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Fibrin is a naturally occurring protein network that forms a temporary structure to enable remodeling during wound healing. It is also a common tissue engineering scaffold because the structural properties can be controlled. However, to fully characterize the wound healing process and improve the design of regenerative scaffolds, understanding fibrin mechanics at multiple scales is necessary. Here, we present a strategy to quantify both the macroscale (1–10 mm) stress-strain response and the deformation of the mesoscale (10–1000 µm) network structure during unidirectional tensile tests. The experimental data were then used to inform a computational model to accurately capture the mechanical response of fibrin gels. Simultaneous mechanical testing and confocal microscopy imaging of fluorophore-conjugated fibrin gels revealed up to an 88% decrease in volume coupled with increase in volume fraction in deformed gels, and non-affine fiber alignment in the direction of deformation. Combination of the computational model with finite element analysis enabled us to predict the strain fields that were observed experimentally within heterogenous fibrin gels with spatial variations in material properties. These strategies can be expanded to characterize and predict the macroscale mechanics and mesoscale network organization of other heterogeneous biological tissues and matrices. 

Perivascular adipose tissue (PVAT) is increasingly recognized as an essential layer of the functional vasculature, being responsible for producing vasoactive substances and assisting arterial stress relaxation. Here, we test the hypothesis that PVAT reduces aortic stiffness. Our model was the thoracic aorta of the male Sprague–Dawley rat. Uniaxial mechanical tests for three groups of tissue were performed: aorta with PVAT attached (+PVAT) or removed (−PVAT), and isolated PVAT (PVAT only). The output of the mechanical test is reported in the form of a Cauchy stress-stretch curve. This work presents a novel, physiologically relevant approach to measure mechanical stiffness ex vivo in isolated PVAT. Low-stress stiffness ( E 0 ), high-stress stiffness ( E 1 ), and the stress corresponding to a stretch of 1.2 (σ 1.2 ) were measured as metrics of distensibility. The low-stress stiffness was largest in the −PVAT samples and smallest in PVAT only samples. Both the high-stress stiffness and the stress at 1.2 stretch were significantly higher in −PVAT samples when compared with +PVAT samples. Taken together, these results suggest that −PVAT samples are stiffer (less distensible) both at low stress (not significant) as well as at high stress (significant) when compared with +PVAT samples. These conclusions are supported by the results of the continuum mechanics material model that we also used to interpret the same experimental data. Thus, tissue stiffness is significantly lower when considering PVAT as part of the aortic wall. As such, PVAT should be considered as a target for improving vascular function in diseases with elevated aortic stiffness, including hypertension. NEW & NOTEWORTHY We introduce a novel and physiologically relevant way of measuring perivascular adipose tissue (PVAT) mechanical stiffness which shows that PVAT’s low, yet measurable, stiffness is linearly correlated with the amount of collagen fibers present within the tissue. Including PVAT in the measurement of the aortic wall’s mechanical behavior is important, and it significantly affects the resulting metrics by decreasing aortic stiffness. 

We introduce a data-driven fractional modeling framework for complex materials, and particularly bio-tissues. From multi-step relaxation experiments of distinct anatomical locations of porcine urinary bladder, we identify an anomalous relaxation character, with two power-law-like behaviors for short/long long times, and nonlinearity for strains greater than 25%. The first component of our framework is an existence study, to determine admissible fractional viscoelastic models that qualitatively describe linear relaxation. After the linear viscoelastic model is selected, the second stage adds large-strain effects to the framework through a fractional quasi-linear viscoelastic approach for the nonlinear elastic response of the bio-tissue of interest. From single-step relaxation data of the urinary bladder, a fractional Maxwell model captures both short/long-term behaviors with two fractional orders, being the most suitable model for small strains at the first stage. For the second stage, multi-step relaxation data under large strains were employed to calibrate a four-parameter fractional quasi-linear viscoelastic model, that combines a Scott-Blair relaxation function and an exponential instantaneous stress response, to describe the elastin/collagen phases of bladder rheology. Our obtained results demonstrate that the employed fractional quasi-linear model, with a single fractional order in the range α = 0.25–0.30, is suitable for the porcine urinary bladder, producing errors below 2% without need for recalibration over subsequent applied strains. We conclude that fractional models are attractive tools to capture the bladder tissue behavior under small-to-large strains and multiple time scales, therefore being potential alternatives to describe multiple stages of bladder functionality.