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Silvestros P, Athwal GS, Giles JW. Scapular morphology variation affects reverse total shoulder arthroplasty biomechanics. A predictive simulation study using statistical and musculoskeletal shoulder models. J Orthop Res 2024. [PMID: 38341683 DOI: 10.1002/jor.25801] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Revised: 09/11/2023] [Accepted: 01/20/2024] [Indexed: 02/13/2024]
Abstract
Reverse total shoulder arthroplasty (RTSA) accounts for over half of shoulder replacement surgeries. At present, the optimal position of RTSA components is unknown. Previous biomechanical studies have investigated the effect of construct placement to quantify mobility, stability and functionality postoperatively. While studies have provided valuable information on construct design and surgical placement, they have not systematically evaluated the importance of scapular morphology on biomechanical outcomes. The aim of this study was to assess the influence of scapular morphology variation on RTSA biomechanics using statistical models, musculoskeletal modeling and predictive simulation. The scapular geometry of a musculoskeletal model was altered across six modes of variation at four levels (±1 and ±3 SD) from a clinically derived statistical shape model. For each model, a standardized virtual surgery was performed to place RTSA components in the same relative position on each model then implemented in 50 predictive simulations of upward and lateral reaching tasks. Results showed morphology affected functional changes in the deltoid moment arms and recruitment for the two tasks. Variation of the anatomy that reduced the efficiency of the deltoids showed increased levels of muscle force production, joint load magnitude and shear. These findings suggest that scapular morphology plays an important role in postoperative biomechanical function of the shoulder with an implanted RTSA. Furthermore a "one-size-fits-all" approach for construct surgical placement may lead to suboptimal patient outcomes across a clinical population. Patient glenoid as well as scapular anatomy may need to be carefully considered when planning RTSA to optimize postoperative success.
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Affiliation(s)
- Pavlos Silvestros
- Department of Mechanical Engineering, University of Victoria, Victoria, British Columbia, Canada
| | - George S Athwal
- Division of Shoulder and Elbow Surgery, Department of Orthopaedic Surgery, Roth/McFarlane Hand and Upper Limb Centre, London, Ontario, Canada
| | - Joshua W Giles
- Department of Mechanical Engineering, University of Victoria, Victoria, British Columbia, Canada
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Veerkamp K, Carty CP, Waterval NFJ, Geijtenbeek T, Buizer AI, Lloyd DG, Harlaar J, van der Krogt MM. Predicting Gait Patterns of Children With Spasticity by Simulating Hyperreflexia. J Appl Biomech 2023; 39:334-346. [PMID: 37532263 DOI: 10.1123/jab.2023-0022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Revised: 06/24/2023] [Accepted: 06/24/2023] [Indexed: 08/04/2023]
Abstract
Spasticity is a common impairment within pediatric neuromusculoskeletal disorders. How spasticity contributes to gait deviations is important for treatment selection. Our aim was to evaluate the pathophysiological mechanisms underlying gait deviations seen in children with spasticity, using predictive simulations. A cluster analysis was performed to extract distinct gait patterns from experimental gait data of 17 children with spasticity to be used as comparative validation data. A forward dynamic simulation framework was employed to predict gait with either velocity- or force-based hyperreflexia. This framework entailed a generic musculoskeletal model controlled by reflexes and supraspinal drive, governed by a multiobjective cost function. Hyperreflexia values were optimized to enable the simulated gait to best match experimental gait patterns. Three experimental gait patterns were extracted: (1) increased knee flexion, (2) increased ankle plantar flexion, and (3) increased knee flexion and ankle plantar flexion when compared with typical gait. Overall, velocity-based hyperreflexia outperformed force-based hyperreflexia. The first gait pattern could mostly be explained by rectus femoris and hamstrings velocity-based hyperreflexia, the second by gastrocnemius velocity-based hyperreflexia, and the third by gastrocnemius, soleus, and hamstrings velocity-based hyperreflexia. This study shows how velocity-based hyperreflexia from specific muscles contributes to different spastic gait patterns, which may help in providing targeted treatment.
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Affiliation(s)
- Kirsten Veerkamp
- Department of Rehabilitation Medicine, Amsterdam UMC location Vrije Universiteit Amsterdam, Amsterdam,The Netherlands
- Rehabilitation & Development, Amsterdam Movement Sciences, Amsterdam,The Netherlands
- School of Health Sciences and Social Work, Griffith University, Gold Coast, QLD,Australia
- Griffith Centre of Biomedical & Rehabilitation Engineering (GCORE), Menzies Health Institute Queensland, Griffith University, Gold Coast, QLD,Australia
- Advanced Design and Prototyping Technologies Institute (ADAPT), Griffith University, Gold Coast, QLD,Australia
| | - Christopher P Carty
- School of Health Sciences and Social Work, Griffith University, Gold Coast, QLD,Australia
- Griffith Centre of Biomedical & Rehabilitation Engineering (GCORE), Menzies Health Institute Queensland, Griffith University, Gold Coast, QLD,Australia
- Advanced Design and Prototyping Technologies Institute (ADAPT), Griffith University, Gold Coast, QLD,Australia
- Department of Orthopaedics, Children's Health Queensland Hospital and Health Service, Queensland Children's Hospital, Brisbane, QLD,Australia
| | - Niels F J Waterval
- Department of Rehabilitation Medicine, Amsterdam UMC location Vrije Universiteit Amsterdam, Amsterdam,The Netherlands
- Rehabilitation & Development, Amsterdam Movement Sciences, Amsterdam,The Netherlands
- Department of Rehabilitation Medicine, Amsterdam UMC location University of Amsterdam, Amsterdam,The Netherlands
| | - Thomas Geijtenbeek
- Department of Biomechanical Engineering, Delft University of Technology, Delft,The Netherlands
| | - Annemieke I Buizer
- Department of Rehabilitation Medicine, Amsterdam UMC location Vrije Universiteit Amsterdam, Amsterdam,The Netherlands
- Rehabilitation & Development, Amsterdam Movement Sciences, Amsterdam,The Netherlands
- Emma Children's Hospital, Amsterdam UMC, University of Amsterdam, Amsterdam,The Netherlands
| | - David G Lloyd
- School of Health Sciences and Social Work, Griffith University, Gold Coast, QLD,Australia
- Griffith Centre of Biomedical & Rehabilitation Engineering (GCORE), Menzies Health Institute Queensland, Griffith University, Gold Coast, QLD,Australia
- Advanced Design and Prototyping Technologies Institute (ADAPT), Griffith University, Gold Coast, QLD,Australia
| | - Jaap Harlaar
- Department of Biomechanical Engineering, Delft University of Technology, Delft,The Netherlands
- Department of Orthopedics and Sports Medicine, Erasmus Medical Center, Rotterdam,The Netherlands
| | - Marjolein M van der Krogt
- Department of Rehabilitation Medicine, Amsterdam UMC location Vrije Universiteit Amsterdam, Amsterdam,The Netherlands
- Rehabilitation & Development, Amsterdam Movement Sciences, Amsterdam,The Netherlands
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Abstract
In statistical phylogenetic analyses of DNA sequences, models of evolutionary change commonly assume that base composition is stationary through time and across lineages. This assumption is violated by many data sets, but it is unclear whether the magnitude of these violations is sufficient to mislead phylogenetic inference. We investigated the impacts of compositional heterogeneity on phylogenetic estimates using a method for assessing model adequacy. Based on a detailed simulation study, we found that common frequentist criteria are highly conservative, such that the model is often rejected when the phylogenetic estimates do not show clear signs of bias. We propose new criteria and provide guidelines for their usage. We apply these criteria to genome-scale data from 40 birds and find that loci with severely non-homogeneous base composition are uncommon. Our results show the importance of using well-informed diagnostic statistics when testing model adequacy for phylogenomic analyses.
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Affiliation(s)
- David A Duchêne
- School of Life and Environmental Sciences, University of Sydney, Sydney, NSW, Australia
| | - Sebastian Duchêne
- Centre for Systems Genomics, University of Melbourne, Melbourne, VIC, Australia
| | - Simon Y W Ho
- School of Life and Environmental Sciences, University of Sydney, Sydney, NSW, Australia
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Anyan ME, Amiri A, Harvey CW, Tierra G, Morales-Soto N, Driscoll CM, Alber MS, Shrout JD. Type IV pili interactions promote intercellular association and moderate swarming of Pseudomonas aeruginosa. Proc Natl Acad Sci U S A 2014; 111:18013-8. [PMID: 25468980 PMCID: PMC4273417 DOI: 10.1073/pnas.1414661111] [Citation(s) in RCA: 52] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
Pseudomonas aeruginosa is a ubiquitous bacterium that survives in many environments, including as an acute and chronic pathogen in humans. Substantial evidence shows that P. aeruginosa behavior is affected by its motility, and appendages known as flagella and type IV pili (TFP) are known to confer such motility. The role these appendages play when not facilitating motility or attachment, however, is unclear. Here we discern a passive intercellular role of TFP during flagellar-mediated swarming of P. aeruginosa that does not require TFP extension or retraction. We studied swarming at the cellular level using a combination of laboratory experiments and computational simulations to explain the resultant patterns of cells imaged from in vitro swarms. Namely, we used a computational model to simulate swarming and to probe for individual cell behavior that cannot currently be otherwise measured. Our simulations showed that TFP of swarming P. aeruginosa should be distributed all over the cell and that TFP-TFP interactions between cells should be a dominant mechanism that promotes cell-cell interaction, limits lone cell movement, and slows swarm expansion. This predicted physical mechanism involving TFP was confirmed in vitro using pairwise mixtures of strains with and without TFP where cells without TFP separate from cells with TFP. While TFP slow swarm expansion, we show in vitro that TFP help alter collective motion to avoid toxic compounds such as the antibiotic carbenicillin. Thus, TFP physically affect P. aeruginosa swarming by actively promoting cell-cell association and directional collective motion within motile groups to aid their survival.
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Affiliation(s)
- Morgen E Anyan
- Departments of Civil and Environmental Engineering and Earth Sciences
| | | | | | - Giordano Tierra
- Applied and Computational Mathematics and Statistics, and Mathematical Institute, Charles University, 18675 Prague, Czech Republic; and
| | - Nydia Morales-Soto
- Departments of Civil and Environmental Engineering and Earth Sciences, Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN 46556
| | - Callan M Driscoll
- Departments of Civil and Environmental Engineering and Earth Sciences, Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN 46556
| | - Mark S Alber
- Physics, Applied and Computational Mathematics and Statistics, and Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202
| | - Joshua D Shrout
- Departments of Civil and Environmental Engineering and Earth Sciences, Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN 46556; Biological Sciences, and
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