Overload in a Rat In Vivo Model of Synergist Ablation Induces Tendon Multiscale Structural and Functional Degeneration

Abstract

Tendon degeneration is typically described as an overuse injury with little distinction made between magnitude of load (overload) and number of cycles (overuse). Further, in vivo, animal models of tendon degeneration are mostly overuse models, where tendon damage is caused by a high number of load cycles. As a result, there is a lack of knowledge of how isolated overload leads to degeneration in tendons. A surgical model of synergist ablation (SynAb) overloads the target tendon, plantaris, by ablating its synergist tendon, Achilles. The objective of this study was to evaluate the structural and functional changes that occur following overload of plantaris tendon in a rat SynAb model. Tendon cross-sectional area (CSA) and shape changes were evaluated by longitudinal MR imaging up to 8 weeks postsurgery. Tissue-scale structural changes were evaluated by semiquantified histology and second harmonic generation microscopy. Fibril level changes were evaluated with serial block face scanning electron microscopy (SBF-SEM). Functional changes were evaluated using tension tests at the tissue and microscale using a custom testing system allowing both video and microscopy imaging. At 8 weeks, overloaded plantaris tendons exhibited degenerative changes including increases in CSA, cell density, collagen damage area fraction (DAF), and fibril diameter, and decreases in collagen alignment, modulus, and yield stress. To interpret the differences between overload and overuse in tendon, we introduce a new framework for tendon remodeling and degeneration that differentiates between the inputs of overload and overuse. In summary, isolated overload induces multiscale degenerative structural and functional changes in plantaris tendon.

1 Introduction

Tendon degeneration and mechanical damage are widely referred to as an overuse injury, with little distinction in the clinical or research communities between the magnitude of load (overload) or the number of cycles (overuse) as the injury mechanism. Clinically, there are two primary tendon disorders, overuse tendinopathy and acute tendon rupture, and these are associated with different loading environments. Overuse tendinopathy is a painful disorder that most commonly occurs in individuals who perform a high number of repeated motions at relatively normal load magnitudes such as athletes and manual laborers [1–3]. In contrast, tendon rupture most commonly occurs in an apparently asymptomatic (pain-free) tendon and is associated with rapid increases in force magnitude or direction during activity [4–7]. Importantly, both tendinopathy and tendon rupture occur in degenerating tendons, as indicated by evaluation of the tendon after acute rupture [7–9]. Because the clinical presentation between tendinopathy and tendon rupture is quite different, it is likely that different mechanisms and pathways lead to the end-stage degenerative state. However, animal models of tendon degeneration are mostly focused on overuse [10–12]. As a result, there is a need to understand how overload, in the absence of overuse, leads to tendon degeneration.

Prior animal models of overuse induce damage primarily via increasing the number of loading cycles (e.g., using treadmill running). Additionally, previous animal models have used an increased number of loading cycles to induce degeneration combined with a moderately increased magnitude of load via inclined treadmill running [13,14]. Notably, some overuse animal models do not develop degenerative tendon changes; and therefore, may be more accurately considered exercise models, where tendons adapt to the increased loading demands with increasing cross-sectional area (CSA) and stiffness but without degenerative changes, similar to humans [15,16]. Degenerative structural tendon changes in animal models include atypical collagen fibril size, organization, type, and content; increased proteoglycan content; and increased cell density as well as cell and nuclear morphology changes [13,14,17–25]. Degenerative tendons also experience functional deficits, such as decreases in tendon stiffness or modulus, and ultimate stress [10,13,26–29].

In contrast to overuse models, synergistic ablation (SynAb) is an animal model originally used to study muscular hypertrophy in which the tendon-muscle unit of interest is overloaded by surgically ablating its synergist [30–33]. To overload the plantaris tendon in rodent hindlimbs, the Achilles tendon has been surgically ablated [34–36]. Short-term remodeling of the plantaris up to four weeks following SynAb has demonstrated increases in CSA, proteoglycan content, collagen expression, and regional increases in cell density [34–37]. Similarly, a recent study used a comparable procedure in the murine shoulder where the infraspinatus tendon was ablated and the synergist tendon (supraspinatus) exhibited increased CSA, decreased proteoglycan content, and decreases in stiffness, maximum force, and ultimate stress after 4 weeks [26]. It remains unknown, however, whether tendon overload will lead to chronic tendon degeneration, as previous studies of isolated overload cover a relatively short time duration [26,35–37]. Clinical and preclinical model definitions for “chronic” tendon disorders vary, with clinical chronic tendinopathy spanning 3 months to 30 years, while previous preclinical animal studies have considered timepoints from 6 to 8 weeks as the beginning of chronic changes [38–44]. Therefore, the objective of this study was to investigate whether overload of the plantaris tendon leads to chronic degeneration by investigating the multiscale structure and function up to 8 weeks following SynAb of the Achilles tendon. We hypothesized that tendon overload via SynAb will result in degenerative changes, such as an increase in tendon CSA, increased cell density, decreased collagen alignment, increase in collagen fibril diameter, and decrease in tissue modulus.

2 Methods

2.1 Surgical Procedure.

All experiments were approved by the University of Delaware Institutional Animal Care and Use Committee. Seven-month-old Long-Evans female virgin rats were obtained (Charles River Laboratory, Table 1). These rats were randomly assigned to one of three groups: surgical synergistic ablation of the Achilles tendon (SynAb), sham surgery (Sham), or intact nonsurgical control (Intact). To increase loading of the plantaris tendon in the SynAb group, bilateral Achilles tenectomy was performed under 2–3% isoflurane anesthesia. First, a subcutaneous injection of bupivacaine (0.1 mg/kg) was administered at the site of incision to reduce sensation during the procedure, while a subcutaneous buprenorphine injection (0.05 mg/kg) was given to alleviate pain at the end of the procedure. Incision sites were closed with Vicryl 3-0 sutures or skin glue (VetBond, 3M, Maplewood, MN). Silver sulfadiazine was applied topically to the incision site to mitigate infection risk for incisions closed with sutures. Following surgery, animals were allowed to ambulate at will with access to water, solid food, and a heat source for at least 4 h before returning to their normal cages. The sham group followed the same bilateral surgical protocol described for SynAb without resection of the Achilles tendon. The intact group included age-matched animals which received no surgical intervention. Animals were evaluated for activity and tendon geometry for up to 8 weeks, as described below. As experiments were completed in two age-matched cohorts, activity monitoring was completed for the second group only, and not all animals underwent this analysis. After 8 weeks, animals were euthanized, and the left and right tendons were block randomized. One tendon was immediately prepared for histology and serial block face scanning electron microscopy (SBF-SEM), while the other limb was left intact and frozen for multiscale biomechanical testing and second harmonic generational (SHG) imaging, as described below.

Table 1.

Distribution of study animals

Assay	# Animals	# Tendons
Activity monitoring	6 (2/group)	N/A
MRI	18 (6/group)	36 (12/group)
Histology	H&E: 12 (4/group)	H&E: 12 (4/group)
	PSR: 17 (5–6/group)	PSR: 17 (5–6/group)
SBF-SEM imaging	3 (1/group)	3 (1/group)
Mechanical testing	17 (5–6/group)	17 (5–6/group)
SHG imaging	18 (6/group)	18 (6/group)

Note: Three groups were used: intact control, sham control, and synergist ablation (SynAb) Treatment.

2.2 Activity Monitoring.

Activity monitoring was performed to evaluate animal activity postsurgery. Rats (n = 2/group) were housed individually on the evening of monitoring (∼5PM) in a standard clear cage with a frame containing an infrared activity monitoring system placed on the outside of the cage (ActiTrack, PanLab, Barcelona, Spain). Distance traveled and number of hindlimb rearings were monitored throughout the night, and the recorded data were analyzed for an 8-h dark cycle, in 10-min bins and summed. Recordings were made pre-operatively for three consecutive nights for an average baseline activity and for one monitoring cycle 3-days, 2-, 4-, and 8-weeks postsurgery.

2.3 Longitudinal High-Resolution Magnetic Resonance Imaging.

To evaluate changes in cross-sectional area and shape of the plantaris tendon, rats were anesthetized using 2–3% inhaled isoflurane, and limbs were imaged using high-resolution magnetic resonance (MR) images (Bruker Biospec 94/20, Billerica, MA). MR images were acquired 2–3 days before surgery as a baseline measurement and at 4- and 8-weeks postsurgery (n = 4 rats/group, Table 1). The intact controls were imaged only at baseline and 8 weeks. For MR image acquisition, a 2 cm surface coil with global shimming was used to acquire multislice axial images using a three-dimensional T1 FISP sequence (TR/TE = 584/2.9 ms, Field of View = 16 × 31 × 86 mm, matrix = 165 × 224 × 43, spatial resolution = 100 × 140 × 200 μm, excitations = 4, flip angle = 10.0 deg and acquisition time = 6 min). The plantaris tendon and granulation tissue (in the SynAb group) were manually segmented using itk-snap software [45]. After segmentation and realignment of the tendon neutral axis in itk-snap, the tendon CSA and eccentricity and the granulation tissue CSA were calculated using matlab [45]. As the aspect ratio of the tendon changes rapidly close to the enthesis, we compared the median plantaris CSA and eccentricity at each time point for all segmented slices in a sample. This was to reduce the bias from the distance of a slice to the enthesis, as there was some variation between samples in number of slices with free tendon visible. Therefore, no comparisons were made along the length of the tendon because of the relatively large slice thickness and difficulty indexing location between slices.

2.4 Histology.

Immediately posteuthanasia, one plantaris tendon from each animal was dissected for use in structural assays, with half the tendon prepared for SBF-SEM, and the other going to histology. The plantaris tendon was dissected and then one-half fixed with 4% paraformaldehyde in Sorenson's buffer for at least 48 h before paraffin embedding, with the other half prepared for electron microscopy. Tendons were processed for paraffin histology. Paraffin processed tendons were transversely bisected at the midline, with one half randomly assigned to longitudinal sectioning. Longitudinal slices were stained using either Hematoxylin & Eosin (H&E) for cell density and morphology or Picrosirius Red (PSR) for collagen organization. H&E-stained sections were imaged using a brightfield microscope (EVOS M5000, Invitrogen, Waltham, MA). Sections stained with PSR were imaged using circular polarized light microscopy (Zeiss Imager A2, Zeiss, Oberkocken, Germany).

Sections stained with H&E were used to quantify the cell density and the cell nuclear aspect ratio (NAR). A custom ImageJ (Fiji) macro was used to segment the nuclei from the tendon similar to David et al. [46]. Briefly, we performed color deconvolution (vectors=H&E) followed by Gaussian blur (sigma = 2) and contrast enhancement (0.35%, normalize) to segment nuclei based on their high intensity threshold. Segmented nuclei were masked, and the analyze particles function in ImageJ was used to quantify nuclei number and morphological parameters, specifically NAR. Cell density was calculated based on the nuclei number per mm².

PSR stained sections were scored by 3 blinded reviewers using a semiquantitative scale from 1 to 5, with 5 being the best organization (5 = extremely organized and yellow, 4 = predominantly organized and orange, 3 = mixed organization and green, 2 = predominantly random and red/green, 1 = extremely random and red/black) as previously [47].

2.5 Serial Block Face Scanning Electron Microscopy

2.5.1 Sample Preparation.

Immediately posteuthanasia, one plantaris tendon from each animal was dissected for use in structural assays, with half the tendon prepared for SBF-SEM, and the other going to histology. Distal and proximal tendon bisections were block randomized between the two assays, with the medial portion of bisection used for imaging. The tendons were cut into 1 mm × 1 mm pieces before fixation in 2% paraformaldehyde, 2% glutaraldehyde with 2 mM calcium chloride in 0.1 M sodium cacodylate buffer for a minimum of 5 days. The samples were stained for SBF-SEM by adapting an established protocol that included steps with osmium tetroxide, potassium ferrocyanide, thiocarbohydrazide, 1% uranyl acetate, and en bloc lead aspartate, before dehydration with an ascending ethanol series. Finally, samples were infiltrated with Epon hard resin in an ascending series over 10 days before polymerization in a 60 °C oven for 48 h [48].

2.5.2 Serial Block Face Scanning Electron Microscopy Imaging.

SBF-SEM image stacks were collected after confirming axial alignment of the samples (FEI Apreo VolumeScope SEM, Thermo Fisher Scientific). The samples were sliced every 100 nm with images taken every other image for a total slice thickness of 200 nm and a pixel resolution of 6.67 nm. Overall, the in-plane field of view was 20.48 μm × 13.65 μm.

2.5.3 UNet Segmentation and Analysis.

To segment the collagen fibril cross section, an adapted UNet algorithm was used [49]. Raw images were processed with Gaussian and anisotropic diffusions filters to reduce noise while preserving edges. For each sample algorithm training was completed, where 1/6 of 10 slices from a full stack were segmented by hand to use as ground truth. Training of the adapted UNet was completed on a GPU for 200 epochs. The trained UNet was then applied to the full image stack that included the training images and applied to other ROIs from the same sample. Following segmentation, a watershed and two erode functions were applied in imagej to separate fibrils for particle analysis to measure area fraction, estimated fibril diameter, and fibril circularity for all slices in the stack.

2.6 Multiscale Mechanics

2.6.1 Sample Preparation.

On the day of mechanical testing, samples were thawed at room temperature before dissection. The plantaris tendons were removed at the calcaneal insertion and the musculotendinous junction, with some muscle and fibrocartilage preserved for gripping [50]. To ensure that tenocytes embedded in between collagen fiber bundles, and not superficial cells, were being imaged for microscale strain analysis, 150 μm of the tendon surface was removed using a freezing-stage microtome. The cross-sectional area was calculated using laser displacement in a custom device across the sample midportion after microtoming [50]. Samples were stained in 0.5 ug/ml Hoechst 33342 (2′-[4-ethoxyphenyl]-5-[4-methyl-1-piperazinyl]-2,5′-bi-1H-benzimidazole, ThermoFisher) for at least 15 min to stain the cell nuclei for fluorescence imaging [51]. Further, a fluorescence fiducial marker was made with CellMask Orange cell membrane stain (ThermoFisher) on the surface of the tendon to assist in locating the same ROI throughout the loading protocol. Two ink markers on the tendon surface at the midportion were used as fiducial markers for tissue strain calculation. All samples were kept at room temperature after thawing and throughout mechanical testing. To maintain tissue hydration, samples were kept in a bathing solution of 8 weight/volume %PEG (polyethylene glycol, 20 kDa) and 15 mM Tris-buffered saline [52,53].

2.6.2 Mechanical Testing Protocol.

The testing protocol (Fig. 1(a)) was similar to that used in prior studies [52,54,55]. Each sample was tested using a custom uni-axial testing device mounted on an inverted confocal microscope (Zeiss 880 Airyscan, objective Plan-Apochromat 10×/0.45W), which allows for simultaneous imaging and mechanical loading. The sample was gripped and loaded to a reference length by applying a 5 mN (0.5 g) preload and preconditioned for 5 cycles between 0 and 5% strain. Each sample was then ramped to 25% strain, held for 10 min at constant 25% grip strain, and unloaded back to the reference length. The sample remained at the reference length for a 15-minute recovery period before undergoing a final ramp until failure. All loading and unloading rates were 0.1%/s. We chose 25% strain to be within the linear region based on pilot tests and previous work in plantaris tendon [56].

Fig. 1.

(a) Mechanical loading protocol used in experiment, showing the time points for confocal imaging with circles and SHG imaging with X. (b) A representative stress–strain curve from the Intact group, showing the 25% ramp as a solid line and ramp to failure as a dashed line. Transition point (circle), modulus (dashed line), and yield point (square) are indicated.

2.6.3 Imaging and Data Acquisition.

To measure the tissue strain, we imaged the tendon with a monochrome CCD camera (Basler Ace2) and tracked displacement of the ink markers on the midportion surface using image correlation. For microscale analysis, confocal image stacks were taken after preconditioning, and at the beginning of loading with a 10× water-immersion lens (425 × 425 μm). Following preconditioning, samples were also imaged with second harmonic generation (SHG) to assess collagen fiber alignment and damage [57].

2.6.4 Tissue-Level Data Analysis.

The stress–strain ( $\mathit{\sigma }-\mathbf{ϵ}$) curves were analyzed for transition point, yield point, and linear region modulus, with the transition point defined as the end of the toe region and yield point as the inflection point where the curve changes from strain-stiffening to strain-softening, as previously described (Fig. 1(b)) [52,54,56]. Because the ink marks could not be tracked in some samples, the analysis mainly used grip-to-grip strain (image correlation-based strains are in Fig. S1 available in the Supplemental Materials on the ASME Digital Collection). The yield point was calculated by fitting a cubic smoothing spline with the csaps function in matlab and finding the first zero crossing point of the second derivative. The stress–strain curve between zero and the yield point was fit to a nonlinear exponential constitutive model which was optimized to obtain the transition strain (p), transition stress (q), and linear region modulus (E)

$$\mathit{\sigma }=\left\{\begin{array}{c}\mathit{A}*\left(\mathbf{exp}\left(\mathit{B}\mathbf{ϵ}\right)-1\right),\hspace{0.17em}\hspace{0.17em}\hspace{0.17em}\hspace{0.17em}|\forall \epsilon \le \mathit{p}\hspace{0.17em}\\ \mathit{E}*\left(\mathrm{\epsilon }-\mathit{p}\right)+q,\hspace{1em}\hspace{1em}|\forall \epsilon >\mathit{p}\end{array}\right\}$$ (1)

The optimization was performed on three of the parameters (p, A, B) and was completed using the matlab function fmincon to minimize the mean square error. Data analysis was performed for both the ramp to 25% strain and ramp to failure. The ramp to 25% strain did not reach a yield point, so the yield stress and strain, along with the failure (peak) stress and strain, were only determined for the ramp to failure, and 25% strain was used as a yield value for curve fitting the 25% ramps.

2.6.5 Microscale Data Analysis.

Microscale deformations were determined from displacements of stained tenocyte nuclei in confocal images at reference and immediately following the 25% ramp (Fig. 1(a)). Deformations were calculated using IMARIS (Oxford Instruments, Abingdon, UK). These displacements were used to calculate two-dimensional deformation gradient (F) and Lagrangian strain using a custom matlab program [58]. Lagrangian strain was calculated as E = ½ (C – I), where I is the identity matrix and C is the right Cauchy-Green deformation tensor (C = F^T • F, where F is the deformation gradient). To calculate the Lagrangian strain across the field of view, all tracked cells were pooled (n = 24–45 cells per sample). Maximum principal strains (e₁) were then calculated, using the relationship

$$e_1=\frac{E_{11}+E_{22}}{2}+\sqrt{{\left(\frac{E_{11}+E_{22}}{2}\right)}^2+{E_{12}}^2}$$ (2)

To evaluate load transfer attenuation within the sample, the ratio of tissue to microscale strain at the end of ramp to 25% strain was calculated.

2.7 Collagen Organization and Damage Area Fraction From Second Harmonic Generation Images.

SHG images were taken at the same time and ROI as the reference stacks used for cell tracking (Fig. 1(a)), having a 425 × 425 μm FOV and 0.29 μm in-plane pixel resolution (Zeiss 880 Airyscan, objective Plan-Apochromat 10×/0.45W). Quantification of collagen organization from images was automated using matlab based on Seresky et al. [57]. SHG images were divided into approximately 850 individual 41 × 41-pixel blocks (0.01 × 0.01 mm) and a colormap was created to determine the variance of pixel intensities. Extreme intensities that were not associated with tissue were removed. A Fourier transform followed by a 3 × 3 Gaussian filter was applied to each block. A high pass filter was then used to remove all pixels except those with the top 20% of intensities to isolate collagen. Next, the image was binarized and ellipses were fit to the remaining pixels. The length of the major and minor axis and orientation of the major axis were collected for each ellipse and plotted against the original image. Fiber angle was calculated by subtracting the angle from the major axis to the x-axis from 90 deg. Strength of alignment was found for the fiber orientation of each ellipse by subtracting 1 from the ratio of the length of the major axis to the length of the minor axis. The fiber orientation of each block was then compared to the orientations of the adjacent blocks. If the difference between the orientation of the center block and the orientation of both adjacent blocks was greater than 5 deg, the window was labeled as damaged. Damage Area Fraction (DAF) was then calculated by normalizing the number of damaged blocks by the total number of blocks in the image (see Fig. S1 available in the Supplemental Materials on the ASME Digital Collection).

2.8 Statistics.

Variation in activity within each subject between timepoints was analyzed using a mixed effects model with only time as an effect. Plantaris CSA and eccentricity between groups were compared using a mixed effects model (effects: treatment, time, time x treatment, and between-subject effect) with standard least squares and restricted maximum likelihood estimation followed by Tukey posthoc tests for all pairwise comparisons. The difference in CSA of the granulation tissue between 4- and 8-weeks postsurgery was determined with a pairwise Student's t-test. Differences in cell density, average NAR, fiber orientation, and DAF at 8 weeks were determined with a nonparametric one-way anova and Dunn's multiple comparison tests posthoc. Differences in matrix organization from PSR at 8 weeks were determined with a Kruskal-Wallis test. In all the above tests, significance was defined as p < 0.05. Differences in modulus, transition strain, and transition stress were calculated with repeated measures two-way anova and multiple comparisons completed using Tukey's HSD tests. Differences in yield strain, yield stress, failure strain, and failure stress were calculated with one-way anova (as all measures did not significantly deviate from normality as assessed by Kolmogorov–Smirnov tests) and multiple comparisons completed with Dunn's multiple comparison tests.

3 Results

3.1 Activity Monitoring.

There was no difference in total distance traveled and total number of rearings over time, specifically postsurgery (Fig. 2). This indicates that any structural changes are due to overload and not altered number of loading cycles; animals did not alter their activity either due to surgery or developing degeneration. However, our sample size is limited, and activity levels are highly variable between rats and over time.

Fig. 2.

Activity monitoring (n = 2 rats/group) for 3 presurgical sessions to obtain an average baseline, and then at 3 days, 2-, 4-, 6-, and 8-weeks postsurgery. (a) Normalized distance traveled for each animal and (b)normalized number of rearings to own average baseline measures. The gray band shows the average baseline standard deviation for all animals.

3.2 Tendon Geometry From Magnetic Resonance Imaging.

In vivo MRI was performed to evaluate the macroscale changes over time (Fig. 3, representative midtendon slice). The MRIs showed the plantaris tendon against the surrounding fat pad (at baseline and in Intact and Sham groups across time). The plantaris tendon macroscale measures of CSA and eccentricity were calculated from segmented MR images (Figs. 3(a) and 3(b)). There was no difference in the median CSA between any groups prior to surgery (0.18 mm² ± 0.03 mm² (n = 24), p = 0.63). At 8 weeks, the SynAb median CSA was 14% larger than Sham (p = 0.001) and 22% larger than Intact (p = 0.002). Sham and Intact controls were not different at 8 weeks (p = 1.0). Sham and Intact tendons were also not different at 8 weeks compared to their own baseline scans at 0 weeks (p = 1.0, p = 0.18). At 8 weeks, the SynAb CSA increased by 30% compared to its own 0-week CSA (p = 0.06, Fig. 4(a)). The median eccentricity was not different with treatment; however, the SynAb tendon had a lower eccentricity compared to its own baseline (p = 0.03, Fig. 4(b)). The CSA of the granulation tissue decreased from 4 to 8 weeks postsurgery in the SynAb group (p = 0.03, Fig. S3 available in the Supplemental Materials on the ASME Digital Collection). To check for a potential increase in CSA due to overall animal growth, the correlation in animal weight to median CSA was found to have no effect (R²=0.01, Fig. S4 available in the Supplemental Materials on the ASME Digital Collection).

Fig. 3.

MRI of a representative SynAb sample before surgery (Week 0), and 4 & 8 weeks after surgery. Week 0 shows normal structures, including the Achilles tendon, while Week 4 and Week 8 show plantaris and formation (then resolution) of granulation tissue filling the Achilles void. Arrow indicates plantaris tendon, * Achilles tendon, G granulation tissue, and T tibia.

Fig. 4.

(a) Median CSA and (b) median eccentricity with standard deviation between Intact, Sham, and SynAb groups at each time point. 8 weeks after surgery, the SynAb tendons were larger in cross-sectional area compared to Intact and Sham at 8 weeks, and SynAb at 0 weeks. 8 weeks after surgery, SynAb tendons were less round than SynAb at 0 weeks, but no differences were observed between groups. Line (between groups) and # (compared to 0 wk baseline) show p < 0.05.

3.3 Histology.

Histological staining with H&E was conducted to quantify cell density and nuclear aspect ratio (NAR) (Fig. 5(a)) and staining with PSR was conducted to quantify collagen alignment in plantaris tendons (Fig. 5(b)). At 8 weeks, SynAb cell density was 46% higher than Sham (p = 0.03) and Intact (p = 0.03, Fig. 5(c)). Sham and Intact were not different from each other at 8 weeks (p = 0.95) and there were no differences in NAR between any group at 8 weeks (p = 0.6, Fig. 5(d)). At 8 weeks, SynAb matrix organization was lower than Sham (p = 0.04), but not Intact (p = 0.18, Fig. 5(e)), with Sham and Intact again showing no difference (p = 0.67).

Fig. 5.

(a) Representative longitudinal H&E for each group (Intact, Sham, SynAb) at each time point (b) Representative longitudinal PSR for each group (Intact, Sham, SynAb) at each time point. (b) Cell density, and (c) nuclear aspect ratio (NAR) for Intact, Sham, and SynAb at 8 weeks from H&E images. At 8 weeks, SynAb had a higher cell density than Intact and Sham, while no changes were seen in NAR between groups. (e) Semiquantified matrix organization for Intact, Sham, and SynAb at 8 weeks. At 8 weeks, SynAb was more disorganized than Sham, but not Intact. Lines with * show p < 0.05.

3.4 Serial Block Face Scanning Electron Microscopy.

SBF-SEM imaging was conducted to investigate changes in collagen fibril structure following overload. SynAb had a larger area fraction of fibrils compared to Intact and Sham, with SynAb having a mean area fraction of 47%, compared to 39% for Intact and 40% for Sham (Fig. 6). For the examined samples, SynAb also had a larger mean fibril diameter of 0.16 μm, compared to 0.12 μm for both Intact and Sham. SynAb also had a larger third quartile diameter than Intact or Sham, showing that the size of the largest fibrils has increased in SynAb, in addition to a increase in the number of large fibrils (Table 2). There seemed to be no clear trend in circularity, with Intact having a mean circularity of 0.67, Sham of 0.75, and SynAb of 0.71.

Fig. 6.

Representative regions (6.8 × 6.8 μm) from (a) Intact, (b) Sham, and (c) SynAb SBF-SEM image stacks. (d)Mean collagen fibril area fraction with standard deviation and histograms of (e) collagen fibril diameter and (f) fibril circularity for Intact, Sham, and SynAb tendons.

Table 2.

SBFSEM diameter quartile values and mean

Sample	First quartile diameter (μm)	Mean diameter (μm)	Third quartile diameter (μm)
Intact	0.08	0.12	0.16
Sham	0.09	0.12	0.16
SynAb	0.11	0.16	0.22

Table 2 shows quartile values and means from fibril diameter distributions.

3.5 Multiscale Mechanics.

Multiscale mechanics tests were performed to evaluate the functional changes between groups. All mechanical parameters were compared between treatment groups (Intact, Sham, or SynAb), and the modulus and transition point were additionally compared between the first ramp to 25% and the second ramp to failure (Fig. 7). A two-way anova was performed to analyze the effect of the loading. During the initial 25% Ramp, SynAb had a trending decrease in modulus compared to Sham (p = 0.09), but not compared to Intact (p = 0.21, Fig. 7(a)). During the ramp to failure, SynAb had a lower modulus than Sham (p = 0.04), but not to Intact (p = 0.20). During the ramp to failure, SynAb also had a lower stiffness than Sham (p = 0.03), but not to Intact (p = 0.64, Fig. 7(h)). There were no differences between groups for transition strain (Fig. 7(b)). There was no difference between groups for transition stress (p = 0.15, Fig. 7(c)). As yield and failure parameters were only measured during the Ramp to Failure, the effect of treatment was assessed with a one-factor anova. The SynAb yield stress was 60% lower than Sham (p = 0.02), but not different from Intact (p = 0.49), and Sham and Intact were not different from each other (p = 0.16, Fig. 7(e)). There were no differences between any groups for yield strain, failure strain, failure stress, or failure load (p = 0.29, p = 0.50, p = 0.16, p = 0.54, Figs. 7(d), 7(f), 7(g), 7(i)). Mechanical parameters calculated from tissue strains, obtained by tracking ink marks on the tissue, had overall findings of treatment consistent with these results (Fig. S2 available in the Supplemental Materials on the ASME Digital Collection).

Fig. 7.

(a) Mean modulus, (b) transition strain, (c) transition stress, (d) yield strain, (e) yield stress, (f) failure strain, (g) failure stress, (h) stiffness, and (i) failure load with standard deviation for Intact, Sham, and SynAb groups. Modulus and transition point were evaluated during both the 25% ramp and ramp to failure, while yield and failure were evaluated only during the ramp to failure. After 8 weeks of overload, SynAb samples had a lower modulus than Sham during ramp to failure as well as a lower yield stress. Line and * show p < 0.05.

To assess load transfer within the tissue, the ratio of microscale to tissue-level strain was calculated at the end of the 25% Ramp (Fig. 8(a)). There was no significant difference between groups for the micro: tissue strain ratio with an average micro:tissue strain ratio for SynAb being 0.43, Sham 0.78, and Intact 0.82 (p = 0.23, Fig. 8(b)).

Fig. 8.

(a) Correlation between microscale strain measured from cell nuclei displacements and sample tissue strain measured from digital image correlation, with the 1:1 line showing perfect load transfer across length scales, and a value below the 1:1 line shows strain attenuation down the length scales and (b) mean ratio of micro:tissue strain with standard deviation

3.6 Second Harmonic Generation.

SHG images at reference were acquired following preconditioning during the mechanical testing to assess collagen fiber orientation and damage (Figs. 9(a)–9(c)). After 8 weeks, there was a trending increase in SynAb DAF compared to Intact (p = 0.15), with SynAb trending 92% larger than Intact (p = 0.15), but not compared to Sham (p = 0.39, Fig. 9(d)). At 8 weeks, there were no differences between groups in mean fiber angle (p = 0.20, Fig. 9(e)).

Fig. 9.

Representative z-projections of SHG stacks for (a) Intact, (b) Sham, and (c) SynAb, (d) damage area fraction (DAF), and (e) mean fiber orientation with standard deviation between Intact, Sham, and SynAb groups calculated from SHG images taken under preload

4 Discussion

We observed degenerative structural and functional changes in SynAb tendons compared to our Sham and Intact controls. Structurally, there was an increase in tendon CSA at 8 weeks postsurgery, an increase in cell density, a decrease in matrix organization, and an increase in collagen fibril diameter. Mechanically, there was a decrease in modulus and yield stress at 8 weeks postsurgery. These alterations indicate tendon degeneration after 8 weeks of sustained overload.

SynAb tendons experienced a decrease in modulus, indicating that the tissue is mechanically inferior compared to controls. Yield stress was also decreased, and although the other metrics (transition, yield, and failure stress) were not significantly different between treatment groups, qualitatively there was a downward shift in the SynAb group. These impaired material properties were also observed in the structural mechanical properties, as the stiffness also decreased in SynAb tendons. Thus, although we observed increased CSA and fibril diameter in the SynAb tendons, this additional material was not of high enough quality to maintain functional integrity. This is possibly explained at the microscale, where there tended to be less load transfer in the SynAb tendons compared to controls (Fig. 8), which suggests more fibril sliding [56,59,60]. While some tendon remodeling studies have shown that the adaptation of increased CSA and fibril diameter correlate with an increase in tendon stiffness [61–63], others have similarly observed this mismatch of increased fibril diameter and decrease in stiffness [64].

While interpreting this work against the landscape of tendon clinical research and animal models of tendon disorders, we developed a new two-factor framework to distinguish the effects of overload and overuse and explain the transition from adaptation (exercise) to degeneration (Fig. 10). This new framework separates the role of load from cycle number (along the x- and y- axes) and captures many types of activity that are a combination of load and cycle number. This framework suggests that as tendons transition from homeostasis to a degenerative state, there are different mechanisms due to overload and overuse environments. Unique animal models may be important to study these different pathways and mechanisms (Fig. 10, dashed boxes). This new framework can be applied to include other loading environments important to tendon clinical and basic research such as immobilization and strength training. This framework also includes the positive adaptation that occurs with moderately increased load and cycle number (Fig. 10). Positive adaptation to increased loading without experiencing detrimental functional changes or pain is observed by increased cross-sectional area and stiffness after habitual exercise [65–69]. The thresholds between tendon homeostasis, tendon adaptation, and tendon degeneration are driven by a combination of loading components, as well as shifts due to other factors including age, genetics, lifestyle, and other medical conditions [66].

Fig. 10.

Schematic illustrating the changes in response to altered activity via load and frequency. The “Cycles” and “Load” axes allow for differentiation between high load magnitudes and high load cycle numbers. The dark center circle indicates the region in which normal activity induces no changes, the lightest oblong region indicates where increased activity leads to positive adaptation, and the medium-tone outer region indicates where degeneration and/or impairment occur. Asterisks indicated representative activities. Dashed rectangles indicate approximate locations of various animal models.

Our findings and our proposed framework for tendon overload and overuse as different degenerative mechanisms can be compared to changes to the supraspinatus tendon observed by Abraham et al. [26]. Abraham et al. Recently investigated the effect of different loading conditions on mouse supraspinatus tendon, including unloading (via botulinum toxin A), normal activity, overuse (via downhill treadmill running), and joint destabilization (via surgical excision of the synergist infraspinatus tendon) [26]. In the context of our proposed framework (Fig. 10), the normal cage activity group would be within the homeostatic region, the destabilization group (overload) would be high on the loading y-axis within the degeneration region, and the overuse downhill treadmill running group has both increased load and cycle, so would be in the “High Load, High Cycles” region between the two axes. Notably, the overuse group in their study did not degenerate, so the load magnitude and cycle count must have been within the adaptation region of our proposed framework [26]. This is similar to several studies of Achilles' tendon overuse that show adaptation but not degeneration [13,70,71].

We observed an increase in tendon CSA at 8 weeks after SynAb. This finding is consistent with both tendon adaptation and degeneration, thus additional measurements were taken to elucidate where the tendon changes occur along the adaptation to degeneration continuum (boundary between adaptation and degeneration, Fig. 10). For example, human tendon CSA adaptively increases with both endurance training and resistance training [65,67] and also increases with tendinopathy [72]. We observed hypercellularity at 8 weeks and trend for decrease in matrix organization after SynAb, consistent with degenerative alterations due to overload in this model. Increased cell density and decreased organization similarly occur in human tendinosis and ruptured tendons [8,24,73]. We also observed decreases in the overall disorganization of the tendon matrix following overload in our histological PSR images. Matrix disorganization and loss of collagen alignment are hallmarks of tendon degeneration [57,74–76]. However, we did not observe a significant decrease in DAF from SHG images. This may have been caused by selecting the imaging ROI during mechanical testing to be an area of tissue with highly aligned tenocytes to allow for cell tracking. As a result, for SynAb samples, the SHG images were taken of the most structurally preserved regions. Finally, our SynAb tendons observed an increase in collagen fibril diameter, consistent with changes seen in human degenerative tendons [77]. While some of the structural changes could be examples of tendon adaptation, the observed decrease in tendon modulus and stiffness when combined with an increase in matrix disorganization suggests that the SynAb overload results in a degenerate tendon, rather than an adapted one [14,78–80]. Although the fibril diameter and collagen area fraction increased, other load-bearing mechanisms which influence modulus may have been altered, such as collagen cross-linking or an increase in fibril sliding.

The joint destabilization group in the Abraham forelimb study is similar to our SynAb overload group and was noted by the authors to be inspired by the hindlimb synergist ablation models [26,35]. Abraham et al. also observed a similar increase in tendon CSA in their destabilization group akin to our SynAb group. For mechanics, they also observed a decrease in stiffness, and their destabilization group led to decreases in maximum force and ultimate stress as well. Our findings for increased CSA and cell density at 8 weeks are generally consistent with previous SynAb studies of the plantaris tendon, where histology demonstrated an increase in CSA but no increase in cell density at early timepoints of 1 and 4 weeks [35]. However, in a second study by the same group in plantaris tendon, no changes in CSA or cell density were observed 4 weeks postsurgery [36]. More broadly, the mechanical behavior for Intact was consistent with previous findings for healthy tissue [56].

Several animal studies have identified structural and functional changes that occur following overuse, especially in rodent overuse models like treadmill running [10,13,14,27–29]. However, the presence of degenerative changes with treadmill running is highly variable and depends on the duration of training as well as the incline/decline used during treadmill running, which is correlated with magnitude of load [17]. For rotator cuff and supraspinatus tendon overuse, treadmill running that is done using a downhill incline is consistently degenerative, with increases in collagen fiber disorganization, cell density, CSA, and decreases in modulus and maximum stress [14,81]. However, other overuse protocols, particularly with hind limb tendons, are less consistently degenerative. For example, no differences were found in tendon CSA or elastic properties in a rat Achilles tendon using a downhill running model [13], while another downhill model showed increases in collagen fiber disorganization and cross-sectional area [14]. Some uphill running models show increases in collagen fiber disorganization, and cell density [75], while others show no differences between running subjects and controls [82]. In the context of our proposed framework (Fig. 10), flat treadmill running studies would be examples of overuse, with uphill/downhill running models representing overuse models with possible moderate overload. Further, these previous results show that varying levels of increased cycles, or cycles in combination with increased load by changing incline during running, can result in adaptation or degeneration, seemingly moving from homeostasis with increasing intensity.

This study has some limitations. First, in vivo loads were not measured. Although the observed changes in tendon size (i.e., increased CSA) partially confirm that the plantaris tendon was effectively overloaded following SynAb, we did not directly confirm increased in vivo loads in this study. Based on a simple ratio of CSA of the plantaris and Achilles, we estimate that the load increased by a factor of 5. Second, the plantaris tendon is small relative to the in-plane MRI resolution of 100 × 140 μm. We estimated the CSA uncertainty to be ± 0.05 mm² based on a circular area and a precision of ± 0.5 voxels (±60 μm). This uncertainty is acceptable, as it is of similar magnitude as the measured CSA standard deviation (0.08 mm² for Intact group and 0.12 mm² for SynAb). Third, no inflammation assays were performed in this study to account for immunomodulatory effects following SynAb. We saw an early inflammatory response to surgery with the formation of granulation scar tissue in the space where the Achilles' tendon was removed; however, it is likely this inflammation resolved within a short time after surgery. By eight weeks, we did not observe a noticeable inflammatory response, however, the increased cellularity indicated active remodeling that would include upregulation of cytokines [83]. Finally, though previous studies have considered 8 weeks sufficient for chronic changes, it is possible that further mechanical impairment and structural disorganization could occur with prolonged chronic overload.

Inflammation is an important part of the tendon healing cycle; when the healing response is dysregulated or tendon degeneration surpasses the tissue's intrinsic healing ability, aberrant remodeling occurs [84]. In our study, the acute overload from surgical resection, as well as iatrogenic effects from the surgery itself, may illicit an inflammatory response. The presence of inflammatory and degenerative changes in adjacent tissues in tendinopathic limbs shows that inflammation can be cross-tissue and that the granulation tissue caused by the Achilles ablation in our model likely has biological effects on the plantaris tendon [66].

In summary, this study used a SynAb model to overload tendon in vivo and demonstrated the structural and functional changes up to 8 weeks using longitudinal high-resolution MRI, histology, SHG imaging, SBF-SEM, and multiscale mechanics. We observed that overload, without increasing the number of loading cycles, is sufficient to induce degenerative changes in cross-sectional area, cellularity, matrix organization, fibril diameter, modulus, and yield stress at 8 weeks. We also introduce a new framework for evaluating tendon loading that separates overload (increased magnitude) from overuse (increased cycles). It is likely that the landscape of pathology is not uniform between tendon overload and overuse, and these differences may explain the discrepancies between the asymptomatic degeneration that precedes tendon rupture and painful tendinopathy. This work establishes SynAb as a model to study overload-induced degeneration, separate from overuse, providing an important tool to support study of different mechanisms and treatments between tendon overload and overuse injuries. Additionally, this new visual framework more clearly highlights the complexities of tendon's remodeling landscape and can help researchers and clinicians to discuss the effects of tendon loading.

Supplementary Material

Supplementary Material

Supplementary Figures

Funding Data

• National Institutes of Health, National Institute of Arthritis and Musculoskeletal and Skin Diseases (Grant Nos. 5F31AR078005 and R01AR080059; Funder ID: 10.13039/100000069).

• National Institutes of Health – NIH – COBRE (Grant No. P20 GM139760; Funder ID: 10.13039/100000057).

• Institutional Development Award (IDeA) from the NIH NIGMS (Grant No. P20GM103446; Funder ID: 10.13039/100000057).

• Delaware Center for Neuroscience Research COBRE from the NIH NIGMS (Grant No. P20 GM103653; Funder ID: 10.13039/100000057).