Quantitative polarization microscopy as a potential tool for quantification of mechanical stresses within 3D matrices
Bibliographic record
Abstract
3D mechanical stresses within tissues/extracellular matrices (ECMs) play a significant role in pathological and physiological processes, making their quantification a necessary step to understand the mechanobiological phenomena. Unfortunately, it is rather challenging to quantify these 3D mechanical stresses due to the highly nonlinear and heterogeneous nature of the fibrous matrix. A number of techniques have been developed to address this challenge, including 3D traction force microscopy (TFM), micropillar devices or microparticle-based force sensors; yet, these techniques come with certain drawbacks. Here, we are presenting quantitative polarization microscopy (QPOL) as a non-invasive and label-free technique to quantify mechanical stresses in 3D matrix without a necessity to assume a matrix material model. Taking collagen as a birefringent material, we demonstrated the correlation between the retardance signals obtained by QPOL and the mechanical parameters associated with the 3D collagen hydrogel, i.e. applied external forces and maximum shear stresses. Using cantilever-collagen systems wherein cantilevers applied external loads on the collagen hydrogel, we showed that the retardance signal within loaded collagen positively correlated with the applied load. Also, the retardance signal values within the collagen hydrogel correlated with the maximum shear stress values derived from computational finite element (FE) models. Finally, we obtained the retardance signals around the spheroids of different contractility levels embedded in collagen hydrogel, and the retardance distribution around the spheroids reflected the stress distribution and applied force. This study provides the framework to use QPOL as a tool for quantification of mechanical stresses within 3D ECM. STATEMENT OF SIGNIFICANCE: Mechanical stresses within the 3D extracellular matrix play an important role during physiological and pathological processes. Quantification of such 3D forces is paramount to our understanding of such phenomena and potentially developing therapeutic interventions based on mechanobiological status of the disease. The existing approaches to quantify these 3D mechanical stresses face certain drawbacks such as high computational cost or introduce discontinuities and alteration within the natural 3D microenvironment of the cells. Here, we provide the framework to use quantitative polarization microscopy (QPOL) as an optical-based, non-invasive and computationally efficient technique to quantify the 3D mechanical stresses within the 3D matrix.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".