Biology subjects

Murtola, T.

Publications and source records attributed to Murtola, T..

5 recordsLinked to original sources

bioRxiv2025

The effect of the number motor units and their maximum firing rate in a musculoskeletal model of human reaching

Vertebrate muscle has two features which heavily influence its force generation characteristics: rate-coded control and the division of muscles into multiple motor units (MUs). Studying how these features affect functional outcomes is difficult in vivo, but also in silico due to scarcity of modelling frameworks integrating rate-coded MU pool models with musculoskeletal models for functional tasks. We implement a human upper limb reaching model with muscles consisting of multiple rate-coded MUs and demonstrate its ability to generate accurate reaching movements under online control. Using this model, we investigate how reaching performance is influenced by two key features of MU pools, the number of MUs and their maximum firing rates. Our simulations suggest that very small MU pools with low firing rates tend to produce less accurate reaching movements compared to larger pools with higher firing rates. Increasing either the size of the pool or the maximum firing rate generally improves performance, but benefits become negligible beyond about 10-20 MUs and firing rates of 25-50 Hz. This pattern holds for the entire workspace but targets on the distal boundaries appear more sensitive to MU pool properties. Hence, our results indicate that rate coding and MU properties may play a part in determining functional outcomes in a task- and MU pool-dependent manner.

bioengineering↗

bioRxiv2025

Visualising joint force-velocity properties in musculoskeletal models

Musculoskeletal modelling opens windows into how muscle properties interact with neural control to govern movement. Though musculoskeletal models produce vast computational data, they lack a visual language which compactly communicates how joint dynamics relate to time-varying muscle activation, force and length change. We developed a novel representation of joint-level force-velocity (joint-FV) properties which shows how agonist and antagonist muscles contribute to overall joint state and its trajectory throughout a movement. Using a model of human goal-directed reaching, we used joint-FV visualisations to discern the salient joint dynamic features across joints and between different reach targets. Regardless of target, we found that the shoulder, elbow and wrist joints traversed a near circular trajectory through joint-FV space when muscle forces were dominant, but trajectories were more complex when joint-interaction forces dominated (i.e. cross-joint forces due to Coriolis, Euler and centrifugal effects). Additionally, we found that co-contraction steepens the instantaneous slope of the instantaneous joint-fv curve causing damping which helps stabilise against small perturbations. We therefore propose that our joint-FV visualisation can be used to explain the intricate features seen in musculoskeletal simulation data to reveal how intrinsic muscle properties govern the behaviour of dynamical systems.

bioengineering↗

bioRxiv2024

Androgen deprivation therapy-resistant club cells are linked to myeloid cell-driven immunosuppression in the prostate tumor microenvironment

Prostate cancer treatment resistance is a significant challenge facing the field. Genomic and transcriptomic profiling have partially elucidated the mechanisms through which cancer cells escape treatment, but their relation toward the tumor microenvironment (TME) remains elusive. Here we present a comprehensive transcriptomic landscape of the prostate TME at multiple points in the standard treatment timeline employing single-cell RNA-sequencing and spatial transcriptomics data from 110 patients. We identify club-like cells as a key epithelial cell subtype that acts as an interface between the prostate and the immune system. Tissue areas enriched with club-like cells have depleted androgen signaling and upregulated expression of luminal progenitor cell markers. Club-like cells display a senescence-associated secretory phenotype and their presence is linked to increased polymorphonuclear myeloid-derived suppressor cell (PMN-MDSC) activity. Our results indicate that club-like cells partake in inducing myeloid inflammation previously associated with androgen deprivation therapy resistance, providing a rationale for their therapeutic targeting.

cancer biology↗

bioRxiv2024

Matching dynamically varying forces with multi-motor-unit muscle models: A simulation study

Human muscles exhibit great versatility, not only generating forces for demanding athleticism, but also for fine motor tasks. While standard musculoskeletal models may reproduce this versatility, they often lack multiple motor units (MUs) and rate-coded control. To investigate how these features affect a muscles ability to generate desired force profiles, we performed simulations with nine alternative MU pool models for two cases: 1) a tibialis anterior muscle generating an isometric trapezoidal force profile, and 2) a generic shoulder muscle generating force for a reaching movement whilst undergoing predetermined length changes. We implemented two control strategies, pure feedforward and combined feedforward-feedback, each parameterised using elementary tasks. The results suggest that the characteristics of MU pools have relatively little impact on the pools overall ability to match forces across all tasks, although performances for individual tasks varied. Feedback improved performance for nearly all MU pools and tasks, but the physiologically more relevant MU pool types were more responsive to feedback particularly during reaching. While all MU pool models performed well in the conditions tested, we highlight the need to consider the functional characteristics of the control of rate-coded MU pools given the vast repertoire of dynamic tasks performed by muscles.

physiology↗

bioRxiv2021

Single-cell ATAC and RNA sequencing reveal pre-existing and persistent subpopulations of cells associated with relapse of prostate cancer

Prostate cancer is profoundly heterogeneous and patients would benefit from methods that stratify clinically indolent from more aggressive forms of the disease. We employed single-cell assay for transposase-accessible chromatin (ATAC) and RNA sequencing in models of early treatment response and resistance to enzalutamide. In doing so, we identified pre-existing and treatment-persistent cell subpopulations that possess transcriptional stem-like features and regenerative potential when subjected to treatment. We found distinct chromatin landscapes associated with enzalutamide treatment and resistance that are linked to alternative transcriptional programs. Transcriptional profiles characteristic of persistent stem-like cells were able to stratify the treatment response of patients. Ultimately, we show that defining changes in chromatin and gene expression in single-cell populations from pre-clinical models can reveal hitherto unrecognized molecular predictors of treatment response. This suggests that high analytical resolution of pre-clinical models may powerfully inform clinical decision-making.

cancer biology↗