Biology subjects

Konno, R. N.

Publications and source records attributed to Konno, R. N..

4 recordsLinked to original sources

bioRxiv2026

A time-dependent mechano-bioenergetics model of muscle contraction

Predictions of skeletal muscle energy consumption under a diverse range of muscle contractile conditions are critical for improving our understanding of locomotion. Existing mathematical models, while capturing the mechanical dependence of energy consuming processes, neglect the time-dependent behaviour and recovery costs associated with regenerating ATP. This time-dependence is important for predicting the energetic response of muscles during repetitive or cyclical tasks like locomotion, where muscle undergoes many contraction cycles. This study presents a novel model to predict energetic rates based on physiological processes: Ca2+ transport costs, cross-bridge cycling costs, and ATP regeneration. Previous mathematical models include the dependence on Ca2+ transport and cross-bridge cycling, but neglect the time-dependent response and the subsequent recovery of ATP following the contraction. Model parameters were obtained from existing data on isolated muscle preparations, and predicted energetic rates were validated on separate datasets across a range of contractile conditions including dynamic, sub-maximal, and twitch contractions. The time-dependent model was able to capture the influence of contraction frequency on peak energetic rates and the time-course of energetic recovery observed experimentally. The model captures key physiological processes while maintaining a minimal number of free parameters and low computational cost. This enables generalis-ability across muscles and species, and implementation into larger scale musculoskeletal models.

physiology↗

bioRxiv2025

The impact of mechanical requirements on the neural control of skeletal muscle and subsequent energetic rates

1The energetic cost of skeletal muscle contraction is a fundamental driver in the selection of locomotor strategies. Muscle energy consumption depends on muscle-fibre typology, neural drive, and mechanical state. While the influence of fibre-type and mechanical state on energy use has been extensively characterised in isolated muscle preparations, these experiments fail to capture the influence of realistic in vivo motor unit recruitment strategies. Hence, this study aims to capture neural drive in the tibialis anterior, in particular motor unit recruitment thresholds and rate coding, and the corresponding changes in energy use across a range of mechanical demands. Fixed ankle angle dorsiflexion contractions were performed at varying rates of torque development, while high density electromyography characterized motor unit spiking activity, B-mode ultrasound captured muscle fascicle dynamics, and indirect calorimetry measured energetic rates. Faster rates of torque development required earlier recruitment of motor units with increased motor unit firing rates which coincided with increased fascicle strain rates. At higher rates of torque development, these altered motor unit discharge patterns and muscle mechanics coincided with increased muscle energy use. Together, these findings highlight that in vivo muscle energetics emerge from the dynamic interplay between neural control and mechanical demands.

physiology↗

bioRxiv2024

Using physiologically-based models to predict in vivo skeletal muscle energetics

Understanding how muscles use energy is essential for elucidating the role of skeletal muscle in animal locomotion. Yet, experimental measures of in vivo muscle energetics are challenging to obtain, so physiologically-based muscle models are often used to estimate energy use. These predictions of individual muscle energy expenditure are not often compared to indirect whole body measures of energetic cost. Here, we examined and illustrated the capability of physiologically-based muscle models to predict in vivo measures of energy use. To improve model predictions and ensure a physiological basis for model parameters, we refined our model to include data from isolated muscle experiments. Simulations were performed to capture three different experimental protocols, which involved varying contraction frequency, duty cycle, and muscle fascicle length. Our results demonstrated that these models are able capture the general features of whole body energetics across contractile conditions, but tended to under predict the magnitude of energetic cost. Our analysis revealed that when predicting in vivo energetic rates across contractile conditions, the model was most sensitive to the force-velocity parameters and the data informing the energetic rates when predicting in vivo energetic rates across contractile conditions. This work highlights it is the mechanics of skeletal muscle contraction that govern muscle energy use.

bioengineering↗

bioRxiv2021

The contributions of extracellular matrix and sarcomere properties to passive muscle stiffness in cerebral palsy

Cerebral palsy results from an upper motor neuron lesion and has significant effects on skeletal muscle stiffness throughout the body. The increased stiffness that occurs is partly a result of changes in the microstructural components of muscle. In particular, alterations in extracellular matrix, sarcomere length, fibre diameter, and fat content have been reported; however, experimental studies have shown wide variability in the degree to which each component is altered. Many studies have reported alterations in the extracellular matrix, while others have reported no changes. A consistent finding throughout the literature is increased sarcomere length in cerebral palsy muscle. Often more than one component is altered, making it difficult to determine the individual effects on stiffness. The purpose of this study is to use a modeling approach to isolate individual effects of microstructural alterations that typically occur during cerebral palsy on whole muscle behavior; in particular, the extracellular matrix volume fraction, stiffness, and sarcomere length. These microstructural effects can be captured using a three dimensional model of muscle. We found that the extracellular matrix volume fraction has a larger effect on stiffness compared to sarcomere length, even when coupled with decreased extracellular matrix stiffness. Additionally, the effects of sarcomere length in passive stiffness are mitigated by the increased extracellular matrix volume fraction. Using this model, we can achieve a better understanding of the possible combinations of microstructural changes that can occur during cerebral palsy. Developing these insights into diseased muscle tissue will help to direct future clinical and experimental procedures.

physiology↗