Abstract

Aging is a primary risk factor for degenerative tendon injuries, yet the etiology and progression of this degeneration are poorly understood. While aged tendons have innate cellular differences that support a reduced ability to maintain mechanical tissue homeostasis, the response of aged tendons to altered levels of mechanical loading has not yet been studied. To address this question, we subjected young and aged murine flexor tendon explants to various levels of in vitro tensile strain. We first compared the effect of static and cyclic strain on matrix remodeling in young tendons, finding that cyclic strain is optimal for studying remodeling in vitro. We then investigated the remodeling response of young and aged tendon explants after 7 days of varied mechanical stimulus (stress deprivation, 1%, 3%, 5%, or 7% cyclic strain) via assessment of tissue composition, biosynthetic capacity, and degradation profiles. We hypothesized that aged tendons would show muted adaptive responses to changes in tensile strain and exhibit a shifted mechanical setpoint, at which the remodeling balance is optimal. Interestingly, we found that 1% cyclic strain best maintains native physiology while promoting extracellular matrix (ECM) turnover for both age groups. However, aged tendons display fewer strain-dependent changes, suggesting a reduced ability to adapt to altered levels of mechanical loading. This work has a significant impact on understanding the regulation of tissue homeostasis in aged tendons, which can inform clinical rehabilitation strategies for treating elderly patients.

Introduction

Tendons are constantly under loads imposed by muscular contractions during movement, and this stimulus is in turn essential for tendon health [1,2]. Mechanical loads on the whole tissue are transmitted through the hierarchical extracellular matrix (ECM) structure to the cells that reside within it. Resident tendon cells, tenocytes, sense alterations in their mechanical environment through cell–cell and cell–ECM interactions and can alter their structure and composition to meet the functional needs of the tissue. This dynamic, feedback-driven process that maintains tissue homeostasis requires a delicate balance of matrix degradation and synthesis. Tenocytes produce matrix-degrading enzymes, such as matrix metalloproteinases (MMPs), to clear damaged or unneeded matrix proteins. In parallel, tenocytes synthesize new proteins that are incorporated into the matrix and re-organized into functional tissue structure. It has previously been established that moderate mechanical loading, such as exercise, improves tissue function through increases in matrix synthesis [38]. Chronic overloading, on the other hand, can shift the balance to catabolic processes, characterized by high breakdown and increased inflammation [914]. Therefore, the appropriate regulation of this homeostatic balance of ECM turnover is critical for preventing injury and chronic disease.

Tendon explants allow us to assess extracellular matrix remodeling within an isolated tissue while preserving cell–cell and cell–ECM interactions. As explants can be harvested from donors with different ages, sexes, and genetic backgrounds, explant models can address differences between tissue structure and cell behavior independently. Additionally, mechanical loading of tendon explants using bioreactor systems enables precise control of the mechanical environment experienced by tissues over the culture period. However, defining the appropriate mechanical stimulation to mimic physiological loading and maintain tissue homeostasis ex vivo has proven to be a challenge over the past decade. Multiple studies have worked toward establishing optimal loading protocols to maintain the tendon ex vivo and establish a mechanical setpoint that simulates physiological and pathological (e.g., overload, fatigue) loading conditions [5,12,15]. However, findings appear to be highly dependent on biological variables, such as tendon site or species, and experimental variables, such as loading rates and modes. Regardless, early work has established that stress deprivation (SD), complete mechanical unloading, causes a degenerative response, while low-level mechanical loading can better maintain native phenotypes [8,12,15,16].

It has been hypothesized that the process of aging itself could lead to a loss in tissue homeostasis. Aging is a primary risk factor for degenerative tendon injuries; however, the progression and biological drivers of age-related tendon degeneration are poorly understood. Despite many studies on the alterations in mechanical properties, tissue composition, and matrix organization of aged tendons, there is no consensus on specific age-related changes, with significant results often depending on the tendon type and exact donor age of tissue samples [17]. However, it is clear that aged tendons exhibit alterations in cell-mediated processes that support a compromised ability of aged cells to regulate tissue homeostasis [18]. Specifically, aged tendons show decreases in cell density and cellular activity (proliferation, metabolism, matrix synthesis) [16,17,19]. Additionally, multiple studies have documented impaired healing in aged tendons, suggesting an altered ECM repair capacity [2022]. There has also been reported dysregulation of cell–cell communication in aged tendon stem cells, suggesting a reduced ability to elicit a coordinated tissue-wide remodeling response [23]. Despite this extensive work, the effect of aging on the ability of cells to sense and respond to changing mechanical loads is still largely unexplored. In a previous study from our group, we investigated the response of young and aged tendon explants to stress deprivation [16]. Despite no age-related differences at baseline, we found that aged tendons show an altered response to mechanical unloading injury with reduced metabolic activity, proliferation, and matrix biosynthesis. However, the response of geriatric tendons to altered mechanical demands and the ability to adapt accordingly has not yet been studied.

The objective of this study was to (1) identify optimal loading protocols to stimulate physiological ECM turnover ex vivo in both young and aged tendon explants and (2) investigate the effect of aging on strain-dependent mechanisms of extracellular matrix remodeling. We hypothesized that aged tendon explants would display a muted adaptive response to changes in tensile strain and exhibit a shifted mechanical setpoint from that of young tendons.

Methods

Sample Preparation.

Flexor digitorum longus (FDL) tendon explants were harvested from the limbs of 72 young (4 months) and 40 aged (22 months) C57BL/6J male mice immediatly following sacrifice per approved animal use protocol (BU IACUC PROTO202000046). The 4-month-old and 22-month-old mice were selected as they represent skeletally mature young and geriatric adults, respectively [24]. Following previously described methods [16], all explants were washed in 1× PBS supplemented with 100 units/mL penicillin G, 100 μg/mL streptomycin (Fisher Scientific, Waltham, MA), and 0.25 μg/mL Amphotericin B (Sigma-Aldrich). All explants were then immediately loaded into grips using a custom loading rig to ensure all tendons were reliably gripped at a 10-mm gauge length (with the intrasynovial segment of the FDL situated between the grips). The gripped tendons were then placed into a custom-built tensile loading bioreactor (Fig. 1(a)). Left and right tendons from every mouse were used to conserve animal numbers, but the best effort was made to ensure that left and right tendons from the same animal were not attributed to the same experimental group. Throughout culture, explants were kept in a culture medium consisting of low glucose Dulbecco's Modified Eagle's Media (1 g/L; Fisher Scientific) supplemented with 10% fetal bovine serum (Cytiva, Marlborough, MA), 100 units/mL penicillin G, 100 μg/mL streptomycin (Fisher Scientific), and 0.25 μg/mL Amphotericin B (Sigma-Aldrich). Medium was changed every 2 days in culture for up to 7 days.

Fig. 1
(a) Custom-designed bioreactor (left) and experimental setup of gripped tendon explants (right). (b) Static strain tendons were loaded on day 0 and held at 3%, 5%, or 7% maximum strain for the duration of the culture. Cyclic strain (CS) groups were loaded using a triangle waveform from 0% to either 1%, 3%, 5%, or 7% strain at 1 Hz for 1 h followed by a 5 h hold at 0% strain. This protocol was repeated 4× a day for 7 days. Stress-deprived explants were gripped and left slack for the culture period.
Fig. 1
(a) Custom-designed bioreactor (left) and experimental setup of gripped tendon explants (right). (b) Static strain tendons were loaded on day 0 and held at 3%, 5%, or 7% maximum strain for the duration of the culture. Cyclic strain (CS) groups were loaded using a triangle waveform from 0% to either 1%, 3%, 5%, or 7% strain at 1 Hz for 1 h followed by a 5 h hold at 0% strain. This protocol was repeated 4× a day for 7 days. Stress-deprived explants were gripped and left slack for the culture period.
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In Vitro Mechanical Stimulation.

Our custom-designed bioreactor system allows for direct control over the mechanical environment experienced by tendon explants. This incubator-housed, tensile-loading bioreactor includes a load cell to measure force and an linear variable differential transformer to record displacements in real-time (Fig. 1(a)). We first explored the effect of loading mode (static versus cyclic strain) on tendon composition and ECM turnover in young tendon explants only. Then, we investigated the response of both young and aged tendon explants subjected to various levels of cyclic tensile strain. Tendon explants were preloaded to 20 g to ensure that the tendons were not slack between the grips, consistent with previous studies in mouse flexor tendon [25,26]; this was set as 0% strain. Static strain (SS) tendons were loaded on day 0 and held at their respective strain level for the duration of the culture. Cyclic strain (CS) groups were loaded using a triangle waveform from 0% to either 1%, 3%, 5%, or 7% strain at 1 Hz for 1 h followed by a 5 h hold at 0% strain. This protocol was repeated four times a day for the duration of the culture (Fig. 1(b)). All tendons were loaded within 1 h of harvest. An additional group was subjected to stress deprivation (SD), where the explants were gripped but held slack for the duration of the culture period. The SD explants were left slack between the grips because it has been shown that the tendons will remodel to contract and become taut [27]. We left the tendons slack between the grips to ensure that they were unloaded throughout the course of culture.

Metabolism, Biosynthesis, and Composition.

Explant cell metabolism was measured using a resazurin reduction assay, as previously described [28]. Following a 3h incubation with resazurin (diluted 1:10 in culture medium), the intensity of the reduced product, resorufin, was measured in the collected medium using excitation/emission of 554/584 nm. Values were normalized to daily control wells without explants, such that a value of 1 is representative of a culture without a viable explant. Synthesis of sulfated glycosaminoglycans (sGAG) and total protein (indicative of collagen synthesis) was measured by 24 h incorporation of 35S-sulfate (20 Ci/ml) and 3H-proline (10 Ci/ml), respectively (Perkin-Elmer, Norwalk, CT). After culture, explant (n = 5–10/group) wet weight was determined by soaking the tendons in 1× PBS for 1 min, dabbing excess PBS on a paper towel, and taking the weight of the tendon. This weighing procedure was done in triplicate, and the average value of the three weights was considered as the wet weight. The tendons were then lyophilized for at least 3 h, and dry weights were taken in triplicate. The water content of the tendon was calculated as the difference in wet weight and dry weight divided by the dry weight and multiplied by 100. Following weights, explants were digested overnight with proteinase K (5 mg/mL) (Sigma-Aldrich, St. Louis, MO). From each digested sample, radiolabel incorporation, sGAG content, double-stranded DNA content, and collagen content were determined. One sample provides a data point for radiolabel incorporation, sGAG content, double-stranded DNA content, and collagen content. Radiolabel incorporation was measured in tissue digests using a liquid scintillation counter (Perkin-Elmer), and the incorporation rate was determined. sGAG content was measured using the dimethyl methylene blue assay [29]. Double-stranded DNA content was measured using the PicoGreen dye binding assay [30]. A 100 μL portion of each explant digest was then hydrolyzed using 12 M HCl, dried, resuspended, and assayed to measure total collagen content using the hydroxyproline (OHP) assay [31].

Matrix Metalloproteinases Activity.

The activity of MMPs (1,2,3,7,8,9,10,13,14) was determined via analysis of spent culture medium (n = 8–10/group) using a commercially available FRET-based generic MMP cleavage kit (SensoLyte 520 Generic MMP Activity Kit Fluorimetric, Anaspec, Fremont, CA). MMP activity was represented as the concentration of MMP cleaved product (5-FAM-Pro-Leu-OH), the final product of the MMP enzymatic reaction.

Quantitative Gene Expression.

Explants were harvested from each group at day 0 (baseline) and day 7 (n = 5–6/group/day). Explants were immediately flash frozen with liquid nitrogen and stored at −80 °C until RNA extraction. Samples were placed in Trizol reagent, homogenized with a bead homogenizer (Benchmark Scientific), and then separated using phase-gel tubes (Qiagen) [32]. The supernatant was then purified according to the Zymo Quick-RNA purification kit protocol (Zymo Research). The RNA was then converted into cDNA with reverse transcription, and qPCR was performed with the Applied Biosystems StepOne Plus RT-PCR (Applied Biosystems, Foster City, CA). Primer pairs and sequences are listed in Supplemental Data (Table S1 available in the Supplemental Materials on the ASME Digital Collection). We measured genes responsible for matrix synthesis (Col1a1), regulation of collagen fibrillogenesis (Fmod, Dcn, Bgn), matrix degradation (Mmp3, Mmp8, Mmp9, Mmp13), as well as markers of injury (Il6, Il1b, Tnfa, Casp3). Expression for each gene was calculated from the threshold cycle (Ct) value and was normalized to the housekeeping gene β-Actin. All data are represented in log space.

Data and Statistics.

All data are presented as individual data points with summary statistics of mean ± 95% confidence interval. Biosynthesis and composition data are normalized to tendon dry weight to account for any size difference between samples. Data points more than 2 standard deviations outside of the mean were removed as outliers. Statistical evaluation on this set of data was performed using one-way ANOVAs. Bonferroni corrected posthoc t-tests were then used to identify differences from day 0 metrics and differences from the stress-deprived group. For all comparisons, significance was noted at *p < 0.05.

Results

The influence of strain mode (static versus cyclic) on matrix turnover of young tendons was assessed after 7 days of culture. Explant metabolic activity was increased for both strain modes regardless of the strain level (Fig. 2(a)). At 5% CS, metabolic activity is significantly higher than SS. CS at all levels increased MMP activity, whereas static loading maintained low MMP levels (Fig. 2(b)). Protein synthesis was induced by all strain levels across both strain modes (Fig. 3(c)). Regardless of strain level, cyclic loading induced a more robust increase in collagen content compared to SS, which better maintained baseline levels of collagen content (Fig. 2(d)). sGAG synthesis was also induced by all strain levels across both strain modes (Fig. 2(e)), and SS induced greater sGAG incorporation than CS at the 5% strain level only. GAG content was decreased from day 0 levels with CS regardless of strain level, whereas SS maintained GAG content through the 7 days of culture (Fig. 2(f)). While we did not see any notable differences, we did assess gene expression changes between static and cyclic strain modes after 7 days in culture (Fig. S3 available in the Supplemental Materials on the ASME Digital Collection).

Fig. 2
(a) Metabolic activity, (b) MMP activity, (c) total protein synthesis, (d) collagen content, (e) sGAG synthesis, and (f) GAG content of young explants maintained with static strain (left) and cyclic strain (right) after 7 days in culture under 3%, 5%, or 7% strain conditions. Data are presented as individual data points with a mean ±95% confidence interval. Bar (-) indicates a significant difference between strain modes at a given strain level (p < 0.05). Asterisk (*) indicates significant differences from day 0 baseline data (p < 0.05), which is represented on graphs by a dotted line.
Fig. 2
(a) Metabolic activity, (b) MMP activity, (c) total protein synthesis, (d) collagen content, (e) sGAG synthesis, and (f) GAG content of young explants maintained with static strain (left) and cyclic strain (right) after 7 days in culture under 3%, 5%, or 7% strain conditions. Data are presented as individual data points with a mean ±95% confidence interval. Bar (-) indicates a significant difference between strain modes at a given strain level (p < 0.05). Asterisk (*) indicates significant differences from day 0 baseline data (p < 0.05), which is represented on graphs by a dotted line.
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Fig. 3
(a) Hydration, (b) DNA content, (c) GAG content, and (d) collagen content of young (left) and aged (right) explants after 7 days in culture under stress deprivation (SD), 1% cyclic strain, 3% cyclic strain, 5% cyclic strain, or 7% cyclic strain conditions. Data are presented as individual data points with a mean ± 95% confidence interval. Plus sign (+) indicates a significant difference from SD (p < 0.05). Asterisk (*) indicates significant differences from day 0 baseline data (p < 0.05), which is represented on graphs by a dotted line.
Fig. 3
(a) Hydration, (b) DNA content, (c) GAG content, and (d) collagen content of young (left) and aged (right) explants after 7 days in culture under stress deprivation (SD), 1% cyclic strain, 3% cyclic strain, 5% cyclic strain, or 7% cyclic strain conditions. Data are presented as individual data points with a mean ± 95% confidence interval. Plus sign (+) indicates a significant difference from SD (p < 0.05). Asterisk (*) indicates significant differences from day 0 baseline data (p < 0.05), which is represented on graphs by a dotted line.
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We next moved to investigate the differences in the response of young and aged tendon explants to various levels of cyclic tensile strain. At baseline, directly following tissue harvest, young FDL explants have more DNA content (indicative of cellularity), GAG content, and collagen content than aged explants (Fig. S1 available in the Supplemental Materials). There is also greater expression of Col1a1 and Fmod and reduced expression of Dcn, Mmp3, Il1b, and Tnfa at baseline in aged tissues (Fig. S2 available in the Supplemental Materials).

The ECM remodeling response of young and aged explants was then assessed after a week under cyclic loading only. Water content is maintained by all strain levels in the young tendons, and this is significantly different from stress deprivation where tissues are more hydrated after culture (Fig. 3(a)). In aged samples, all loading protocols maintain baseline values except for 3% strain. In the young explants, all loading protocols result in a decrease in DNA content over culture (Fig. 3(b)). However, in the aged explants, the DNA content is maintained with both the 1% and 3% groups (Fig. 3(b)). Cyclic loading of young tendons resulted in a decrease in GAG content over culture, whereas aged explants maintained GAG content (Fig. 3(c)). For collagen content, all loading protocols resulted in an increase in collagen content in young tendons and maintenance of collagen content in aged tendons (Fig. 3(d)).

Metabolic activity was increased from baseline for every group regardless of age (Fig. 4(a)). In the young explants, the increase in metabolic activity increases with strain, peaking at 5% CS. However, in the aged explants, 1% CS showed the highest metabolic activity. Protein synthesis, which is indicative of collagen synthesis, is more responsive to changes in CS loading conditions in young explants (Fig. 4(b)). The young explants have lower matrix protein synthesis in the 1% and 5% CS groups when compared to the SD group. The aged explants are all at a low level of protein synthesis regardless of the magnitude of strain applied to the tendons during culture. For sGAG synthesis, all tendons but 5% had moderate levels of sGAG synthesis (Fig. 4(c)). For the aged tendons, sGAG synthesis appears to increase with increasing strain level and is increased compared to SD at 3% and 7% CS. MMP activity, which is indicative of matrix degradation, increases with greater strain magnitudes in young tendons (Fig. 4(d)). In the aged tendons, high strains do not initiate high MMP activity, as seen in young samples.

Fig. 4
(a) Metabolic activity, (b) total protein synthesis, (c) sGAG synthesis, and (d) MMP activity of young (left) and aged (right) explants after 7 days in culture under stress deprivation (SD), 1% cyclic strain, 3% cyclic strain, 5% cyclic strain, or 7% cyclic strain conditions. Data are presented as individual data points with a mean ± 95% confidence interval. Plus sign (+) indicates a significant difference from SD (p < 0.05). Asterisk (*) indicates significant differences from day 0 baseline data (p < 0.05), which is represented on graphs by a dotted line.
Fig. 4
(a) Metabolic activity, (b) total protein synthesis, (c) sGAG synthesis, and (d) MMP activity of young (left) and aged (right) explants after 7 days in culture under stress deprivation (SD), 1% cyclic strain, 3% cyclic strain, 5% cyclic strain, or 7% cyclic strain conditions. Data are presented as individual data points with a mean ± 95% confidence interval. Plus sign (+) indicates a significant difference from SD (p < 0.05). Asterisk (*) indicates significant differences from day 0 baseline data (p < 0.05), which is represented on graphs by a dotted line.
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We then looked at changes in the expression of genes associated with matrix turnover after 7 days of culture. In the young explants, baseline Col1a1 expression is only maintained by the 7% cyclic group (Fig. 5(a)). Col1a1 expression is increased in the young SD, 3% CS, and 5% CS groups and decreased in the young 1% CS group. In the aged explants, Col1a1 expression is downregulated compared to the baseline day 0 expression at every strain level. For Fmod expression, young explants show downregulation from baseline for every strain level except 5% CS (Fig. 5(b)). In aged explants, all strain levels except 3% CS are downregulated compared to baseline. Young explants maintain day 0 Dcn expression at 1%, 3%, and 5% CS levels, but 7% CS caused a decrease in expression (Fig. 5(c)). In aged tendons, baseline Dcn expression is maintained over the 7 days of culture regardless of strain level. For Bgn, the young explants maintain day 0 expression over the 7 days of culture regardless of CS level (Fig. 5(d)). However, in the aged tendons, Bgn expression is downregulated with SD, 1%, and 7% CS levels and maintained with 3% and 5% CS.

Fig. 5
Gene expression of (a)–(d) extracellular matrix proteins, (e)–(h) matrix metalloproteinases, and (i)–(l) injury markers of young (left) and aged (right) explants after 7 days in culture under stress deprivation (SD), 1% cyclic strain, 3% cyclic strain, 5% cyclic strain, or 7% cyclic strain conditions. Data are presented as individual data points with a mean ± 95% confidence interval. Plus sign (+) indicates a significant difference from SD (p < 0.05). Asterisk (*) indicates significant differences from day 0 baseline data (p < 0.05), which is represented on graphs by a dotted line.
Fig. 5
Gene expression of (a)–(d) extracellular matrix proteins, (e)–(h) matrix metalloproteinases, and (i)–(l) injury markers of young (left) and aged (right) explants after 7 days in culture under stress deprivation (SD), 1% cyclic strain, 3% cyclic strain, 5% cyclic strain, or 7% cyclic strain conditions. Data are presented as individual data points with a mean ± 95% confidence interval. Plus sign (+) indicates a significant difference from SD (p < 0.05). Asterisk (*) indicates significant differences from day 0 baseline data (p < 0.05), which is represented on graphs by a dotted line.
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Next, we considered genes that are involved in regulating matrix degradation. In young explants, Mmp3 expression was only upregulated relative to baseline for the 1% CS strain, whereas in the aged tendons, all strain levels upregulated Mmp3 expression substantially (Fig. 5(e)). For Mmp8, there were no detectable transcript levels at day 0 for either young or aged explants. While there are no strain-dependent differences in Mmp8 expression in young tendons at day 7, there is increased Mmp8 expression in 1% and 7% CS (Fig. 5(f)). For Mmp9, all groups are significantly upregulated from the baseline expression except in the 1% CS group for the young explants and the SD group for the aged explants (Fig. 5(g)). For Mmp13, all strain levels induce a significant increase in expression after 7 days of culture (Fig. 5(h)).

Finally, we evaluated the expression of genes that serve as injury markers after 7 days of culture. In young explants, Il6 expression was maintained at day 0 expression only in the 1% CS group; all other strain levels had a significant downregulation in Il6 expression (Fig. 5(i)). In aged explants, baseline Il6 expression was maintained regardless of the strain level. For Il1b, young explants maintained day 0 expression regardless of the strain level (Fig. 5(j)). In aged tendons, Il1b expression was downregulated in the 1% and 3% CS groups. For Tnfa expression, young explants exhibited a downregulation regardless of strain level (Fig. 5(k)). Aged explants exhibited a downregulation at SD, 1%, and 3% CS levels. Casp3 expression, indicative of apoptosis, was upregulated in young explants subjected to 3% and 5% CS compared to baseline (Fig. 5(l)). In aged explants, only the 3% strain group is able to maintain day 0 expression levels and all other strain levels exhibit an increase in Casp3 expression.

Discussion

Tendon explants are a powerful model system that enables direct interrogation of matrix remodeling processes ex vivo; however, a major challenge of tendon explant culture has been identifying the precise loading conditions that promote homeostasis, matrix remodeling, or matrix damage (injury) [33]. Mechanical loading state depends on a number of factors, including frequency, magnitude, loading duration, rest period, and loading modality. We sought to determine which strain mode was the best at stimulating murine FDL tendons to adapt to a range of physiological strain levels. Typically, tendons in vivo are loaded in the linear range of their stress–strain curve with physiological strains ranging from 2% to 6% [34,35]. Previous research has indicated that in tendon and tendon fascicle explants, physiological cyclic loading between 4% and 6% strain at 0.25–1 Hz leads to tendon remodeling with increased collagen production during culture [11,12,36]. While these studies have indicated that cyclic loading conditions may be best for inducing matrix remodeling in tendon explants, they have been conducted in larger animal models and in different tendons, including Achilles tendons and rat tail tendon fascicles. The extensibility of tendons in response to physiological loads is both tendon- and species-dependent [37]. Therefore, the strain modes and strain levels that promote matrix remodeling in the mouse flexor tendon may be different than previously studied models. This knowledge gap compelled us to establish whether static or cyclic strain better supports tendon matrix remodeling during explant culture.

Our data suggest that cyclic loading, regardless of strain level, induces turnover and matrix remodeling. We can see that both metabolic activity and matrix synthesis are induced across strain levels (3–7%) and both strain modes. Seven days of explant culture is sufficient to induce tenocyte-mediated synthesis of the fibrillar collagen matrix, indicated by 3H-proline incorporation, and the synthesis of nonfibrillar matrix proteins, such as proteoglycans, indicated by 35S-sulfate incorporation. While matrix synthesis is comparable between the strain modes, matrix degradation, the other key mechanism of matrix turnover, is more sensitive to cyclic strain. Whereas static loading maintained low MMP levels, cyclic strain at all levels increased the activity of MMPs, which are important to the tenocytes ability to cleave and remove damaged or unneeded matrix [38]. It is possible that static strain does not result in as much microdamage formation as cyclic strain, and therefore increased MMP activity is less necessary. Finally, CS has a larger effect on explant tissue composition. Regardless of strain level, cyclic loading induced collagen incorporation and GAG loss whereas static loading maintained collagen and GAG content. This would suggest that while a static strain is able to support the synthesis of matrix proteins and the production of MMPs, it is unable to induce compositional change to the tendon explant over the 7 days of culture. With lower levels of matrix turnover throughout the culture, static strain explants may have been more quiescent synthetically, resulting in the maintenance of matrix composition. We also have to keep in mind that this current study is only out to 7 days of culture, and it is possible that static strain wouldn't be ideal for long-term studies. Furthermore, long duration at high strains may start to become injurious to the tendon. For studying how ECM turnover mechanisms are altered with conditions such as exercise, injury, or aging, cyclic loading protocols appear to be more optimal, as they promote higher levels of tissue remodeling and are more physiologically similar to in vivo loading.

One of the primary goals of this project was to establish age-specific mechanical setpoints by identifying optimal loading conditions that stimulate in vitro matrix remodeling. We assessed this by identifying which cyclic strain magnitude best maintained the baseline tendon physiology for each of the biomarkers assessed in this study. These conclusions are summarized in Fig. 6, where we established the mechanical setpoint of the tendons to be the lowest magnitude of cyclic strain that most closely maintains the baseline physiology of the tendon for each age group. We found that 1% cyclic strain best maintains tendon explants in vitro, regardless of age. Previous work has primarily explored cyclic strain protocols in young tendon explants [5,12,15,36,39,40]. These studies lack a consensus on the optimal strain to maintain tendons in vitro, primarily because each study is conducted in a different tendon model with inconsistencies in the number of loading cycles, duration of loading, and length of culture. Despite the variability in methodology, together these studies indicate that a low level of strain (1–6%) is sufficient to preserve the tendon during culture. This diversity in strain level is likely due to the variety of anatomical roles of the studied tendons, which can have a substantial influence on the biomechanical response [37]. For positional tendons, such as the FDL, as examined here, the optimal strain was identified to be around 1% and within the range of the toe region of the stress–strain curve [15,33,39].

Fig. 6
Summary figure indicating the lowest magnitude of cyclic strain that most closely maintains baseline physiology. Blank boxes signify that none of the tested cyclic loading protocols could maintain native conditions. (G) indicates gene expression and (P) indicates protein-level biomarkers.
Fig. 6
Summary figure indicating the lowest magnitude of cyclic strain that most closely maintains baseline physiology. Blank boxes signify that none of the tested cyclic loading protocols could maintain native conditions. (G) indicates gene expression and (P) indicates protein-level biomarkers.
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While our conclusions about 1% cyclic strain as an optimal loading protocol for tendon explants aligns with previous work, it is important to note some additional considerations with the mechanical loading protocols used in this set of studies. We recognize that load-controlled mechanical loading has been suggested to be more physiologically relevant [41]; however, we chose to utilize a stain-controlled bioreactor system because of the technical simplicity of the system and better control of mechanical parameters. Using our strain-controlled protocols, we have demonstrated that a low level of cyclic strain is sufficient to maintain tendon physiology while also inducing physiological mechanisms of matrix turnover. Despite this, we believe there is room for further optimization of our cyclic loading protocol, including further assessment of rest periods and cycle numbers. In the future, we hope to confirm similar findings using load-controlled mechanical actuation.

While young and aged tendons exhibit no differences in their homeostatic mechanical setpoints, we do observe that aged tenocytes exhibit desensitized remodeling responses to altered levels of cyclic strain compared to young tenocytes. Examining tissue composition after 7 days of culture with optimal strain conditions, we see significant deviations in content (DNA, GAG, collagen) from baseline levels in young tissues but not in aged tissues. In young tissues, we document increased collagen content and decreased GAG content over the culture period, indicating both a sensitivity to cyclic mechanical loading and initiation of protective remodeling processes. The failure of aged tissues to elicit a similar response suggests a loss of adaptive mechanisms that allow the tissue to meet changing mechanical demands, thus increasing the risk of injury. We also document an interesting trend in strain-dependent metabolic activity in young and aged tissues. In young tissues, metabolic activity increases with increasing strain, signifying an increased metabolic demand to adapt to higher mechanical loads. Aged tissues do not experience comparable increases in metabolic activity, suggesting a failure to produce the necessary levels of energy for tissue adaptation.

We also document a significant increase in the activity of degradative enzymes at higher strains in young tissues, which is not replicated in aged tissues. It's important to note that our generic MMP activity captures all MMP families, not just those specific to collagen breakdown, and that our data only captures late-stage biosynthetic activity (day 7). Therefore, it is possible that differences were present earlier in culture. Future studies should investigate early timepoints to fully determine the time course of strain-dependent degradation and synthesis. Additionally, strain-dependent trends were not consistent between gene and protein assays. Across all strain groups, the expression of Mmp8, Mmp9, and Mmp13 is significantly increased from baseline for both age groups. However, for Mmp3, which is known to degrade proteoglycans [42], an upregulation from baseline is only seen in aged tissues, suggesting a potential ramp-up in proteoglycan degradation. As we see a substantial loss of GAG over culture for young but not aged tissues, this potentially indicates a delayed response to GAG breakdown in aged tissues. Notably, while we observed a decrease in GAG content in the young explants, we did not see the expected accompanying decrease in explant hydration. This discrepancy may be due to the sensitivity of our hydration measurement. In addition, tendon hydration also depends on other structure parameters not measured. For example, we found strain-dependent changes in collagen content, which could influence collagen density and structure, altering the permeability of the tissue [43].

Surprisingly, we did not see an upregulation of the injury markers Il6, Il1b, Tnfa, or Casp3 in either the young or aged tendons at any strain level despite the 7% strain being greater than the assumed physiologic range. The lack of injury response may be due to substantial recovery during the rest period or that the tested strains did not reach high enough magnitudes, as previous studies have indicated that cyclic strains above 9% are sufficient to induce injury to the tendon, with matrix and cell damage as well as increased apoptosis [1114]. It is also possible that the expression of the injury markers at the higher strain levels may have occurred earlier in the culture, and the expression reduced as culture time progressed. Future studies will aim to identify the stain levels that may be injurious to both young and aged tendon explants by exploring higher strain levels, assessing timepoints earlier in culture, and quantifying cell death and apoptosis.

Regardless, across the multiple metrics of ECM turnover assessed in this work, we document pronounced strain-dependency of young tendon ECM remodeling. The lack of comparable responses in aged tissues signifies a loss of strain sensitivity and adaptive remodeling with aging. Interestingly, our findings about the lack of tensile strain adaptation in aged tissues are similar to what was found recently in another study from our group that examined the response of young and aged tendons to an acute compressive injury [44]. In both studies, while young tissues display significant remodeling changes in response to the various mechanisms of mechanical loading, aged tendons exhibit a more muted response, with little or no remodeling changes. It is possible that this lack of adaptation could be attributed to decreases in cellularity in aged tissues or altered cellular communication [16,21,23]. Previous in vivo work has documented mechanosensitive mechanisms in aged human Achilles tendons, documenting increased stiffness following 14 weeks of cyclic loading exercise [45]. While we observe mechanosensitive, strain-dependent changes in our aged tendons, the differences are muted compared to those in young tissues.

Of course, this study is not without its limitations. We recognize that analysis of tendon composition, synthetic activity, and gene expression at day 7 of culture only captures the late-stage adaptation of the tendon to altered mechanical conditions. While assessing late-stage markers is sufficient to identify the establishment of homeostasis, this analysis lacks the ability to fully characterize distinct stages of cellular responses as well as the mechanisms responsible for age-dependent remodeling outcomes. We also recognize that it is typically common to evaluate tendon function via mechanical assessment [15,36,45] after culture. Unfortunately, we did not have enough samples to perform mechanical testing due to the large number of experiments necessary for the other assays examining specific cell-mediated processes. In the future, we will perform these endpoint assessments as well as utilize real-time load and displacement data collected from our bioreactor system to assess how tendon mechanics change throughout the culture period. We would also like to acknowledge that our strain measure was based on grip-to-grip strain using day 0 gauge length as the initial length. This method lacks the ability to accurately quantify the local tissue strains, sample elongation during testing, and sample grip slippage that may have occurred. We are currently working to obtain a quantitative measure of local tissue strains, tissue elongation, and potential grip slippage. We plan to do this by using fiducial markers to ensure tissue strain matches the recorded and measured grip to grip strain. Furthermore, to focus on the scope of this study, we only assessed one loading duration and frequency. While we were able to identify a sufficient strain level to maintain tendon physiology using the protocol described in this study, there could be more optimal loading parameters that would better meet our desired outcomes. For example, to our knowledge, there is no measure of a physiological loading rate for the mouse FDL. Therefore, we decided to start our exploration of the optimal loading condition with a loading rate that is commonly used across cyclic loading studies in tendons. Although we choose to start our exploration of the optimal loading condition with this loading frequency, it has been shown that loading frequency influences the response to loading in other musculoskeletal tissues [46]. Thus, in future studies, we plan to better characterize the response of the tendon tissue to load by exploring different loading frequencies. Future studies will also aim to refine our loading protocol further to optimize tendon health and matrix remodeling during culture.

Despite these limitations, we have utilized in vitro tensile loading of murine FDL tendon explants to establish a homeostatic loading protocol of 1% cyclic strain. This gives us the ability to explore pathological conditions of mechanical loading and resulting remodeling profiles in both young and aged tissues. Furthermore, we document a reduced response in aged tendons and a lack of specific strain-dependent adaptations that could contribute to the high prevalence of tendon injuries in elderly populations. Future work will continue to explore the ability of young and aged tendons to sense mechanical loads and establish new states of tissue homeostasis, specifically through analysis of mechanical and biological properties before and after step changes in tissue strain. We also hope to tease out individual mechanisms resulting in altered ECM remodeling in aged tissues through the investigation of age-related biological processes, such as cellular senescence [47]. Finally, we are now working to evaluate how age-associated remodeling is altered with biological sex and sex hormone levels by performing similar studies in female animals [16].

In light of our findings, this study furthers our understanding of the regulation of tissue homeostasis in aged and young tendons during mechanical loading. Importantly, this work is the first to confirm that young and aged tendons display altered mechanisms of matrix remodeling in response to tensile loading, supporting the notion that tendon pathologies require age-specific clinical interventions and therapies. Furthermore, this study establishes a strong model for future work to explore mechanosensitive matrix remodeling mechanisms that promote matrix adaptation or pathological degeneration. These explorations into age-specific cellular responses to in vitro mechanical loading will provide fundamental insights into the regulation of tissue homeostasis in aged tendons, which can inform clinical rehabilitation strategies for treating elderly patients.

Acknowledgment

We would like to thank Elliot Frank for his expertise with the tensile bioreactor system and Henry Chow for his assistance in the explant culture experiments.

Funding Data

  • Boston University, NIH/NIA (Award ID: R00‐AG063896; Funder ID: 10.13039/100000049).

  • NSF (Award ID: GRFP (Stowe); Funder ID: 10.13039/100000001).

Conflicts of Interest

The authors have no conflicts of interest with this work to disclose.

Data Availability Statement

The datasets generated and supporting the findings of this article are obtainable from the corresponding author upon reasonable request.

Nomenclature

Anova =

analysis of variance

Bgn =

biglycan

Casp3 =

caspase 3

Col1a1 =

collagen, type I, alpha 1

CS =

cyclic strain

Dcn =

decorin

ECM =

extracellular matrix

FDL =

flexor digitorum longus

Fmod =

fibromodulin

GAG =

glycosaminoglycan

Il1b =

interleukin 1 beta

Il6 =

interleukin 6

MMP =

matrix metalloproteinase

Mmp3 =

matrix metallopeptidase 3

Mmp8 =

matrix metallopeptidase 8

Mmp9 =

matrix metallopeptidase 9

Mmp13 =

matrix metallopeptidase 13

PBS =

phosphate buffered saline

SD =

stress deprivation

sGAG =

sulfated glycosaminoglycan

SS =

static strain

Tnfa =

tumor necrosis factor alpha

References

1.
Maganaris
,
C. N.
, and
Paul
,
J. P.
,
1999
, “
In Vivo Human Tendon Mechanical Properties
,”
J. Physiol.
,
521
(
1
), pp.
307
313
.10.1111/j.1469-7793.1999.00307.x
2.
Bojsen-Møller
,
J.
, and
Magnusson
,
S. P.
,
2015
, “
Heterogeneous Loading of the Human Achilles Tendon In Vivo
,”
Exercise Sport Sci. Rev.
,
43
(
4
), pp.
190
197
.10.1249/JES.0000000000000062
3.
Bohm
,
S.
,
Mersmann
,
F.
, and
Arampatzis
,
A.
,
2015
, “
Human Tendon Adaptation in Response to Mechanical Loading: A Systematic Review and Meta-Analysis of Exercise Intervention Studies on Healthy Adults
,”
Sports Med. - Open
,
1
(
1
), pp.
1
18
.10.1186/s40798-015-0009-9
4.
Rooney
,
S. I.
,
Tobias
,
J. W.
,
Bhatt
,
P. R.
,
Kuntz
,
A. F.
, and
Soslowsky
,
L. J.
,
2015
, “
Genetic Response of Rat Supraspinatus Tendon and Muscle to Exercise
,”
Plos One
,
10
(
10
), p.
e0139880
.10.1371/journal.pone.0139880
5.
Screen
,
H. R. C.
,
Shelton
,
J. C.
,
Bader
,
D. L.
, and
Lee
,
D. A.
,
2005
, “
Cyclic Tensile Strain Upregulates Collagen Synthesis in Isolated Tendon Fascicles
,”
Biochem. Biophys. Res. Commun.
,
336
(
2
), pp.
424
429
.10.1016/j.bbrc.2005.08.102
6.
Heinemeier
,
K. M.
,
Olesen
,
J. L.
,
Haddad
,
F.
,
Langberg
,
H.
,
Kjaer
,
M.
,
Baldwin
,
K. M.
, and
Schjerling
,
P.
,
2007
, “
Expression of Collagen and Related Growth Factors in Rat Tendon and Skeletal Muscle in Response to Specific Contraction Types
,”
J. Physiol.
,
582
(
3
), pp.
1303
1316
.10.1113/jphysiol.2007.127639
7.
Abreu
,
E. L.
,
Leigh
,
D.
, and
Derwin
,
K. A.
,
2008
, “
Effect of Altered Mechanical Load Conditions on the Structure and Function of Cultured Tendon Fascicles
,”
J. Orthop. Res.
,
26
(
3
), pp.
364
373
.10.1002/jor.20520
8.
Arnoczky
,
S. P.
,
Tian
,
T.
,
Lavagnino
,
M.
, and
Gardner
,
K.
,
2004
, “
Ex Vivo Static Tensile Loading Inhibits MMP-1 Expression in Rat Tail Tendon Cells Through a Cytoskeletally Based Mechanotransduction Mechanism
,”
J. Orthop. Res.
,
22
(
2
), pp.
328
333
.10.1016/S0736-0266(03)00185-2
9.
Spiesz
,
E. M.
,
Thorpe
,
C. T.
,
Chaudhry
,
S.
,
Riley
,
G. P.
,
Birch
,
H. L.
,
Clegg
,
P. D.
, and
Screen
,
H. R. C.
,
2015
, “
Tendon Extracellular Matrix Damage, Degradation and Inflammation in Response to In Vitro Overload Exercise
,”
J. Orthop. Res.
,
33
(
6
), pp.
889
897
.10.1002/jor.22879
10.
Fung
,
D. T.
,
Wang
,
V. M.
,
Andarawis-Puri
,
N.
,
Basta-Pljakic
,
J.
,
Li
,
Y.
,
Laudier
,
D. M.
,
Sun
,
H. B.
,
Jepsen
,
K. J.
,
Schaffler
,
M. B.
, and
Flatow
,
E. L.
,
2010
, “
Early Response to Tendon Fatigue Damage Accumulation in a Novel In Vivo Model
,”
J. Biomech.
,
43
(
2
), pp.
274
279
.10.1016/j.jbiomech.2009.08.039
11.
Legerlotz
,
K.
,
Jones
,
G. C.
,
Screen
,
H. R. C.
, and
Riley
,
G. P.
,
2013
, “
Cyclic Loading of Tendon Fascicles Using a Novel Fatigue Loading System Increases Interleukin-6 Expression by Tenocytes
,”
Scand. J. Med. Sci. Sports
,
23
(
1
), pp.
31
37
.10.1111/j.1600-0838.2011.01410.x
12.
Wang
,
T.
,
Lin
,
Z.
,
Day
,
R. E.
,
Gardiner
,
B.
,
Landao-Bassonga
,
E.
,
Rubenson
,
J.
,
Kirk
,
T. B.
, et al.,
2013
, “
Programmable Mechanical Stimulation Influences Tendon Homeostasis in a Bioreactor System
,”
Biotechnol. Bioeng.
,
110
(
5
), pp.
1495
1507
.10.1002/bit.24809
13.
Szczesny
,
S. E.
,
Aeppli
,
C.
,
David
,
A.
, and
Mauck
,
R. L.
,
2018
, “
Fatigue Loading of Tendon Results in Collagen Kinking and Denaturation but Does Not Change Local Tissue Mechanics
,”
J. Biomech.
,
71
, pp.
251
256
.10.1016/j.jbiomech.2018.02.014
14.
Scott
,
A.
,
Khan
,
K. M.
,
Heer
,
J.
,
Cook
,
J. L.
,
Lian
,
O.
, and
Duronio
,
V.
,
2005
, “
High Strain Mechanical Loading Rapidly Induces Tendon Apoptosis: An Ex Vivo Rat Tibialis Anterior Model
,”
Br. J. Sports Med.
,
39
(
5
), p.
e25
.10.1136/bjsm.2004.015164
15.
Wunderli
,
S. L.
,
Widmer
,
J.
,
Amrein
,
N.
,
Foolen
,
J.
,
Silvan
,
U.
,
Leupin
,
O.
, and
Snedeker
,
J. G.
,
2018
, “
Minimal Mechanical Load and Tissue Culture Conditions Preserve Native Cell Phenotype and Morphology in Tendon—A Novel Ex Vivo Mouse Explant Model
,”
J. Orthop. Res.
,
36
(
5
), pp.
1383
1390
.10.1002/jor.23769
16.
Connizzo
,
B. K.
,
Piet
,
J. M.
,
Shefelbine
,
S. J.
, and
Grodzinsky
,
A. J.
,
2020
, “
Age-Associated Changes in the Response of Tendon Explants to Stress Deprivation is Sex-Dependent
,”
Connect. Tissue Res.
,
61
(
1
), pp.
48
62
.10.1080/03008207.2019.1648444
17.
Birch
,
H. L.
,
Peffers
,
M. J.
, and
Clegg
,
P. D.
,
2016
, “
Influence of Ageing on Tendon Homeostasis
,”
Adv. Exp. Med. Biol.
,
920
, pp.
247
260
.10.1007/978-3-319-33943-6
18.
Korcari
,
A.
,
Przybelski
,
S. J.
,
Gingery
,
A.
, and
Loiselle
,
A. E.
,
2023
, “
Impact of Aging on Tendon Homeostasis, Tendinopathy Development, and Impaired Healing
,”
Connect. Tissue Res.
,
64
(
1
), pp.
1
13
.10.1080/03008207.2022.2102004
19.
Magnusson
,
S. P.
, and
Kjaer
,
M.
,
2019
, “
The Impact of Loading, Unloading, Ageing and Injury on the Human Tendon
,”
J. Physiol.
,
597
(
5
), pp.
1283
1298
.10.1113/JP275450
20.
Mienaltowski
,
M. J.
,
Dunkman
,
A. A.
,
Buckley
,
M. R.
,
Beason
,
D. P.
,
Adams
,
S. M.
,
Birk
,
D. E.
, and
Soslowsky
,
L. J.
,
2016
, “
The Injury Response of Geriatric Mouse Patellar Tendons
,”
J. Orthop. Res
,
34
(
7
), pp.
1256
1263
.10.1002/jor.23144
21.
Ackerman
,
J. E.
,
Bah
,
I.
,
Jonason
,
J. H.
,
Buckley
,
M. R.
, and
Loiselle
,
A. E.
,
2017
, “
Aging Does Not Alter Tendon Mechanical Properties During Homeostasis, but Does Impair Flexor Tendon Healing
,”
J. Orthop. Res.
,
35
(
12
), pp.
2716
2724
.10.1002/jor.23580
22.
Lai
,
F.
,
Tang
,
H.
,
Wang
,
J.
,
Lu
,
K.
,
Bian
,
X.
,
Wang
,
Y.
,
Shi
,
Y.
, et al.,
2021
, “
Effects of Aging on the Histology and Biochemistry of Rat Tendon Healing
,”
BMC Musculoskeletal Disord.
,
22
(
1
), p.
949
.10.1186/s12891-021-04838-w
23.
Popov
,
C.
,
Kohler
,
J.
, and
Docheva
,
D.
,
2016
, “
Activation of EphA4 and EphB2 Reverse Signaling Restores the Age-Associated Reduction of Self-Renewal, Migration, and Actin Turnover in Human Tendon Stem/Progenitor Cells
,”
Front. Aging Neurosci.
,
7
, p.
246
.10.3389/fnagi.2015.00246
24.
Flurkey
,
K. M.
,
Currer
,
J.
, and
Harrison
,
D. E.
,
2007
, “
Chapter 20 - Mouse Models in Aging Research
,”
The Mouse in Biomedical Research
, 2nd ed.,
J. G.
Fox
,
M. T.
Davisson
,
F. W.
Quimby
,
S. W.
Barthold
,
C. E.
Newcomer
, and
A. L.
Smith
, eds.,
Academic Press
,
Burlington
, VT, pp.
637
672
.
25.
Beason
,
D. P.
,
Kuntz
,
A. F.
,
Hsu
,
J. E.
,
Miller
,
K. S.
, and
Soslowsky
,
L. J.
,
2012
, “
Development and Evaluation of Multiple Tendon Injury Models in the Mouse
,”
J. Biomech.
,
45
(
8
), pp.
1550
1553
.10.1016/j.jbiomech.2012.02.022
26.
Connizzo
,
B. K.
,
Bhatt
,
P. R.
,
Liechty
,
K. W.
, and
Soslowsky
,
L. J.
,
2014
, “
Diabetes Alters Mechanical Properties and Collagen Fiber Re-Alignment in Multiple Mouse Tendons
,”
Ann. Biomed. Eng.
,
42
(
9
), pp.
1880
1888
.10.1007/s10439-014-1031-7
27.
Gardner
,
K.
,
Lavagnino
,
M.
,
Egerbacher
,
M.
, and
Arnoczky
,
S. P.
,
2012
, “
Re-Establishment of Cytoskeletal Tensional Homeostasis in Lax Tendons Occurs Through an Actin-Mediated Cellular Contraction of the Extracellular Matrix
,”
J. Orthop. Res.
,
30
(
11
), pp.
1695
1701
.10.1002/jor.22131
28.
Connizzo
,
B. K.
, and
Grodzinsky
,
A. J.
,
2018
, “
Release of Pro-Inflammatory Cytokines From Muscle and Bone Causes Tenocyte Death in a Novel Rotator Cuff In Vitro Explant Culture Model
,”
Connect. Tissue Res.
,
59
(
5
), pp.
423
436
.10.1080/03008207.2018.1439486
29.
Farndale
,
R. W.
,
Buttle
,
D. J.
, and
Barrett
,
A. J.
,
1986
, “
Improved Quantitation and Discrimination of Sulphated Glycosaminoglycans by Use of Dimethylmethylene Blue
,”
Biochim. Biophys. Acta
,
883
(
2
), pp.
173
177
.10.1016/0304-4165(86)90306-5
30.
Singer
,
V. L.
,
Jones
,
L. J.
,
Yue
,
S. T.
, and
Haugland
,
R. P.
,
1997
, “
Characterization of PicoGreen Reagent and Development of a Fluorescence-Based Solution Assay for Double-Stranded DNA Quantitation
,”
Anal. Biochem.
,
249
(
2
), pp.
228
238
.10.1006/abio.1997.2177
31.
Dourte
,
L. M.
,
Pathmanathan
,
L.
,
Mienaltowski
,
M. J.
,
Jawad
,
A. F.
,
Birk
,
D. E.
, and
Soslowsky
,
L. J.
,
2013
, “
Mechanical, Compositional, and Structural Properties of the Mouse Patellar Tendon With Changes in Biglycan Gene Expression
,”
J. Orthop. Res.
,
31
(
9
), pp.
1430
1437
.10.1002/jor.22372
32.
Grinstein
,
M.
,
Dingwall
,
H. L.
,
Shah
,
R. R.
,
Capellini
,
T. D.
, and
Galloway
,
J. L.
,
2018
, “
A Robust Method for RNA Extraction and Purification From a Single Adult Mouse Tendon
,”
PeerJ
,
6
, p.
e4664
.10.7717/peerj.4664
33.
Wunderli
,
S. L.
,
Blache
,
U.
, and
Snedeker
,
J. G.
,
2020
, “
Tendon Explant Models for Physiologically Relevant In Vitro Study of Tissue Biology – A Perspective
,”
Connect. Tissue Res.
,
61
(
3–4
), pp.
262
277
.10.1080/03008207.2019.1700962
34.
Wang
,
T.
,
Chen
,
P.
,
Zheng
,
M.
,
Wang
,
A.
,
Lloyd
,
D.
,
Leys
,
T.
,
Zheng
,
Q.
, and
Zheng
,
M. H.
,
2018
, “
In Vitro Loading Models for Tendon Mechanobiology
,”
J. Orthop. Res.
,
36
(
2
), pp.
566
575
.10.1002/jor.23752
35.
Benage
,
L. G.
,
Sweeney
,
J. D.
,
Giers
,
M. B.
, and
Balasubramanian
,
R.
,
2022
, “
Dynamic Load Model Systems of Tendon Inflammation and Mechanobiology
,”
Front Bioeng. Biotechnol.
,
10
, p.
896336
.10.3389/fbioe.2022.896336
36.
Wang
,
T.
,
Lin
,
Z.
,
Ni
,
M.
,
Thien
,
C.
,
Day
,
R. E.
,
Gardiner
,
B.
,
Rubenson
,
J.
, et al.,
2015
, “
Cyclic Mechanical Stimulation Rescues Achilles Tendon From Degeneration in a Bioreactor System
,”
J. Orthop. Res.
,
33
(
12
), pp.
1888
1896
.10.1002/jor.22960
37.
Kjær
,
M.
,
2004
, “
Role of Extracellular Matrix in Adaptation of Tendon and Skeletal Muscle to Mechanical Loading
,”
Physiol. Rev.
,
84
(
2
), pp.
649
698
.10.1152/physrev.00031.2003
38.
Del Buono
,
A.
,
Oliva
,
F.
,
Osti
,
L.
, and
Maffulli
,
N.
,
2019
, “
Metalloproteases and Tendinopathy
,”
Muscles Ligaments Tendons J.
,
3
(
1
), pp.
51
57
.10.32098/mltj.01.2013.08
39.
Tohidnezhad
,
M.
,
Zander
,
J.
,
Slowik
,
A.
,
Kubo
,
Y.
,
Dursun
,
G.
,
Willenberg
,
W.
,
Zendedel
,
A.
,
Kweider
,
N.
,
Stoffel
,
M.
, and
Pufe
,
T.
,
2020
, “
Impact of Uniaxial Stretching on Both Gliding and Traction Areas of Tendon Explants in a Novel Bioreactor
,”
Int. J. Mol. Sci.
,
21
(
8
), p.
2925
.10.3390/ijms21082925
40.
Maeda
,
E.
,
Shelton
,
J. C.
,
Bader
,
D. L.
, and
Lee
,
D. A.
,
2007
, “
Time Dependence of Cyclic Tensile Strain on Collagen Production in Tendon Fascicles
,”
Biochem. Biophys. Res. Commun.
,
362
(
2
), pp.
399
404
.10.1016/j.bbrc.2007.08.029
41.
Pedaprolu
,
K.
, and
Szczesny
,
S. E.
,
2022
, “
A Novel, Open-Source, Low-Cost Bioreactor for Load-Controlled Cyclic Loading of Tendon Explants
,”
ASME J. Biomech. Eng.
,
144
(
8
), p.
084505
.10.1115/1.4053795
42.
Cui
,
N.
,
Hu
,
M.
, and
Khalil
,
R. A.
,
2017
, “
Biochemical and Biological Attributes of Matrix Metalloproteinases
,”
Prog. Mol. Biol. Transl. Sci.
,
147
, pp.
1
73
.10.1016/bs.pmbts.2017.02.005
43.
Connizzo
,
B. K.
, and
Grodzinsky
,
A. J.
,
2018
, “
Multiscale Poroviscoelastic Compressive Properties of Mouse Supraspinatus Tendons Are Altered in Young and Aged Mice
,”
ASME J. Biomech. Eng.
,
140
(
5
), p.
051002
.10.1115/1.4038745
44.
Mlawer
,
S. J.
,
Frank
,
E. H.
, and
Connizzo
,
B. K.
,
2023
, “
Aged Tendons Lack Adaptive Response to Acute Compressive Injury
,”
J. Orthop. Res.
, epub.10.1002/jor.25752
45.
Epro
,
G.
,
Mierau
,
A.
,
Doerner
,
J.
,
Luetkens
,
J. A.
,
Scheef
,
L.
,
Kukuk
,
G. M.
,
Boecker
,
H.
,
Maganaris
,
C. N.
,
Brüggemann
,
G.-P.
, and
Karamanidis
,
K.
,
2017
, “
The Achilles Tendon is Mechanosensitive in Older Adults: Adaptations Following 14 Weeks Versus 1.5 Years of Cyclic Strain Exercise
,”
J. Exp. Biol.
,
220
(
6
), pp.
1008
1018
.10.1242/jeb.146407
46.
Grodzinsky
,
A. J.
,
Levenston
,
M. E.
,
Jin
,
M.
, and
Frank
,
E. H.
,
2000
, “
Cartilage Tissue Remodeling in Response to Mechanical Forces
,”
Annu. Rev. Biomed. Eng.
,
2
(
1
), pp.
691
713
.10.1146/annurev.bioeng.2.1.691
47.
Stowe
,
E. J.
,
Keller
,
M. R.
, and
Connizzo
,
B. K.
,
2023
, “
Cellular Senescence Impairs Tendon Extracellular Matrix Remodeling in Response to Mechanical Unloading
,” eprint
bioRxiv
.10.1101/2023.12.22.572594

Supplementary data