Investigating biocomplexity through the agent-based paradigm.

Capturing the dynamism that pervades biological systems requires a computational approach that can accommodate both the continuous features of the system environment as well as the flexible and heterogeneous nature of component interactions. This presents a serious challenge for the more traditional mathematical approaches that assume component homogeneity to relate system observables using mathematical equations. While the homogeneity condition does not lead to loss of accuracy while simulating various continua, it fails to offer detailed solutions when applied to systems with dynamically interacting heterogeneous components. As the functionality and architecture of most biological systems is a product of multi-faceted individual interactions at the sub-system level, continuum models rarely offer much beyond qualitative similarity. Agent-based modelling is a class of algorithmic computational approaches that rely on interactions between Turing-complete finite-state machines--or agents--to simulate, from the bottom-up, macroscopic properties of a system. In recognizing the heterogeneity condition, they offer suitable ontologies to the system components being modelled, thereby succeeding where their continuum counterparts tend to struggle. Furthermore, being inherently hierarchical, they are quite amenable to coupling with other computational paradigms. The integration of any agent-based framework with continuum models is arguably the most elegant and precise way of representing biological systems. Although in its nascence, agent-based modelling has been utilized to model biological complexity across a broad range of biological scales (from cells to societies). In this article, we explore the reasons that make agent-based modelling the most precise approach to model biological systems that tend to be non-linear and complex

Numerical Simulations of Skin Formation: Convergence of Moisture Transport and Stratum Corneum Thickness

As the epidermis adapts to different environments, desquamation of keratinocytes is affected by the water content in the epidermis. The thickness of the outermost layer of skin is determined by the interaction between exfoliation and moisture evaporation. The balance between these processes is the key to healthy skin, but has not been studied. The present study constructs a qualitative numerical model of stratum corneum thickness based on the interaction between exfoliation and evaporation processes.9th Thai Society of Mechanical Engineers, International Conference on Mechanical Engineering (TSME-ICoME 2018) 11–14 December 2018, Phuket, Thailan

3D Numerical Simulation of Epidermal Skin Turnover Process Using a Particle Model

Skin is the largest organ of the human body. In recent years, concern regarding the cosmetics area has increased, and research studies on anti-aging therapy or cosmetics have been rapidly conducted. Skin cells are not only changing its shape but also its physical properties during the epidermal skin turnover process. Computational simulation can be useful in further understanding the mechanisms of skin formation. We propose a particle model that can handle complex biological phenomena, including cell interactions and is a suitable method for simulating skin formation. The particle model was applied to simulate three-dimensional skin formation accompanied by proliferation and cornification of skin cells. The simulation results represented and reproduced the epidermal skin turnover phenomenon

Particle Simulation of Skin Basal Layer Formation

There has been increasing concern regarding the cosmetic aspects of skin in recent years. Computational simulation can be useful in understanding the mechanism underlying skin formation. The bottom of the epidermis is called the basal layer and is very undulation. In this study, we focus on the basal layer formation. We created a particle model, which forms an undulation basal layer and regenerates the basal layer formation by numerical simulation. At first, two-dimensional basal layer formation without epidermal turnover was simulated. The results showed film shape changes and the stability, as a layer in the process of long-time with an increase and decrease of basal cells. Next, the model was applied to three-dimensional basal layer formation with epidermal turnover. As the structure of the basal layer was deformed, the upper structure of the epidermis comprising the cells divided from the basal layer also became irregular. The simulation results accurately represented and reproduced the three-dimensional basal layer formation and epidermis turnover process.2nd Conference on Advances in Prevention and Treatment of Cancer (CAPTC 2016), March 18-20, 2016, Los Angeles, US

3D Numerical Simulation of Epidermal Skin Turnover Process Using a Particle Model

Skin is the largest organ of the human body. In recent years, concern regarding the cosmetics area has increased, and research studies on anti-aging therapy or cosmetics have been rapidly conducted. Skin cells are not only changing its shape but also its physical properties during the epidermal skin turnover process. Computational simulation can be useful in further understanding the mechanisms of skin formation. We propose a particle model that can handle complex biological phenomena, including cell interactions and is a suitable method for simulating skin formation. The particle model was applied to simulate three-dimensional skin formation accompanied by proliferation and cornification of skin cells. The simulation results represented and reproduced the epidermal skin turnover phenomenon

Particle Simulation on Epidermal Skin Formation - Mechanism of Basal Layer Formation -

Skin is the largest organ of the human body. The bottom of the epidermis is called the basal layer and is very uneven. However, the mechanism of uneven formation of the basal layer has not yet been elucidated. Computational simulation can be useful in further understanding the mechanisms of skin formation. We propose a particle model that can handle complex biological phenomena, including cell interactions and is a suitable method for the simulation of skin formation. In this study, we created a model similar to the actual skin using three-dimensional analysis and elucidated the formation mechanism of the basal layer. Particularly, each basal cell of this model is subjected to three patterns of cell division, which can simulate skin formation with an increase and decrease of basal cells and the consequent generation of upper cell layers. Therefore, we analyzed the association between these cell division patterns and the uneven formation of the cell layer.The 6th TSME International Conference on Mechanical Engineering, 16-18 December 2015, the Regent Cha-am beach Resort, Hua-Hin, Thailand

Mathematical modelling of epithelium homeostasis

The body and organs of all animals are covered by epithelial tissues, such as the epidermis and the airway epithelium. Epithelial tissues play a key role in protecting the body from environmental aggressors. Failure to maintain a competent epithelium can lead to the onset of many diseases, including Atopic dermatitis (AD) and infection by Streptococcus pneumoniae. Treatment of AD is currently restricted to the relief of symptoms, mainly because the underlying mechanisms remain elusive. Antibiotic resistance threatens the effectiveness of the prevalent treatments for infection. Devising new and effective therapeutic strategies that halt the progression of these diseases requires an understanding of the different disease mechanisms that can cause loss of epithelial homeostasis in different patients. Intricate regulatory networks of several biochemical and cellular interactions maintain epithelium homeostasis in healthy individuals, but can also propagate different disturbances, resulting in a wide spectrum of possible disease phenotypes. In this thesis, we propose mathematical models of these regulatory networks to analyse the mechanisms that lead to the onset and progression of AD and pneumococcal infection from a systems-level perspective. Our mathematical model of AD reproduced, for the first time, the different stages of the disease that have been observed in the clinic. Moreover, we proposed different pathogenic mechanisms, triggered by different genetic and environmental risk factors that are known to predispose to AD. By assessing the effects of common treatments for AD, we suggested effective treatment strategies that can prevent the aggravation of the disease, in a patient-specific way. Our data-driven mathematical model of pneumococcal infection identified four qualitatively different mechanisms by which co-infection can drive the pathogenic process. They can be counteracted by distinctive treatment strategies that only partially involve antibiotics. Our work provides a theoretical framework for the integration and analysis of clinical and experimental data describing epithelial homeostasis.Open Acces

Engineering simulations for cancer systems biology

Computer simulation can be used to inform in vivo and in vitro experimentation, enabling rapid, low-cost hypothesis generation and directing experimental design in order to test those hypotheses. In this way, in silico models become a scientific instrument for investigation, and so should be developed to high standards, be carefully calibrated and their findings presented in such that they may be reproduced. Here, we outline a framework that supports developing simulations as scientific instruments, and we select cancer systems biology as an exemplar domain, with a particular focus on cellular signalling models. We consider the challenges of lack of data, incomplete knowledge and modelling in the context of a rapidly changing knowledge base. Our framework comprises a process to clearly separate scientific and engineering concerns in model and simulation development, and an argumentation approach to documenting models for rigorous way of recording assumptions and knowledge gaps. We propose interactive, dynamic visualisation tools to enable the biological community to interact with cellular signalling models directly for experimental design. There is a mismatch in scale between these cellular models and tissue structures that are affected by tumours, and bridging this gap requires substantial computational resource. We present concurrent programming as a technology to link scales without losing important details through model simplification. We discuss the value of combining this technology, interactive visualisation, argumentation and model separation to support development of multi-scale models that represent biologically plausible cells arranged in biologically plausible structures that model cell behaviour, interactions and response to therapeutic interventions

Particle Simulation on Human Epidermal Aging- Effect of Basal Layer and Cell Division Rate -

Wrinkles and freckles appear on people due to aging and, as such, affect their appearance. The epidermis is the outermost layer of a human’s skin, and epidermal conditions can be diagnosed from it in order to provide appropriate care. Recently, those interested in anti-aging treatments have paid greater attention to the aging of the epidermal layer. The epidermis consists of four different layers. In particular, the basal layer, which is at the bottom of epidermis, has an undulating structure. This undulation is associated with aging: undulations in the basal layer become flat when the epidermis ages. However, the mechanisms between the aging process and the basal layer have not yet been made clear because it is difficult to directly observe the skin’s basal layer. In order to investigate long-term skin formation, we created a model that simulates actual skin. Our model can analyze the epidermis while including undulations in the structure of the basal layer. In order to test this, we set conditions for the number of basal cells and the basal cell division rate so as to simulate aging and young epidermises. In the case of aging epidermises, the number of basal cells was fewer and the basal cell division rate was lower than for young skin. As a result of this analysis, the characteristics of aging skin were found.The 7th International Conference on Mechanical Engineering (TSME-ICoME 2016), 13-16 December 2016, Chiang Mai, Thailand