This PDF file contains the front matter associated with SPIE Proceedings Volume 11964, including the Title Page, Copyright information, Table of Contents, and Conference Committee listings.

This work reports on the development of a low-cost and compact optofluidic add-on device for converting a conventional wide-field microscope to a light sheet fluorescence microscope for immobilization-free imaging of the C. elegans model organism. The developed Polydimethylsiloxane (PDMS)-based optofluidic device consists of an integrated PDMS cylindrical lens for light-sheet generation and a microfluidics channel for flow-based translation of samples through the light sheet. Validation experiments on several strains of C. elegans demonstrate the ability of the device in volumetric imaging of the fluorescence expressions of entire worms in a few seconds, at the single-neuron resolution, and with high contrast.

Mouse models are essential tools for understanding cancer growth and accelerating the development of therapeutic and diagnostic technologies. Xenografts, generated by implanting tumor cells directly into mice through injection, are frequently used to study cancer biology and therapeutics. In these models, assessment of tumor growth and development is necessary to support the study of disease progression and model validation. Unfortunately, such measurements often require sacrificing the animal to create organ explants or tissue cultures, resulting in increased animal use and hampering longitudinal measurements of individual tumors. A tool enabling in vivo tumor monitoring for xenograft models could improve the efficiency of these animal models and provide more robust growth measurements through true longitudinal measurement.

One method of optical tumor assessment involves tagging biomolecules of interest with fluorescent species to enable detection with minimally invasive fluorescence imaging, implemented endoscopically or laparoscopically. However, utilizing fluorescence imaging in vivo in murine models poses challenges due to both tortuous anatomy and small gastrointestinal lumen caliber.

This work reports a miniature fluorescence imaging probe equipped with a multiband filter and biopsy device to image and sample fluorescently-tagged, xenografted tumors as they develop in mouse models. We present the design and characterization of the device and report measurements of the modulation transfer function and ex vivo imaging performance, demonstrating its promise as a valuable research tool to advance cancer research in xenograft models, enabling the development of imaging biomarkers for cancer detection in a clinical setting without the need for exogenous contrast.

The metastatic profile of the cancer cell is considered to be one of the most problematic characteristics from the pathogenic point of view. Because the metastatic cancer cells often show higher mobility compared to the non-metastatic cancer cells, distinguishing the metastatic cancer cell by their images can contain a clue to understanding the molecular process of the cellular metastasis-associated behaviors. In this study, we suggest a deep-learning approach to classify the metastatic cancer cells and non-metastatic cancer cells by their single-cell images acquired by phase-contrast microscopy.

Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer defined by the lack of hormone receptor overexpression. TNBC patients are at a higher risk of recurrence than patients with other breast cancers. As this disease disproportionally affects young women of color, there is an urgent need to address this health inequity by improving disease detection, prognostication, and therapy guidance. Currently, TNBC patients are expected to have better prognosis if a biopsy analysis shows more tumor-infiltrating immune cells. However, immunotherapies such as PD-L1 checkpoint blockade have shown variable efficacy. Studies on the immune constituents of a tumor with high phenotypic resolution have largely been reliant on tissue-destructive methods. Immunofluorescence microscopy, which conserves the spatial distribution of cells, is traditionally limited in collecting high numbers of colocalized antibody markers, which limits the phenotypic specificity of a spatial analysis of tumor immunity. To better understand the immune landscape of TNBC, we have collected highly multiplexed immunofluorescence microscopy images of 19 TNBC samples with 20 cellular markers using an iterative staining and imaging method. Here, we show the generalizability of pre-trained convolutional neural networks to T cell segmentation in TNBC, and further improve these algorithms through fine-tuning. We demonstrate a significant improvement in sensitivity after fine-tuning with domain-specific data (p < 0.05, Mann-Whitney U-test with Bonferroni correction). Additionally, we demonstrate that augmenting the fine-tuning dataset with training images from a different pathology can significantly improves cell detection performance.

Neurons form the fundamental centre of the brain and communicate via neuronal excitability. Drosophila melanogaster is extensively used as the best model organism for various studies in neurobiological aspects. The circadian pacemaker in drosophila consists of 150 clock neurons divided into different groups based on their neuroanatomy. Among these, a neuropeptide called pigment dispersing factor (PDF) produced in the small ventral lateral neurons (sLNvs) plays a vital role in regulating circadian rhythm in Drosophila melanogaster. This paper proposes the study of visualizing PDF neurons in Drosophila melanogaster using an in-house developed simultaneous multiple level selective plane illumination microscopy (sMx-SPIM) system. In this study, PDF neurons in drosophila are used to examine the arborizations during signal transmission. Employing our homebuilt microscope, we can analyze the excitability of the PDF neurons in flies. Due to the design of the sMx-SPIM, one can visualize the region of interest at different magnification levels simultaneously, which helps to inspect the minute details and structural changes in neurons. The CCD camera equipped with the microscopic unit assists in observing and acquiring the entire procedure.

Raman spectroscopy is a powerful spectroscopic tool for remote and minimally invasive detection and chemical identification of molecular species. Visible or infrared laser systems are often employed primarily due to their great availability. Ultraviolet (UV) Raman spectroscopy offers several critical advantages over visible and infrared systems, but is often limited by a high maintenance cost and low reliability of the laser system. We have constructed a UV Raman spectroscopic system using a mercury capillary lamp with capabilities to capture Raman spectra from 0 cm−1 to 4000 cm−1. The system’s low acquisition and maintenance cost, portability, high sensitivity and specificity combined with minimal sample preparation make it ideal for the growing demands in increased food quality and safety.

The improper disposal of textile dyes like Rhodamine B into nearby water bodies and land areas affects living organisms nearby. Here, we explore the effects of rhodamine absorption through the soil into the plant root and how variation in rhodamine concentration affects the growth and development of the plant. The developmental defects over time are verified by nuclear staining the plant cells. Furthermore, we hypothesis that the chemotropic effect seen in plants guides the root away from rhodamine B high concentration regions to low concentration regions. This will in turn help the plant recover from the injury. These minute structural variations are analyzed with the help of our in-house developed dual-arm multi-level magnification light-sheet microscopy (DMx-LSFM) system. The microscope consists of an automated (translating and rotating) sample holding stage, which helps to observe nearby regions by bringing the region of interest into a plane of focus without disturbing the sample.

The cell wall is the hard layer outside the cell membrane, composed of cellulose, and provides strength to the plant body. Moreover, the tensile strength of the cell wall helps in maintaining the mechanical rigidity and expansion of cells. Any deformation to the cell wall will affect the vitality of the plants. Studies reveal the solubility of cellulose in alcohols, and here we report the study of endurance of cell wall when exposed to methanol. We employed a home-built light sheet microscopy system to visualize the time-dependent deterioration of the cell wall due to the intake of methanol by the plant. The studies were repeated for different concentrations of methanol and show a concentration-dependent degradation curve.

Cord blood collected from the umbilical cord differs from human adult blood in many aspects and haematological properties. Viscosity and surface tension of adult blood is higher than that of cord whole blood. Therefore, in the present study, Adult blood-RBC and Cord blood-RBC were optically trapped using an Optical Tweezer. The Optical Tweezer consists of laser of λ=975 nm with 100 mW maximum power and quadrant photodetector (QPD) based force measurement system. Power spectrum density (PSD), cut off frequency (f_c) and optical force calculation for both the types of RBC showed significant differences. RBC folding and unfolding time which is an indicator of RBC rigidity was measured for both Adult and Cord blood-RBC.

We report a novel transparent ultrasound transducer (TUT) platform for low intensity pulsed ultrasound (LIPUS) stimulation of cells and simultaneously imaging live cell fluorescent calcium dynamics using time lapse microscopy. By culturing cells directly on the biocompatible TUT surface, this platform eliminated the need for additional acoustic coupling and reduced the risk of contamination. High light transmission (> 80%) and compact size of TUTs allowed easy integration with state-of-the-art microscopy for high-resolution imaging of cells in both bright and fluorescent modes while stimulating with optimal LIPUS stimulation conditions. Quantitative single cell fluorescence analysis results demonstrated that the proposed TUT allows uniform and high-throughput stimulation of all plated cells. Dead cell assay results confirmed cell viability after LIPUS. In the future, the TUT based platform can be combined with optical cell imaging and manipulation technologies to favor many biomedical applications and help gain insights into the mechanobiology of cells.

In-vivo, real-time study of the local and collective cellular biomechanical responses requires the fine and selective control of the cellular environment. Optical manipulation provides a suitable pathway to achieve non-contact, selective, local, temporal and spatial stimuli. The spectacular photomechanical properties of photoactive bio-substrates such as azobenzene-containing thin polymer films are a new promising strategy to achieve optically triggered local mechanical stimulation of cells. Excited cells exhibit spectacular morphological modifications and area shrinkage, which are dependent on the illumination. In this work we demonstrate that the capabilities of photomechanically active azocontaining substrates to optically stimulate cells’ mechanical response can be strongly influenced by the adhesion binding agent used to deposit the living cells on the photoactive layer. This provides a further tool for the photomechanical control of the cellular environment and of the cellular response.

We present a cytometric and metabolic screening tool that measures shifts in NAD(P)H autofluorescence and autofluorescence lifetimes from single cells based on metabolite-enzyme interactions. Short autofluorescence lifetimes of NAD(P)H (~0.1-1ns) indicate the metabolite is unbound from metabolic enzymes and the cell is favoring glycolysis for energy production. In contrast, longer autofluorescence lifetimes of NAD(P)H (~1-7ns) are an inference that the metabolite is bound to metabolic enzymes and the cell is respiring under oxidative phosphorylation. Using a simple time-resolved flow cytometer we are able to measure autofluorescence lifetimes of MCF-7 and T47D breast cancer cells, which we relate to metabolic changes within each cell line. In order to determine the resolution limits of our time-resolved instrument, we first treated cells under different conditions that directly alter the metabolic pathway that drives their energy production. We deprived cells of serum in their growth media, which drives the cell to utilize glycolysis as a metabolic pathway. By comparing normal to deprived cells, we were able to determine if our cytometry system is able to measure differences in the autofluorescence lifetimes. Results show a decrease in lifetime and autofluorescence intensity for both T47D and MCF7 following serum deprivation. Initial cytometric analysis illustrates consistent lifetime data with respect to fluorescence lifetimes and fluorescence intensities decreasing as expected. This study is a preliminary confirmation that our timeresolved cytometer can effectively detect autofluorescence signals, albeit with some limitations in lifetime resolution. Future work will include refinement of lifetime analysis, frequency domain approaches, and improving sensitivity.

Traditional fluorescence-activated cell sorting (FACS) is a common method to purify or isolate desired cell populations from the bulk cell suspension with high throughput. However, there are many biological applications that aren’t possible on FACS because they require imaging to classify cell types. A major challenge to image-activated cell sorters (IACS) is its robustness to handle various cell shapes and morphology when using hand-crafted image features in real-time. With recent development in machine learning, convolutional neural networks can learn more effective and compact cell image features than traditional feature design techniques. We use these developments to propose and test a cell image classification workflow for real-time:

1. A spatial feature encoder is trained from collected datasets to identify common features of cell images.

2. Such learned features are used to perform Unsupervised Clustering to identify the subpopulations in the sample, from which users can pick the subpopulations to sort.

3. Images from the selected subpopulations are used to refine a pretrained base neural network for Supervised Classification for the current experiment.

4. The refined classifier is then used to make a sorting decision to determine if the input cell should be sorted or not as it travels through the IACS.

We present results using this workflow that performed label-free classification of 5 types of white blood cells with a 98.0% precision and 93.0% recall with a latency of less than 0.4 ms per cell. This accuracy and speed demonstrate that this classification workflow can be used in an Image Activated Cell Sorter.

Oblique back-illumination capillaroscopy (OBC) has recently demonstrated clear images of unlabeled human blood cells in vivo. Combined with deep learning-based algorithms, this technology may enable non-invasive blood cell counting and analysis as flowing red blood cells, platelets, and white blood cells can be observed in their native environment. To harness the full potential of OBC, new techniques and methods must be developed that provide ground truth data using human blood cells. Here we present such a model, where human blood cells with paired ground truth information are imaged flowing in a custom tissue-mimicking micro fluidic device. This model enables the acquisition of OBC datasets that will help with both training and validating machine learning models for applications including the complete blood count, specific blood cell classification, and the study of hematologic disorders such as anemia.

In-vitro testing of novel photodynamic therapy/radiotherapy procedures relies heavily on the use of different assays to fully probe various parameters such as cytotoxicity or cell-death pathways. These assays utilise sometimes expensive dyes or antibodies, along with cumbersome sample preparation for flow-cytometry. In this work, we propose a novel image-processing algorithm that uses the flow cytometry plots obtained through a Propidium Iodide based live-dead assay on cancerous and non-cancerous cells to deduce the possible cell-death mechanisms in the process of radiotherapy. Propidium Iodide (PI) is a membrane-impermeable dye taken up by those cells with loss of cell membrane integrity, and does not give any information about the integrity of intracellular components or cellular death pathways. In our novel image-processing algorithm, we determine the centroid of the Forward Scatter (FSC) and the Side Scatter (SSC) cytometer plots of such a PI assay, after suitable clustering. This algorithm is initially applied to an unirradiated control cell population where the FSC centroid gives an estimate of the mean cell size, while the SSC centroid gives the baseline granularity of the cell population. Thereafter, the centroids of the FSC and the SSC plots are calculated for the irradiated cell population, and the deviation in these centroids calculated. These differences are correlated to change in average cell size and denaturation/granularity, and serve as a useful substitute for the cell death mechanism. This can potentially pave the way for in-situ qualitative cell-death analysis in large-volume in-vitro studies in a cost-effective manner.

Studies of the cAMP signaling pathway have led to the hypothesis that localized cAMP signals regulate distinct cellular responses. Much of this work focused on measurement of localized cAMP signals using cAMP sensors based upon Fӧrster resonance energy transfer (FRET). FRET-based probes are comprised of a cAMP binding domain sandwiched between donor and acceptor fluorophores. Binding of cAMP triggers a conformational change which alters FRET efficiency. In order to study localized cAMP signals, investigators have targeted FRET probes to distinct subcellular domains. This approach allows detection of cAMP signals at distinct subcellular locations. However, these approaches do not measure localized cAMP signals per se, rather they measure cAMP signals at specific locations and typically averaged throughout the cell. To address these concerns, our group implemented hyperspectral imaging approaches for measuring highly multiplexed signals in cells and tissues. We have combined these approaches with custom analysis software implemented in MATLAB and Python. Images were filtered both spatially and temporally, prior to adaptive thresholding (OTSU) to detect cAMP signals. These approaches were used to interrogate the distributions of isoproterenol and prostaglandin triggered cAMP signals in human airway smooth muscle cells (HASMCs). Results demonstrate that cAMP signals are spatially and temporally complex. We observed that isoproterenol- and prostaglandin-induced cAMP signals are triggered at the plasma membrane and in the cytosolic space. We are currently implementing analysis approaches to better quantify and visualize the complex distributions of cAMP signals.

Ca²⁺ and cAMP are ubiquitous second messengers known to differentially regulate a variety of cellular functions over a wide range of timescales. Studies from a variety of groups support the hypothesis that these signals can be localized to discrete locations within cells, and that this subcellular localization is a critical component of signaling specificity. However, to date, it has been difficult to track second messenger signals at multiple locations. To overcome this limitation, we utilized excitation scan-based hyperspectral imaging approaches to track second messenger signals as well as labeled cellular structures and/or proteins in the same cell. We have previously reported that hyperspectral imaging techniques improve the signal-to-noise ratios of both fluorescence measurements, and are thus well suited for the measurement of localized Ca²⁺ signals. We investigated the spatial spread and intensities of agonist-induced Ca²⁺ signals in primary human airway smooth muscle cells (HASMCs) using the Ca²⁺ indicator Cal520. We measured responses triggered by three agonists, carbachol, histamine, and chloroquine. We utilized custom software coded in MATLAB and Python to assess agonist induced changes in Ca²⁺ levels. Software algorithms removed the background and applied correction coefficients to spectral data prior to linear unmixing, spatial and temporal filtering, adaptive thresholding, and automated region of interest (ROI) detection. All three agonists triggered transient Ca²⁺ responses that were spatially and temporally complex. We are currently analyzing differences in both ROI area and intensity distributions triggered by these agonists.

Intracellular organelles in live cells have played a significant role in the spatiotemporal regulation and processes of cellular systems. The visualization of submicron-scale organelle structures and dynamics inside cells requires high-resolution highthroughput microscopic techniques, together with 3D multicolor live imaging capabilities. Light-field microscopy (LFM), which rapidly emerged in recent years as a scanning-free and scalable imaging method, has been widely used for observing structural and functional information spanning many spatiotemporal scales from single cells to mammalian brains. Recent developments of Fourier light-field microscopy (FLFM) have further improved image quality and enhanced computational efficiency by capturing the 4D light field in the Fourier domain. Unlike previous works, which primarily focus on largescale tissues and fixed biological samples, here, we report a high-resolution FLFM (HR-FLFM) to broaden its applications to the realm of high-resolution volumetric and optofluidic imaging for live cells. In HR-FLFM, we have designed a hexagonal microlens array (MLA) to achieve uncompromised subcellular visualization. A 3D deconvolution algorithm using a hybrid PSF has been innovatively developed to reduce the reconstruction artifacts and upgrade the performance of the system. We have demonstrated the 3D optofluidic imaging capabilities of HR-FLFM on typical biological models such as mitochondria and peroxisomes in both fixed and live cells, and the integration with microfluidic systems to achieve a high imaging throughput of the system. We anticipate that HR-FLFM will provide a multiplexed methodology for investigating subcellular anatomy, functions and cell-to-cell variability, paving a promising pathway for broad single-cell investigations and technological breakthroughs.

To assess the effectiveness of newly established wavelength-controlled illuminating method for improving the visibility in clinical settings, we applied and evaluated feasibility of the illuminating method on immunochromatographic tests reading. Using the obtained spectral measurement data of the test kit, we designed the illumination to improve the visibility. We evaluated the visibility of the test kits reacted with diluted positive control solution under several lighting conditions. The illumination designed by our method improved the visibility of the test line by up to 11.3% compared to xenon illumination. We confirmed that our method is effective in improving the visibility in clinical settings.

A ubiquitous second messenger molecule, cAMP is responsible for orchestrating many different cellular functions through a variety of pathways. Fӧrster resonance energy transfer (FRET) probes have been used to visualize cAMP spatial gradients in pulmonary microvascular endothelial cells (PMVECs). However, FRET probes have inherently low signal-to-noise ratios; multiple sources of noise can obscure accurate visualization of cAMP gradients using a hyperspectral imaging system. FRET probes have also been used to measure cAMP gradients in 3D; however, it can be difficult to differentiate between true FRET signals and noise. To further understand the effects of noise on experimental data, a model was developed to simulate cAMP gradients under experimental conditions. The model uses a theoretical cAMP heatmap generated using finite element analysis. This heatmap was converted to simulate the FRET probe signal that would be detected experimentally with a hyperspectral imaging system. The signal was mapped onto an image of unlabeled PMVECs. The result was a time lapse model of cAMP gradients obscured by autofluorescence, as visualized with FRET probes. Additionally, the model allowed the simulated expression level of FRET signal to be varied. This allowed accurate attribution of signal to FRET and autofluorescence. Comparing experimental data to the model results at different levels of FRET efficiency has allowed improved understanding of FRET signal specificity and how autofluorescence interferes with FRET signal detection. In conclusion, this model can more accurately determine cAMP gradients in PMVECs. This work was supported by NIH award P01HL066299, R01HL58506 and NSF award 1725937.

We propose an on-chip photonic tweezer to trap particles based on the photonic antenna for the first time. The proposed antenna, composed of some etched trenches on a waveguide, can produce a quasi-spherical-wave beam above the antenna. The beam is demonstrated to have a large gradient for generating gradient forces, which are up to hundreds of pN/W in this work and large enough for microparticle trapping. In addition, the particles far away from the top surface of the antenna, as high as 25 μm, are demonstrated to be trapped by the proposed tweezer. Furthermore, the proposed antenna tweezer shows the possibility of trapping sub-micron particles and the excellent tolerance for fabrication errors. This photonicantenna- based optical tweezer is considered to pave the way for developing fully integrated photonic circuits capable of large-scale parallel particle manipulation.

Microgravity, vacuum, and high-intensity ultraviolet waves are widely known characteristics of space. These different environments from the earth affect physical changes including ocular tissue changes while astronauts stay in the universe. The changes in ocular tissue in the space environment, also known as visual impairment intracranial pressure (VIIP) syndrome, including fundus optic disc edema, hyperopic drift, choroidal folds, cotton spots, and permanent fundus damage could influence astronauts’ vision system and ability of space operations. Especially, hyperopic drift by posterior flattening and folded retina by choroidal folds are reported to affect the retina's structures as a vision sensor directly. To investigate microgravity's effect on ocular tissues and vision, previous research on earth are used special facilities and various microgravity simulators, including head-down tilt bed-rest and random positioning machines. This study suggests that an experiment expose wild-type zebrafish to microgravity using a rotary cell culture system (RCCs) applied to experiments using cell and zebrafish's embryos in microgravity. Unlike previous research using zebrafish's embryos and larva, adult and growing zebrafish were employed in this study for observing ocular changes in simulated space environments. After exposing zebrafish to microgravity, in-vivo zebrafish's eye images were acquired by custom-built optical coherence tomography (OCT). This research for presenting the new method for small animal experiments in microgravity environments could be applied to investigate the influence of staying in the universe on an animal model with ophthalmic diseases.