Particle retracking algorithm capable of quantifying large, local matrix deformation for traction force microscopy

Haarman, Samuel E.; Kim, Sue Y.; Isogai, Tadamoto; Dean, Kevin M.; Han, Sangyoon J.

doi:10.1371/journal.pone.0268614

Cited by 4 publications

(1 citation statement)

References 29 publications

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“…The subpixel correlation via image interpolation method was used for individual bead tracking for correction of bead tracking and removal of outliers before traction estimation. For bead images of challenging displacement field, we used our PTVR (particle tracking velocimetry with re-tracking) method to rescue potentially missed displacement vectors (55). Boussiness equation assuming infinite gel thickness was used for solving the force field (defined as the expected deformation of the gel with all the bead locations applied with unit force at a particular force grid mesh).…”

Section: Live-cell Imaging Traction Reconstruction and Analysismentioning

confidence: 99%

Low Shear in Short-Term Impacts Endothelial Cell Traction and Alignment in Long-Term

Chandurkar,

Mittal,

Royer-Weeden

et al. 2023

Preprint

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Fluid shear stress (FSS) plays a vital role in endothelial cell (EC) function, impacting vascular health. Low FSS triggers an inflammatory, atheroprone EC phenotype, while high FSS promotes atheroprotective responses. Yet, the adaptation of ECs to high FSS following low FSS exposure remains poorly understood. We explored this process's influence on vascular tension by measuring traction in human umbilical vein endothelial cells (HUVECs) subjected to high FSS (1 Pa) after prior low FSS exposure (0.1 Pa). We discovered that HUVECs experienced an immediate traction increase after low FSS exposure. Intriguingly, the transition to high FSS did not further enhance traction; instead, a secondary traction rise emerged after 2 hours under high FSS, lasting over 10 hours before gradually diminishing. Conversely, HUVECs exposed directly to high FSS displayed an initial traction surge within 30 minutes, followed by a rapid decline within an hour, falling below initial levels. Notably, even after more than 20 hours of exposure to high FSS, HUVECs previously preconditioned with 1-hour of low FSS exhibited traction alignment perpendicular to the flow direction, whereas those directly exposed to high FSS displayed alignment with the flow direction, both in the short and long terms. Collectively, these results suggest that even brief exposure to low FSS can initiate a low-shear-sensitive response in ECs, which requires a much-extended period to recover towards tension relaxation under laminar high shear flow conditions.

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Section: Live-cell Imaging Traction Reconstruction and Analysismentioning

confidence: 99%

Low Shear in Short-Term Impacts Endothelial Cell Traction and Alignment in Long-Term

Chandurkar,

Mittal,

Royer-Weeden

et al. 2023

Preprint

Self Cite

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Establishment and application of TSDPSO-SVM model combined with multi-dimensional feature fusion method in the identification of fracture-related infection

Hu,

Chen,

Zheng

et al. 2023

Sci Rep

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Fracture-related infection (FRI) is one of the most common and intractable complications in orthopedic trauma surgery. This complication can impose severe psychological burdens and socio-economic impacts on patients. Although the definition of FRI has been proposed recently by an expert group, the diagnostic criteria for FRI are not yet standardized. A total of 4761 FRI patients and 4761 fracture patients (Non-FRI) were included in the study. The feature set of patients included imaging characteristics, demographic information, clinical symptoms, microbiological findings, and serum inflammatory markers, which were reduced by the Principal Component Analysis. To optimize the Support Vector Machine (SVM) model, the Traction Switching Delay Particle Swarm Optimization (TSDPSO) algorithm, a recognition method was proposed. Moreover, five machine learning models, including TSDPSO-SVM, were employed to distinguish FRI from Non-FRI. The Area under the Curve of TSDPSO-SVM was 0.91, at least 5% higher than that of other models. Compared with the Random Forest, Backpropagation Neural Network (BP), SVM and eXtreme Gradient Boosting (XGBoost), TSDPSO-SVM demonstrated remarkable accuracy in the test set ($$\chi^{ 2} = 29.17, \,50.46, \,56.66,\,35.88, P < 0.01$$ χ 2 = 29.17 , 50.46 , 56.66 , 35.88 , P < 0.01 ). The recall of TSDPSO-SVM was 98.32%, indicating a significant improvement ($$\chi^{2} = 91.78,\, 107.42, \,135.69, P < 0.01$$ χ 2 = 91.78 , 107.42 , 135.69 , P < 0.01 ). Compared with BP and SVM, TSDPSO-SVM exhibited significantly superior specificity, false positive rate and precision ($$\chi^{2} > 3.84, P < 0.05)$$ χ 2 > 3.84 , P < 0.05 ) . The five models yielded consistent results in the training and testing of FRI patients across different age groups. TSDPSO-SVM is validated to have the maximum overall prediction ability and can effectively distinguish between FRI and Non-FRI. For the early diagnosis of FRI, TSDPSO-SVM may provide a reference basis for clinicians, especially those with insufficient experience. These results also lay a foundation for the intelligent diagnosis of FRI. Furthermore, these findings exhibit the application potential of this model in the diagnosis and classification of other diseases.

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Myosin-independent stiffness sensing by fibroblasts is regulated by the viscoelasticity of flowing actin

Mittal,

Michels,

Massey

et al. 2024

Commun Mater

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The stiffness of the extracellular matrix induces differential tension within integrin-based adhesions, triggering differential mechanoresponses. However, it has been unclear if the stiffness-dependent differential tension is induced solely by myosin activity. Here, we report that in the absence of myosin contractility, 3T3 fibroblasts still transmit stiffness-dependent differential levels of traction. This myosin-independent differential traction is regulated by polymerizing actin assisted by actin nucleators Arp2/3 and formin where formin has a stronger contribution than Arp2/3 to both traction and actin flow. Intriguingly, despite only slight changes in F-actin flow speed observed in cells with the combined inhibition of Arp2/3 and myosin compared to cells with sole myosin inhibition, they show a 4-times reduction in traction than cells with myosin-only inhibition. Our analyses indicate that traditional models based on rigid F-actin are inadequate for capturing such dramatic force reduction with similar actin flow. Instead, incorporating the F-actin network’s viscoelastic properties is crucial. Our new model including the F-actin viscoelasticity reveals that Arp2/3 and formin enhance stiffness sensitivity by mechanically reinforcing the F-actin network, thereby facilitating more effective transmission of flow-induced forces. This model is validated by cell stiffness measurement with atomic force microscopy and experimental observation of model-predicted stiffness-dependent actin flow fluctuation.

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Particle retracking algorithm capable of quantifying large, local matrix deformation for traction force microscopy

Cited by 4 publications

References 29 publications

Low Shear in Short-Term Impacts Endothelial Cell Traction and Alignment in Long-Term

Low Shear in Short-Term Impacts Endothelial Cell Traction and Alignment in Long-Term

Establishment and application of TSDPSO-SVM model combined with multi-dimensional feature fusion method in the identification of fracture-related infection

Myosin-independent stiffness sensing by fibroblasts is regulated by the viscoelasticity of flowing actin

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