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Plasticity of the gastrocnemius elastic system in response to decreased work and power demand during growth

Citation

Cox, Suzanne et al. (2021), Plasticity of the gastrocnemius elastic system in response to decreased work and power demand during growth, Dryad, Dataset, https://doi.org/10.5061/dryad.w3r2280r7

Abstract

Elastic energy storage and release can enhance performance that would otherwise be limited by the force-velocity constraints of muscle. While functional influence of a biological spring depends on tuning between components of an elastic system (the muscle, spring, driven mass, and lever system), we do not know whether elastic systems systematically adapt to functional demand. To test whether altering work and power generation during maturation alters the morphology of an elastic system, we prevented growing guinea fowl (Numida Meleagris) from jumping. At maturity, we compared the jump performance of our treatment group to that of controls and measured the morphology of the gastrocnemius elastic system. We found that restricted birds jumped with lower jump power and work, yet there were no significant between-group differences in the components of the elastic system. Further, subject-specific models revealed no difference in energy storage capacity between groups, though energy storage was most sensitive to variations in muscle properties (most significantly operating length and least dependent on tendon stiffness). We conclude that the gastrocnemius elastic system in the guinea fowl displays little to no plastic response to decreased demand during growth and hypothesize that neural plasticity may explain performance variation.

Methods

Experimental Protocol

Animals. To study these questions, one-day-old guinea fowl keets (Numida meleagris) were obtained from a regional breeder (Guinea Farm; New Vienna, IA).  After a 2-wk brooding period, the keets were pen reared through skeletal maturity (>6 months) in one of two conditions, as we previously described in detail (Cox et al 2020).  A control group (C; n =8) was housed in a large, circular pen (3.14 m2) that allowed ample room for locomotion and objects for jumping and perching. The restricted treatment group (R; n = 7) were raised in a smaller pen (1 m2 at maturity) with low mesh ceilings that prevented jumping. Food and water were available ad libitum (food intake did not differ between groups). Lights were programmed to be on a 12:12-h light-dark cycle.  This protocol resulted in no changes in time spent walking or standing between groups, but drastically altered the average number of jumps per day.  The control group jumped twice their body height, on average, 194 times a day while the restricted birds were restricted from jumping entirely [43]. The experimental protocol was approved by Institutional Animal Care and Use Committee at The Pennsylvania State University (IACUC; Ref. #46435)

Functional Measures 

As described previously [39], at skeletal maturity (between 29 and 31 weeks old) jump performance was measured by placing each bird in turn on 6x6 in. force plates (AMTI HE6x6; Watertown, MA, USA) enclosed in a tapered box and encouraging the birds to jump.  Jump power was calculated from the instantaneous net vertical ground reaction and the vertical center of mass velocity. The horizontal component of GRF was ignored since the experimental setup constrained jumps to be nearly vertical.  Velocity was obtained by integrating the center of mass acceleration, which was in turn found from the net ground reaction force and the body mass.  We calculated jump work by integrating the instantaneous power with respect to time over the course of the jump.  At the end of functional data collection, birds were euthanized (intravenous pentobarbital, >160 mg/kg).

Quantification of properties of individual components of the elastic system

Specimen muscle architecture preparation. The pelvic limb was separated from the upper body and the left and right legs were then split by sectioning the pelvis at the midline while avoiding muscle attachments. Right limbs were placed into neutral buffered formalin for fixation (10%) for at least two weeks, while left legs were fresh-frozen and kept at -20 °C. Right limbs were positioned with joint angles approximating those at mid-swing during running (hip: 30°, knee: 80°, ankle: 125°, within ±2° [44]). Joint angles were confirmed for the fixed limbs using photographs made with a digital camera (Canon EOS550D; Surrey, United Kingdom) and analyzed with ImageJ (National Institutes of Health, Betesda, MD).

Muscle Analyses. We made measurements of the lateral and medial heads of the gastrocnemius muscle (LG and MG), the muscle group of the MTU thought primarily responsible for storage and release of elastic strain energy during running and jumping [32,37]. The third (intermedia) head of the gastrocnemius only comprises ~10% of the total mass of the gastrocnemius muscles in this species [45] and thus was not included in the analysis.  MG and LG were dissected from the fresh-frozen left limbs and weighed to the nearest 0.1 milligram.  The LG and MG were then dissected from the fixed limbs for fascicle length, pennation angle, and sarcomere analysis. LG was first split longitudinally through the mid-belly to view fascicle arrangement. Photographs of whole MG and split LG made with a digital camera (Cannon EOS550D with Canon EFS 18-55 and 10X lens) were imported into ImageJ for measurement of the pennation angle between muscle fascicles and their insertions on the aponeurosis [46].

Due to the expected within-muscle heterogeneity of strain [47,48], each muscle was divided into sections for analysis. MG was split into anterior and posterior fascicles [49] and then again split proximally/distally, resulting in four sections. The LG was split into proximal, middle, and distal sections, each spanning one-third the length of the muscle belly. Average pennation angle was found for each section by taking the mean of three angle measurements.  Sarcomere lengths for each section were found using the laser diffraction techniques described in [46]. A minimum of three sarcomere length measurements were taken from each muscle fascicle bundle and these measurements were averaged to obtain the mean measured sarcomere length.

Optimal fascicle length, LO, was calculated by multiplying the length of the fascicle by the ratio of optimal sarcomere length of guinea fowl muscle (2.36 μm; [49]) to the mean measured sarcomere length.

Pennation angle at optimal fascicle length, θOFL , was calculated from the average measured pennation angle, θ  , and the ratio of measure fiber length, Fl, and calculated optimal fascicle length, LO according to the equation [50]:

 

θOFL= sin-1FlsinθLO

(1)

Maximum isometric force along the muscle fiber for the MG and LG was approximated from the muscle mass, m, optimal fascicle length, LO and muscle density (ρmusc = 1060 kg/m3 [51] using the specific tension, f (3 x 105 N/m2, Rospars and Meyer-Vernet, 2016), according to the equation:

 

Fmax= f*mρmusc L0

(2)

We specifically calculated isometric force along the muscle fiber for input into the musculoskeletal model rather than including the influence of pennation angle because pennation angle is a separate input into the OpenSim Millard muscle model (see below for model description), which accounts for the change in pennation angle with muscle length  [53].

Moment Arm. Gastrocnemius moment arm at the ankle was experimentally measured using the tendon travel method [54,55] as described by Salzano[56][56].  The gastrocnemius moment arm at the ankle was experimentally measured using the tendon travel method as described by Salzano [56]. In short, the Achilles tendon (which attaches only to the LG, MG and IG in guinea fowl) was attached to a linear transducer (Model P510-2-S11-N0S-10C, UniMeasure, Inc., Corvallis, OR) to measure excursion and kept at a constant 10N tension to prevent changes in tendon strain (Figure 1). Retroreflective markers were placed on dissected limbs to track the relative movement of the tibia and tarsometatarsus in 3D across a range of joint angles using a 4-camera Motion Analysis system (300 Hz; Kestrel, Motion Analysis Corporation, Santa Rosa, CA), and automatically synchronized to the linear transducer data within the motion analysis software (Cortex , Motion Analysis Corporation). Joint centres and a mean helical axis were calculated from motion data for

Graphical user interface, application

Description automatically generated Figure 1: Setup for the tendon travel experiment. The limb was positioned so that the tibiotarsus was held firm by a 3D printed clamp. In the knee joint motion trial, the femur was rotated to move the knee through its ROM. The tibiotarsus was then cut to remove the proximal portion of the limb, allowing for LVDT to be attached to the Achilles tendon. For tendon travel trials, the TMT was rotated to move the ankle through its ROM. Gray coloring represents retroreflective markers on the limb and LVDT. The dotted line outlines the pelvis femur, and knee, which were removed after the knee joint motion trial. The dashed line represents location at which the tibiotarsus was cut after the knee joint motion trial. Figure adapted from Salzano, 2020 [56].

each trial and used to calculate flexion angle at the ankle at each timepoint [57].  A cubic spline was fit to the tendon excursion versus flexion angle points using least-squares approximation and tendon excursion was differentiated with respect to angle to estimate moment arm across the measured range of motion (30°-90°). Average values are reported in Table 1.

Tendon force-length curves. We quantified the tendon force-length properties with material analysis as described in [26]. In short, tendons were detached from the gastrocnemius muscles but left attached at their insertion points on the tarsometatarsus bone.  Both the bone and the tendon’s proximal end were connected to a material testing machine (858 Mini Bionix II; MTS Systems Corp; Eden Prairie, MN, United States). Samples were mounted vertically using custom clamps on the tendon aponeurosis and the TMT and attached to a 50-pound load cell (MTS Systems Corp; Eden Prairie, MN, United States). The upper clamp gripped the entire aponeurosis of each sample, leaving only the free tendon exposed to loading.  The tendon force-length properties were quantified by loading the tendon cyclically (20 cycles) to 4% strain.  The tendon force-length curves were calculated by averaging the data from last 5 cycles of the loading protocol. Tendon force-strain curves were calculated by normalizing displacement by the length of the tendon, TL, measured to the nearest 0.1 mm with calipers while under zero force in the material testing setup.  Average values for tendon stiffness given in Table 1 were calculated from the slope of the tendon force-length curve across the last 50 points measured in the last 5 cycles of trials, at strain between 3 and 5%.

Tendon Slack Length. The tendon slack lengths for the LG and MG were estimated from experimental measures as described in Appendix A.  Because model based estimates of muscle fiber length in a given posture are particularly sensitive to the tendon slack length [58–60] and our calculations involved several simplifying assumptions, we further refined our experimental estimates of tendon slack length by fine-adjusting the tendon slack length parameter in the OpenSim model (see Appendix A for experimental tendon slack length measurement and see below and Appendix B for model development). After experimental moment arms and tendon and muscle properties were added to subject specific models, each model was posed in the individual’s fixed posture. The model’s tendon slack length was adjusted iteratively in the model until the LG and MG normalized fiber lengths were within 1% of the experimentally measured values. These final values are listed in Table 2.

Usage Notes

The four CSV files and the one matlab data file 'Vo2JumpData91417.mat' are read into the the files 'Code2MakeFigure.m' and the two R scripts 'RCode4FigureAndStats.rmd' and 'SixMonthMorphPaperV4.rmd.'  A ReadMe file describes all variables used in the csv and matlab files.

Funding

National Institutes of Health, Award: R21AR071588