Microstructurally-based constitutive modelling of the skin – Linking intrinsic ageing to microstructural parameters

Pond, Damien; McBride, Andrew; Davids, Lameez; Reddy, B. D.; Limbert, Georges

doi:10.1016/j.jtbi.2018.01.014

Cited by 31 publications

(29 citation statements)

References 116 publications

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“…Daly et al [47] noted that the final slope of the strain-stress curve of skin in tension remains constant with age while the stiffness of collagen remains constant, possibly due to the reduction in the collagen content in the dermal layer. These data point to potentially complex microstructural reorganisation of the collagen network [80] and that of elastin, the combined effect of which is translated into macroscopic stiffening of the skin. Escoffier et al [71] and Reihsner et al [45] report an increased collagen crosslinking with age, which, from a mechanical standpoint, would reduce any slippage between neighbouring fibres and, ultimately result in stiffening of Sthe collagen network [103].…”

Section: Effects On the Dermal Matrixmentioning

confidence: 93%

“…It is generally accepted that skin ageing is associated with a noticable increase in macroscopic or apparent stiffness, see [12,20,80] and references therein, although some studies suggest otherwise [81]. An increase of skin elastic modulus of around 20% after the age of 70 has been reported [71,72].…”

Section: General Observations On Skin Ageingmentioning

confidence: 99%

“…In the clinical sense, skin wrinkles are defined as ageing-induced amplification of natural skin microrelief [130]. In the light of what is known about the physics of multi -layer assemblies [126] and reported experimental evidence in the skin science literature [80,131], it is reasonable to infer that skin wrinkles are a by-product of alterations in the material and structural properties of its microstructural consti tuents caused by intrinsic and extrinsic ageing.…”

Section: Skin Surface Topographymentioning

confidence: 99%

“…It is straightforward to realise that the evolution of biomechanics of the ageing skin is a highly dynamic process with complex non-linear feedback loops [70,80]. Ultimately, these mechano-structural variations modify the tribological response of the skin.…”

Section: Accepted Manuscriptmentioning

confidence: 99%

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Biotribology of the ageing skin—Why we should care

et al. 2019

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Ageing of populations has emerged as one of the most pressing societal, economic and healthcare challenges currently facing most nations across the globe. The ageing process itself results in degradation of physiological functions and biophysical properties of organs and tissues, and more particularly those of the skin. Moreover, in both developed and emerging economies, population ageing parallels concerning increases in lifestyleassociated conditions such as Type 2 diabetes, obesity and skin cancers. When considered together, these demographic trends call for even greater urgency to find clinical and engineering solutions for the numerous age-related deficits in skin function. From a tribological perspective, detrimental alterations of skin bioph ysical properties with age have fundamental consequences on how one interacts with the body's inner and outer environments. This stems from the fact that, besides being the largest organ of the human body, and also nearly covering its entirety, the skin is a multifunctional interface which mediates these interactions. The aim of this paper is to present a focused review to discuss some of the consequences of skin ageing from the viewpoint of biotribology, and their implications on health, well -being and human activities. Current and future research questions/challenges associated with biotribology of the ageing ski n are outlined. They provide the background and motivation for identifying future lines of research that could be taken up by the biotribology and biophysics communities.

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Section: Effects On the Dermal Matrixmentioning

confidence: 93%

Section: General Observations On Skin Ageingmentioning

confidence: 99%

Section: Skin Surface Topographymentioning

confidence: 99%

Section: Accepted Manuscriptmentioning

confidence: 99%

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Biotribology of the ageing skin—Why we should care

et al. 2019

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“…7. Following the recent work of the authors [29], a mechanistic constitutive model of the skin linking microstructural constitutive parameters with intrinsic ageing is described in Sec. 8.…”

Section: Introductionmentioning

confidence: 99%

Constitutive Modelling of Skin Ageing

Limbert

Pond

McBride

2019

Studies in Mechanobiology, Tissue Engineering and Biomaterials

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The objective of this chapter is to review the main biomechanical and structural aspects associated with both intrinsic and extrinsic skin ageing, and to present potential research avenues on how to account for these effects in mathematical and computational models of the skin. This will be illustrated through recent work of the authors which provides a basis to those interested in developing mechanistic constitutive models capturing the mechanobiology of skin across the life course.

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A mechanics‐informed artificial neural network approach in data‐driven constitutive modeling

Asad

Avery

Farhat

2022

Numerical Meth Engineering

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A mechanics‐informed artificial neural network approach for learning constitutive laws governing complex, nonlinear, elastic materials from strain–stress data is proposed. The approach features a robust and accurate method for training a regression‐based model capable of capturing highly nonlinear strain–stress mappings, while preserving some fundamental principles of solid mechanics. In this sense, it is a structure‐preserving approach for constructing a data‐driven model featuring both the form‐agnostic advantage of purely phenomenological data‐driven regressions and the physical soundness of mechanistic models. The proposed methodology enforces desirable mathematical properties on the network architecture to guarantee the satisfaction of physical constraints such as objectivity, consistency (preservation of rigid body modes), dynamic stability, and material stability, which are important for successfully exploiting the resulting model in numerical simulations. Indeed, embedding such notions in a learning approach reduces a model's sensitivity to noise and promotes its robustness to inputs outside the training domain. The merits of the proposed learning approach are highlighted using several finite element analysis examples. Its potential for ensuring the computational tractability of multi‐scale applications is demonstrated with the acceleration of the nonlinear, dynamic, multi‐scale, fluid‐structure simulation of the supersonic inflation dynamics of a parachute system with a canopy made of a woven fabric.

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Microstructurally-based constitutive modelling of the skin – Linking intrinsic ageing to microstructural parameters

Cited by 31 publications

References 116 publications

Biotribology of the ageing skin—Why we should care

Biotribology of the ageing skin—Why we should care

Constitutive Modelling of Skin Ageing

A mechanics‐informed artificial neural network approach in data‐driven constitutive modeling

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