Quantitative fluorescence imaging of entire organs at the cellular level is crucial in understanding tissue structure and function. However, it is often time-consuming and labor-intensive to section tissue for high-resolution microscopy. We developed a deep ultraviolet fluorescence microscope for rapid surface imaging of thick unsectioned tissue at cellular resolution. Fast staining and tissue microscopy protocols were designed for practical use cases. We investigated the effects of vancomycin on mouse kidneys and also conducted studies on uterine ageing and its association with extracellular matrix protein expression. Deep ultraviolet fluorescence microscopy offers a promising approach in quantitative mapping of whole organs.

We introduce a novel, antigen-independent biolaser method to generate distinctive cellular signatures. Suspension of nucleic acid-stained cells is deposited into a Fabry-Perot cavity. The cells are excited by a pump laser at various power densities and the lasing signatures of these cells are collected. A neural network based on ResNet 34 is trained to detect and differentiate lasing patterns of CTCs from WBCs using the collected lasing signatures. This neural network structure is designed to be robust against inter-cavity discrepancies in laser cavities. We tested our system on detecting circulating pancreatic cancer cells from cell lines of T cells (Jurkat) and later spiked patient samples (filtered WBCs), from lasing cavities with uncharacterized Q factors. In both cases, we were able to differentiate the CTCs with an accuracy higher than 90%.

The biopharmaceutical industry relies on selecting high-performing cell lines to meet quality and manufacturability criteria. However, this process is time- and labor-intensive. To address this, label-free multimodal multiphoton microscopy techniques were employed to characterize biopharmaceutical cell lines in early passages. Using a machine learning-assisted single-cell analysis pipeline, over 95% accuracy for monoclonal cell line classification was achieved in all passages. Additionally, Open Set Recognition allowed the differentiation of desired cell lines in polyclonal pools. The study offers a promising solution to expedite the cell line selection process, reducing time and resources while ensuring the identification of high-performance biopharmaceutical cell lines.

Successful cancer treatment continues to elude modern medicine and its arsenal of therapeutic strategies. Therapy resistance is driven by tumor heterogeneity, complex interactions between tumor and its microenvironment. Advances in molecular characterization technologies have helped unravel this interaction network and identify therapeutic targets such as tyrosine kinase inhibitors (TKI). However, while tumors may initially respond to TKI therapy, disease progression is inevitable due to acquired resistance. With the ultimate goal of improved molecularly targeted therapeutic efficacy, we have developed and optimized a fluorescence imaging platform termed TRIPODD (Therapeutic Response Imaging through Proteomic and Optical Drug Distribution), resulting in the only methodology capable of simultaneous quantification of single-cell drug target availability and protein expression with preserved spatial context within a tumor. Analysis of preclinical tumor models with TRIPODD enabled discovery of unique cell subpopulations of TKI therapeutic response, where the relationship between drug target availability and therapeutic response was unraveled.

Metabolic features of mitosis remain poorly understood because this phase of the cell cycle is rapid and heterogeneous between cells within a dish. Label-free optical metabolic imaging (OMI) can monitor rapid changes in cell metabolism with single cell resolution using two-photon microscopy of the optical redox ratio (NAD(P)H/FAD) and NAD(P)H fluorescence lifetimes. Here, we brought together image analysis tools to quantify OMI time-courses of single cells undergoing mitosis across multiple cell lines. Alignment of OMI and morphological features over time provided unique insight into metabolic changes during mitosis within unperturbed systems.

Identifying and relocating individual cells, especially sperm for IVF, is challenging due to their similar look, rotation, and transparency. We propose a new method using a vision transformer network, trained on 3D images of cells taken with a holotomographic microscope. Our approach uses a Detection Transformer (DETR) network, which makes unique predictions about the cells and their context. This method improves the speed and accuracy of cell identification in IVF, offering potential for better success rates and optimization of high-throughput imaging.

Pancreatic neuroendocrine tumors (PNETs) are a relatively rare type of cancer whose preferred method of treatment is surgery, however current intraoperative guidance techniques have poor contrast. Multiphoton microscopy (MPM) is an imaging technique capable of capturing many biomarkers indicative of cancer; this project examines whether MPM images may provide a basis for a robust method of PNET localization. 14 fixed frozen and 57 formalin-fixed paraffin-embedded samples were imaged using MPM and classified using linear discriminant analysis. The model performed well across both sample preparations, indicating our approach could be applied to improve surgical localization of PNETs.

We present a novel technique that uses hybrid digital holography to observe three-dimensional morphological changes in cardiac organoids and measure heart rates simultaneously. By reconstructing the real-time spatial topology, we capture dynamic morphological changes in three-dimensional cardiac organoids, especially in the central region where traditional optical imaging methods are limited. We analyze the correlation between the phase analysis results of digital holography and the corresponding electronic signal amplitude with heartbeat data. Fluorescent modes can also be used to investigate heart rate, ROS activation, and organic cell activation. In addition, dark field mode allows you to simultaneously evaluate the distribution of nanoparticles about 100 nm in size on the heart surface and their effect on the heart rate. Our work demonstrates the potential of hybrid digital holography as an innovative optical analysis method in heart and tissue analysis, providing valuable insights into the relationship between cardiac tissue dynamics and heart rate

In this study, we investigate the use of microlasers as light sources for digital holographic microscopy embedded in the sample. Microlasers are 50-μm sized dye-doped self-assembled cholesteric liquid-crystal microdroplets that isotropically emit single-mode laser light. By employing an epi-illumination configuration of a standard optical microscope, we excited a single microlaser beneath the sample plane and subsequently acquired in-line holograms of various samples placed between the microlaser and microscope objective. Embedding the light source enabled us to uniquely acquire in-line digital holograms in transmission even though the sample is observed in an epi-illumination configuration and could in principle be infinitely thick on one side.

Using complementary optical microscopy techniques provides more detailed insight into biological samples. However, misinterpretation can occur by temporal discrepancies due to differences in temporal resolution and switching imaging modalities. Here, we demonstrated multimodal imaging of cryofixed cells using Raman and fluorescence structured illumination microscopy (SIM). Cryofixation preserves structures and chemical states of samples in their near-native states, allowing multimodal imaging without artifacts caused by temporal discrepancy. We demonstrated multimodal imaging of cryofixed HeLa cells stained with an actin probe, where Raman microscope visualized cytochromes, proteins and lipids, and SIM visualized fluorescence-labelled actin filaments.

The CNNs have significantly advanced in analyzing cellular movements. Unfortunately, the CNN-based networks incorporate the information loss caused by the intrinsic characteristics of the convolution operators, leading to degrading the performance of cell segmentation and tracking. Researchers have proposed consecutive CNNs to overcome these limitations, although these models are still in the preproduction stage. In this study, we present a novel approach that utilizes cumulative CNNs to segment and track cells in fluorescence videos. Our method incorporates the state-of-the-art Vision Transformer (ViT) and Bayesian Network to improve accuracy and performance. By leveraging the ViT architecture and Bayesian network, we aim to mitigate information losses and enhance the precision of cell segmentation and tracking tasks.

In this work, multimodal two-photon excitation fluorescence (TPEF) and third-harmonic generation (THG) microscopy is used together with second-harmonic generation (SHG) to image gold standard hematoxylin and eosin histology slides. The nonlinear responses were investigated for hematoxylin and eosin stains. It is shown that the extracellular matrix (ECM) can be visualized using THG image contrast. THG signal is typically associated with interfaces and nanostructures where abrupt changes in the refractive index takes place, e.g. at blood vessel walls as well as the dense nuclei. Polarimetric THG provides a new method for ultrastructural ECM visualization. The ability of THG microscopy to visualize simultaneously nuclei and ECM is exemplified by imaging clinical tissue samples. THG turned out to be an excellent counterstaining contrast to SHG that reveals ECM proteins, cells and cell nuclei, which can be utilized for studying interactions between cells and ECM. Multiphoton imaging can be applied for investigation of structural changes in connective tissue due to various diseases and is beneficial in observing ECM and cell nuclei in cancer diagnostics and prognostics.

Antibiotic resistance is a critical public health concern requiring fast, affordable, and reliable diagnostic methods. This study focuses on identifying optimal wavelengths for multispectral imaging in antibiotic susceptibility testing. Deuterium isotope probing and FTIR spectroscopy were used to analyze the metabolic impact of antibiotics on bacteria. Characteristic wavelengths indicating variations in bacterial metabolism were identified. This approach holds promise for expedited antibiotic sensitivity assessment, potentially delivering results within two hours. The utilization of multispectral imaging presents a cost-effective and innovative tool for bacterial identification and combating antibiotic resistance.

Otoscopy is an important procedure for the diagnosis of otitis media allowing examiners to visually inspect a patient's eardrum. However, a traditional otoscope enables imaging of the target under white light only, limiting the capability to assess color differences and tympanum morphology, which are distinguishing features in the diagnosis of otitis media. We present a smartphone-attachable trimodal otoscope head capable of spectral, autofluorescence, and photometric 3D stereo imaging. This device uses LEDs, optical fibers, and a smartphone camera to collect quantitative spectral signatures and qualitative morphological data that carry information about the biochemistry and 3D morphology of the sampled eardrum and middle ear to aid examiners in providing precise diagnosis with ubiquitous connectivity and portability of a smartphone device, which is beneficial in telemedicine applications. Finally, we collected normal, otitis media with effusion, and adhesive otitis media data and evaluated our device’s capabilities using deep-learning classifiers.

Autofluorescence lifetime measurements allow label-free differentiation of normal and diseased tissues. This study utilized mesoscopic autofluorescence imaging on colorectal cancer (CRC) surgical specimens from 73 patients, focusing on differentiating normal, adenomatous and cancerous tissues. Collagen and FAD achieved the highest discriminative power, while NADH revealed metabolic variability within tumors. Additionally, we studied the effect of radiation on rectal cancer autofluorescence signatures, aiming to develop a method for quantifying treatment response. Our findings demonstrate the sensitivity of autofluorescence lifetime measurements to radiation-induced changes, offering potential improvements in rectal cancer management. This research contributes to CRC assessment and advances personalized treatment approaches.

Dimethyl sulfoxide (DMSO) is one of the most commonly used pharmaceutical drugs in life sciences. It has a wide spectrum of pharmacological effects, including anti-inflammatory effects, local analgesia, weak bacteriostasis and most importantly membrane penetration. We recently developed novel hyperspectral excitation-resolved near-infrared fluorescence imaging system (HER-NIRF) based on a continuous-wave wavelength-swept laser. In this study, this technique is applied for measuring the distribution of the therapeutic agent dimethyl sulfoxide (DMSO) by utilizing solvatochromic shift in the spectral profile of albumin-bound Indocyanine green (ICG). Phantom experiments are conducted to evaluate the performance of the HER-NIRF system. The results show that the distribution of DMSO can be visualized in the wide-field reflection geometry.

Optical control technologies have been demonstrated with high spatial precision. However, present methods are facing challenges in real-time selection and manipulation. To address these limitations, we present a real-time precision optical control technology (RPOC) which is a close-loop optoelectronic system integrated with a laser scanning confocal fluorescence microscope. This technology allows us to control chemical processes at the target sites in real time with high spatiotemporal precision. Using it, we demonstrated the precise generation of reactive oxygen species (ROS) solely at selected organelles and monitored ROS-induced changes in microtubule polymerization dynamics. We also selectively inhibit tubulin polymerization using RPOC with a photoswitchable inhibitor. Meanwhile, a software-based optical control system is developed for more flexible selections of chemical targets and optical manipulation.

In response to a hostile environment, some bacteria form a biofilm by secreting a glue-like matrix called extracellular polymeric substance (EPS) that functions as a physical barrier. In this work, we study the biofilm formation of Bacillus subtilis within minimal biofilm-promoting media (MSgg) and how optical trapping affects bacteria aggregation and biofilm formation. We demonstrate that a laser with a low absorbent wavelength can be used to manipulate biofilm and aggregate bacteria without causing significant photodamage. Whereas, even at low power, a laser with a high absorbent wavelength disrupts biofilm formation and causes significant photodamage to trapped bacteria.

Virtual biopsy enables non-invasive diagnosis through machine-learning analysis of high-resolution images. But difficulties in generating accurate co-registered training sets and the resolution/field-of-view (FOV) tradeoff have hindered clinical applications. We present a method enabling reliable and accurate co-registration of 3D cellular-resolution OCT of fresh human skin with downstream histology. Orientation data is encoded across the sample by photobleaching a fiduciary grid pattern into fluorescent gel encasing the tissue. These markers persist in histology sections, permitting accurate co-registration to the 3D volume within ~20µm, and enabling cellular-resolution imaging with a cm-level FOV by laterally tiling OCT volumes, crucial steps toward in-vivo high-resolution Virtual Biopsy.