Abstracts

Adérito Araújo | CMUC, University of Coimbra

Title: Seeking viable paradigms for hydrogen peroxide signalling in the cytoplasm of human cells

Abstract: Hydrogen peroxide  (H2O2)  is a key signaling agent in important physiological processes such as cell proliferation, inflammation, and apoptosis. However, how such a featureless molecule achieves sensitive and specific regulation remains poorly understood. At the cytosol of human cells, H2O2 signaling is spatially localized due to the high activity of the peroxiredoxin (Prdx)/thioredoxin (Trx) system. And it is partly mediated by redox relays whereby Prdx act as H2O2 receptors, being oxidized, and in turn oxidizing other protein targets. In this talk we will present and discuss reaction-diffusion model of the cytosolic human peroxiredoxin (Prdx)-based system that accounts for the differential kinetic parameters. The results confirm that H2O2 signalling at the cytosol of human cells is spatially localised and that site-specific scaffold proteins allow H2O2 released to the cytosol at distinct sites to independently regulate distinct genes and processes.

Co-authors: Matthew Griffith (1,2), Rui Travasso (3), Armindo Salvador (1,4,5)

1 CNC, Centre for Neuroscience Cell Biology, University of Coimbra, Coimbra, Portugal

2 Department of Mathematical Sciences, University of Bath, Claverton Down, Bath BA2 7AY, UK

3 CFisUC, Department of Physics, University of Coimbra, Coimbra, Portugal

4 Coimbra Chemistry Center ? Institute of Molecular Sciences (CQC-IMS), University of

Coimbra, Coimbra, Portugal

5 Institute for Interdisciplinary Research, University of Coimbra, Coimbra, Portugal

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Davide Cusseddu | CMAT, University of Minho

Title: On the application of fractional derivatives in compartmental modelling 

Abstract: In recent years, fractional calculus has grown in popularity, causing fast developments in this field. A lot of interest also arises in the modelling world, as fractional operators might be powerful tools in applications. Indeed, since fractional derivatives, such as the Riemann-Liouville or Caputo derivatives, are nonlocal operators, they might be able to translate biological memory effects into a mathematical system. However, the research in fractional calculus is still in its early stages and a lot still needs to be investigated. For instance, a clear physical interpretation of what a fractional derivative might represent still constitutes an open problem. Therefore, a lot of care should be taken when applying such operators.

During this talk, I will discuss some ideas and problems related to the applications of fractional derivatives in compartmental models. I will also present some fractional operators and investigate their properties for potential applications.

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Marta Cousido | Instituto Español de Oceonografia (IEO, CSIC), Centro Oceanográfico de Vigo, Spain

Title: INLA Bayesian spatio-temporal Models in Action: Fisheries Science Applications   

Abstract: Spatio-temporal models enable us to explore complex interactions and patterns that evolve both in space and time, providing valuable information on dynamic phenomena in various fields. However, these models sometimes need to deal with overly complex spatio-temporal problems as large geospatial datasets, intricate spatial dependencies, or irregular temporal patterns. In such scenarios, Bayesian spatio-temporal models implemented through the INLA (Integrated Nested Laplace Approximation; Rue et al., 2009) methodology and R package are recommended. Indeed, INLA's computational efficiency handle complex spatio-temporal structures delivering accurate results in a reasonable time of computation. To highlight the potential of these models, we focus on explaining two applications within the fisheries science field.

Our first application considers the process of standardizing a relative biomass index, a common practice in fisheries science. Time series of biomass indices are the main source of information to calibrate stock assessment models and hence essential data for successful conservation and management of fish stocks. Fishery-dependent data collected from fishery observers on-board commercial vessels or logbooks can be used to construct standardized indices of relative biomass. The standardization process involves correcting and removing biases within the species biomass data. In particular, we used INLA Bayesian spatio-temporal models to correct for inherent spatio-temporal biases in the relative biomass index of a yellowfin tuna (Thunnus albacares) stock in the Indian ocean.

The second application shifts the focus to characterizing fundamental distributional patterns of common sole (Solea solea) in the northern Iberian Waters (Pennino et al., 2022). More precisely, through Bayesian spatio-temporal models these distributional patterns are classified as either persistent, opportunistic, or progressive, providing crucial information on the ecological dynamics of this fish species.

These examples serve as an evidence that INLA Bayesian spatio-temporal models are a powerful tool for addressing complex spatio-temporal challenges in a wide range of fields where such issues arise and can be used as a guide for similar application in other contexts.

References

Rue, H., Martino, S., Chopin, N., 2009. Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations. J. R. Stat. Soc. Ser. b (Stat. Methodol.) 71 (2), 319–392.

Pennino, M.G., Izquierdo, F., Paradinas, I., Cousido, M., Velasco, F., Cerviño, S. (2022). Identifying persistent biomass areas: The case study of the common sole in the northern Iberian Waters. Fisheries Research, 248, 106196.

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Erida Gjini | CEMAT, University of Lisbon

Title: Understanding multispecies co-colonization systems with the replicator equation

Abstract: Microbial community composition and dynamics are key to health and disease across biological scales. Explaining the drivers of diversity in the microbial consortia making up our body's defenses or the forces maintaining multiple pathogen strains in an epidemiological setting, remains a challenge. For this, computationally- and analytically-tractable models are needed, that bridge the gap between pattern observations and underlying mechanisms. In a series of recent papers, we develop a general mathematical modeling framework whereby colonization systems with multiple interacting strains can be studied. In our model, N strains or similar microbial ‘species’ grow, propagate and interact in co-colonization via pairwise environmental modification. Using separation of timescales, we simplify the model into a fast and slow dynamics, and obtain an explicit replicator equation for species frequency dynamics in the system. This replicator equation allows deeper and more direct understanding of the competition, cooperation and selection dynamics between species in the system, and can describe stable coexistence, competitive exclusion, limit cycles and other complex attractors as possible final outcome. I will present this framework, starting from our original SIS epidemiological model with co-colonization, highlight some key mathematical and biological features, and sketch the first links with data. Applications of this model may go beyond epidemiology to microbiota modeling, opinion propagation, or social evolution. 

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Marco Menale | University of Naples Federico II, Italy

Title: Kinetic modeling of interacting systems under the action of an external force field: recent results and perspectives 

Abstract: Kinetic theory frameworks allow to model the evolution of binary stochastic interacting systems. Nonconservative interaction rates also emerge in some applications. Among others, ecological systems modeled by Lotka-Volterra type equations, require the introduction of suitable birth/death rates. Nevertheless, in some situations, binary interactions alone are not enough to gain a realistic description of the overall system. Among others, the action of the external environment cannot be neglected; for instance, when the system into account is open. Therefore, a suitable external force field can be introduced in order to model this external action, where the specific analytical shape depends on the particular application taken into account. Recently, these kinetic models under the action of an external force field have been applied in mathematical epidemiology [1], ecology [2] and medical treatment [3]. They have been analytically investigated, even if some questions remain open, such as globally in time existence of solution. 

[1] Menale, M., Munafò, C. F. A kinetic framework under the action of an external force field: Analysis and application in epidemiology. Chaos, Solitons & Fractals, 174 (2023), 113801.

[2] Menale, M., Venturino, E. kinetic theory approach to modeling prey-predator ecosystems with expertise levels: analysis, simulations and stability considerations. Submitted. 

[3] Menale, M., Travaglini, R. A nonconservative kinetic model under the action of an external force field for modeling the medical treatment of autoimmune response. Submitted. 

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Ana Isabel Ribeiro | ISPUP, University of Porto

Title:  The Natural Remedy: How Do Green Spaces Support Public Health?

Abstract: As urbanization continues to bring more people to densely populated urban environments, a growing number find themselves in areas lacking green spaces, which can significantly influence health and well-being. This seminar aims to offer a comprehensive overview of the research conducted within the Health and Territory Lab at the Public Health Institute University of Porto (ISPUP), connecting the exposure to green spaces to health across the life course.

The seminar will feature a variety of studies, using both quantitative and qualitative approaches. These will include longitudinal investigations involving population-based cohorts, nationwide cross-sectional surveys, and qualitative examinations, such as those informed by focus groups.

During the seminar, we are going to explore the ways in which green spaces support respiratory and cognitive health in childhood. We will also discuss how contact with nature during the COVID-19 lockdown acted as a buffer against the mental health challenges triggered by this stressful life event. Furthermore, we will explore how green spaces support healthy ageing and we will speak about the complex dynamics between adolescents and urban green spaces, elucidating the factors that either hinder or drive their engagement with these environments.

The overarching goal of this seminar is to promote the scientific discussion about public health benefits offered by green spaces. Ultimately, this seminar aims to establish a robust evidence base that can serve as a guide for local stakeholders working in the fields of public health and urban planning, encouraging the creation of greener and healthier environments.

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Adélia Sequeira | Department of Mathematics and CEMAT, University of Lisbon

Title: Modeling and Simulation of the Cardiovascular System: a Mathematical Challenge 

Abstract: Cardiovascular diseases, such as heart attack and strokes, are the major causes of death in developed countries,  with a significant impact in the cost and overall status of healthcare. Understanding the fundamental mechanisms  of the pathophysiology and treatment of these diseases are matters of the greatest importance around the world. 

This gives a key impulse to the progress in mathematical and numerical modeling of the associated phenomena  governed by complex physical laws, using adequate and fully reliable in silico settings.

The acquisition of medical data and the understanding of the local hemodynamics and its relation with global  phenomena, in both healthy and pathological cases, using appropriate mathematical models and accurate  numerical methods, play an important role in medical research. They help, for instance, in predicting the  consequences of surgical interventions, or in identifying regions of the vascular systems prone to the formation  and growth of atherosclerotic plaques or aneurysms.

In this talk we will consider some mathematical models and simulations of the cardiovascular system and comment on their significance to yield realistic and accurate numerical results, using stable, reliable and  efficient computational methods. Results on the simulation of some image-based patient-specific clinical  cases will also be presented.

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Romina  Travaglini | INdAM, Università di Parma, Italy, and CMAT, University of Minho

Title: Modeling Multiple Sclerosis by means of a reaction-diffusion system derived from kinetic models

Abstract: We present the latest results in studies modeling anomalous immune responses, which extend the work proposed in the literature [1]. These models provide a description of the dynamics over time of a large number of interacting cells within an autoimmune framework, utilizing the tools of the kinetic theory of active particles. We describe a spatio-temporal model, considering the motion of immune cells stimulated by cytokines [2] and applying it to a specific case of autoimmune disease, Multiple Sclerosis [3]. We derive macroscopic reactiondiffusion equations for the number densities of the constituents with a chemotaxis term. A natural progression is to study the system, exploring the formation of spatial patterns through a Turing instability analysis of the problem, and basing the discussion on microscopic parameters of the model. In particular, we observe spatial patterns that reproduce the brain lesions characteristic of the pathology during its different stages.

References

[1] R. Della Marca, M. P. D. Machado Ramos, C. Ribeiro, A. J. Soares, Mathematical modelling of oscillating patterns for chronic autoimmune diseases. Math.l Meth. Appl. Sci., 45(11), 7144-7161 (2022)

[2] J. Oliveira, A. J. Soares, R. Travaglini, Kinetic models leading to pattern formation in the response of the immune system. Special Issue of Rivista di Matematica dell’Universit`a di Parma in memory of Giampiero Spiga. (Accepted for publication)

[3] J. M. S. Oliveira, R. Travaglini, Reaction-diffusion systems derived from kinetic models for Multiple Sclerosis. arXiv preprint arXiv:2309.05119

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