Simulating the sensitivity of cell nutritive environment to composition changes within the intervertebral disc

Wills, Carlos Ruiz; Malandrino, Andrea; Rijsbergen, Mm. van; Lacroix, Damien; Ito, Keita; Noailly, Jérôme

doi:10.1016/j.jmps.2016.02.003

Cited by 19 publications

(5 citation statements)

References 57 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As mentioned before, our AB input parameters, i.e., local nutrient concentrations, were obtained through the results at the element level of mechanotransport FE simulations ( Ruiz Wills et al, 2018 ). Our predicted CA targets the differential regulation of extracellular matrix turnover that can be used to update the properties of composition-based disc tissue models ( Barthelemy et al, 2016 ; Ruiz Wills et al, 2016 ), leading to incremental perturbation of local CA in a next iteration of FE-AB simulations. Hence, the present model is deemed to importantly contribute to the development of multiscale modelling approaches to explore intervertebral disc degeneration, where biologically-driven tissue injury includes dynamics over multiple spatial scales ( Vergroesen et al, 2015 ).…”

Section: Discussionmentioning

confidence: 99%

Evidence-Based Network Modelling to Simulate Nucleus Pulposus Multicellular Activity in Different Nutritional and Pro-Inflammatory Environments

Baumgartner

Sadowska

Tío

et al. 2021

Front. Bioeng. Biotechnol.

Self Cite

View full text Add to dashboard Cite

Initiation of intervertebral disc degeneration is thought to be biologically driven. This reflects a process, where biochemical and mechanical stimuli affect cell activity (CA) that compromise the tissue strength over time. Experimental research enhanced our understanding about the effect of such stimuli on different CA, such as protein synthesis or mRNA expression. However, it is still unclear how cells respond to their native environment that consists of a “cocktail” of different stimuli that might locally vary. This work presents an interdisciplinary approach of experimental and in silico research to approximate Nucleus Pulposus CA within multifactorial biochemical environments. Thereby, the biochemical key stimuli glucose, pH, and the proinflammatory cytokines TNF-α and IL1β were considered that were experimentally shown to critically affect CA. To this end, a Nucleus Pulposus multicellular system was modelled. It integrated experimental findings from in vitro studies of human or bovine Nucleus Pulposus cells, to relate the individual effects of targeted stimuli to alterations in CA. Unknown stimulus-CA relationships were obtained through own experimental 3D cultures of bovine Nucleus Pulposus cells in alginate beads. Translation of experimental findings into suitable parameters for network modelling approaches was achieved thanks to a new numerical approach to estimate the individual sensitivity of a CA to each stimulus type. Hence, the effect of each stimulus type on a specific CA was assessed and integrated to approximate a multifactorial stimulus environment. Tackled CA were the mRNA expressions of Aggrecan, Collagen types I & II, MMP3, and ADAMTS4. CA was assessed for four different proinflammatory cell states; non-inflamed and inflamed for IL1β, TNF-α or both IL1β&TNF-α. Inflamed cell clusters were eventually predicted in a multicellular 3D agent-based model. Experimental results showed that glucose had no significant impact on proinflammatory cytokine or ADAMTS4 mRNA expression, whereas TNF-α caused a significant catabolic shift in most explored CA. In silico results showed that the presented methodology to estimate the sensitivity of a CA to a stimulus type importantly improved qualitative model predictions. However, more stimuli and/or further experimental knowledge need to be integrated, especially regarding predictions about the possible progression of inflammatory environments under adverse nutritional conditions. Tackling the multicellular level is a new and promising approach to estimate manifold responses of intervertebral disc cells. Such a top-down high-level network modelling approach allows to obtain information about relevant stimulus environments for a specific CA and could be shown to be suitable to tackle complex biological systems, including different proinflammatory cell states. The development of this methodology required a close interaction with experimental research. Thereby, specific experimental needs were derived from systematic in silico approaches and obtained results were directly used to enhance model predictions, which reflects a novelty in this research field. Eventually, the presented methodology provides modelling solutions suitable for multiscale approaches to contribute to a better understanding about dynamics over multiple spatial scales. Future work should focus on an amplification of the stimulus environment by integrating more key relevant stimuli, such as mechanical loading parameters, in order to better approximate native physiological environments.

show abstract

Section: Discussionmentioning

confidence: 99%

Evidence-Based Network Modelling to Simulate Nucleus Pulposus Multicellular Activity in Different Nutritional and Pro-Inflammatory Environments

Baumgartner

Sadowska

Tío

et al. 2021

Front. Bioeng. Biotechnol.

Self Cite

View full text Add to dashboard Cite

show abstract

“…Hence, metabolic bio-mechanical models appeared focusing on the cellular viability mechanisms, the nutrient diffusion 4 (oxygen, glucose and lactate) and the effect of applied mechanical loads on their distribution all over the disc [35][36][37][38][39][40][41]. Recently, these models evolved largely by incorporating the influence of the nutrient distribution and the disc metabolism on the cells synthesis, the microstructure remodeling of the proteoglycan network and the water content [42][43][44] and their incidence on the stress distribution inside the disc. Despite the important advance accomplished by these models and their promising results, they cannot yet investigate sufficiently the global long-term effects on the mechanical behavior of the disc tissues.…”

Section: Introductionmentioning

confidence: 99%

A microstructure-based modeling approach to assess aging-sensitive mechanics of human intervertebral disc

Kandil

Zaïri

Messager

et al. 2021

Computer Methods and Programs in Biomedicine

View full text Add to dashboard Cite

“…To elucidate the relationship between biphasic/poroelastic models and IVD deformations quantified by J, it's essential to connect the variables in the equations for the non-fibrillar solid matrix's effective stress S11 and the osmotic potential S15. The proteoglycan fixed charge density is determined by the ratio of the normal fixed charge density (c f ) in milliequivalents per milliliter of total fluid to the extra-fibrillar water (n f,exf ), as defined by Ruiz et al (2016):…”

Section: Tissue Model Parameters and Relation To Composition Measurem...mentioning

confidence: 99%

“…To ascertain water content, the initial step involves measuring the tissue sample's wet weight (WW) (Huyghe et al, 2003;Malandrino et al, 2015;Ruiz et al, 2016), followed by lyophilization to obtain the dry weight (DW). These measurements facilitate the calculation of the initial total water content (n f,0 ) and, subsequently, the initial solid fraction and the current fluid fraction:…”

Section: Tissue Model Parameters and Relation To Composition Measurem...mentioning

confidence: 99%

See 1 more Smart Citation

DataSheet1.pdf

View full text Add to dashboard Cite

Simulating the sensitivity of cell nutritive environment to composition changes within the intervertebral disc

Cited by 19 publications

References 57 publications

Evidence-Based Network Modelling to Simulate Nucleus Pulposus Multicellular Activity in Different Nutritional and Pro-Inflammatory Environments

Evidence-Based Network Modelling to Simulate Nucleus Pulposus Multicellular Activity in Different Nutritional and Pro-Inflammatory Environments

A microstructure-based modeling approach to assess aging-sensitive mechanics of human intervertebral disc

DataSheet1.pdf

Contact Info

Product

Resources

About