed with a potential improvement in the net concentration ratio relative to the thermodynamic ideal limit beyond 65% compared to commercial Parabolic Trough Collectors (PTC) while maintaining or increasing the rim ang...

Introduction: Glioblastoma (GBM) is the most common of primary brain tumours. Nowadays, the survival mean time in patients who received medical treatment, is based on local radiotherapy and chemotherapy with temozolomide (TMZ), is 12-14 months. Despite all research, development of more effective treatments remains elusive. This tumour is characteri...