Optical Phase Measurements of Disorder Strength Link Microstructure to Cell Stiffness

Utilizing quantitative phase microscopy to localize fluorescence in three dimensions via the transport of intensity equation

We demonstrate the use of a novel, to the best of our knowledge, localization algorithm for digitally refocusing fluorescence images from a three-dimensional cell culture. Simultaneous phase and fluorescence intensity images are collected through a multimodal system that combines digital holography via quantitative phase microscopy (QPM) and fluorescence microscopy. Defocused fluorescence images are localized to a specific z-plane within the three-dimensional (3D) matrix using the transport of intensity equation (TIE) and depth-resolved information derived from the QPM measurements. This technique is applied to cells stained with different fluorescent tags suspended in 3D collagen hydrogel cultures. Experimental findings demonstrate the localization of defocused images, facilitating the analysis and comparison of cells within the hydrogel matrix. This method holds promise for comprehensive cellular imaging of fluorescence labeling in three-dimensional environments, enabling detailed investigations into cellular behavior and interactions.

High-resolution assessment of multidimensional cellular mechanics using label-free refractive-index traction force microscopy

A critical requirement for studying cell mechanics is three-dimensional assessment of cellular shapes and forces with high spatiotemporal resolution. Traction force microscopy with fluorescence imaging enables the measurement of cellular forces, but it is limited by photobleaching and a slow acquisition speed. Here, we present refractive-index traction force microscopy (RI-TFM), which simultaneously quantifies the volumetric morphology and traction force of cells using a high-speed illumination scheme with 0.5-Hz temporal resolution. Without labelling, our method enables quantitative analyses of dry-mass distributions and shear (in-plane) and normal (out-of-plane) tractions of single cells on the extracellular matrix. When combined with a constrained total variation-based deconvolution algorithm, it provides 0.55-Pa shear and 1.59-Pa normal traction sensitivity for a 1-kPa hydrogel substrate. We demonstrate its utility by assessing the effects of compromised intracellular stress and capturing the rapid dynamics of cellular junction formation in the spatiotemporal changes in non-planar traction components.

Contributions of viral oncogenes of HPV-18 and hypoxia to oxidative stress and genetic damage in human keratinocytes

Infection with high-risk human papillomaviruses like HPV-16 and HPV-18 is highly associated with the development of cervical and other cancers. Malignant transformation requires viral oncoproteins E5, E6 and E7, which promote cell proliferation and increase DNA damage. Oxidative stress and hypoxia are also key factors in cervical malignant transformation. Increased levels of reactive species of oxygen (ROS) and nitrogen (RNS) are found in the hypoxic tumor microenvironment, promoting genetic instability and invasiveness. In this work, we studied the combined effect of E5, E6 and E7 and hypoxia in increasing oxidative stress and promoting DNA damage and nuclear architecture alterations. HaCaT cells containing HPV-18 viral oncogenes (HaCaT E5/E6/E7-18) showed higher ROS levels in normoxia and higher levels of RNS in hypoxia compared to HaCaT parental cells, as well as higher genetic damage in hypoxia as measured by γH2AX and comet assays. In hypoxia, HaCaT E5/E6/E7-18 increased its nuclear dry mass and both cell types displayed marked heterogeneity in nuclear dry mass distribution and increased nuclear foci. Our results show contributions of both viral oncogenes and hypoxia to oxidative stress, DNA damage and altered nuclear architecture, exemplifying how an altered microenvironment combines with oncogenic transformation to promote tumor progression.

Rapid and precise tracking of water influx and efflux across cell membranes induced by a pulsed electric field

Quantitative measurements of water content within a single cell are notoriously difficult. In this work, we introduce a single-shot optical method for tracking the intracellular water content, by mass and volume, of a single cell at video rate. We utilize quantitative phase imaging and a priori knowledge of a spherical cellular geometry, leveraging a two-component mixture model to compute the intracellular water content. We apply this technique to study CHO-K1 cells responding to a pulsed electric field, which induces membrane permeabilization and rapid water influx or efflux depending upon the osmotic environment. The effects of mercury and gadolinium on water uptake in Jurkat cells following electropermeabilization are also examined.

Multiscale optical phase fluctuations link disorder strength and fractal dimension of cell structure

Optical methods for examining cellular structure based on endogenous contrast rely on analysis of refractive index changes to discriminate cell phenotype. These changes can be visualized using techniques such as phase contrast microscopy, detected by light scattering, or analyzed numerically using quantitative phase imaging. The statistical variations of refractive index at the nanoscale can be quantified using disorder strength, a metric seen to increase with neoplastic change. In contrast, the spatial organization of these variations is typically characterized using a fractal dimension, which is also seen to increase with cancer progression. Here, we seek to link these two measurements using multiscale measurements of optical phase to calculate disorder strength and in turn to determine the fractal dimension of the structures. First, quantitative phase images are analyzed to show that the disorder strength metric changes with resolution. The trend of disorder strength with length scales is analyzed to determine the fractal dimension of the cellular structures. Comparison of these metrics is presented for different cell lines with varying phenotypes including MCF10A, MCF7, BT474, HT-29, A431, and A549 cell lines, in addition to three cell populations with modified phenotypes. Our results show that disorder strength and fractal dimension can both be obtained with quantitative phase imaging and that these metrics can independently distinguish between different cell lines. Furthermore, their combined use presents a new approach for better understanding cellular restructuring during different pathways.

Quantitative Phase Imaging: Recent Advances and Expanding Potential in Biomedicine

Quantitative phase imaging (QPI) is a label-free, wide-field microscopy approach with significant opportunities for biomedical applications. QPI uses the natural phase shift of light as it passes through a transparent object, such as a mammalian cell, to quantify biomass distribution and spatial and temporal changes in biomass. Reported in cell studies more than 60 years ago, ongoing advances in QPI hardware and software are leading to numerous applications in biology, with a dramatic expansion in utility over the past two decades. Today, investigations of cell size, morphology, behavior, cellular viscoelasticity, drug efficacy, biomass accumulation and turnover, and transport mechanics are supporting studies of development, physiology, neural activity, cancer, and additional physiological processes and diseases. Here, we review the field of QPI in biology starting with underlying principles, followed by a discussion of technical approaches currently available or being developed, and end with an examination of the breadth of applications in use or under development. We comment on strengths and shortcomings for the deployment of QPI in key biomedical contexts and conclude with emerging challenges and opportunities based on combining QPI with other methodologies that expand the scope and utility of QPI even further.

Quantitative phase velocimetry measures bulk intracellular transport of cell mass during the cell cycle

Transport of mass within cells helps maintain homeostasis and is disrupted by disease and stress. Here, we develop quantitative phase velocimetry (QPV) as a label-free approach to make the invisible flow of mass within cells visible and quantifiable. We benchmark our approach against alternative image registration methods, a theoretical error model, and synthetic data. Our method tracks not just individual labeled particles or molecules, but the entire flow of bulk material through the cell. This enables us to measure diffusivity within distinct cell compartments using a single approach, which we use here for direct comparison of nuclear and cytoplasmic diffusivity. As a label-free method, QPV can be used for long-term tracking to capture dynamics through the cell cycle.

Viscoelasticity, Like Forces, Plays a Role in Mechanotransduction

Viscoelasticity and its alteration in time and space has turned out to act as a key element in fundamental biological processes in living systems, such as morphogenesis and motility. Based on experimental and theoretical findings it can be proposed that viscoelasticity of cells, spheroids and tissues seems to be a collective characteristic that demands macromolecular, intracellular component and intercellular interactions. A major challenge is to couple the alterations in the macroscopic structural or material characteristics of cells, spheroids and tissues, such as cell and tissue phase transitions, to the microscopic interferences of their elements. Therefore, the biophysical technologies need to be improved, advanced and connected to classical biological assays. In this review, the viscoelastic nature of cytoskeletal, extracellular and cellular networks is presented and discussed. Viscoelasticity is conceptualized as a major contributor to cell migration and invasion and it is discussed whether it can serve as a biomarker for the cells' migratory capacity in several biological contexts. It can be hypothesized that the statistical mechanics of intra- and extracellular networks may be applied in the future as a powerful tool to explore quantitatively the biomechanical foundation of viscoelasticity over a broad range of time and length scales. Finally, the importance of the cellular viscoelasticity is illustrated in identifying and characterizing multiple disorders, such as cancer, tissue injuries, acute or chronic inflammations or fibrotic diseases.

Live-dead assay on unlabeled cells using phase imaging with computational specificity

Existing approaches to evaluate cell viability involve cell staining with chemical reagents. However, the step of exogenous staining makes these methods undesirable for rapid, nondestructive, and long-term investigation. Here, we present an instantaneous viability assessment of unlabeled cells using phase imaging with computation specificity. This concept utilizes deep learning techniques to compute viability markers associated with the specimen measured by label-free quantitative phase imaging. Demonstrated on different live cell cultures, the proposed method reports approximately 95% accuracy in identifying live and dead cells. The evolution of the cell dry mass and nucleus area for the labeled and unlabeled populations reveal that the chemical reagents decrease viability. The nondestructive approach presented here may find a broad range of applications, from monitoring the production of biopharmaceuticals to assessing the effectiveness of cancer treatments.

Common methods for characterising cell viability involve cell staining with chemical reagents. Here the authors report a method for cell viability assessment that does not require labelling; this uses quantitative phase imaging combined with deep learning.

Synthetic aperture interference light (SAIL) microscopy for high-throughput label-free imaging

Quantitative phase imaging (QPI) is a valuable label-free modality that has gained significant interest due to its wide potentials, from basic biology to clinical applications. Most existing QPI systems measure microscopic objects via interferometry or nonlinear iterative phase reconstructions from intensity measurements. However, all imaging systems compromise spatial resolution for the field of view and vice versa, i.e., suffer from a limited space bandwidth product. Current solutions to this problem involve computational phase retrieval algorithms, which are time-consuming and often suffer from convergence problems. In this article, we presented synthetic aperture interference light (SAIL) microscopy as a solution for high-resolution, wide field of view QPI. The proposed approach employs low-coherence interferometry to directly measure the optical phase delay under different illumination angles and produces large space-bandwidth product label-free imaging. We validate the performance of SAIL on standard samples and illustrate the biomedical applications on various specimens: pathology slides, entire insects, and dynamic live cells in large cultures. The reconstructed images have a synthetic numeric aperture of 0.45 and a field of view of 2.6 × 2.6 mm2. Due to its direct measurement of the phase information, SAIL microscopy does not require long computational time, eliminates data redundancy, and always converges.

Cancer-Cell Deep-Learning Classification by Integrating Quantitative-Phase Spatial and Temporal Fluctuations

We present a new classification approach for live cells, integrating together the spatial and temporal fluctuation maps and the quantitative optical thickness map of the cell, as acquired by common-path quantitative-phase dynamic imaging and processed with a deep-learning framework. We demonstrate this approach by classifying between two types of cancer cell lines of different metastatic potential originating from the same patient. It is based on the fact that both the cancer-cell morphology and its mechanical properties, as indicated by the cell temporal and spatial fluctuations, change over the disease progression. We tested different fusion methods for inputting both the morphological optical thickness maps and the coinciding spatio-temporal fluctuation maps of the cells to the classifying network framework. We show that the proposed integrated triple-path deep-learning architecture improves over deep-learning classification that is based only on the cell morphological evaluation via its quantitative optical thickness map, demonstrating the benefit in the acquisition of the cells over time and in extracting their spatio-temporal fluctuation maps, to be used as an input to the classifying deep neural network.

Quantitative phase microscopy monitors subcellular dynamics in single cells exposed to nanosecond pulsed electric fields

A substantial body of literature exists to study the dynamics of single cells exposed to short duration (<1 μs), high peak power (~1 MV/m) transient electric fields. Much of this research is limited to traditional fluorescence-based microscopy techniques, which introduce exogenous agents to the culture and are only sensitive to a single molecular target. Quantitative phase imaging (QPI) is a coherent imaging modality which uses optical path length as a label-free contrast mechanism, and has proven highly effective for the study of single-cell dynamics. In this work, we introduce QPI as a useful imaging tool for the study of cells undergoing cytoskeletal remodeling after nanosecond pulsed electric field (nsPEF) exposure. In particular, we use cell swelling, dry mass and disorder strength measurements derived from QPI phase images to monitor the cellular response to nsPEFs. We hope this demonstration of QPI's utility will lead to a further adoption of the technique for the study of directed energy bioeffects.

Single Cell Analysis of Stored Red Blood Cells Using Ultra-High Throughput Holographic Cytometry

Holographic cytometry is introduced as an ultra-high throughput implementation of quantitative phase imaging of single cells flowing through parallel microfluidic channels. Here, the approach was applied for characterizing the morphology of individual red blood cells during storage under regular blood bank conditions. Samples from five blood donors were examined, over 100,000 cells examined for each, at three time points. The approach allows high-throughput phase imaging of a large number of cells, greatly extending our ability to study cellular phenotypes using individual cell images. Holographic cytology images can provide measurements of multiple physical traits of the cells, including optical volume and area, which are observed to consistently change over the storage time. In addition, the large volume of cell imaging data can serve as training data for machine-learning algorithms. For the study here, logistic regression was used to classify the cells according to the storage time points. The analysis showed that at least 5000 cells are needed to ensure accuracy of the classifiers. Overall, results showed the potential of holographic cytometry as a diagnostic tool.

Label-free SARS-CoV-2 detection and classification using phase imaging with computational specificity

Efforts to mitigate the COVID-19 crisis revealed that fast, accurate, and scalable testing is crucial for curbing the current impact and that of future pandemics. We propose an optical method for directly imaging unlabeled viral particles and using deep learning for detection and classification. An ultrasensitive interferometric method was used to image four virus types with nanoscale optical path-length sensitivity. Pairing these data with fluorescence images for ground truth, we trained semantic segmentation models based on U-Net, a particular type of convolutional neural network. The trained network was applied to classify the viruses from the interferometric images only, containing simultaneously SARS-CoV-2, H1N1 (influenza-A virus), HAdV (adenovirus), and ZIKV (Zika virus). Remarkably, due to the nanoscale sensitivity in the input data, the neural network was able to identify SARS-CoV-2 vs. the other viruses with 96% accuracy. The inference time for each image is 60 ms, on a common graphic-processing unit. This approach of directly imaging unlabeled viral particles may provide an extremely fast test, of less than a minute per patient. As the imaging instrument operates on regular glass slides, we envision this method as potentially testing on patient breath condensates. The necessary high throughput can be achieved by translating concepts from digital pathology, where a microscope can scan hundreds of slides automatically.

Visualizing bleb mass dynamics in single cells using quantitative phase microscopy

Understanding biological responses to directed energy (DE) is critical to ensure the safety of personnel within the Department of Defense. At the Air Force Research Laboratory, we have developed or adapted advanced optical imaging systems that quantify biophysical responses to DE. One notable cellular response to DE exposure is the formation of blebs, or semi-spherical protrusions of the plasma membrane in living cells. In this work, we demonstrate the capacity of quantitative phase imaging (QPI) to both visualize and quantify the formation of membrane blebs following DE exposure. QPI is an interferometric imaging tool that uses optical path length as a label-free contrast mechanism and is sensitive to the non-aqueous mass density, or dry mass, of living cells. Blebs from both CHO-K1 and U937 cells were generated after exposure to a series of 600 ns, 21.2 kV/cm electric pulses. These blebs were visualized in real time, and their dry mass relative to the rest of the cell body was quantified as a function of time. It is our hope that this system will lead to an improved understanding of both DE-induced and apoptotic blebbing.

Toward deep biophysical cytometry: prospects and challenges

The biophysical properties of cells reflect their identities, underpin their homeostatic state in health, and define the pathogenesis of disease. Recent leapfrogging advances in biophysical cytometry now give access to this information, which is obscured in molecular assays, with a discriminative power that was once inconceivable. However, biophysical cytometry should go 'deeper' in terms of exploiting the information-rich cellular biophysical content, generating a molecular knowledge base of cellular biophysical properties, and standardizing the protocols for wider dissemination. Overcoming these barriers, which requires concurrent innovations in microfluidics, optical imaging, and computer vision, could unleash the enormous potential of biophysical cytometry not only for gaining a new mechanistic understanding of biological systems but also for identifying new cost-effective biomarkers of disease.

Cell viscoelasticity is linked to fluctuations in cell biomass distributions

The viscoelastic properties of mammalian cells can vary with biological state, such as during the epithelial-to-mesenchymal (EMT) transition in cancer, and therefore may serve as a useful physical biomarker. To characterize stiffness, conventional techniques use cell contact or invasive probes and as a result are low throughput, labor intensive, and limited by probe placement. Here, we show that measurements of biomass fluctuations in cells using quantitative phase imaging (QPI) provides a probe-free, contact-free method for quantifying changes in cell viscoelasticity. In particular, QPI measurements reveal a characteristic underdamped response of changes in cell biomass distributions versus time. The effective stiffness and viscosity values extracted from these oscillations in cell biomass distributions correlate with effective cell stiffness and viscosity measured by atomic force microscopy (AFM). This result is consistent for multiple cell lines with varying degrees of cytoskeleton disruption and during the EMT. Overall, our study demonstrates that QPI can reproducibly quantify cell viscoelasticity.

Simple adaptive mobile phone screen illumination for dual phone differential phase contrast (DPDPC) microscopy

Phase contrast imaging is widely employed in the physical, biological, and medical sciences. However, typical implementations involve complex imaging systems that amount to in-line interferometers. We adapt differential phase contrast (DPC) to a dual-phone illumination-imaging system to obtain phase contrast images on a portable mobile phone platform. In this dual phone differential phase contrast (dpDPC) microscope, semicircles are projected sequentially on the display of one phone, and images are captured using a low-cost, short focal length lens attached to the second phone. By numerically combining images obtained using these semicircle patterns, high quality DPC images with ≈ 2 micrometer resolution can be easily acquired with no specialized hardware, circuitry, or instrument control programs.

A Toolbox for Organelle Mechanobiology Research-Current Needs and Challenges

Mechanobiology studies from the last decades have brought significant insights into many domains of biological research, from development to cellular signaling. However, mechano-regulation of subcellular components, especially membranous organelles, are only beginning to be unraveled. In this paper, we take mitochondrial mechanobiology as an example to discuss recent advances and current technical challenges in this field. In addition, we discuss the needs for future toolbox development for mechanobiological research of intracellular organelles.

Studying nucleic envelope and plasma membrane mechanics of eukaryotic cells using confocal reflectance interferometric microscopy

Mechanical stress on eukaryotic nucleus has been implicated in a diverse range of diseases including muscular dystrophy and cancer metastasis. Today, there are very few non-perturbative methods to quantify nuclear mechanical properties. Interferometric microscopy, also known as quantitative phase microscopy (QPM), is a powerful tool for studying red blood cell biomechanics. The existing QPM tools, however, have not been utilized to study biomechanics of complex eukaryotic cells either due to lack of depth sectioning, limited phase measurement sensitivity, or both. Here, we present depth-resolved confocal reflectance interferometric microscopy as the next generation QPM to study nuclear and plasma membrane biomechanics. The proposed system features multiple confocal scanning foci, affording 1.5 micron depth-resolution and millisecond frame rate. Furthermore, a near common-path interferometer enables quantifying nanometer-scale membrane fluctuations with better than 200 picometers sensitivity. Our results present accurate quantification of nucleic envelope and plasma membrane fluctuations in embryonic stem cells.

Biomechanical studies of eukaryotic cells have been limited due to low sensitivity and axial resolution in interferometric imaging. Here, the authors present depth-resolved confocal reflectance interferometric microscopy with high sensitivity and temporal resolution, which enables quantification of nucleic envelope and plasma membrane fluctuations.

Shear Modulus Measurement by Quantitative Phase Imaging and Correlation with Atomic Force Microscopy

Many approaches have been developed to characterize cell elasticity. Among these, atomic force microscopy (AFM) combined with modeling has been widely used to characterize cellular compliance. However, such approaches are often limited by the difficulties associated with using a specific instrument and by the complexity of analyzing the measured data. More recently, quantitative phase imaging (QPI) has been applied to characterize cellular stiffness by using an effective spring constant. This metric was further correlated to mass distribution (disorder strength) within the cell. However, these measurements are difficult to compare to AFM-derived measurements of Young's modulus. Here, we describe, to our knowledge, a new way of analyzing QPI data to directly retrieve the shear modulus. Our approach enables label-free measurement of cellular mechanical properties that can be directly compared to values obtained from other rheological methods. To demonstrate the technique, we measured shear modulus and phase disorder strength using QPI, as well as Young's modulus using AFM, across two breast cancer cell-line populations dosed with three different concentrations of cytochalasin D, an actin-depolymerizing toxin. Comparison of QPI-derived and AFM moduli shows good agreement between the two measures and further agrees with theory. Our results suggest that QPI is a powerful tool for cellular biophysics because it allows for optical quantitative measurements of cell mechanical properties.

Light scattering methods for tissue diagnosis

Light scattering has become a common biomedical research tool, enabling diagnostic sensitivity to myriad tissue alterations associated with disease. Light-tissue interactions are particularly attractive for diagnostics due to the variety of contrast mechanisms that can be used, including spectral, angle-resolved, and Fourier-domain detection. Photonic diagnostic tools offer further benefit in that they are non-ionizing, non-invasive, and give real-time feedback. In this review, we summarize recent innovations in light scattering technologies, with a focus on clinical achievements over the previous ten years.

Optical excitation and detection of neuronal activity

Optogenetics has emerged as an exciting tool for manipulating neural activity, which in turn, can modulate behavior in live organisms. However, detecting the response to the optical stimulation requires electrophysiology with physical contact or fluorescent imaging at target locations, which is often limited by photobleaching and phototoxicity. In this paper, we show that phase imaging can report the intracellular transport induced by optogenetic stimulation. We developed a multimodal instrument that can both stimulate cells with subcellular spatial resolution and detect optical pathlength (OPL) changes with nanometer scale sensitivity. We found that OPL fluctuations following stimulation are consistent with active organelle transport. Furthermore, the results indicate a broadening in the transport velocity distribution, which is significantly higher in stimulated cells compared to optogenetically inactive cells. It is likely that this label-free, contactless measurement of optogenetic response will provide an enabling approach to neuroscience.

Tissue spatial correlation as cancer marker

We propose an intrinsic cancer marker in fixed tissue biopsy slides, which is based on the local spatial autocorrelation length obtained from quantitative phase images. The spatial autocorrelation length in a small region of the tissue phase image is sensitive to the nanoscale cellular morphological alterations and can hence inform on carcinogenesis. Therefore, this metric can potentially be used as an intrinsic cancer marker in histopathology. Typically, these correlation length maps are calculated by computing two-dimensional Fourier transforms over image subregions-requiring long computational times. We propose a more time-efficient method of computing the correlation map and demonstrate its value for diagnosis of benign and malignant breast tissues. Our methodology is based on highly sensitive quantitative phase imaging data obtained by spatial light interference microscopy.

Preservation of cellular nano-architecture by the process of chemical fixation for nanopathology

Transformation in chromatin organization is one of the most universal markers of carcinogenesis. Microscale chromatin alterations have been a staple of histopathological diagnosis of neoplasia, and nanoscale alterations have emerged as a promising marker for cancer prognostication and the detection of predysplastic changes. While numerous methods have been developed to detect these alterations, most methods for sample preparation remain largely validated via conventional microscopy and have not been examined with nanoscale sensitive imaging techniques. For these nanoscale sensitive techniques to become standard of care screening tools, new histological protocols must be developed that preserve nanoscale information. Partial Wave Spectroscopic (PWS) microscopy has recently emerged as a novel imaging technique sensitive to length scales ranging between 20 and 200 nanometers. As a label-free, high-throughput, and non-invasive imaging technique, PWS microscopy is an ideal tool to quantify structural information during sample preparation. Therefore, in this work we applied PWS microscopy to systematically evaluate the effects of cytological preparation on the nanoscales changes of chromatin using two live cell models: a drug-based model of Hela cells differentially treated with daunorubicin and a cell line comparison model of two cells lines with inherently distinct chromatin organizations. Notably, we show that existing cytological preparation can be modified in order to maintain clinically relevant nanoscopic differences, paving the way for the emerging field of nanopathology.

A Wearable Fiberless Optical Sensor for Continuous Monitoring of Cerebral Blood Flow in Mice

Continuous and longitudinal monitoring of cerebral blood flow (CBF) in animal models provides information for studying the mechanisms and interventions of various cerebral diseases. Since anesthesia may affect brain hemodynamics, researchers have been seeking wearable devices for use in conscious animals. We present a wearable diffuse speckle contrast flowmeter (DSCF) probe for monitoring CBF variations in mice. The DSCF probe consists of a small low-power near-infrared laser diode as a point source and an ultra-small low-power CMOS camera as a 2D detector array, which can be affixed on a mouse head. The movement of red blood cells in brain cortex (i.e., CBF) produces spatial fluctuations of laser speckles, which are captured by the camera. The DSCF system was calibrated using tissue phantoms and validated in a human forearm and mouse brains for continuous monitoring of blood flow increases and decreases against the established technologies. Significant correlations were observed among these measurements (R² ≥ 0.80, p < 10^-5). This small fiberless probe has the potential to be worn by a freely moving conscious mouse. Moreover, the flexible source-detector configuration allows for varied probing depths up to ~8 mm, which is sufficient for transcranially detecting CBF in the cortices of rodents and newborn infants.

Molecular and biophysical analysis of apoptosis using a combined quantitative phase imaging and fluorescence resonance energy transfer microscope

Apoptotic mechanisms are often dysregulated in cancerous phenotypes. Additionally, many anticancer treatments induce apoptosis and necrosis, and the monitoring of this apoptotic activity can allow researchers to identify therapeutic efficiency. Here, we introduce a microscope which combines quantitative phase imaging (QPI) with the ability to detect molecular events via fluorescence (or Förster) resonance energy transfer (FRET). The system was applied to study cells undergoing apoptosis to correlate the onset of apoptotic enzyme activity as observed using a FRET-based apoptosis sensor with whole cell morphological changes analyzed via QPI. The QPI data showed changes in cell disorder strength during the initiation of apoptotic enzymatic activity.

Quantitative assessment of cell contractility using polarized light microscopy

Cell contractility regulates multiple cell behaviors which contribute to both normal and pathological processes. However, measuring cell contractility remains a technical challenge in complex biological samples. The current state of the art technologies employed to measure cell contractility have inherent limitations that greatly limit the experimental conditions under which they can be used. Here, we use quantitative polarization microscopy to extract information about cell contractility. We show that the optical retardance signal measured from the cell body is proportional to cell contractility in 2-dimensional and 3-dimensional platforms, and as such can be used as a straightforward, tractable methodology to assess cell contractility in a variety of systems. This label-free optical method provides a novel and flexible way to assess cellular forces of single cells and monolayers in several cell types, fixed or live, in addition to cells present in situ in mouse tumor tissue samples. This easily implementable and experimentally versatile method will significantly contribute to the cell mechanics field.

Fabrication of Refractive-index-matched Devices for Biomedical Microfluidics

The use of microfluidic devices has emerged as a defining tool for biomedical applications. When combined with modern microscopy techniques, these devices can be implemented as part of a robust platform capable of making simultaneous complementary measurements. The primary challenge created by the combination of these two techniques is the mismatch in refractive index between the materials traditionally used to make microfluidic devices and the aqueous solutions typically used in biomedicine. This mismatch can create optical artifacts near the channel or device edges. One solution is to reduce the refractive index of the material used to fabricate the device by using a fluorinated polymer such as MY133-V2000 whose refractive index is similar to that of water (n = 1.33). Here, the construction of a microfluidic device made out of MY133-V2000 using soft lithography techniques is demonstrated, using O2 plasma in conjunction with an acrylic holder to increase the adhesion between the MY133-V2000 fabricated device and the polydimethylsiloxane (PDMS) substrate. The device is then tested by incubating it filled with cell culture media for 24 h to demonstrate the ability of the device to maintain cell culture conditions during the course of a typical imaging experiment. Finally, quantitative phase microscopy (QPM) is used to measure the distribution of mass within the live adherent cells in the microchannel. This way, the increased precision, enabled by fabricating the device from a low index of refraction polymer such as MY133-V2000 in lieu of traditional soft lithography materials such as PDMS, is demonstrated. Overall, this approach for fabricating microfluidic devices can be readily integrated into existing soft lithography workflows in order to reduce optical artifacts and increase measurement precision.

Endoscopic diffraction phase microscopy

In this Letter, we present, to our knowledge, the first endoscopic diffraction phase microscopy (eDPM) system. This instrument consists of a gradient-index-lens-based endoscope probe followed by a DPM module, which enables single-shot phase imaging at a single-cell-level resolution. Using the phase information provided by eDPM, we show that the geometric aberrations associated with the endoscope can be reduced by digitally applying a spectral phase filter to the raw data. The filter function is a linear combination of polynomials with weighting optimized to improve resolution. We validate the principle of the proposed method using reflective semiconductor samples and blood cells. This research extends the current scope of quantitative phase imaging applications, and proves its potential for future in vivo studies.

A high-throughput flow cytometry-on-a-CMOS platform for single-cell dielectric spectroscopy at microwave frequencies

This work presents a microfluidics-integrated label-free flow cytometry-on-a-CMOS platform for the characterization of the cytoplasm dielectric properties at microwave frequencies. Compared with MHz impedance cytometers, operating at GHz frequencies offers direct intracellular permittivity probing due to electric fields penetrating through the cellular membrane. To overcome the detection challenges at high frequencies, the spectrometer employs on-chip oscillator-based sensors, which embeds simultaneous frequency generation, electrode excitation, and signal detection capabilities. By employing an injection-locking phase-detection technique, the spectrometer offers state-of-the-art sensitivity, achieving a less than 1 aFrms capacitance detection limit (or 5 ppm in frequency-shift) at a 100 kHz noise filtering bandwidth, enabling high throughput (>1k cells per s), with a measured cellular SNR of more than 28 dB. With CMOS/microfluidics co-design, we distribute four sensing channels at 6.5, 11, 17.5, and 30 GHz in an arrayed format whereas the frequencies are selected to center around the water relaxation frequency at 18 GHz. An issue in the integration of CMOS and microfluidics due to size mismatch is also addressed through introducing a cost-efficient epoxy-molding technique. With 3-D hydrodynamic focusing microfluidics, we perform characterization on four different cell lines including two breast cell lines (MCF-10A and MDA-MB-231) and two leukocyte cell lines (K-562 and THP-1). After normalizing the higher frequency signals to the 6.5 GHz ones, the size-independent dielectric opacity shows a differentiable distribution at 17.5 GHz between normal (0.905 ± 0.160, mean ± std.) and highly metastatic (1.033 ± 0.107) breast cells with p ≪ 0.001.

Response to Comment on "Is the nuclear refractive index lower than cytoplasm? Validation of phase measurements and implications for light scattering technologies": A Comment on "How a phase image of a cell with nucleus refractive index smaller than that of the cytoplasm should look like?", e201800033

Recently, Maxim A. Yurkin commented on our paper "Is the nuclear refractive index lower than cytoplasm? Validation of phase measurements and implications for light scattering technologies" as well as on a complementary study "Cell nuclei have lower refractive index and mass density than cytoplasm" from Schürmann et al. In his comment, Yurkin concluded that quantitative phase images of cells with nuclei that are less optically dense than the cytoplasm must exhibit a characteristic concavity, the absence of which is evidence against our conclusion of a less-dense nucleus. In this response, we suggest that Yurkin's conclusion is reached through an oversimplification of the spatial refractive index distribution within cells, which does not account for high index inclusions such as the nucleolus. We further cite recent studies in 3-dimensional refractive index imaging, in which the preponderance of studies supports our conclusion. Finally, we comment on the current state of knowledge regarding subcellular refractive index distributions in living cells.

Label-free quantitative evaluation of breast tissue using Spatial Light Interference Microscopy (SLIM)

Breast cancer is the most common type of cancer among women worldwide. The standard histopathology of breast tissue, the primary means of disease diagnosis, involves manual microscopic examination of stained tissue by a pathologist. Because this method relies on qualitative information, it can result in inter-observer variation. Furthermore, for difficult cases the pathologist often needs additional markers of malignancy to help in making a diagnosis, a need that can potentially be met by novel microscopy methods. We present a quantitative method for label-free breast tissue evaluation using Spatial Light Interference Microscopy (SLIM). By extracting tissue markers of malignancy based on the nanostructure revealed by the optical path-length, our method provides an objective, label-free and potentially automatable method for breast histopathology. We demonstrated our method by imaging a tissue microarray consisting of 68 different subjects −34 with malignant and 34 with benign tissues. Three-fold cross validation results showed a sensitivity of 94% and specificity of 85% for detecting cancer. Our disease signatures represent intrinsic physical attributes of the sample, independent of staining quality, facilitating classification through machine learning packages since our images do not vary from scan to scan or instrument to instrument.

Disorder strength measured by quantitative phase imaging as intrinsic cancer marker in fixed tissue biopsies

Tissue refractive index provides important information about morphology at the nanoscale. Since the malignant transformation involves both intra- and inter-cellular changes in the refractive index map, the tissue disorder measurement can be used to extract important diagnosis information. Quantitative phase imaging (QPI) provides a practical means of extracting this information as it maps the optical path-length difference (OPD) across a tissue sample with sub-wavelength sensitivity. In this work, we employ QPI to compare the tissue disorder strength between benign and malignant breast tissue histology samples. Our results show that disease progression is marked by a significant increase in the disorder strength. Since our imaging system can be added as an upgrading module to an existing microscope, we anticipate that it can be integrated easily in the pathology work flow.

Characterization of the mechanical properties of resected porcine organ tissue using optical fiber photoelastic polarimetry

Characterizing the mechanical behavior of living tissue presents an interesting challenge because the elasticity varies by eight orders of magnitude, from 50Pa to 5GPa. In the present work, a non-destructive optical fiber photoelastic polarimetry system is used to analyze the mechanical properties of resected samples from porcine liver, kidney, and pancreas. Using a quasi-linear viscoelastic fit, the elastic modulus values of the different organ systems are determined. They are in agreement with previous work. In addition, a histological assessment of compressed and uncompressed tissues confirms that the tissue is not damaged during testing.