Content area
Quantifying the material properties of tissues and hydrogels aids in the development of biomedical applications through better understanding of the mechanics and mechanobiological principles at play. This study introduces a mechanical testing platform designed to address challenges in measuring mm-scale tissue and hydrogel material properties. Using a floating buoy design, the platform enables horizontal submerged tensile testing with non-submersible load cells. Buoy drag testing without a sample attached resulted in signal noise (mean ± standard deviation) of −1.6E-4 ± 2.8E-2 mN for stationary recording and 1.3E-2 ± 6.7E-2 mN for maximum buoy displacement speed (1000 µm/s), suggesting the magnitude of drag forces from buoy movement are negligible in comparison to the minimum resolution of force measurement. Validation testing with latex orthodontic bands showed a ∼ 28 × reduction in signal noise with the buoy approach compared to a previously used approach, and similar force displacement recordings using the buoy approach with 2 separate hardware systems. Simultaneous imaging enabled geometrical and microstructural analysis of the sample. Murine bladder tissue was mechanically tested using two different hardware systems and testing protocols. The platform was able to accurately capture the nonlinear stress-stretch response, alongside expected strain-softening and preconditioning behavior. Stress-relaxation testing yielded results consistent with expected microstructural and viscoelastic responses of mouse bladder tissue. The versatility of the platform underscores the potential for it to integrate with various force measurement and actuator-based systems. In conclusion, this platform offers a new avenue for accurate measurement of tissue and hydrogel mechanics, facilitating mm-scale soft material research.
Quantifying tissue mechanics is crucial for understanding tissue physiology, as tissues like tendons, bones, the urinary bladder, and blood vessels provide essential mechanical support (Viano, 1986). Pathological changes in microstructure can impair mechanical function, contributing to dysfunction in diseases affecting the urinary bladder (Cortivo et al., 1981; Eika et al., 1992; Gloeckner et al., 2002; Wang et al., 2009; Zwaans et al., 2022). Relating microstructure to mechanical properties is key to understanding disease progression, treatment efficacy, and developing predictive disease models (Chen et al., 2020). For example, cystometry is a common technique for clinical evaluation of bladder function. Interpretation of cystometric measurements relies on relating microstructural composition and configuration to accurate measures of tissue level biomechanics (Gammie and Wachter, 2023; Hennig et al., 2022; McCormack et al., 2024).
Despite its importance, current methods of measuring soft tissue mechanics are difficult to implement and often provide insufficient data quality, particularly at the mm- and mN-scale. Mechanical testing systems for soft tissues often require custom setups involving load cells, actuators, and mounts tailored to specific tissues and protocols. Tensile testing, a commonly used method, faces challenges due to factors like viscoelasticity, tissue hydration, and sample geometry, complicating mechanical response characterization.
Systems designed to test tissues from larger animals (e.g. pigs or rats (Tuttle et al., 2023; Tuttle et al., 2022b)) can result in low signal-to-noise ratios when used on mm- and mN-scale materials (e.g. from mice (Zwaans et al., 2022)). This occurs due to the low force range needed for these tissues, and high signal noise that is affected by load cell capacity, working voltage, electromagnetic interference, and mechanical noise (e.g. vibrational). Commercially available systems typically employ upright configurations (Jayyosi et al., 2018), as do many custom setups (Li et al., 2018; Tuttle et al., 2022a; Tuttle et al., 2022b; Zwaans et al., 2022), complicating microstructural imaging. Other drawbacks include open air testing (Jiang et al., 2020; Svensson et al., 2018; Ye et al., 2017), indirect force measurement (Acuna et al., 2021), force estimation based on displacement tracking (Elhebeary et al., 2019; Rosalia et al., 2023), need for submersible load cells (Tuttle et al., 2023), or hanging clamps (Jiang et al., 2020; Tuttle et al., 2023), which can induce damaging loads on sensitive load cells.
We address these challenges by introducing a buoy-based mechanical testing platform, enabling horizontal submerged tensile testing of small gels and tissues. This setup facilitates sample hydration and microstructural imaging, avoids damaging loads on sensitive load cells, and eliminates the need for submersible load cells. The platform was validated through off-target force testing without samples, mechanical testing of orthodontic bands, and testing of murine urinary bladder tissue, which exhibits a known viscoelastic response (Cullingsworth et al., 2020; Speich et al., 2005). Two different hardware systems were used to demonstrate versatility and consistency. The widespread availability of 3D printing and the platform’s modular design allow for easy adaptation to various load cells and actuators. These innovations enhance our ability to quantify changes in tissue microstructure and mechanics, facilitating improved understanding of how alterations due to disease pathophysiology affects the material properties of load-bearing tissues.
2 Methods2.1 Design
2.1.1 Conceptual overview
The mechanical testing platform (Fig. 1) is comprised of a load cell and actuator, connected to a buoy immersed in a bath. The sample is submerged in solution (e.g. Hanks' Balanced Salt Solution with calcium (HBSS+)) and mounted to the bath and buoy for unidirectional tensile testing. The systems presented here were designed specifically for gels and tissues ranging in stiffness from 0.6–60 kPa. The authors recommend proper consideration of specimen geometry, load cell, component materials, and imaging modalities to accommodate forces and deformations outside of the intended range.
The custom designed system components and 3D renderings were created in SOLIDWORKS (Dassaut Systemes, Vélizy-Villacoublay FR), and 3D printed (Prusa MK3S+, Prusa Research, Prague CZ), using polylactide (PLA) at 220 °C, 0.4 mm brass nozzle, 100 % infill, and 1.05 extrusion multiplier. The 3D models in Fig. 1 are available on Mendeley Data (Tyler Tuttle, 2024).
2.1.2 Actuator / load cellTwo hardware systems were used, each comprised of a load cell and actuator. Actuator movement and force recording was coordinated in LabVIEW, as previously described (Acuna et al., 2021). System 1 (Fig. 1b–c) incorporated a FemtoTools micromanipulator (FT-RS1002) with a 100 mN capacity force sensor (FT-S100000) featuring a 65 µm mounting hook. System 2 (Fig. 1d–e) used a 3-axis translation stage (Thorlabs PT3), with one axis controlled by a linear actuator (ThorLabs ZST225B) and controller (ThorLabs KST201), a 10 g capacity load cell (Futek LSB200), and a laser cut (Trotec Speedy 360) 500 µm mounting hook. A 44 AWG (0.0508 µm diameter) 316L stainless steel wire attached to the buoy arm with cyanoacrylate adhesive served as an attachment point between the force sensor and buoy.
2.1.3 BuoyA four-barrel buoy was designed with circular cylinder rear barrels (r × h, 4.8 × 11.1 mm) and stadium cylinder front barrels (a × r × h, 4.8 × 4.8 × 12.7 mm) to ensure stable floating and shift center of buoyancy to compensate for overhanging arm weight. Buoy dimensions were iteratively updated to achieve even floating in HBSS+, which was confirmed visually and with angular measurements from side-view images. The overhanging arm extends over the front of the bath, allowing the force sensor to hook onto the buoy in alignment with the mounted sample. The mounting side of the buoy can be customized to the researchers’ needs. The sample mount shown used 0.79 mm diameter 316 stainless steel dowel pins (McMaster-Carr 97395A357) attached vertically to the buoy and bath. Ring-shaped samples were mounted around the pins and deformed unidirectionally, a method commonly employed for blood vessels and urinary bladder tissue (Grobbel et al., 2021; Tuttle et al., 2022a; Tuttle et al., 2022b; Zwaans et al., 2022).
2.1.4 BathBarriers were included to keep the buoy stationary when the pins are engaged with a sample. A mirror affixed to the bath at 45° to enabled top and side viewing of the sample for geometrical evaluation.
2.2 Validation testing2.2.1 Off-Target forces
Using System 1, off-target forces, such as inertial or drag forces between the buoy and testing solution, were assessed by displacing the buoy in the bath with the force sensor attached but no sample. The protocol (Fig. 2a) included 10 s of stationary recording, followed by buoy displacement at speeds of 1, 10, 100, and 1000 µm/s for 10 s each, then a final 10 s of stationary recording, repeated three times per speed. For a test starting with a sample circumscribing contacting pins, the displacement rates equated to strain rates of ∼0.0005, 0.005, 0.05, and 0.5 s−1.
2.2.2 Validation testingMechanical tests were performed on latex orthodontic bands (light − 3/16″, Prairie Horse Supply) using the buoy approach with System 1 and System 2 (n = 3), and a rail-slider approach with System 2 hardware (n = 1). The rail-slider was used previously in our lab with a higher capacity load cell (Luetkemeyer et al., 2023). After removing slack (∼10 mN), a band was stretched to 1.5 mm displacement at 30 µm/s and unloaded to the initial length. Signal to noise ratio was calculated by normalizing the force range of the linear fit of the loading data to the standard deviation of residuals. Force and displacement data were zero-offset to the linear force–displacement region, defined as the last 1 mm of displacement, and tangential stiffness was calculated by linearly fitting a line to the data. A paired t-test was performed between systems on tangential stiffness values.
2.2.3 Tissue mechanical testingMouse bladders were excised from adult wild type mice (n = 5) on a C57BL/6 background. All murine experiments were approved by the University of Colorado’s Institutional Animal Care and Use Committee (IACUC, protocol #2705). IACUC ensures that all animal programs, procedures and facilities at the university adhere to the policies, recommendation, guidelines, and regulations of the USDA and the United States Public Health Service following the Animal Welfare Act and university Animal Welfare Assurance. Mice were euthanized via CO2 inhalation followed by cervical dislocation. Urinary bladders were isolated and circumferential rings were prepared, as shown previously (Tuttle et al., 2022b). Cyclical and stress-relaxation tensile testing were conducted. For cyclical testing (System 1), a preload of 500 µN was applied, followed by 5 cycles of force-mediated deformation from ∼ 0–5 kPa at a loading speed of 30 µm/s (∼1.3 s−1) and unloading speed of 60 µm/s. Video of the deformation was recorded with a camera (Lumenera Infinity 3) and brightfield microscope (Leica M80). Pin locations were tracked using the Fiji plugin TrackMate (Schindelin et al., 2012; Tinevez et al., 2017). Stretch was defined by post-preload configuration () or 5th cycle starting configuration (). Stress was calculated by normalizing forces to initial sample cross-sectional area, measured manually from initial mounted images (Fig. 2b).
Stress-relaxation testing (System 2) used a 100 µN preload, deformation to a force of 11 mN at 60 µm/s, followed by 15 min of stationary relaxation. Microstructural images were captured before and at maximum deformation with second harmonic generation (SHG), using a GEMINI Olympus FVMPE-RS twin laser multi-photon microscope (MPM) in the University of Colorado Boulder Light Microscopy Core Facility.
3 Results3.1 Off-Target forces
Minimal off-target forces were measured when displacing the buoy with no sample attached. During the initial stationary phase (Fig. 2a–f, Fig. S1), forces were centered around ∼0 µN (mean ± standard deviation of −1.6E-4 ± 2.8E-2 mN). During the dynamic phase (10–20 s), force remained centered around zero, but noise (i.e. magnitude of standard deviation) increased at 100 and 1000 µm/s (mean ± standard deviation for 1, 10, 100, 1000 µm/s, respectively: 3.4E-3 ± 2.9E-2, 1.1E-2 ± 3.0E-2, −8.7E-4 ± 3.7E-2, 1.3E-2 ± 6.7E-2 mN) (Fig. 2f). At 1000 µm/s, force increased at the initiation of movement (Fig. 2f, M1), but quickly returned to zero (Fig. 2f, M2).
3.2 System comparison testingThe buoy approach had appreciably less noise than the rail-slider approach when tensile testing orthodontic bands using System 2 hardware (Fig. 2g). Standard deviation of linear fit residuals was 0.68 and 24.59 mN, and signal to noise ratios were 129.1 and 4.5, respectively. Individual orthodontic bands demonstrated similar force–displacement curves in the linear region when comparing System 1 and 2 using the buoy approach (Fig. 2h), with no significant difference in linear tangential stiffness (p = 0.702, Fig. 2i).
3.3 Tissue mechanical testingThe buoy approach captured the viscoelasticity, high compliance, preconditioning, and strain-softening of murine bladder tissue. On System 1, the mouse bladder ring sample was clearly distinguishable from the mounting pins and background (Fig. 3b–c). During force-mediated cyclical testing, zero-load tissue length increased after the first cycle (Fig. 3 e), and force recordings were nonlinear (Fig. 3d,f). Differences between cycle 1 and cycles 2–5 in force–displacement and stress-stretch plots demonstrate preconditioning (Fig. 3f–h), while 5th cycle loading stress-stretch curves demonstrate biological variability (Fig. 3h,i).
During stress-relaxation testing, the bladder tissue relaxed 25.8 % over the timeframe (Fig. 4b). In MPM images, collagen fibers appeared wavy in undeformed tissue (Fig. 4c), and more aligned in deformed tissue (Fig. 4d).
4 DiscussionThe described buoy-based mechanical testing platform features unique flotation and attachment capabilities, allows accurate force measurement with high signal–noise ratio, minimal off-target forces, and adaptability to different testing hardware and experimental protocols. Submerged tensile testing allows physiologically relevant mechanical assessment. Simultaneous imaging capabilities of the platform enhance its utility by allowing examination of microstructural alterations under mechanical loading conditions. While murine bladders are compliant compared to many other tissues, our previous work utilized different embodiments of the platform to study less compliant materials such as fibrin gels and murine uterosacral ligaments (Bastías et al., 2023; Jimenez et al., 2023), highlighting the adaptability of the design.
Minimal off-target forces were observed during sample-free testing with HBSS+ (Fig. 2a–f), indicating negligible contributions to force measurement from inertia and drag exerted on the force sensor by buoy movement. This is evidenced by the mean force recordings during the dynamic phases at all displacement rates being smaller in magnitude than the standard deviation (i.e. noise) in the stationary signal. Further statistical analysis is shown in supplementary material (Table S1). Notably, at 1000 µm/s displacement (∼0.5 s−1 based on our typical sample size), a transient force jump occurred that rapidly diminished. This indicates a momentary measurable inertial force at the start of high-speed movement, but negligible drag forces thereafter. These forces would likely only impact the data in stress-relaxation tests with similarly high displacement rates, which is a common occurrence in other systems (Nagatomi et al., 2008).
When testing latex orthodontic bands using System 2 hardware, the buoy approach markedly outperformed the rail-slider approach with a ∼ 28 × increase in the signal to noise ratio. Additionally, oscillating off-target forces induced by friction from the ball bearings were evident in the rail-slider force–displacement data (Fig. 2g). System 1 and 2 recordings using the buoy approach were consistent for each sample tested, with no significant difference in tangential stiffness (Fig. 2i, p = 0.702).
Cyclical mechanical testing (Fig. 3) yielded results consistent with the anticipated mechanical response of bladder tissue (Chen et al., 2013; Colhoun et al., 2017; Sacks, 2000), displaying a nonlinear stress-stretch relationship, preconditioning evidenced by differences between the first and subsequent cycles, and strain-softening characterized by increased zero-load tissue length. Imaging provided sufficient resolution and contrast to estimate sample geometry from top and side perspectives.
Stress-relaxation tests (Fig. 4) captured the viscoelastic response of mouse bladder tissue, with relaxation times comparable to studies in pigs and rats (Nagatomi et al., 2004; Tuttle et al., 2023). The capability to image bladder microstructure at various deformation levels offers valuable insights into bladder physiology, enhancing data quality for computational modeling and advancing our understanding of tissue mechanics.
The system has some limitations. Due to the sensitivity of the load cells, small perturbations to the testing fluid (e.g. due to submersion of the microscope objective) can result in increased noise in force recording. Additionally, evaporation of solution during long tests (>1hr) can decrease buoy height, affecting force readings, which can be remedied by measuring the evaporation rate from the system and replacing fluid periodically throughout testing.
In summary, the mechanical testing platform introduced in this study effectively addresses key challenges in assessing tissue mechanics at the mm- and mN-scale. The innovative buoy design provides an easy method of sample to load cell attachment while facilitating high measurement accuracy with minimal off-target forces. The improvements upon other systems in the literature, combined with the versatility of the design to integrate into existing setups will help facilitate experiments that further the understanding of the biomechanics of mm- and mN-scale gels and tissues.
CRediT authorship contribution statementTyler Tuttle: Writing – review & editing, Writing – original draft, Visualization, Validation, Supervision, Methodology, Investigation, Funding acquisition, Formal analysis, Conceptualization. Daniel Deuel: Writing – review & editing, Visualization, Validation, Methodology, Formal analysis. Sarah Calve: Writing – review & editing, Writing – original draft, Supervision, Resources, Project administration, Funding acquisition, Conceptualization.
Declaration of competing interestThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
AcknowledgementsThis work was supported by NIH R21 AG085874, NIH T32 AG000279, and NIH DP2 AT009833.
Appendix A Supplementary materialSupplementary data to this article can be found online at https://doi.org/10.1016/j.jbiomech.2024.112442.
Appendix A Supplementary materialThe following are the Supplementary data to this article:Supplementary Data 1
©2024. Elsevier Ltd