Real-time and non-invasive measurements of cell mechanical behaviour with optical coherence phase microscopy

Gillies, Donald C.; Gamal, Wesam; Downes, Andrew; Reinwald, Yvonne; Yang, Ying; Haj, Alicia J. El; Bagnaninchi, Pierre O.

doi:10.1016/j.ymeth.2017.10.010

Cited by 5 publications

(3 citation statements)

References 41 publications

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“…8 OCE can be performed through estimating local displacement maps from subsequent acquisitions of a sample under different loads. 54 This displacement estimation is limited by noise in the images, which can be high in dynamic systems due to the inability to perform long exposures or B-scan averaging. Dr. Bagnaninchi's group proposed a framework for enhancing both the image quality and displacement map by motion compensated denoising with the block-matching and 4-D filtering, followed by a re-estimation of displacement.…”

Section: Poster Sessionmentioning

confidence: 99%

Optical elastography and tissue biomechanics

2019

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Mechanical forces play an important role in the behavior and development of biological systems and disease at all spatial scales, from cells and their constituents to tissues and organs. Such forces have a profound influence on the health, structural integrity, and normal function of cells and organs. Accurate knowledge of cell and tissue biomechanical properties is essential to map the distribution of forces and mechanical cues in biological systems. Cell and tissue biomechanical properties are also known to be important on their own as indicators of health or disease states. Hence, optical elastography and biomechanics methods can aid in the understanding and clinical diagnosis of a wide variety of diseases. We provide a brief overview and highlight of the Optical Elastography and Tissue Biomechanics VI conference, which took place in San Francisco, February 2 and 3, 2019, as a part of Photonics West symposium.

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Section: Poster Sessionmentioning

confidence: 99%

Optical elastography and tissue biomechanics

2019

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“…That such a large enhancement factor can be attained by simply altering the training set to reflect the well-conditioned WSI system is remarkable. Figure 9: Experimental and simulated sensitivities for DNN 1 and DNN 4 . σ CRB and σ S PCRB are also shown.…”

Section: Sensitivitymentioning

confidence: 99%

“…Microscopy techniques that measure the phase distribution of a specimen to generate high contrast images are generally referred to as quantitative phase imaging (QPI) [1]. Some examples include holographic phase microscopy [2], spatial light interference microscopy [3], optical coherence phase microscopy [4], and optical diffraction tomography [5]. These and other techniques are reviewed in [6].…”

Section: Introductionmentioning

confidence: 99%

Neural Network for Optical Pathlength Demodulation in Wavelength Shifting Interferometry

Black

Chen

Zhu

2019

Frontiers in Optics + Laser Science APS/DLS

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Analytical phase demodulation algorithms in optical interferometry typically fail to reach the theoretical sensitivity limit set by the Cramér-Rao bound (CRB). We show that deep neural networks (DNNs) can perform efficient phase demodulation by achieving or exceeding the CRB by significant margins when trained with new information that is not utilized by conventional algorithms, such as noise statistics and parameter constraints. As an example, we developed and applied DNNs to wavelength shifting interferometry. When trained with noise statistics, the DNNs outperform the conventional algorithm in terms of phase sensitivity and achieve the traditional three parameter CRB. Further, by incorporating parameter constraints into the training sets, they can exceed the traditional CRB. For well confined parameters, the phase sensitivity of the DNNs can even approach a fundamental limit we refer to as the single parameter CRB. Such sensitivity improvement can translate into significant increase in single-to-noise ratio without hardware modification, or be used to relax hardware requirements.

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Determining Which Hydrostatic Pressure Regimes Promote Osteogenesis in Human Mesenchymal Stem Cells

Henstock,

Price,

El Haj

2024

Tissue Eng Regen Med

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Background: Compressive loading of bone causes hydrostatic pressure changes which have been proposed as an osteogenic differentiation stimulus for mesenchymal stem cells (hMSCs). We hypothesised that hMSCs are adapted to differentiate only in response to cyclic hydrostatic pressures above critical thresholds of magnitude and frequency which correspond to physiological levels of anabolic bone loading. Methods: Using a pneumatic-hydrostatic bioreactor, we applied hydrostatic pressure regimes to human hMSCs in 3D collagen hydrogel cultures for 1 h/day over 28 days to determine which levels of pressure and frequency stimulated osteogenesis in vitro. Results: Stimulation of the 3D cultures with 0–280 kPa cyclic hydrostatic pressure at 1 Hz resulted in up to 75% mineralisation in the hydrogel (without exogenous growth factors), whilst static culture or variations of the regime with either constant high pressure (280 kPa, 0 Hz), low-frequency (0.05 Hz, 280 kPa) or low-magnitude (70 kPa, 1 Hz) stimulation had no osteogenic effects (< 2% mineralisation). Nuclear translocation of YAP was observed following cyclic hydrostatic pressure in mature MLO-A5 osteoblasts but not in hMSCs, suggesting that cyclic hydrostatic pressure activates different mechanotransduction pathways in undifferentiated stem cells and committed osteoblasts. Conclusions: Hydrostatic pressure is a potent stimulus for differentiating MSC into highly active osteoblasts and may therefore be a versatile tool for translational cell engineering. We have demonstrated that there are minimum levels of force and frequency needed to trigger osteogenesis, i.e. a pressure ‘switch’, which corresponds to the physiological forces experienced by cells in their native mesenchymal niche. The mechanotransduction mechanisms underpinning these effects are the subject of further study.

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Real-time and non-invasive measurements of cell mechanical behaviour with optical coherence phase microscopy

Cited by 5 publications

References 41 publications

Optical elastography and tissue biomechanics

Optical elastography and tissue biomechanics

Neural Network for Optical Pathlength Demodulation in Wavelength Shifting Interferometry

Determining Which Hydrostatic Pressure Regimes Promote Osteogenesis in Human Mesenchymal Stem Cells

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