Get Our e-AlertsSubmit Manuscript
Cyborg and Bionic Systems / 2022 / Article

Review Article | Open Access

Volume 2022 |Article ID 9842169 | https://doi.org/10.34133/2022/9842169

Iain L. Sander, Nicole Dvorak, Julie A. Stebbins, Andrew J. Carr, Pierre-Alexis Mouthuy, "Advanced Robotics to Address the Translational Gap in Tendon Engineering", Cyborg and Bionic Systems, vol. 2022, Article ID 9842169, 18 pages, 2022. https://doi.org/10.34133/2022/9842169

Advanced Robotics to Address the Translational Gap in Tendon Engineering

Received10 Jun 2022
Accepted25 Aug 2022
Published15 Sep 2022

Abstract

Tendon disease is a significant and growing burden to healthcare systems. One strategy to address this challenge is tissue engineering. A widely held view in this field is that mechanical stimulation provided to constructs should replicate the mechanical environment of native tissue as closely as possible. We review recent tendon tissue engineering studies in this article and highlight limitations of conventional uniaxial tensile bioreactors used in current literature. Advanced robotic platforms such as musculoskeletal humanoid robots and soft robotic actuators are promising technologies which may help address translational gaps in tendon tissue engineering. We suggest the proposed benefits of these technologies and identify recent studies which have worked to implement these technologies in tissue engineering. Lastly, key challenges to address in adapting these robotic technologies and proposed future research directions for tendon tissue engineering are discussed.

1. Introduction

Tendons are the viscoelastic connective tissues which attach the muscle to the bone (Box 1). Tendon injuries represent the highest proportion of musculoskeletal conditions for which patients seek medical treatment [1]. These injuries are painful and present a significant socioeconomic burden. The lifetime cost of a rotator cuff tear to society has been estimated at 20,000-30,000 GBP/patient in the United Kingdom and 20,000-100,000 USD/patient in the United States, with the US rotator cuff tendon repair market being estimated at 1.5 billion USD/year [24]. The main treatment for a full thickness rotator cuff tears is surgical repair. Although more than 250,000 rotator cuff tendon surgeries are performed per year in the United States alone, patient outcomes remain poor, with upwards of 40% of tendon repairs failing postoperatively [5]. Revision surgeries further compound the social and economic impacts of tendon disease. With the increasing prevalence of tendon injury due to an ageing population and poor treatment outcomes, there is a growing need for knowledge from other disciplines to inform and advance therapy for tendon disease.

A promising repair strategy is the development of engineered tendon grafts for clinical use. Tendon tissue engineering (TTE) involves using bioreactor systems to generate tissue in vitro using scaffolds, human or animal cells, and appropriate growth conditions. As demonstrated through physical therapy, providing tendon tissue with the appropriate amount and types of mechanical stimulation is essential for healthy tissue development, maintenance, and repair [6]. In vitro research has shown that mechanically stimulated tendon tissue demonstrates increased extracellular matrix (ECM) deposition, a greater degree of structural protein alignment, and stronger biomechanical properties when compared to statically cultured tissue [7]. A widely held opinion is that the mechanical context provided in TTE experiments should closely mirror loading experienced by native tendon tissue [7]. The lack of bioreactor systems which can recapitulate in vivo tendon loading (Box 2) is a major translational gap in the development of functional engineered grafts for clinical use. Despite mechanical stimulation being discussed in a number of recent TTE reviews [711], no clear consensus exists on the specific obstacles to providing physiologically relevant mechanical context and the technologies which may help address these obstacles.

Biomimetic robotic systems are uniquely positioned for advancing TTE. Robotic technology is already being used clinically for a variety of medical applications, including orthopaedic surgery, advanced prostheses, and powered exoskeletons for rehabilitation following neurological injury [12]. There is a growing interest in applying robotic technologies for TTE, and several recent papers have suggested convergence between these fields [13, 14]. This review article advances discussion by summarising trends in recent TTE literature, identifying current limitations to providing physiologically relevant mechanical loading, and highlighting the potential role of musculoskeletal humanoids and soft robotics in providing mechanical stimulation to engineered tendon constructs.

2. Conventional Tendon Tissue Engineering

Tissue engineering involves the complex interplay of gas exchange, nutrient and waste transfer, temperature and pH control, and maintenance of a sterile environment. As shown through in vitro studies, tendon tissue also requires appropriate mechanical context to grow and develop properly. It is important to ensure that tendon tissue constructs experience the right amount of mechanical loading; insufficient stimulation has been shown to lead to catabolic gene expression and eventual loss of structural integrity, while excess loading of tendon tissue leads to inflammation, degradative enzyme production, undesirable fibroblast differentiation, and programmed cellular death [26, 33]. In vivo imaging studies done in humans estimate that peak tendon strain for physiologic motion ranges from 3 to 15% depending on tendon location and individual anatomy [18, 2325]. TTE studies prior to 2014 typically applied 2-10% strain cyclically at a frequency of 0.1-2 Hz [7]. As discussed later in this section, most bioreactors currently being used offer only uniaxial tensile loading. A list of recent in vitro studies using traditional bioreactor systems with human and animal cells is compiled in Table 1.


Bioreactor systemTypes and directions of mechanical stimulationReferenceLoading frequency and durationMeasured loadMeasured strainStrain distributionCell source and tissue construct details (dimensions)

Flexcell® tissue train culture systemUniaxial tensileWee et al. [34]1 h/day over 1-14-day period at 0.5 HzNot available0-5%Modelled as uniformTonsil-derived MSCs seeded to Dulbecco’s modified eagle medium in UniFlex bioreactor plates
Ciardulli et al. [35]4 h/day over 11-day period at 1 Hzpa10%Modelled as nonuniformhBMSCs seeded in a hyaluronate/polylactic-co-glycolic acid hydrogel ()
Mubyana and Corr [36]8 h loading cycles over 7-day period at 0.1 Hz0-100 kN/m20-0.70%Modelled as uniformHDF seeded in agarose growth channels

Bose ElectroForce® bioreactorUniaxial tensileBaumgartner et al. [37]3 h/day over 7-day period at 1 HzNot available10%Modelled as uniformHuman adipose-derived stem cells (ADSCs) seeded to electrospun poly(vinylidene fluoride-co-hexafluoropropylene)/polydimethylsiloxane (PDMS) patches ()
Chen et al. [38]3 h/day over 7-day period at 1 HzNot available6%Modelled as uniformLeporine tenocytes seeded to electrospun hyaluronic acid-(PCL)/platelet rich plasma fibre scaffolds (length: 5 mm; width: 5 mm)
Yuan et al. [39]2 h/day over 7-day period at 0.25 HzNot available3%Modelled as uniformhBMSCs seeded to electrospun poly(L-lactic acid) (PLLA) scaffold coated with type I collagen and chondroitin sulphate ()
Garcia Garcia et al. [40]Twice daily for 1 h over 5-12-day period at 1 Hz0-250 kN/m25%Modelled as uniformRat BMSCs seeded to electrospun (PCL) mats ()

Ebers TC-3 bioreactor systemUniaxial tensileDeniz et al. [41]30 min/d for 2 days then 1 h/day over 10-day period at 0.33 HzNot available3-6%Modelled as uniformHuman tenocytes seeded to polyglycerol sebacate sheet (surface area: )

MCT6 bioreactorUniaxial tensileWu et al. [42]2 h/day over 12-day culture period at 0.5 HzNot available4%Modelled as uniformhADSCs seeded to electrospun polycaprolactone (PCL) scaffold (length: 1.2 cm; width: 1.2 cm; thickness: 180 μm)

Strex STB-140-10 stretching systemUniaxial tensileNam et al. [43]Continuous over 6-72 h period at 0.5-1 HzNot available4-12%Modelled as uniformhBMSCs seeded to silicon chambers (surface area: 10 cm2)
Uniaxial tensileChen et al. [44]8 h/day over 6-day period at 0.25 HzNot available6%Modelled as uniformMurine tendon derived stem cells (TDSCs) seeded to CelGro culture scaffold ()
Uniaxial tensileJanvier et al. [45]5 h/day for 5 days/week over 3-week period at 0.5 HzNot available5%Modelled as uniformhBMSCs seeded to fibrin hydrogel in 3D-printed PLLA wells ( between construct attachment points)
Uniaxial tensileBanik and Brown [46]2 h/day over 21-day period at 0.01 HzNot available3-6%Modelled as uniformhMSCs seeded to electrospun type I collagen and PCL encased in a 3D-printed frame (length: 2.8 cm; diameter: 6.4 mm)
Uniaxial tensileAtkinson et al. [47]8 h/day over 14-day period at 0.67 Hz0.1-25 kN/m210%Modelled as nonuniformEquine tenocytes suspended in 200 μl collagen solution

Custom uniaxial tensile stage bioreactorsUniaxial tensileSawadkar et al. [48]Dynamic trial: 15 min then 15 min rest, repeated over 24 h period; static trial: constant loading over 24 h period0-3700 μN (dynamic)
3250 μN (static)
0-10% (dynamic)
10% (static)
Modelled as uniformRabbit tibial tendon fibroblasts seeded to collagen lattice derived from rat tail ()
Uniaxial tensileHsiao et al. [49]Continuous 8 h period at 0.5 HzNot available4 or 8%Modelled as nonuniformRat patella tenocytes, cultured in wells on a tensile plate (no scaffold)
Uniaxial tensileMorita et al. [50]Continuous over 2-day period at 1 HzNot available2-8%Modelled as nonuniformhBMSCs seeded to polydimethylsiloxane coated glass membrane ()
Uniaxial tensileNakanishi et al. [51]Static loading over 4-8-week periodNot availableNot availableModelled as uniformHDFs seeded into 3D-printed DMEM spheroids (diameter: 500 μm–600 μm)
Uniaxial tensileGrier et al. [52]40 min/day over 6-day period at 1 HzNot available10%Modelled as nonuniformhBMSCs seeded to bovine collagen-glycosaminoglycan (GAG) scaffold (length: 15 mm)
Uniaxial tensileRaveling et al. [53]Continuous over 3-day period at 0.05 Hz0-190 kN/m20-10%Modelled as uniformMurine MSC cells seeded to bovine type I collagen sponges (length: 12 mm; width: 4 mm)
Uniaxial tensileEngebretson et al. [54]0.5-2 h/day for culture of up to 7 days at 0.01-0.03 HzNot available2%Modelled as uniformRat BMSCs seeded to decellularised human umbilical vein (diameter: 6.75 mm; length: 6.5 cm)
Uniaxial tensileTesta et al. [55]1 h/day over 15-day period at 0.5 HzNot available10%Modelled as uniformMurine embryonic fibroblast cells seeded to crosslinked polyethylene glycol (PEG)-fibrinogen hydrogel ()
Uniaxial tensileGrier et al. [56]10 min every 6 h over 6-day period at 1 HzNot available10%Modelled as uniformhBMSCs seeded to collagen-GAG scaffold extracted from bovine tendon ()
Uniaxial tensileJoo Kim et al. [57]Continuous 12 h period at 0.5 HzNot available2-4%Modelled as nonuniformRat tail tenocytes suspended in DMEM and tested in moulded polydimethylsiloxane bioreactor wells ()
Uniaxial tensileCook et al. [58]1 h/day over 5-day period at 0.5 Hz0-5 mN1-9%Modelled as nonuniformhADSCs seeded in electrospun fibrin/alginate scaffold bundles ()
Uniaxial tensileBurk et al. [59]15-30-60 min loading alternated by 15-30-60 min rest at 1 HzNot available2%Modelled as uniformEquine ADSCs seeded to decellularised equine tendon scaffold ()
Uniaxial tensileYoungstrom et al. [60]0.5-1 h/day over 8 days at 0.33 HzNot available0-5%Modelled as uniformEquine BMSCs seeded to decellularised equine tendon scaffolds ()
Uniaxial tensileQin et al. [61]20 min/h for 12 h for 7-day period at 0.2 HzNot available3%Modelled as uniformCanine BMSCs seeded to decellularised canine tendon (length: 40 mm; width: 300 μm)
Uniaxial tensileCardwell et al. [62]30 min over 3-day period at 0.25 HzStatic tensile loading of 50 mN (daily)4%Modelled as uniformMurine fibroblasts seeded to electrospun polyurethane mesh (length: 4.5 cm; width: 1 cm)

MCB1 bioreactorBiaxial tensileSensini et al. [63]1 h/day on day 3 and 6 over 7-day period at 1 HzNot available5%Modelled as uniformForeskin HDFs seeded to electrospun PLLA/collagen (cross-section: ; length: )

Custom diaphragm pump bioreactorUniaxial compressiveLiu et al. [64]3-9 h/day over 14-day period at 0.8 HzNot available5-16%Modelled as nonuniformhBMSCs seeded in PEG-norbornene hydrogel discs (ø–9 mm, h–250 μm)

Custom oscillating uniaxial tensile stage bioreactorUniaxial tensileTalo et al. [65]15-30-60 min loading alternated by 15-30-60 min rest 2 times/day over 7-day period at 0.33 Hz4-25 N1-7%Modelled as uniformRabbit BMSCs seeded to decellularised equine tendon tissue ()

Custom perfused uniaxial tensile stage bioreactorUniaxial tensile, shear stressRaimondi et al. [66]30 min alternating cyclic and static loading over 7-14-day culture period at 0.5-2 Hz1.5-4.5 N3-10%Modelled as uniformPorcine Achilles tenocytes, seeded to equine type I collagen sponge scaffold

Custom torsional and uniaxial tensile bioreactorUniaxial tensile, torsionalLee et al. [67]Cyclic loading for 1-7-day periods at 1 HzNot available10% tensile; 45°-90° torsionModelled as uniformhBMSCs, seeded to decellularised porcine tibialis tendon (length: 12 cm; width: 1 cm)

To create appropriate mechanical context for TTE constructs, it is important to have bioreactor systems that provide physiologically relevant loading, scaffolds and growth factors that induce a desirable biological response during tissue culture, and cell types that respond appropriately to mechanical stimulation. The different cell lines used in TTE are briefly discussed below as recent reviews of these subjects already exist [6871]. This article is primarily focused on the role of bioreactor systems in developing appropriate mechanical context.

2.1. Cell Types Used in TTE

Cell selection in TTE is a balance of the following criteria: ability to successfully proliferate during incubation, ability to differentiate into in situ tendon cells, availability for research purposes, and no ethical or legal concerns associated with their use [68]. Although native tenocytes and in situ fibroblasts represent the most clinically relevant cell source for TTE, obtaining these cells can be challenging in practice. Tendon cell extraction poses a significant risk of donor morbidity and extracting a satisfactory quantity of tendon cells is challenging given their low cell number in native tissue [8]. With these practical limitations, other cell types are also currently being used for TTE research. The broad categories of cells currently being used include stem cells, tenocytes, and dermal fibroblasts [8].

Nontendon stem cells, including embryonic stem cells (ESCs), bone marrow mesenchymal stem cells (BMSCs), and adipose-derived stem cells (ADSCs), have been used in most studies listed in Table 1. Advantages of these cell types include their potential to differentiate and high proliferative capacity. Limitations for translational applicability in the use of BMSCs and ADSCs include the risk of ectopic bone formation within the constructs and senescence with increased cell passaging. Pluripotent ESCs are appealing due to their proliferative ability but have limited availability due to strict policy and ethical concerns surrounding their use. Using retroviruses or lentiviruses to generate induced pluripotent stem cells (IPSCs) is of growing interest for TTE as this technique offers unlimited proliferative ability without the ethical concerns associated with ESC tissue. Several recent studies have demonstrated tenogenic differentiation in transfected IPSCs [72, 73]. A recurrent limitation in studies using IPSCs has been the low yield of successfully transfected cells [68, 72, 73]. Song et al.’s recent study has demonstrated that biophysical cues, such as nuclear deformation, can cause epigenetic changes and eventually alter gene expression, resulting in increased yield of transfected IPSCs from a cell population [30]. As further research on this topic develops, there may be increased use of these cells in TTE.

In contrast to immature cell lines, dermal fibroblasts—used in a number of the studies listed in Table 1—are an alternative cell population commonly used in TTE [36, 51, 63]. These mature collagen producing cells have similar morphology to tenocytes and readily proliferate. These cells can be readily sourced via skin punch biopsy and have low risk of donor site morbidity [68]. Disadvantages of this cell type include the risk of fibrotic scar formation and suppression of tendon-like healing in absence of tenocyte biomarkers [7, 68]. Given these disadvantages, it is likely that these cell populations are more useful for demonstrating feasibility of response to mechanical stimulation in research settings rather than translation for eventual clinical use. There is ongoing research to determine the appropriate growth factors required for successful differentiation in nontenocyte cell lines.

In addition to cell type, cell sources in TTE literature also vary. Murine, porcine, and equine cells are often used in lieu of human tissue due to commercial availability within research settings. While these models may be cost-efficient and more readily available than human cells, the translational utility of these models is lower, given that human and animal tissues experience different types of in vivo mechanical stimulation. Overall, the benefits and drawbacks of each cell type and source continue to be further studied as TTE moves towards translational applications.

2.2. Traditional Bioreactor Systems in TTE

Most bioreactors being used in traditional TTE studies consist of a stepper motor actuating a tendon construct clamped to a tensile stage or contained within a tissue culture plate (Figure 3) [74]. Commercially available bioreactors using this mechanism include the ElectroForce series [3739], Ebers TC-3 [41], and MechanoCulture T6 Mechanical Stimulation System [40, 42] for solid scaffold constructs, or the FlexCell Tissue Train [3436] and Strex Cell ST-140-10 Mechanical Stretch Device [43] for gel based constructs on a tissue culture plate. These systems have been priced from 25,000 to upwards of 50,000 USD [75]. A number of recent studies have also developed customized tensile stage-stepper motor systems. Qin et al. presented a bioreactor which could stimulate up to four constructs simultaneously with a stepper motor and microcontroller. Cyclic uniaxial strain was applied in precise amplitudes and frequencies to their scaffolds, with rest periods in between stimulation cycles [61]. The bioreactor presented by Talo et al. combined a uniaxial tensile stage with an oscillating mechanism which provides bidirectional culture media to their tissue construct, attempting to mimic physiologic fluid flow [65]. A limited number of studies have presented tensile stage bioreactors which can provide bidirectional or different types of loading. Although Sensini et al. only applied a uniaxial load to their tissue construct, the CellScale MCB1 bioreactor used in their study can provide biaxial loading [63]. The custom-built bioreactor developed by Lee et al. relies on a group of driving motors which provide torsional stress and a second group which provide tensile stress to simulate physiologic loading experienced by the knee. The bioreactor-stimulated tissues from this study demonstrated superior mechanical properties to statically cultured constructs [67].

While several recent studies have provided alternative approaches to actuating their bioreactors, the constructs lack physiologic relevance given that these systems largely rely on uniaxial loading, involve tissue constructs that are not representative of an anatomic location for the tissue construct to be used in and offer inadequate mechanical load to tissue constructs. The diaphragm pump and pressure regulator system used in Liu et al.’s study allowed for the tissue construct to receive compressive mechanical stimulation by cyclic bulging and deformation of the membrane the tissue was cultured upon [64]. Raimondi et al. proposed a bioreactor which provided pulsatile shear stress and uniaxial tensile loading using an electromagnetic actuator. This was achieved by employing a magnet externally to a petri dish culture. The outside body of this system contains a permanent magnet and the inside body contains an electromagnet. By adjusting the current flow, a piston was electromagnetically moved back and forth and translated onto their collagen construct, resulting in the cells and the scaffold fibres aligning in the direction of loading [66]. The range of stress reported in this study, 1.5-4.5 N, is orders of magnitude lower than the load experienced by Achilles tendons in vivo, which can often experience loads of 6-8 times body weight (upwards of 3500 N) when running [76].

Despite progress in achieving reasonable strain ranges, the bioreactor systems presented in traditional TTE literature are fairly basic and do not faithfully replicate physiologic mechanical loading. Some researchers have suggested that uniaxial tensile loading is the only mechanical stimulation required for optimal engineered tendon growth [11, 77], but since the effects of different types and directions of strain have not been thoroughly explored in TTE literature, this suggestion has not been substantiated. Instead, based upon current evidence, it is likely that bioreactors with closer mimicry to native tendon would produce superior engineered constructs for clinical use. In vivo studies have consistently demonstrated that healthy tendon tissue deforms nonuniformly [2327] and mechanobiology studies have shown that tendon cells respond uniquely to different types of loading in a directionally dependent manner [28, 29, 31]. Furthermore, mechanical testing has shown that tendon tissue will deform differently depending on anatomic location. Positional tendons, such as the supraspinatus, will deform less prior to failure, whereas energy storing tendons, such as the Achilles tendon, are more elastic than positional tendons [18, 22]. As discussed in Box 1 and Box 2, current research suggests that tendon tissue requires multiaxial loading for physiologically relevant development and that tendons have different functions and exhibit varying mechanical properties depending on their anatomic location. New bioreactor systems will be required to address the limitations of uniaxial tensile devices.

3. Advanced Robotics for Provision of Mechanical Loading

3.1. Musculoskeletal Humanoid Robots

To address the lack of current bioreactor systems which can provide mechanical loading in consideration of anatomic location and typical joint motion, musculoskeletal humanoid robots have been proposed as a bioreactor platform to assist in growing tissue grafts for clinical application (Figure 4) [14]. Initially designed for applications such as crash test dummies, prostheses, and athletic enhancement, there are four characteristics of human musculoskeletal anatomy and functionality that humanoid musculoskeletal robots imitate to be suitable for these applications: (i) body proportion, (ii) skeletal structure, (iii) muscle arrangement, and (iv) joint performance [80, 81]. Musculoskeletal robots currently in use include “Eccerobot,” developed by a cross-European partnership, “Kenshiro,” developed by the Inaba group in Japan, “Roboy,” developed by Devanthro GmbH, and Suzumori Endo’s multifilament muscle robot [8084].

The arrangement of actuators and joint performance of these systems are of particular interest for TTE applications. Conventional humanoid robots such as Atlas, are articulated by rigid joints that restrict movement and have fewer degrees of freedom compared to human joints, have limited energy storing capacity, and provide kinematically constrained motion. These systems use torques between rigid links or stiff joint position tracking for movement control [84]. In contrast, a number of musculoskeletal robots rely on tendon-driven myorobotic systems, which better imitate the motion and characteristics of humans compared to traditional humanoids. MSK robots such as Roboy, Kenshiro, and Eccerobot use myorobotic units consisting of a brushless dc motor which generates tension like human muscles, attachment cables which act as the tendon unit, and a motor driver board and a spring encoder which act as the neurologic system by sensing variables including tension, compression, muscle length, and temperature [80, 83]. These myorobotic units are strategically positioned based on human anatomy, with the attachment cables replicating human muscle attachment points. Kenshiro’s myorobotic unit achieves flexible joint movements that are adaptive to external forces by implementing Hill’s muscle model and replicates physiologically relevant behaviours, such as a tendon stretch reflex (Figure 4(b)) [81]. Both Kenshiro and Roboy use measured muscle length and tension in their musculoskeletal control system to achieve desired movements (Figure 4(c)).

In addition to the development of tendon-driven myorobotic actuators, MSK robots with multifilament muscles are an attractive alternative for TTE. The lower extremity musculoskeletal robot presented by Kurumaya et al. relies on McKibben artificial muscles (Figure 4(e)). These actuators consist of an inner bladder which expands when pressurized and a helical braided sheath which transforms the circumferential pressure into an axial contraction force. The thin multifilament McKibben muscles described by Kurumaya et al.’s study can densely connect between joints, providing muscle redundancy for completing movements, similar to the human body. Another significant advantage to the McKibben muscle is that multiple filaments can be arranged in various configurations to replicate the shapes of various human muscles, such as biceps or deltoids. The lower extremity robot presented in this study was able to reasonably replicate ankle and knee motion with muscle activation patterns that were obtained from an OpenSim lower extremity model that was developed by analysing human motion [84].

By having similar dimensions and weights to human limbs, tendon-driven and multifilament musculoskeletal humanoid robots strive to imitate the range of forces observed in vivo while actuating these structures [83]. Furthermore, since the number of degrees of freedom and arrangement of actuators are designed according to the anatomic position of analogous muscles, the direction and types of loading experienced by musculoskeletal robot joints can be considered physiologically relevant [83].

Mouthuy et al.’s recent pilot study demonstrates the viability of musculoskeletal humanoid robots as a platform for tissue engineering [85]. The Roboy musculoskeletal humanoid robot was implemented to imitate the motion and structure of a human shoulder. As a starting point, Mouthuy et al. focussed on low range of motion abduction-adduction movements, which mirror physiologic loading experienced by the supraspinatus rotator cuff tendon [86, 87]. A flexible tendon tissue construct with dimensions that match a supraspinatus tendon was attached to the humerus side of the humanoid robot, forming a tendon-bone interface, while the other side of the construct connected to the biomimetic tendon-driven actuators, forming a musculotendinous junction (Figure 4(g)). As an endpoint, the tissue construct cultured on the musculoskeletal robot showed increased immunofluorescence expression 14 days postculture when exposed to mechanical stimulation between 0 and 45 N loading cycles over the culture period. Although the dynamic culture on the humanoid was not found to be superior to static culture, the results of this study are encouraging as it is a first step indicating that musculoskeletal humanoids are a feasible strategy for applying mechanical stimulation. Next steps discussed in this study include working to incorporate a greater number of movements into the loading regime and completing a study with a uniaxial control to evaluate whether multiaxial loading results in a better tissue construct. With longer experiments, it would also be beneficial to explore the effect of incrementally increasing loading throughout the culture. It has been shown that incremental loading is necessary for sustained improvement in the mechanical properties of MSK tissues [64]. The capability of the humanoid robot presented in Mouthuy et al.’s study to offer multiple force loading regimes consistent with estimated quantities of force in human tendon during abduction is promising for the eventual development of physiologically relevant tissue constructs [8790]. The cost of purchasing and modifying the Roboy arm in Mouthuy et al.’s study was around 25,000 USD.

Advantages of musculoskeletal humanoid robots compared to conventional bioreactor systems include the ability to provide multiaxial loading patterns, potential for loading in consideration of human movement patterns, and provision of loading magnitude similar to estimated in vivo forces. Kurumaya et al.’s lower extremity McKibben muscle humanoid has been programmed to move and recruit muscles using a model based on human kinematic data [84]. This allows for the joint structures to experience variable multiaxial loading, in contrast to conventional bioreactors which are limited to uniaxial linear tensile loading. As discussed in Box 1, tendon properties vary by anatomic location. It will therefore also be important for future bioreactors to provide anatomically targeted loading. Although one conventional study tried imitating knee loading through a combination of torsional and tensile strain [67], other conventional bioreactor systems have generally been unable to achieve this. Mouthuy et al.’s recent pilot study demonstrated the feasibility of using a musculoskeletal shoulder robot to mechanically stimulate a cell-material construct through abduction-adduction movements. The humanoid Kenshiro would also likely be able to provide loading in consideration of human movement patterns, given that the majority of its joints had similar range of motion to humans [80]. Clinically useful grafts will need to withstand loading quantities like those experienced by tendons in vivo. Mouthuy et al.’s supraspinatus tendon construct was exposed to tensile forces up to 45 N. This quantity is consistent predicted human supraspinatus tensile force predicted by musculoskeletal modelling and cadaveric models during abduction-adduction movement [87, 88, 90]. Conversely, the measured tensile force in a number of conventional TTE studies was found to be orders of magnitude lower than predicted in vivo forces [35, 48, 58, 66].

3.2. Soft Robotics

Biohybrid soft robotics is focussed on developing robots which are biomimetic and compliant (Figure 5). These systems are designed to “permit adaptive, flexible interactions with unpredictable environments” and have been proposed as a platform for medical applications such as tissue engineering [13]. Soft robotics technology can be actuated through a number of modalities, including temperature, pneumatic pressure, and light. They are made of soft materials such as hydrogels, rubber, and even engineered human skeletal muscle tissue [13, 9193]. Although still in early development, soft robots may be particularly well-suited for actuating TTE bioreactors. Soft robotic systems offer advantages compared to conventional bioreactors given that (i) their flexible, compliant properties allow them to mimic the anatomic conformation of native tendon, (ii) they are capable of providing multiaxial actuation, and (iii) a number of the techniques used in soft robotics overlap with current TTE practices [92]. These characteristics allow for greater control in providing mechanical stimulation to tissue constructs and could allow for development of models that exhibit physiologic strain distributions [94].

Biohybrid soft robotics are already being used to mimic in vivo strain for smooth muscle. Fell et al. developed a biohybrid soft robot which used pneumatic actuation to achieve angular flexion up to 140° and radial distention to 20° of the tissue construct, imitating the range of motion experienced by the femoropopliteal artery during locomotion (Figure 5(a)) [94]. Tissue constructs which received multiaxial stimulation in Fell et al.’s study were shown to have greater collagen production and upregulation of smooth muscle phenotypes compared to unstimulated constructs. Paek et al. presented a soft robotic actuator which was able to induce cellular alignment and actin polymerization in mechanosensitive cell lines, including respiratory and vascular connective tissue (Figure 5(c)) [95]. Their elastomeric actuator was pneumatically regulated and capable of dynamic bending motion, mimicking the constriction of tubular organs. The system was compatible with primary culture of human endothelial cells, fibroblasts, and smooth muscle cells. The actuator was advanced as it is capable of organotypic modelling of complex tissues such as vascular networks, and the effects of compressive forces on them. Paek et al.’s actuation system could be applied to TTE to mimic stretching of a tendon that is bent or wrapped around a structure in its natural position, such as a rotator cuff tendon. Furthermore, this system is capable of coculture, an approach that has been advantageous in producing tissue constructs with morphologic similarity to tendon tissue [96].

Damian et al.’s robotic implant that provides in vivo tissue regeneration in a porcine model via mechanical stimulation is another approach that could be adapted to TTE [97]. The robot is designed to induce lengthening of tubular organs, such as the oesophagus and intestines, by computer-controlled application of traction forces (Figure 5(e)). The applied forces induced cell proliferation and lengthening of the organ without a reduction in diameter, while the animal was awake, mobile, and able to eat normally. Damian et al.’s system was able to provide incremental traction to the tissue construct as it developed to continuously enhance mechanical properties. This study differs greatly from the above discussed approaches as it used in vivo conditions and existing structures as attachment points in the subjects. This approach could be interesting if applied to two ends of a ruptured tendon, potentially in combination with a seeded graft to bridge the gap. Ideally, an implantable soft robotics system would provide incrementally decreasing support to the engineered tendon graft as seeded cells proliferate and the injured tissue heals. The success of such an intervention would depend greatly on the state of the ruptured tendon and therefore might be difficult to take into clinics. Another way this setup could be studied is in vitro, as an approach to form large tissue grafts for complete tendon tears. The in vitro setup could benefit from a whole-joint system, such as those being used for shear force studies, tribology studies on implants, and for orthopaedic intervention testing [98, 99].

Recent studies have shown that soft robots synergise well with technologies currently being explored in TTE for scaffold production. Raman et al. developed a skeletal muscle bioactuator using bioprinting capable of self-healing after being damaged (Figure 5(h)) [100]. Bioprinting is an emerging strategy in TTE which is growing in interest for establishing microarchitectural context at the scaffold level. Proposed benefits of this technique include higher initial cell densities, resulting in increased ECM production, comparable structural complexity to native tissues, and higher throughput compared to traditional scaffolding methods for eventual large-scale implementation [101103]. Soft robotic systems can also rely on more traditional TTE technologies; a recent review has presented a number of muscle inspired coiled soft actuators have been produced using electrospinning [104].

Collectively, soft robotics technology is already being adopted in tissue engineering and has potential to help advance development of physiologically relevant tendon constructs. Longer term tissue cultures with incremental loading have not been fully explored in conventional TTE studies. Damian et al.’s in vivo study involving scalable loading provides vision as to how a soft robotics system may be used to fulfil this purpose. An additional benefit of these relatively small, modular systems is greater possibility of eventual in vivo repair of tendon injuries using robotic systems. Rigid tensile stage bioreactors used in conventional TTE studies are often limited to the development of linear rod-shaped tissue constructs which are not designed to undergo bending or shear. In contrast, native tendons wrap around bony structures and are known to undergo torsion, shear, compression, and multiaxial tensile loading simultaneously as joints move [2327]. A significant advantage of flexible, soft robotic actuators such as those presented by Fell et al. or Paek et al. is the ability to produce anatomically relevant tissue constructs capable of undergoing multiaxial loading and bending or wrapping around other structures [94, 95]. Although soft robotic systems have not yet been implemented in TTE studies, there is good opportunity for synergy, given that these studies have already explored culturing mechanosensitive tissue, such as muscle tissue [100], and have implemented techniques which are regularly used in TTE, such as electrospinning and bioprinting.

4. Future Perspectives and Concluding Remarks

Recent TTE experimental work has been summarised, and limitations in current research have been discussed in this review. One of the most significant limitations in conventional TTE studies using uniaxial bioreactors has been the lack of bioreactor systems which can provide physiologically relevant mechanical stimulation. Advanced robotic technologies show promise in addressing this limitation. Musculoskeletal humanoids are developed using anthropometric data and human musculoskeletal models to have biomimetic force and movement profiles. These robots attempt to have similar dimensions to humans and their actuators are arranged to mimic the anatomic configuration of muscles [80, 84]. The ability of these systems to provide multiaxial loading in consideration of physiologic movement patterns is a significant advantage over traditional tensile stage bioreactors. To date, one study has demonstrated the viability of musculoskeletal humanoid robots for mechanically stimulating tendon constructs [85].

Soft robotic actuators are an alternative platform proposed for the advancement of current TTE research. In contrast to the hydrogel sheets or linear rod-shaped tissue constructs produced by tensile stage bioreactors, soft robotic actuators are capable of producing tissue constructs which undergo multiaxial bending movements [94]. The ability to bend or wrap around structures is an important consideration in the development of connective tissues such as tendon. We expect that soft robotics technology would synergise well with current TTE research, given that soft robotics technology has already been used to develop other connective tissue constructs, such as skeletal muscle and blood vessels [95, 100]. An end goal with TTE is translation to clinical use. Damian et al.’s recent work, which has demonstrated in vivo applications of soft robotics technology, helps provide vision to how this technology may eventually be used for clinical tendon repair [97].

There are a number of key challenges to consider as advanced robotic platforms are implemented in TTE. Although in vivo evidence suggests that different types and directions of loading are required for healthy tendon development, there is currently no literature comparing tendon constructs stimulated with traditional uniaxial loading and multiaxial physiologic loading. A main deliverable in future research would be to compare the technologies proposed in this review to current bioreactor systems available for TTE. As discussed in current TTE research, the quantity of strain experienced by tendon tissue is of critical importance to its healthy development. Traditional methods of deformation measurement such as strain gauges will be inadequate for accurately estimating multiaxial deformation. Systems capable of measuring different types of loading in 3D will be required. Digital image correlation and quantitative strain elastography are two technologies that have been explored for in vivo tendon imaging and may be useful in next phases of experimental work [23, 24, 50, 58]. Affordability and accessibility of advanced robotic technology will be important considerations for widespread adoption within the TTE research. Most commercially available conventional TTE bioreactor systems are priced between 25,000 and 50,000 USD, and other recent TTE studies have attempted to develop low-cost bioreactor systems using 3D printing in the range of 5,000–10,000 USD [45, 46]. In contrast, musculoskeletal humanoid robots are in their infancy and there is limited commercial availability, with the bioreactor system used by Mouthuy et al. costing 25,000 USD. Creating open access online repositories with parts lists and sharing software code through portals such as GitHub will make a development of new advanced robotic technology more affordable and accessible to researchers in this field. Regulation of soft robotic systems and musculoskeletal humanoid robots will be an important future consideration as these technologies are more widely implemented in TTE. In the United States, these would likely be classified by the Food and Drug Administration (FDA) as “Combination Biological Products” regulated by the Centre for Biologics Evaluation and Research. In European Union, engineered constructs developed using advanced robotic technology would be regulated as an “Advanced Therapy Medicinal Product” (ATMP) regulated by the European Medicines Agency.

This article has primarily discussed the importance of mechanical loading in the development of healthy tendon tissue. Considering that a number of therapeutic interventions for tendon injury involve contactless stimulation, several recent reviews have suggested that electrical and magnetic stimulation may positively contribute to tendon development and healing [7, 10]. One recent TTE study has developed a piezoelectric scaffold with potential to provide cells with electrical stimulation [58]. Working to better understand the mechanisms of these contactless techniques and evaluating their potential for use in TTE is an interesting future area of study.

In summary, tendon injuries present a tremendous socioeconomic burden and are increasing in prevalence with an ageing demographic. Tissue engineering has received considerable attention for its potential to address this growing challenge. This review article has emphasised the key role of mechanical context in producing useful tendon constructs and has highlighted musculoskeletal robots and soft robotic systems as viable strategies for advancing this field of research.

Data Availability

The data used to support the findings of this review article are available from the corresponding author upon request.

Conflicts of Interest

The authors declare no conflict of interest.

Authors’ Contributions

IS, ND, and PM contributed to write up and editing of manuscript. JS and AC edited the manuscript.

Acknowledgments

This work has been completed with the financial support of the United Kingdom’s Engineering and Physical Sciences Research Council (project number: P/S003509/1) and the Rhodes Trust.

References

  1. J. G. Snedeker and J. Foolen, “Tendon injury and repair - a perspective on the basic mechanisms of tendon disease and future clinical therapy,” Acta Biomaterialia, vol. 63, pp. 18–36, 2017. View at: Publisher Site | Google Scholar
  2. C. Hopkins, S. C. Fu, E. Chua et al., “Critical review on the socio-economic impact of tendinopathy,” Asia-Pacific journal of sports medicine, arthroscopy, rehabilitation and technology, vol. 4, pp. 9–20, 2016. View at: Publisher Site | Google Scholar
  3. R. C. Mather, L. Koenig, D. Acevedo et al., “The societal and economic value of rotator cuff repair,” The Journal of bone and joint surgery. American volume, vol. 95, no. 22, pp. 1993–2000, 2013. View at: Publisher Site | Google Scholar
  4. P. N. Chalmers, E. Granger, R. Nelson, M. Yoo, and R. Z. Tashjian, “Factors affecting cost, outcomes, and tendon healing after arthroscopic rotator cuff repair,” Arthroscopy, vol. 34, no. 5, pp. 1393–1400, 2018. View at: Publisher Site | Google Scholar
  5. A. J. Carr, C. D. Cooper, M. K. Campbell et al., “Clinical effectiveness and cost-effectiveness of open and arthroscopic rotator cuff repair [the UK rotator cuff surgery (UKUFF) randomised trial],” Health Technology Assessment, vol. 19, no. 80, pp. 1–218, 2015. View at: Publisher Site | Google Scholar
  6. W. R. Thompson, A. Scott, M. T. Loghmani, S. R. Ward, and S. J. Warden, “Understanding mechanobiology: physical therapists as a force in mechanotherapy and musculoskeletal regenerative rehabilitation,” Physical Therapy, vol. 96, no. 4, pp. 560–569, 2016. View at: Publisher Site | Google Scholar
  7. T. Wang, B. S. Gardiner, Z. Lin et al., “Bioreactor design for tendon/ligament engineering,” Tissue Engineering. Part B, Reviews, vol. 19, no. 2, pp. 133–146, 2013. View at: Publisher Site | Google Scholar
  8. T. Wang, P. Chen, M. Zheng et al., “In vitro loading models for tendon mechanobiology,” Journal of Orthopaedic Research, vol. 36, no. 2, pp. 566–575, 2017. View at: Publisher Site | Google Scholar
  9. J. Mace, A. Wheelton, W. S. Khan, and S. Anand, “The role of bioreactors in ligament and tendon tissue engineering,” Current Stem Cell Research & Therapy, vol. 11, no. 1, pp. 35–40, 2016. View at: Publisher Site | Google Scholar
  10. R. Sheng, Y. Jiang, L. J. Backman, W. Zhang, and J. Chen, “The application of mechanical stimulations in tendon tissue engineering,” Stem Cells International, vol. 2020, Article ID 8824783, 14 pages, 2020. View at: Publisher Site | Google Scholar
  11. M. Govoni, C. Muscari, J. Lovecchio, C. Guarnieri, and E. Giordano, “Mechanical actuation Systems for the phenotype commitment of stem cell-based tendon and ligament tissue substitutes,” Stem Cell Reviews and Reports, vol. 12, no. 2, pp. 189–201, 2016. View at: Publisher Site | Google Scholar
  12. E. Guanziroli, M. Cazzaniga, L. Colombo, S. Basilico, G. Legnani, and F. Molteni, “Assistive powered exoskeleton for complete spinal cord injury: correlations between walking ability and exoskeleton control,” European Journal of Physical and Rehabilitation Medicine, vol. 55, no. 2, pp. 209–216, 2019. View at: Publisher Site | Google Scholar
  13. S. Kim, C. Laschi, and B. Trimmer, “Soft robotics: a bioinspired evolution in robotics,” Trends in Biotechnology, vol. 31, no. 5, pp. 287–294, 2013. View at: Publisher Site | Google Scholar
  14. P.-A. Mouthuy and A. Carr, “Growing tissue grafts on humanoid robots: future strategy in regenerative medicine?” Science Robotics, vol. 2, no. 4, article eaam5666, 2017. View at: Publisher Site | Google Scholar
  15. C. T. Thorpe and H. R. Screen, “Tendon structure and composition,” Advances in Experimental Medicine and Biology, vol. 920, pp. 3–10, 2016. View at: Publisher Site | Google Scholar
  16. C. M. McNeilly, A. Banes, M. Benjamin, and J. Ralphs, “Tendon cells in vivo form a three dimensional network of cell processes linked by gap junctions,” Journal of Anatomy, vol. 189, pp. 593–600, 1996. View at: Google Scholar
  17. S. P. Lake, K. S. Miller, D. M. Elliott, and L. J. Soslowsky, “Tensile properties and fiber alignment of human supraspinatus tendon in the transverse direction demonstrate inhomogeneity, nonlinearity, and regional isotropy,” Journal of biomechanics, vol. 43, no. 4, pp. 727–732, 2010. View at: Publisher Site | Google Scholar
  18. C. T. Thorpe, C. P. Udeze, H. L. Birch, P. D. Clegg, and H. R. Screen, “Specialization of tendon mechanical properties results from interfascicular differences,” Journal of the Royal Society Interface, vol. 9, no. 76, pp. 3108–3117, 2012. View at: Publisher Site | Google Scholar
  19. H. L. Birch, “Tendon matrix composition and turnover in relation to functional requirements,” International Journal of Experimental Pathology, vol. 88, no. 4, pp. 241–248, 2007. View at: Publisher Site | Google Scholar
  20. D. T. Kirkendall and W. E. Garrett, “Function and biomechanics of tendons,” Scandinavian Journal of Medicine & Science in Sports, vol. 7, no. 2, pp. 62–66, 1997. View at: Publisher Site | Google Scholar
  21. H. R. Screen, D. E. Berk, K. E. Kadler, F. Ramirez, and M. F. Young, “Tendon functional extracellular matrix,” Journal of Orthopaedic Research, vol. 33, no. 6, pp. 793–799, 2015. View at: Publisher Site | Google Scholar
  22. C. T. Thorpe, P. D. Clegg, and H. L. Birch, “A review of tendon injury: why is the equine superficial digital flexor tendon most at risk?” Equine Veterinary Journal, vol. 42, no. 2, pp. 174–180, 2010. View at: Publisher Site | Google Scholar
  23. L. C. Slane and D. G. Thelen, “Achilles tendon displacement patterns during passive stretch and eccentric loading are altered in middle-aged adults,” Medical Engineering & Physics, vol. 37, no. 7, pp. 712–716, 2015. View at: Publisher Site | Google Scholar
  24. R. L. Chimenti, A. S. Flemister, J. Ketz, M. Bucklin, M. R. Buckley, and M. S. Richards, “Ultrasound strain mapping of Achilles tendon compressive strain patterns during dorsiflexion,” Journal of biomechanics, vol. 49, no. 1, pp. 39–44, 2016. View at: Publisher Site | Google Scholar
  25. Y. S. Kim, J. M. Kim, L. U. Bigliani, H. J. Kim, and H. W. Jung, “In vivo strain analysis of the intact supraspinatus tendon by ultrasound speckles tracking imaging,” Journal of Orthopaedic Research, vol. 29, no. 12, pp. 1931–1937, 2011. View at: Publisher Site | Google Scholar
  26. M. Lavagnino, M. E. Wall, D. Little, A. J. Banes, F. Guilak, and S. P. Arnoczky, “Tendon mechanobiology: current knowledge and future research opportunities,” Journal of Orthopaedic Research, vol. 33, no. 6, pp. 813–822, 2015. View at: Publisher Site | Google Scholar
  27. G. A. Orozco, P. Tanska, M. E. Mononen, K. S. Halonen, and R. K. Korhonen, “The effect of constitutive representations and structural constituents of ligaments on knee joint mechanics,” Scientific reports, vol. 8, no. 1, p. 2323, 2018. View at: Publisher Site | Google Scholar
  28. T. D. Plant, “TRPs in mechanosensing and volume regulation,” Handbook of Experimental Pharmacology, vol. 223, pp. 743–766, 2014. View at: Publisher Site | Google Scholar
  29. X. Varelas, “The hippo pathway effectors TAZ and YAP in development, homeostasis and disease,” Development, vol. 141, no. 8, pp. 1614–1626, 2014. View at: Publisher Site | Google Scholar
  30. Y. Song, J. Soto, B. Chen et al., “Transient Nuclear Deformation Primes Epigenetic State and Promotes Cell Reprogramming,” Nature Materials, 2021. View at: Publisher Site | Google Scholar
  31. M. Stolk, F. Klatte-Schulz, A. Schmock, S. Minkwitz, B. Wildemann, and M. Seifert, “New insights into tenocyte-immune cell interplay in an in vitro model of inflammation,” Scientific reports, vol. 7, no. 1, article 9801, 2017. View at: Publisher Site | Google Scholar
  32. B. Cheng, M. Lin, G. Huang et al., “Cellular mechanosensing of the biophysical microenvironment: a review of mathematical models of biophysical regulation of cell responses,” Physics of Life Reviews, vol. 22-23, pp. 88–119, 2017. View at: Publisher Site | Google Scholar
  33. S. P. Arnoczky, M. Lavagnino, and M. Egerbacher, “The mechanobiological aetiopathogenesis of tendinopathy: is it the over- stimulation or the under-stimulation of tendon cells?” International Journal of Experimental Pathology, vol. 88, no. 4, pp. 217–226, 2007. View at: Publisher Site | Google Scholar
  34. J. Wee, H. Kim, S. J. Shin, T. Lee, and S. Y. Lee, “Influence of mechanical and TGF-β3 stimulation on the tenogenic differentiation of tonsil-derived mesenchymal stem cells,” BMC molecular and cell biology, vol. 23, no. 1, p. 3, 2022. View at: Publisher Site | Google Scholar
  35. M. C. Ciardulli, L. Marino, J. Lovecchio et al., “Tendon and cytokine marker expression by human bone marrow mesenchymal stem cells in a hyaluronate/poly-lactic-co-glycolic acid (PLGA)/fibrin three-dimensional (3D) scaffold,” Cells, vol. 9, no. 5, 2020. View at: Publisher Site | Google Scholar
  36. K. Mubyana and D. T. Corr, “Cyclic uniaxial tensile strain enhances the mechanical properties of engineered, scaffold-free tendon fibers,” Tissue Engineering Part A, vol. 24, no. 23-24, pp. 1808–1817, 2018. View at: Publisher Site | Google Scholar
  37. W. Baumgartner, P. Wolint, S. Hofmann et al., “Impact of electrospun piezoelectric core-shell PVDFhfp/PDMS mesh on tenogenic and inflammatory gene expression in human adipose-derived stem cells: comparison of static cultivation with uniaxial cyclic tensile stretching,” Bioengineering, vol. 9, no. 1, 2022. View at: Publisher Site | Google Scholar
  38. C. H. Chen, D. L. Li, A. D. Chuang, B. S. Dash, and J. P. Chen, “Tension stimulation of tenocytes in aligned hyaluronic acid/platelet-rich plasma-polycaprolactone core-sheath nanofiber membrane scaffold for tendon tissue engineering,” International journal of molecular sciences, vol. 22, no. 20, 2021. View at: Publisher Site | Google Scholar
  39. H. Yuan, X. Li, M. S. Lee et al., “Collagen and chondroitin sulfate functionalized bioinspired fibers for tendon tissue engineering application,” International Journal of Biological Macromolecules, vol. 170, pp. 248–260, 2021. View at: Publisher Site | Google Scholar
  40. A. Garcia Garcia, J. B. Perot, M. Beldjilali-Labro et al., “Monitoring mechanical stimulation for optimal tendon tissue engineering: a mechanical and biological multiscale study,” Journal of Biomedical Materials Research. Part A, vol. 109, no. 10, pp. 1881–1892, 2021. View at: Publisher Site | Google Scholar
  41. P. Deniz, S. Guler, E. Çelik, P. Hosseinian, and H. M. Aydin, “Use of cyclic strain bioreactor for the upregulation of key tenocyte gene expression on poly(glycerol-sebacate) (PGS) sheets,” Materials Science & Engineering. C, Materials for Biological Applications, vol. 106, article 110293, 2020. View at: Publisher Site | Google Scholar
  42. S. Wu, Y. Wang, P. N. Streubel, and B. Duan, “Living nanofiber yarn-based woven biotextiles for tendon tissue engineering using cell tri-culture and mechanical stimulation,” Acta Biomaterialia, vol. 62, pp. 102–115, 2017. View at: Publisher Site | Google Scholar
  43. H. Y. Nam, B. Pingguan-Murphy, A. Amir Abbas, A. Mahmood Merican, and T. Kamarul, “The proliferation and tenogenic differentiation potential of bone marrow-derived mesenchymal stromal cell are influenced by specific uniaxial cyclic tensile loading conditions,” Biomechanics and Modeling in Mechanobiology, vol. 14, no. 3, pp. 649–663, 2015. View at: Publisher Site | Google Scholar
  44. Z. Chen, P. Chen, R. Ruan, and M. Zheng, “In vitro 3D mechanical stimulation to tendon-derived stem cells by bioreactor,” Methods in Molecular Biology, vol. 2436, pp. 135–144, 2022. View at: Publisher Site | Google Scholar
  45. A. J. Janvier, E. Canty-Laird, and J. R. Henstock, “A universal multi-platform 3D printed bioreactor chamber for tendon tissue engineering,” Journal of Tissue Engineering, vol. 11, 2020. View at: Publisher Site | Google Scholar
  46. B. L. Banik and J. L. Brown, “3D-printed bioreactor enhances potential for tendon tissue engineering,” Regenerative Engineering and Translational Medicine, vol. 6, no. 4, pp. 419–428, 2020. View at: Publisher Site | Google Scholar
  47. F. Atkinson, R. Evans, J. E. Guest et al., “Cyclical strain improves artificial equine tendon constructs in vitro,” Journal of Tissue Engineering and Regenerative Medicine, vol. 14, no. 5, pp. 690–700, 2020. View at: Publisher Site | Google Scholar
  48. P. Sawadkar, D. Player, L. Bozec, and V. Mudera, “The mechanobiology of tendon fibroblasts under static and uniaxial cyclic load in a 3D tissue engineered model mimicking native ECM,” Journal of tissue engineering and regenerative medicine, vol. 14, no. 1, pp. 135–146, 2019. View at: Publisher Site | Google Scholar
  49. M. Y. Hsiao, P. C. Lin, W. H. Liao et al., “The effect of the repression of oxidative stress on tenocyte differentiation: a preliminary study of a rat cell model using a novel differential tensile strain bioreactor,” International Journal of Molecular Sciences, vol. 20, no. 14, 2019. View at: Publisher Site | Google Scholar
  50. Y. Morita, T. Sato, K. Higashiura et al., “The optimal mechanical condition in stem cell-to-tenocyte differentiation determined with the homogeneous strain distributions and the cellular orientation control,” Biology open, vol. 8, no. 5, 2019. View at: Publisher Site | Google Scholar
  51. Y. Nakanishi, T. Okada, N. Takeuchi et al., “Histological evaluation of tendon formation using a scaffold-free three- dimensional-bioprinted construct of human dermal fibroblasts under in vitro static tensile culture,” Regenerative therapy, vol. 11, pp. 47–55, 2019. View at: Publisher Site | Google Scholar
  52. W. K. Grier, R. A. Sun Han Chang, M. D. Ramsey, and B. A. Harley, “The influence of cyclic tensile strain on multi-compartment collagen-GAG scaffolds for tendon-bone junction repair,” Connective tissue research, vol. 60, no. 6, pp. 530–543, 2019. View at: Publisher Site | Google Scholar
  53. A. R. Raveling, S. K. Theodossiou, and N. R. Schiele, “A 3D printed mechanical bioreactor for investigating mechanobiology and soft tissue mechanics,” MethodsX, vol. 5, pp. 924–932, 2018. View at: Publisher Site | Google Scholar
  54. B. Engebretson, Z. R. Mussett, and V. I. Sikavitsas, “The effects of varying frequency and duration of mechanical stimulation on a tissue-engineered tendon construct,” Connective Tissue Research, vol. 59, no. 2, pp. 167–177, 2018. View at: Publisher Site | Google Scholar
  55. S. Testa, M. Costantini, E. Fornetti et al., “Combination of biochemical and mechanical cues for tendon tissue engineering,” Journal of Cellular and Molecular Medicine, vol. 21, no. 11, pp. 2711–2719, 2017. View at: Publisher Site | Google Scholar
  56. W. G. Grier, A. S. Moy, and B. A. Harley, “Cyclic tensile strain enhances human mesenchymal stem cell Smad 2/3 activation and tenogenic differentiation in anisotropic collagen-glycosaminoglycan scaffolds,” European cells & materials, vol. 33, pp. 227–239, 2017. View at: Publisher Site | Google Scholar
  57. J. Joo Kim, D. S. Musson, B. G. Matthews, J. Cornish, I. A. Anderson, and V. B. Shim, “Applying physiologically relevant strains to tenocytes in an in vitro cell device induces in vivo like behaviors,” Journal of biomechanical engineering, vol. 138, no. 12, 2016. View at: Publisher Site | Google Scholar
  58. C. A. Cook, P. Y. Huri, B. P. Ginn et al., “Characterization of a novel bioreactor system for 3D cellular mechanobiology studies,” Biotechnology and Bioengineering, vol. 113, no. 8, pp. 1825–1837, 2016. View at: Publisher Site | Google Scholar
  59. J. Burk, A. Plenge, W. Brehm, S. Heller, B. Pfeiffer, and C. Kasper, “Induction of tenogenic differentiation mediated by extracellular tendon matrix and short-term cyclic stretching,” Stem Cells International, vol. 2016, Article ID 7342379, 11 pages, 2016. View at: Publisher Site | Google Scholar
  60. D. W. Youngstrom, I. Rajpar, D. L. Kaplan, and J. G. Barrett, “A bioreactor system for in vitro tendon differentiation and tendon tissue engineering,” Journal of Orthopaedic Research, vol. 33, no. 6, pp. 911–918, 2015. View at: Publisher Site | Google Scholar
  61. T. W. Qin, Y. L. Sun, A. R. Thoreson et al., “Effect of mechanical stimulation on bone marrow stromal cell-seeded tendon slice constructs: a potential engineered tendon patch for rotator cuff repair,” Biomaterials, vol. 51, pp. 43–50, 2015. View at: Publisher Site | Google Scholar
  62. R. D. Cardwell, J. A. Kluge, P. S. Thayer et al., “Static and cyclic mechanical loading of mesenchymal stem cells on elastomeric, electrospun polyurethane meshes,” Journal of Biomechanical Engineering, vol. 137, no. 7, pp. 0710101–0710108, 2015. View at: Publisher Site | Google Scholar
  63. A. Sensini, L. Cristofolini, A. Zucchelli et al., “Hierarchical electrospun tendon-ligament bioinspired scaffolds induce changes in fibroblasts morphology under static and dynamic conditions,” Journal of Microscopy, vol. 277, no. 3, pp. 160–169, 2019. View at: Publisher Site | Google Scholar
  64. H. Liu, J. F. Usprech, P. K. Parameshwar, Y. Sun, and C. A. Simmons, “Combinatorial screen of dynamic mechanical stimuli for predictive control of MSC mechano-responsiveness,” Science Advances, vol. 7, no. 19, article eabe7204, 2021. View at: Publisher Site | Google Scholar
  65. G. Talo, D. D’Arrigo, S. Lorenzi, M. Moretti, and A. B. Lovati, “Independent, controllable stretch-perfusion bioreactor chambers to functionalize cell-seeded decellularized tendons,” Annals of biomedical engineering, vol. 48, no. 3, pp. 1112–1126, 2019. View at: Publisher Site | Google Scholar
  66. M. T. Raimondi, M. Laganà, C. Conci et al., “Development and biological validation of a cyclic stretch culture system for the ex vivo engineering of tendons,” The International Journal of Artificial Organs, vol. 41, no. 7, pp. 400–412, 2018. View at: Publisher Site | Google Scholar
  67. K. I. Lee, J. S. Lee, K. T. Kang et al., “In vitro and in vivo performance of tissue-engineered tendons for anterior cruciate ligament reconstruction,” The American Journal of Sports Medicine, vol. 46, no. 7, pp. 1641–1649, 2018. View at: Publisher Site | Google Scholar
  68. F. Qi, Z. Deng, Y. Ma et al., “From the perspective of embryonic tendon development: various cells applied to tendon tissue engineering,” Annals of Translational Medicine, vol. 8, no. 4, p. 131, 2020. View at: Publisher Site | Google Scholar
  69. P. P. Lui and K. M. Chan, “Tendon-derived stem cells (TDSCs): from basic science to potential roles in tendon pathology and tissue engineering applications,” Stem Cell Reviews and Reports, vol. 7, no. 4, pp. 883–897, 2011. View at: Publisher Site | Google Scholar
  70. J. Xue, T. Wu, Y. Dai, and Y. Xia, “Electrospinning and electrospun nanofibers: methods, materials, and applications,” Chemical reviews, vol. 119, no. 8, pp. 5298–5415, 2019. View at: Publisher Site | Google Scholar
  71. S. Ruiz-Alonso, M. Lafuente-Merchan, J. Ciriza, L. Saenz-Del-Burgo, and J. L. Pedraz, “Tendon tissue engineering: cells, growth factors, scaffolds and production techniques,” Journal of Controlled Release, vol. 333, pp. 448–486, 2021. View at: Publisher Site | Google Scholar
  72. H. Tsutsumi, R. Kurimoto, R. Nakamichi et al., “Generation of a tendon-like tissue from human iPS cells,” Journal of tissue engineering, vol. 13, 2022. View at: Publisher Site | Google Scholar
  73. S. Komura, T. Satake, A. Goto et al., “Induced pluripotent stem cell-derived tenocyte-like cells promote the regeneration of injured tendons in mice,” Scientific reports, vol. 10, no. 1, p. 3992, 2020. View at: Publisher Site | Google Scholar
  74. W. Willenberg, M. S. Marzieh, and B. Markert, “Experimental and numerical investigation of tendons and tendon cells,” Applied Mathematics and Mechanics, vol. 16, no. 1, pp. 113-114, 2016. View at: Publisher Site | Google Scholar
  75. A. H. Huang, Y. U. Lee, E. A. Calle et al., “Design and use of a novel bioreactor for regeneration of biaxially stretched tissue-engineered vessels,” Tissue Engineering. Part C, Methods, vol. 21, no. 8, pp. 841–851, 2015. View at: Publisher Site | Google Scholar
  76. K. K. W. Lee, S. K. K. Ling, and P. S. H. Yung, “Controlled trial to compare the Achilles tendon load during running in flatfeet participants using a customized arch support orthoses vs an orthotic heel lift,” BMC musculoskeletal disorders, vol. 20, no. 1, p. 535, 2019. View at: Publisher Site | Google Scholar
  77. J. H. Wang, Q. Guo, and B. Li, “Tendon biomechanics and mechanobiology--a minireview of basic concepts and recent advancements,” Journal of hand therapy, vol. 25, no. 2, pp. 133–140, 2012. View at: Publisher Site | Google Scholar
  78. J. A. Kluge, G. G. Leisk, R. D. Cardwell et al., “Bioreactor system using noninvasive imaging and mechanical stretch for biomaterial screening,” Annals of Biomedical Engineering, vol. 39, no. 5, pp. 1390–1402, 2011. View at: Publisher Site | Google Scholar
  79. S. Schürmann, S. Wagner, S. Herlitze et al., “The IsoStretcher : an isotropic cell stretch device to study mechanical biosensor pathways in living cells,” Biosensors and Bioelectronics, vol. 81, pp. 363–372, 2016. View at: Publisher Site | Google Scholar
  80. Y. Asano, K. Okada, and M. Inaba, “Design principles of a human mimetic humanoid: humanoid platform to study human intelligence and internal body system,” Science Robotics, vol. 2, no. 13, article eaaq0899, 2017. View at: Publisher Site | Google Scholar
  81. Y. Asano, K. Okada, and M. Inaba, “Musculoskeletal design, control, and application of human mimetic humanoid Kenshiro,” Bioinspiration & biomimetics, vol. 14, no. 3, article 036011, 2019. View at: Publisher Site | Google Scholar
  82. A. Diamond and O. E. Holland, “Reaching control of a full-torso, modelled musculoskeletal robot using muscle synergies emergent under reinforcement learning,” Bioinspiration & Biomimetics, vol. 9, no. 1, article 016015, 2014. View at: Publisher Site | Google Scholar
  83. C. Richter, S. Jentzsch, R. Hostettler et al., “Musculoskeletal robots: scalability in neural control,” IEEE Robotics and Automation Magazine, vol. 23, no. 4, pp. 128–137, 2016. View at: Publisher Site | Google Scholar
  84. S. Kurumaya, K. Suzumori, H. Nabae, and S. Wakimoto, “Musculoskeletal lower-limb robot driven by multifilament muscles,” Robomech Journal, vol. 3, no. 1, p. 18, 2016. View at: Publisher Site | Google Scholar
  85. P.-A. Mouthuy, S. Snelling, R. Hostettler et al., “Humanoid robots to mechanically stress human cells grown in soft bioreactors,” Engineering, vol. 1, no. 1, pp. 1–11, 2022. View at: Publisher Site | Google Scholar
  86. C. Engelhardt, V. Malfroy Camine, D. Ingram et al., “Comparison of an EMG-based and a stress-based method to predict shoulder muscle forces,” Computer Methods in Biomechanics and Biomedical Engineering, vol. 18, no. 12, pp. 1272–1279, 2015. View at: Publisher Site | Google Scholar
  87. Y. Blache and M. Begon, “Influence of shoulder kinematic estimate on joint and muscle mechanics predicted by musculoskeletal model,” IEEE Transactions on Biomedical Engineering, vol. 65, no. 4, pp. 715–722, 2018. View at: Publisher Site | Google Scholar
  88. R. E. Hughes and K. N. An, “Force analysis of rotator cuff muscles,” Clinical Orthopaedics and Related Research, vol. 330, pp. 75–83, 1996. View at: Publisher Site | Google Scholar
  89. C. J. Gatti, C. R. Dickerson, E. K. Chadwick, A. G. Mell, and R. E. Hughes, “Comparison of model-predicted and measured moment arms for the rotator cuff muscles,” Clinical Biomechanics, vol. 22, no. 6, pp. 639–644, 2007. View at: Publisher Site | Google Scholar
  90. N. Wuelker, W. Plitz, B. Roetman, and C. J. Wirth, “Function of the supraspinatus muscle. Abduction of the humerus studied in cadavers,” Acta Orthopaedica Scandinavica, vol. 65, no. 4, pp. 442–446, 1994. View at: Publisher Site | Google Scholar
  91. M. Pilz da Cunha, M. G. Debije, and A. P. H. J. Schenning, “Bioinspired light-driven soft robots based on liquid crystal polymers,” Chemical Society Reviews, vol. 49, no. 18, pp. 6568–6578, 2020. View at: Publisher Site | Google Scholar
  92. L. Ricotti, B. Trimmer, A. W. Feinberg et al., “Biohybrid actuators for robotics: a review of devices actuated by living cells,” Science robotics, vol. 2, no. 12, article eaaq0495, 2017. View at: Publisher Site | Google Scholar
  93. H. Kamble, R. Vadivelu, M. Barton, M. J. A. Shiddiky, and N.-T. Nguyen, “Pneumatically actuated cell-stretching array platform for engineering cell patterns in vitro,” Lab on a Chip, vol. 18, no. 5, pp. 765–774, 2018. View at: Publisher Site | Google Scholar
  94. C. Fell, T. L. Brooks-Richards, M. A. Woodruff, and M. C. Allenby, Bio-hybrid soft robotic bioreactors for mimicking multi-axial femoropopliteal artery mechanobiology, bioRxiv, 2021. View at: Publisher Site
  95. J. Paek, J. W. Song, E. Ban et al., “Soft robotic constrictor for in vitro modeling of dynamic tissue compression,” Scientific reports, vol. 11, no. 1, p. 16478, 2021. View at: Publisher Site | Google Scholar
  96. Q. Luo, G. Song, Y. Song, B. Xu, J. Qin, and Y. Shi, “Indirect co-culture with tenocytes promotes proliferation and mRNA expression of tendon/ligament related genes in rat bone marrow mesenchymal stem cells,” Cytotechnology, vol. 61, no. 1-2, pp. 1–10, 2009. View at: Publisher Site | Google Scholar
  97. D. D. Damian, K. Price, S. Arabagi et al., “In vivo tissue regeneration with robotic implants,” Science robotics, vol. 3, no. 14, article eaaq0018, 2018. View at: Publisher Site | Google Scholar
  98. A. Liu, L. M. Jennings, E. Ingham, and J. Fisher, “Tribology studies of the natural knee using an animal model in a new whole joint natural knee simulator,” Journal of biomechanics, vol. 48, no. 12, pp. 3004–3011, 2015. View at: Publisher Site | Google Scholar
  99. A. Beckmann, C. Herren, M. Mundt et al., “A new in vitro spine test rig to track multiple vertebral motions under physiological conditions,” Biomedical Engineering/Biomedizinische Technik, vol. 63, no. 4, pp. 341–347, 2018. View at: Publisher Site | Google Scholar
  100. R. Raman, L. Grant, Y. Seo et al., “Damage, healing, and remodeling in optogenetic skeletal muscle bioactuators,” Advanced healthcare materials, vol. 6, no. 12, 2017. View at: Publisher Site | Google Scholar
  101. T. Potyondy, J. A. Uquillas, P. J. Tebon et al., “Recent advances in 3D bioprinting of musculoskeletal tissues,” Biofabrication, vol. 13, no. 2, article 022001, 2020. View at: Publisher Site | Google Scholar
  102. S. V. Murphy and A. Atala, “3D bioprinting of tissues and organs,” Nature Biotechnology, vol. 32, no. 8, pp. 773–785, 2014. View at: Publisher Site | Google Scholar
  103. A. Ovsianikov, A. Khademhosseini, and V. Mironov, “The synergy of scaffold-based and scaffold-free tissue engineering strategies,” Trends in Biotechnology, vol. 36, no. 4, pp. 348–357, 2018. View at: Publisher Site | Google Scholar
  104. C. Gotti, A. Sensini, A. Zucchelli, R. Carloni, and M. L. Focarete, “Hierarchical fibrous structures for muscle‐inspired soft‐actuators: a review,” Applied Materials Today, vol. 20, article 100772, 2020. View at: Publisher Site | Google Scholar

Copyright © 2022 Iain L. Sander et al. Exclusive Licensee Beijing Institute of Technology Press. Distributed under a Creative Commons Attribution License (CC BY 4.0).

 PDF Download Citation Citation
Views108
Downloads69
Altmetric Score
Citations