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    <title>Wiley: The Journal of Physiology: Table of Contents</title>
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      <link>https://physoc.onlinelibrary.wiley.com/doi/10.1113/JP289863?af=R</link>
      <pubDate>Thu, 01 Oct 2026 02:42:37 -0700</pubDate>
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      <title>A constitutive modelling framework for applications to in vivo longitudinal data: Evaluation in a 60‐day head‐down bed rest study on arterial function</title>
      <description>The Journal of Physiology, Volume 604, Issue 19, Page 8028-8049, 1 October 2026. </description>
      <dc:description>
Abstract figure legend We proposed a computational constitutive modelling framework that leverages longitudinal acquisitions of haemodynamic waveforms at multiple arterial locations to achieve a biomechanical characterisation of their (micro)structural remodelling processes. We applied our approach to in vivo data from our previous study on the effect of simulated microgravity (i.e. 60‐day head‐down bed rest, HDBR) on arterial function, characterising the remodelling response to altered haemodynamics of the carotid, femoral and popliteal arteries. Our analysis provided a plausible microstructural interpretation of the vascular adaptation to HDBR of leg arteries, which was driven both by increased vasoconstriction during HDBR and by altered collagen biomechanics. 









Abstract
Vascular cells continuously remodel the arterial wall (micro)structure in response to changes in their biomechanical/biochemical environment. Although the functional effects of arterial remodelling can be easily measured, assessing the underlying microstructural mechanisms is complex in vivo. Constitutive modelling is a computational technique that allows for linking whole‐organ function to tissue constituent‐level mechanics. However, the need for comprehensive biomechanical data for model parametrisation hampers its clinical applicability. In the present study, we propose a novel constitutive modelling framework that addresses this limitation by leveraging longitudinal acquisitions of pressure–diameter relationships at different arterial beds to aid model parametrisation. We applied our constitutive framework to data from a study on the effect of 60 days head‐down bed rest (HDBR) on arterial function, where pressure–diameter relationships of three arteries (carotid, femoral and popliteal) were measured at baseline, during HDBR (two time points) and during a 30‐day recovery (two time points). We modelled the arterial wall as a constrained mixture of elastin, collagen and vascular smooth muscle cells (VSMCs). The dimensionality of the parameterisation problem was reduced through assumptions on (i) the time evolution of the behaviour of individual constituents and (ii) consistency in intrinsic constituent mechanical properties across different arterial beds. Overall, the proposed framework captured well the in vivo data (R2 = 0.89 ± 0.05). We identified increased VSMC contraction and microstructural re‐arrangement of collagen fibres as key adaptations to haemodynamic changes during HDBR, also resulting in reversible de‐stiffening of peripheral arteries. The proposed approach appears promising for disentangling microstructural mechanisms of arterial remodelling in clinical settings.









Key points

Constitutive modelling is a computational technique that links the macroscopic behaviour of arteries to the microstructure and mechanics of the constituents of their wall.
Although constitutive modelling is used extensively on ex vivo data, the sparsity of biomechanical data that can be acquired in vivo hinders its applicability in clinical settings, where it could be instrumental in disentangling remodelling processes in ageing and disease.
We propose a novel framework that leverages longitudinal acquisition of arterial waveforms at different arterial sites to aid in the parametrisation of comprehensive constitutive models.
We exemplify the utility of our approach by teasing out the pivotal adaptation roles of vascular smooth muscle cell contraction and collagen microstructural remodelling in response to haemodynamic alterations resulting from prolonged head‐down bed rest.
Our approach shows promise for the quantitative characterisation of arterial remodelling from non‐invasive in vivo data that can be easily measured in clinical settings.


</dc:description>
      <content:encoded>&lt;img src="https://physoc.onlinelibrary.wiley.com/cms/asset/dd411cb4-d666-4749-b75a-676e5196944d/tjp70386-gra-0001-m.png"
     alt="Schematic representation of the arterial waveform acquisition timeline in the 60-day head-down bed rest study by Boutouyrie et al. (2022) Average modelled pressure–diameter relationship of the carotid (A and D), femoral (B and E) and popliteal (C and F) arteries at the five time points of the study and in the in vivo (active + passive) (A–C) and passive contractile states (D–F) Changes in biomechanical variables between the five study time points (B02: baseline, H29 and H52: 29th and 52nd day of head down bed rest, respectively, and R12 and R30: 12th and 30th days of recovery) at the three arterial sites (carotid, femoral, and popliteal artery) in in vivo conditions Changes in biomechanical variables between the five study time points (B02: baseline, H29 and H52: 29th and 52nd day of head down bed rest, respectively, and R12 and R30: 12th and 30th day of recovery) at the three arterial sites (carotid, femoral, and popliteal artery) in passive conditions Identifiability analysis of the VSMC volume fraction and stiffness-like parameter Example of fitted pressure–diameter relationships of the carotid (A, D and G), femoral (B, E and H) and popliteal (C, F and I) arteries of study participants (G2, B1 and H2, respectively) A constitutive modelling framework for applications to in vivo longitudinal data: Evaluation in a 60-day head-down bed rest study on arterial function"/&gt;
&lt;p&gt;&lt;b&gt;Abstract figure legend&lt;/b&gt; We proposed a computational constitutive modelling framework that leverages longitudinal acquisitions of haemodynamic waveforms at multiple arterial locations to achieve a biomechanical characterisation of their (micro)structural remodelling processes. We applied our approach to &lt;i&gt;in vivo&lt;/i&gt; data from our previous study on the effect of simulated microgravity (i.e. 60-day head-down bed rest, HDBR) on arterial function, characterising the remodelling response to altered haemodynamics of the carotid, femoral and popliteal arteries. Our analysis provided a plausible microstructural interpretation of the vascular adaptation to HDBR of leg arteries, which was driven both by increased vasoconstriction during HDBR and by altered collagen biomechanics. 

&lt;/p&gt;
&lt;br/&gt;
&lt;h2&gt;Abstract&lt;/h2&gt;
&lt;p&gt;Vascular cells continuously remodel the arterial wall (micro)structure in response to changes in their biomechanical/biochemical environment. Although the functional effects of arterial remodelling can be easily measured, assessing the underlying microstructural mechanisms is complex &lt;i&gt;in vivo&lt;/i&gt;. Constitutive modelling is a computational technique that allows for linking whole-organ function to tissue constituent-level mechanics. However, the need for comprehensive biomechanical data for model parametrisation hampers its clinical applicability. In the present study, we propose a novel constitutive modelling framework that addresses this limitation by leveraging longitudinal acquisitions of pressure–diameter relationships at different arterial beds to aid model parametrisation. We applied our constitutive framework to data from a study on the effect of 60 days head-down bed rest (HDBR) on arterial function, where pressure–diameter relationships of three arteries (carotid, femoral and popliteal) were measured at baseline, during HDBR (two time points) and during a 30-day recovery (two time points). We modelled the arterial wall as a constrained mixture of elastin, collagen and vascular smooth muscle cells (VSMCs). The dimensionality of the parameterisation problem was reduced through assumptions on (i) the time evolution of the behaviour of individual constituents and (ii) consistency in intrinsic constituent mechanical properties across different arterial beds. Overall, the proposed framework captured well the &lt;i&gt;in vivo&lt;/i&gt; data (&lt;i&gt;R&lt;/i&gt;
&lt;sup&gt;2&lt;/sup&gt; = 0.89 ± 0.05). We identified increased VSMC contraction and microstructural re-arrangement of collagen fibres as key adaptations to haemodynamic changes during HDBR, also resulting in reversible de-stiffening of peripheral arteries. The proposed approach appears promising for disentangling microstructural mechanisms of arterial remodelling in clinical settings.

&lt;/p&gt;
&lt;h2&gt;Key points&lt;/h2&gt;
&lt;p&gt;
Constitutive modelling is a computational technique that links the macroscopic behaviour of arteries to the microstructure and mechanics of the constituents of their wall.
Although constitutive modelling is used extensively on &lt;i&gt;ex vivo&lt;/i&gt; data, the sparsity of biomechanical data that can be acquired &lt;i&gt;in vivo&lt;/i&gt; hinders its applicability in clinical settings, where it could be instrumental in disentangling remodelling processes in ageing and disease.
We propose a novel framework that leverages longitudinal acquisition of arterial waveforms at different arterial sites to aid in the parametrisation of comprehensive constitutive models.
We exemplify the utility of our approach by teasing out the pivotal adaptation roles of vascular smooth muscle cell contraction and collagen microstructural remodelling in response to haemodynamic alterations resulting from prolonged head-down bed rest.
Our approach shows promise for the quantitative characterisation of arterial remodelling from non-invasive &lt;i&gt;in vivo&lt;/i&gt; data that can be easily measured in clinical settings.
&lt;/p&gt;</content:encoded>
      <dc:creator>
Alessandro Giudici, 
Karen Barchetti, 
Umit Gencer, 
Hakim Khettab, 
Elie Mousseaux, 
Carole Leguy, 
Tammo Delhaas, 
Rosa Maria Bruno, 
Bart Spronck, 
Pierre Boutouyrie
</dc:creator>
      <category>Research Article</category>
      <dc:title>A constitutive modelling framework for applications to in vivo longitudinal data: Evaluation in a 60‐day head‐down bed rest study on arterial function</dc:title>
      <dc:identifier>10.1113/JP289863</dc:identifier>
      <prism:publicationName>The Journal of Physiology</prism:publicationName>
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      <prism:url>https://physoc.onlinelibrary.wiley.com/doi/10.1113/JP289863?af=R</prism:url>
      <prism:section>Research Article</prism:section>
      <prism:volume>604</prism:volume>
      <prism:number>19</prism:number>
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