Biology subjects

Pinette, M.

Publications and source records attributed to Pinette, M..

5 recordsLinked to original sources

bioRxiv2025

Big Bones Mean Big Muscles: AI Quantifies 71 Individual Muscles Across the Whole Body, Revealing Widespread Links Between Muscle, Bone, and Body Size

Body sizes and shapes vary widely, even among healthy adults, resulting in diverse muscle sizes, strengths, and performance capacities. This study developed a novel AI-driven algorithm to segment and analyze individual muscles and bones from whole-body MRI. Validated via inter- and intra-observer analyses, the algorithm created 3D segmentations of 71 muscles and 13 bones across the upper limbs, trunk, and lower limbs in 48 healthy adults (24 males, 24 females) aged 18-49 years. Muscle volume, asymmetry, length, and fat fraction were quantified. While asymmetry and fat fraction varied across muscles, they did not differ significantly between sexes. Total muscle volume was the strongest predictor of individual muscle volume, followed by bone volume, which correlated with muscle size at whole-body, regional, and individual levels. Muscle-to-body size relationships (e.g., mass, height, BMI) differed between sexes, while bone-to-body size relationships did not. These findings suggest that skeletal size ("frame size") is a key determinant of muscularity. This study provides the most comprehensive in vivo dataset of human skeletal muscle to date, offering a multi-factorial explanation for variation in muscularity and benchmarks for applications ranging from athletic performance to clinical assessments in muscle disorders. SUMMARYUnderstanding how muscle size varies across the body and what influences these differences is key to advancing both health and performance. This study uses cutting-edge AI to analyze individual muscles across the whole body from MRI scans, creating the most detailed dataset of human muscle and bone relationships to date. The findings reveal how skeletal size ("frame size") and body dimensions shape muscularity, providing new insights into why people differ in muscle size and strength. These results have broad implications, from optimizing athletic training to diagnosing and treating muscle disorders. By uncovering the intricate connections between muscles, bones, and body size, this research offers a powerful framework for understanding human movement and variability.

bioengineering↗

bioRxiv2025

Multi-scale machine learning model predicts muscle and functional disease progression in FSHD

Facioscapulohumeral muscular dystrophy (FSHD) is a genetic neuromuscular disorder characterized by progressive muscle degeneration with substantial variability in severity and progression patterns. FSHD is a highly heterogeneous disease; however, current clinical metrics used tracking disease progression lack sensitivity for personalized assessment, which greatly limits the design and execution of clinical trials. This study introduces a multi-scale machine learning framework leveraging whole-body magnetic resonance imaging (MRI) and clinical data to predict regional, muscle, joint, and functional progression in FSHD. The goal this work is to create a digital twin of individual FSHD patients that can be leveraged in clinical trials. Using a combined dataset of over 100 patients from seven studies, MRI-derived metrics--including fat fraction, lean muscle volume, and fat spatial heterogeneity at baseline--were integrated with clinical and functional measures. A three-stage random forest model was developed to predict annualized changes in muscle composition and a functional outcome (timed up-and-go (TUG)). All model stages revealed strong predictive performance in separate holdout datasets. After training, the models predicted fat fraction change with a root mean square error (RMSE) of 2.16% and lean volume change with a RMSE of 8.1ml in a holdout testing dataset. Feature analysis revealed that metrics fat heterogeneity within muscle predicts muscle-level progression. The stage 3 model that combined functional muscle groups and predicted change in TUG with a RMSE of 0.6 seconds, in the holdout testing dataset. This study demonstrates the machine learning models incorporating individual muscle and performance data can effectively predict MRI disease progression and functional performance of complex tasks, addressing the heterogeneity and nonlinearity inherent in FSHD. Further studies incorporating larger longitudinal cohorts as well as comprehensive clinical and functional measures will allow for expanding and refining this model. As many neuromuscular diseases are characterized by varability and heterogeneity similar to FSHD, such approaches have broad applicability.

bioengineering↗

bioRxiv2023

Distinguishing host responses, extensive viral dissemination and long-term viral RNA persistence in domestic sheep experimentally infected with Crimean-Congo hemorrhagic fever virus Kosovo Hoti

Crimean-Congo hemorrhagic fever orthonairovirus (CCHFV) is a tick-borne, biosafety level 4 pathogen that often causes a severe hemorrhagic disease in humans (CCHF) with high case fatality rates. The virus is believed to be maintained in a tick-vertebrate-tick ecological cycle involving numerous wild and domestic animal species, however the biology of CCHFV infection in these animals remains poorly understood. Here, we challenge domestic sheep with CCHFV Kosovo Hoti, a highly pathogenic clinical isolate increasingly utilized in current research. In the absence of prominent clinical signs, the infection leads to an acute viremia and coinciding viral shedding, high fever and markers for potential impairment in liver and kidney functions. A number of host responses distinguish the subclinical infection in sheep versus fatal infection in humans. These include an early reduction of neutrophil recruitment and its chemoattractant, IL-8, in the blood stream of infected sheep, whereas neutrophil infiltration and elevated IL-8 are features of fatal CCHFV infections reported in immunodeficient mice and humans. Several inflammatory cytokines that correlate with poor disease outcomes in humans and have potential to cause vascular dysfunction, a primary hallmark of severe CCHF, are down-regulated or restricted from increasing in sheep. Of particular interest, the detection of CCHFV RNA in a variety of sheep tissues long after the acute phase of infection indicates a widespread viral dissemination in the host and suggests a potentially long-term persisting impact of CCHFV infection. Consistent with this, antibody responses exhibit features reminiscent of recurring antigenic boost, and a prolonged fever or late fever spike correlates with high levels of viral RNA persistence. These findings reveal previously unrecognized aspects of CCHFV biology in animals and highlight the need for extended experimental infection studies. Author summaryCrimean-Congo hemorrhagic fever orthonairovirus (CCHFV) is a tick-borne virus with potential to cause a fatal hemorrhagic disease in humans. Many wild and domestic animals such as sheep are believed to serve as intermediate hosts that amplify and transmit the virus without developing overt disease. However, the biology of CCHFV infection in animals remains to be better understood through new experimental infection research. Here, we characterize the infection of sheep with a highly pathogenic (to humans) CCHFV clinical isolate. This work confirms early studies indicating that CCHFV infection in animals does not lead to prominent signs of disease despite a short period of viral accumulation in the blood. Importantly, we identify host responses that distinguish the lack of disease in sheep versus the fatal disease in humans. Sheep are able to restrict several immune factors that potentially play a damaging role toward poor disease outcomes. Furthermore, we provide pioneering findings of widespread CCHFV dissemination and persistent presence of CCHFV genetic material in tissues of animal hosts that do not develop major disease. These new data are anticipated to inform medical countermeasure development and guide public health measures, with considerations of potential long-term impact of CCHFV on human and animal health.

microbiology↗

bioRxiv2022

Highly divergent white-tailed deer SARS-CoV-2 with potential deer-to-human transmission

Wildlife reservoirs of SARS-CoV-2 may enable viral adaptation and spillback from animals to humans. In North America, there is evidence of unsustained spillover of SARS-CoV-2 from humans to white-tailed deer (Odocoileus virginianus), but no evidence of transmission from deer to humans. Through a biosurveillance program in Ontario, Canada we identified a new and highly divergent lineage of SARS-CoV-2 in white-tailed deer. This lineage is the most divergent SARS-CoV-2 lineage identified to date, with 76 consensus mutations (including 37 previously associated with non-human animal hosts) and signatures of considerable evolution and transmission within wildlife. Phylogenetic analysis also revealed an epidemiologically linked human case. Together, our findings represent the first clear evidence of sustained evolution of SARS-CoV-2 in white-tailed deer and of deer-to-human transmission.

microbiology↗

bioRxiv2020

Susceptibility of domestic swine to experimental infection with SARS-CoV-2

SARS-CoV-2, the agent responsible for COVID-19 has been shown to infect a number of species. The role of domestic livestock and the risk associated for humans in close contact remains unknown for many production animals. Determination of the susceptibility of pigs to SARS-CoV-2 is critical towards a One Health approach to manage the potential risk of zoonotic transmission. Here, pigs undergoing experimental inoculation are susceptible to SARS-CoV-2 at low levels. Viral RNA was detected in group oral fluids and nasal wash from at least two animals while live virus was isolated from a pig. Further, antibodies could be detected in two animals at 11 and 13 days post infection, while oral fluid samples at 6 days post inoculation indicated the presence of secreted antibodies. These data highlight the need for additional livestock assessment to better determine the potential role domestic animals may contribute towards the SARS-CoV-2 pandemic.

microbiology↗