Live tissue intrinsic emission microscopy using multiphoton-excited native fluorescence and second harmonic generation

Computationally Enabled Polychromatic Polarized Imaging Enables Mapping of Matrix Architectures that Promote Pancreatic Ductal Adenocarcinoma Dissemination

Pancreatic ductal adenocarcinoma (PDA) is an extremely metastatic and lethal disease. In PDA, extracellular matrix (ECM) architectures, known as tumor-associated collagen signatures (TACSs), regulate invasion and metastatic spread in both early dissemination and late-stage disease. As such, TACS has been suggested as a biomarker to aid in pathologic assessment. However, despite its significance, approaches to quantitatively capture these ECM patterns currently require advanced optical systems with signaling processing analysis. Here, we present an expansion of polychromatic polarized microscopy (PPM) with inherent angular information coupled to machine learning and computational pixel-wise analysis of TACS. Using this platform, we are able to accurately capture TACS architectures in hematoxylin and eosin-stained histology sections directly through PPM contrast. Moreover, PPM facilitated identification of transitions to dissemination architectures (ie, transitions from sequestration through expansion to dissemination from both PanINs and throughout PDA). Last, PPM evaluation of architectures in liver metastases, the most common metastatic site for PDA, demonstrates TACS-mediated focal and local invasion as well as identification of unique patterns anchoring aligned fibers into normal-adjacent tumor, suggesting that these patterns may be precursors to metastasis expansion and local spread from micrometastatic lesions. Combined, these findings demonstrate that PPM coupled to computational platforms is a powerful tool for analyzing ECM architecture that can be used to advance cancer microenvironment studies and provide clinically relevant diagnostic information.

Review of Non-Invasive Imaging Technologies for Cutaneous Melanoma

Imaging technologies are constantly being developed to improve not only melanoma diagnosis, but also staging, treatment planning, and disease progression. We start with a description of how melanoma is characterized using histology, and then continue by discussing nearly two dozen different technologies, including systems currently used in medical practice and those in development. For each technology, we describe its method of operation, how it is or would be projected to be most commonly used in diagnosing and managing melanoma, and for systems in current use, we identify at least one current manufacturer. We also provide a table including the biomarkers identified by and main limitations associated with each technology and conclude by offering suggestions on specific characteristics that might best enhance a technology's potential for widespread clinical adoption.

The Emerging Role of Second Harmonic Generation/Two Photon Excitation for Precision Digital Analysis of Liver Fibrosis in MASH Clinical Trials

Conventional histopathological evaluation of liver biopsy slides has been invaluable in assessing the causes of liver injury, the severity of the underlying disease processes, and the degree of resulting fibrosis. However, the use of conventional histologic assessments as endpoints in clinical trials is limited by the reliability of scoring systems, variability in interpretation of histologic features and translation of continuous variables into categorical scores. To increase the precision and reproducibility of liver biopsy assessment, several artificial intelligence/machine learning (AI/ML) approaches have been developed to analyse high resolution digital images of liver biopsy specimens. Multiple AI/ML platforms are in development with promising results in post-hoc analyses of clinical trial biopsies. One such technique employs images generated by Second Harmonic Generation/Two Photon Excitation (SHG/TPE) microscopy that uniquely uses unstained liver biopsies to provide high resolution images of collagen fibres to assess and quantify collagen morphometry, and avoid challenges related to staining variability. One SHG/TPE microscopy methodology coupled with AI/ML based analysis, qFibrosis™, has been used post-hoc as an exploratory endpoint in several clinical trials for metabolic dysfunction-associated steatohepatitis (MASH) demonstrating its ability to provide a consistent and more nuanced assessment of liver fibrosis that still correlates well with traditional staging. This review summarizes the development of qFibrosis and outlines the need for additional studies to validate it as a sensitive marker for changes in fibrosis in the context of treatment trials and correlate these changes with subsequent liver-related outcomes.

Off-Target Interactions of Vancomycin with Vascular Wall Involving Elastin-Induced Self-Assembly

Off-target effects, which arise from drug interactions in nontarget tissues, can lead to unfavored side effects. The treatment efficacy of vancomycin (Vanco) in Gram-positive bacterial infections is often compromised by the frequent occurrence of Vanco-induced vascular injury. However, the potential targets and underlying molecular mechanisms of this phenomenon remain unclear. Here, we developed multidimensional two-photon imaging for dynamic tracking of fluorescently labeled Vanco in vivo, characterizing the molecular behavior of Vanco in situ after administration and providing the first direct evidence of its interactions with vascular wall. Morphological analysis combined with colocalization imaging identified elastin within the vascular wall as the molecular target. After binding, Vanco underwent self-assembly into forming irregular nanoaggregates, primarily driven by electrostatic and hydrophobic forces. This persistent binding and self-assembly on the elastic lamina resulted in significant endothelial cytotoxicity and subsequent apoptosis, suggesting a mechanistic link to the vascular injury observed in clinical settings. Taken together, our findings revealed off-target molecular interactions between Vanco and vascular elastin in situ, highlighting the importance of considering unintended drug-vascular interactions.

Polychromatic Polarization Microscopy Differentiates Collagen Fiber Signatures in Benign Pancreatic Tissue and Pancreatic Ductal Adenocarcinoma

The orientation of collagen fibers in relation to malignant epithelium is known to carry prognostic information in a variety of tissues. The data are the strongest for breast and pancreatic ductal adenocarcinoma. However, information inherent in collagen fiber topology in malignant tissues remains untapped in daily surgical pathology practice, largely because collagen fibers within areas of desmoplasia cannot be resolved with standard diagnostic microscopy. The methodologies used to visualize collagen fiber orientation are either of insufficient resolution to consistently capture collagen fiber topology or require resources in time and money that do not fit into the daily surgical pathology workflow. Polychromatic polarization microscopy has the potential to bring collagen topology to the attention of pathologists during their routine work. It has been demonstrated to be equivalent to the gold standard methodology used to research collagen, second harmonic generation. We use polychromatic polarization microscopy to visualize and describe the differences in collagen topology in normal pancreas, chronic pancreatitis, and pancreatic ductal adenocarcinoma with a standard microscope, using hematoxylin and eosin-stained sections. In the process, we propose a lexicon with which to describe the morphologic characteristics of collagen in benign and malignant pancreatic tissues.

Label-free hyperspectral multiphoton microscopy

Label-free multiphoton microscopy is a powerful tool for investigating pristine biological specimens. This imaging modality leverages optical signals originating from the nonlinear response of native biomolecules to intense optical radiation, nonlinear signals that allow localizing and quantifying the constituents of specimens, driving applications in biology and medicine. However, since its inception over three decades ago, this approach has operated with a narrowband detection scheme, relying on narrow bandwidths from the entire spectra to derive imaging contrast. This detection scheme hinders the analytical power of the nonlinear microscope, preventing the rigorous unmixing of co-localized constituents with spectral overlap. In this Letter, we shift from the narrowband paradigm to the broadband, demonstrating label-free hyperspectral multiphoton imaging of biological specimens. We validate this configuration by disentangling the constituents of fresh murine tissues by virtue of nonlinear spectra.

Accelerating biopharmaceutical cell line selection with label-free multimodal nonlinear optical microscopy and machine learning

The selection of high-performing cell lines is crucial for biopharmaceutical production but is often time-consuming and labor-intensive. We investigated label-free multimodal nonlinear optical microscopy for non-perturbative profiling of biopharmaceutical cell lines based on their intrinsic molecular contrast. Employing simultaneous label-free autofluorescence multiharmonic (SLAM) microscopy with fluorescence lifetime imaging microscopy (FLIM), we characterized Chinese hamster ovary (CHO) cell lines at early passages (0-2). A machine learning (ML)-assisted analysis pipeline leveraged high-dimensional information to classify single cells into their respective lines. Remarkably, the monoclonal cell line classifiers achieved balanced accuracies exceeding 96.8% as early as passage 2. Correlation features and FLIM modality played pivotal roles in early classification. This integrated optical bioimaging and machine learning approach presents a promising solution to expedite cell line selection process while ensuring identification of high-performing biopharmaceutical cell lines. The techniques have potential for broader single-cell characterization applications in stem cell research, immunology, cancer biology and beyond.

Texture Analysis of Fibrous Meningioma Using Label-Free Multiphoton Microscopy

Fibrous meningiomas, a common type of brain tumor, present surgical challenges due to their variable hardness, which is crucial for complete resection and patient prognosis. This study explores the use of label-free multiphoton microscopy (MPM) for the objective assessment of the texture of fibrous meningiomas. Fresh tumor samples from 20 patients were analyzed using both multichannel and lambda mode MPM, with quantitative image analysis algorithms determining collagen content and multi-peak spectral fitting providing additional optical collagen metrics. The study compared medium and hard fibrous meningiomas, utilizing receiver operating characteristic analysis to evaluate predictive performance. Microstructural features were clearly visualized, enabling accurate diagnosis. Collagen-related parameters significantly differentiated between moderate and hard tumors (p < 0.05). High predictive values were observed for collagen content, collagen-to-NADH-free ratio, and collagen-to-FAD ratio (AUC = 0.748-0.839). A multivariate logistic model combining these biomarkers significantly improved diagnostic accuracy (AUC = 0.907). The findings suggest that MPM, with its ability to visualize and quantify microstructures such as collagen and cells without the need for staining, holds strong potential for rapid, objective, and accurate assessment of tumor texture during neurosurgery. The integration of MPM with multiphoton endoscopy paves the way for potential in vivo applications in the future.

FiberO for an automated quantitative analysis of fibers orientation and organization in biological fibrous tissues

Many biological fibrous tissues exhibit distinctive mechanical properties arising from their highly organized fibrous structure. In disease conditions, alterations in the primary components of these fibers, such as type I collagen molecules in bone, tendons, and ligaments, assembly into a disorganized fibers architecture generating a weak and/or brittle material. Being able to quantitatively assess the fibers orientation and organization in biological tissue may help improve our understanding of their contribution to the tissue and organ mechanical integrity, and assess disease progress and therapy effect. In this work, we present FiberO, a new open-source available software that automatically quantifies fibers orientation, by performing morphological image openings, and fibers organization within the tissue, by determining and plotting their continuity in groups. FiberO performance is here evaluated using second harmonic generation microscopy images of mouse bones and tendons as examples of biological fibrous tissues. FiberO outperformed Directionality and OrientationJ, two open-source plugins available in ImageJ, and FiberFit and CT-FIRE, in the calculation and plotting of fibers orientation in reference images with known fibers orientation. Additionally, FiberO is currently the sole software to date able to accurately track the continuity of aligned fibers, and it quantifies and displays the organized surface(s) in the tissue of interest. FiberO can be used in the wider engineering and science field to investigate the fibers orientation and organization of different natural and synthetic fibrous tissues.

Label-Free Detection of Breast Phyllodes Tumors Based on Multiphoton Microscopy

Phyllodes tumors (PTs) are rare breast stroma neoplasms, and their accurate identification at various stages is essential for personalized patient treatment. In this study, multiphoton microscopy (MPM) with two-photon excited fluorescence (TPEF) and second harmonic generation (SHG) imaging was used for label-free detection and differentiation of PTs and normal breast tissue. An automated image processing strategy was developed to quantify changes in collagen fiber morphology within the stroma and boundary of PTs, establishing optical diagnostic characteristics of PTs using MPM. The results demonstrated that MPM could be used for the detection of different stages of PTs, and the morphological alterations in collagen fibers could serve as critical indicators of PT malignancy, offering new insights for the diagnosis and grading of benign, borderline, and malignant PTs. It lays the groundwork for the future application of compact MPM for the rapid detection and diagnosis of PTs.

Hepatic Steatosis Analysis in Metabolic Dysfunction-Associated Steatotic Liver Disease Based on Artificial Intelligence

BACKGROUND

Metabolic dysfunction-associated steatotic liver disease (MASLD) is characterized by the accumulation of fat in the liver, excluding excessive alcohol consumption and other known causes of liver injury. Animal models are often used to explore different pathogenic mechanisms and therapeutic targets of MASLD. The aim of this study is to apply an artificial intelligence (AI) system based on second-harmonic generation (SHG)/two-photon-excited fluorescence (TPEF) technology to automatically assess the dynamic patterns of hepatic steatosis in MASLD mouse models.

METHODS

We evaluated the characteristics of hepatic steatosis in mouse models of MASLD using AI analysis based on SHG/TPEF images. Six different models of MASLD were induced in C57BL/6 mice by feeding with a western or high-fat diet, with or without fructose in their drinking water, and/or by weekly injections of carbon tetrachloride.

RESULTS

Body weight, serum lipids, and liver enzyme markers increased at 8 and 16 weeks in each model compared to baseline. Steatosis grade showed a steady upward trend. However, the non-alcoholic steatohepatitis (NASH) Clinical Research Network (CRN) histological scoring method detected no significant difference between 8 and 16 weeks. In contrast, AI analysis was able to quantify dynamic changes in the area, number, and size of hepatic steatosis automatically and objectively, making it more suitable for preclinical MASLD animal experiments.

CONCLUSIONS

AI recognition technology may be a new tool for the accurate diagnosis of steatosis in MASLD, providing a more precise and objective method for evaluating steatosis in preclinical murine MASLD models under various experimental and treatment conditions.

Deep and dynamic metabolic and structural imaging in living tissues

Label-free imaging through two-photon autofluorescence of NAD(P)H allows for nondestructive, high-resolution visualization of cellular activities in living systems. However, its application to thick tissues has been restricted by its limited penetration depth within 300 μm, largely due to light scattering. Here, we demonstrate that the imaging depth for NAD(P)H can be extended to more than 700 μm in living engineered human multicellular microtissues by adopting multimode fiber-based, low repetition rate, high peak power, three-photon excitation of NAD(P)H at 1100 nm. This is achieved by having more than 0.5 megawatts peak power at the band of 1100 ± 25 nm through adaptively modulating multimodal nonlinear pulse propagation with a compact fiber shaper. Moreover, the eightfold increase in pulse energy enables faster imaging of monocyte behaviors in the living multicellular models. These results represent a substantial advance for deep and dynamic imaging of intact living biosystems. The modular design is anticipated to allow wide adoption for demanding imaging applications, including cancer research, immune responses, and tissue engineering.

Diradicaloid-Loaded Polypeptide Nanoparticles for Two-Photon NIR Phototheranostics

Stable organic radicals, with unique electronic transitions from the ground state (D0) to the doublet excited state (D1), show promise as high-fluorescence quantum yield dyes. While organic small-molecule photosensitizers (PSs) have advanced for tumor photodynamic therapy (PDT), opportunities exist to enhance their performance and functionality. Herein, we synthesized Thiele's fluorocarbon derivative diradicaloid TFC-I with nearly 100% PLQY and integrated it into amphiphilic polypeptide nanoparticles, P-TI, using a precursor-doping approach. P-TI demonstrated notable features including high photostability, aggregation-induced emission, bright near-infrared fluorescence, substantial quantum yield (37% PLQY), robust near-infrared two-photon absorption (∼400 GM cross section), and superior ROS generation compared to commercial PSs. In vitro and in vivo experiments confirmed that P-TI performed well in mitochondria-targeted PDT, two-photon fluorescence imaging, and biosafety. This work highlights the use of organic stable radicals with precursor-doping for efficient PDT and deep tumor tissue imaging.

Label-Free Monitoring of Endometrial Cancer Progression Using Multiphoton Microscopy

Endometrial cancer is the most common gynecological cancer in the developed world. However, the accuracy of current diagnostic methods is still unsatisfactory and time-consuming. Here, we presented an alternate approach to monitoring the progression of endometrial cancer via multiphoton microscopy imaging and analysis of collagen, which is often overlooked in current endometrial cancer diagnosis protocols but can offer a crucial signature in cancer biology. Multiphoton microscopy (MPM) based on the second-harmonic generation and two-photon excited fluorescence was introduced to visualize the microenvironment of endometrium in normal, hyperplasia without atypia, atypical hyperplasia, and endometrial cancer specimens. Furthermore, automatic image analysis based on the MPM image processing algorithm was used to quantify the differences in the collagen morphological features among them. MPM enables the visualization of the morphological details and alterations of the glands in the development process of endometrial cancer, including irregular changes in the structure of the gland, increased ratio of the gland to the interstitium, and atypical changes in the glandular epithelial cells. Moreover, the destructed basement membrane caused by gland proliferation and fusion is clearly shown in SHG images, which is a key feature for identifying endometrial cancer progression. Quantitative analysis reveals that the formation of endometrial cancer is accompanied by an increase in collagen fiber length and width, a progressive linearization and loosening of interstitial collagen, and a more random arrangement of interstitial collagen. Observation and quantitative analysis of interstitial collagen provide invaluable information in monitoring the progression of endometrial cancer. Label-free multiphoton imaging reported here has the potential to become an in situ histological tool for effective and accurate early diagnosis and detection of malignant lesions in endometrial cancer.

Targeting overexpressed surface proteins: A new strategy to manage the recalcitrant triple-negative breast cancer

Triple-negative breast cancer (TNBC) is an aggressive and heterogeneous cancer that lacks all three molecular markers, Estrogen, Progesterone, and Human Epidermal Growth Factor Receptor 2 (HER2). This unique characteristic of TNBC makes it more resistant to hormonal therapy; hence, chemotherapy and surgery are preferred. Active targeting with nanoparticles is more effective in managing TNBC than a passive approach. The surface of TNBC cells overexpresses several cell-specific proteins, which can be explored for diagnostic and therapeutic purposes. Immunohistochemical analysis has revealed that TNBC cells overexpress αVβ3 integrin, Intercellular Adhesion Molecule 1 (ICAM-1), Glucose Transporter 5 (GLUT5), Transmembrane Glycoprotein Mucin 1 (MUC-1), and Epidermal Growth Factor Receptor (EGFR). These surface proteins can be targeted using ligands, such as aptamers, antibodies, and sugar molecules. Targeting the surface proteins of TNBC with ligands helps harmonize treatment and improve patient compliance. In this review, we discuss the proteins expressed, which are limited to αVβ3 integrin proteins, ICAM-1, GLUT-5, MUC1, and EGFR, on the surface of TNBC, the challenges associated with the preclinical setup of breast cancer for targeted nanoformulations, internalization techniques and their challenges, suggestions to overcome the limitations of successful translation of nanoparticles, and the possibility of ligand-conjugated nanoparticles targeting these surface receptors for a better therapeutic outcome.

Quantitative Assessment of Collagen Remodeling during a Murine Pregnancy

Uterine cervical remodeling is a fundamental feature of pregnancy, facilitating the delivery of the fetus through the cervical canal. Yet, we still know very little about this process due to the lack of methodologies that can quantitatively and unequivocally pinpoint the changes the cervix undergoes during pregnancy. We utilize polarization-resolved second harmonic generation to visualize the alterations the cervix extracellular matrix, specifically collagen, undergoes during pregnancy with exquisite resolution. This technique provides images of the collagen orientation at the pixel level (0.4 μm) over the entire murine cervical section. They show tight and ordered packing of collagen fibers around the os at the early stage of pregnancy and their disruption at the later stages. Furthermore, we utilize a straightforward statistical analysis to demonstrate the loss of order in the tissue, consistent with the loss of mechanical properties associated with this process. This work provides a deeper understanding of the parturition process and could support research into the cause of pathological or premature birth.

Towards next-generation diagnostic pathology: AI-empowered label-free multiphoton microscopy

Diagnostic pathology, historically dependent on visual scrutiny by experts, is essential for disease detection. Advances in digital pathology and developments in computer vision technology have led to the application of artificial intelligence (AI) in this field. Despite these advancements, the variability in pathologists' subjective interpretations of diagnostic criteria can lead to inconsistent outcomes. To meet the need for precision in cancer therapies, there is an increasing demand for accurate pathological diagnoses. Consequently, traditional diagnostic pathology is evolving towards "next-generation diagnostic pathology", prioritizing on the development of a multi-dimensional, intelligent diagnostic approach. Using nonlinear optical effects arising from the interaction of light with biological tissues, multiphoton microscopy (MPM) enables high-resolution label-free imaging of multiple intrinsic components across various human pathological tissues. AI-empowered MPM further improves the accuracy and efficiency of diagnosis, holding promise for providing auxiliary pathology diagnostic methods based on multiphoton diagnostic criteria. In this review, we systematically outline the applications of MPM in pathological diagnosis across various human diseases, and summarize common multiphoton diagnostic features. Moreover, we examine the significant role of AI in enhancing multiphoton pathological diagnosis, including aspects such as image preprocessing, refined differential diagnosis, and the prognostication of outcomes. We also discuss the challenges and perspectives faced by the integration of MPM and AI, encompassing equipment, datasets, analytical models, and integration into the existing clinical pathways. Finally, the review explores the synergy between AI and label-free MPM to forge novel diagnostic frameworks, aiming to accelerate the adoption and implementation of intelligent multiphoton pathology systems in clinical settings.

Deep-ultraviolet Fourier ptychography (DUV-FP) for label-free biochemical imaging via feature-domain optimization

We present deep-ultraviolet Fourier ptychography (DUV-FP) for high-resolution chemical imaging of biological specimens in their native state without exogenous stains. This approach uses a customized 265-nm DUV LED array for angle-varied illumination, leveraging the unique DUV absorption properties of biomolecules at this wavelength region. We implemented a robust feature-domain optimization framework to overcome common challenges in Fourier ptychographic reconstruction, including vignetting, pupil aberrations, stray light problems, intensity variations, and other systematic errors. By using a 0.12 numerical aperture low-resolution objective lens, our DUV-FP prototype can resolve the 345-nm linewidth on a resolution target, demonstrating at least a four-fold resolution gain compared to the captured raw images. Testing on various biospecimens demonstrates that DUV-FP significantly enhances absorption-based chemical contrast and reveals detailed structural and molecular information. To further address the limitations of conventional FP in quantitative phase imaging, we developed a spatially coded DUV-FP system. This platform enables true quantitative phase imaging of biospecimens with DUV light, overcoming the non-uniform phase response inherent in traditional microscopy techniques. The demonstrated advancements in high-resolution, label-free chemical imaging may accelerate developments in digital pathology, potentially enabling rapid, on-site analysis of biopsy samples in clinical settings.

Emerging Functional Connections Between Metabolism and Epigenetic Remodeling in Neural Differentiation

Stem cells possess extraordinary capacities for self-renewal and differentiation, making them highly valuable in regenerative medicine. Among these, neural stem cells (NSCs) play a fundamental role in neural development and repair processes. NSC characteristics and fate are intricately regulated by the microenvironment and intracellular signaling. Interestingly, metabolism plays a pivotal role in orchestrating the epigenome dynamics during neural differentiation, facilitating the transition from undifferentiated NSC to specialized neuronal and glial cell types. This intricate interplay between metabolism and the epigenome is essential for precisely regulating gene expression patterns and ensuring proper neural development. This review highlights the mechanisms behind metabolic regulation of NSC fate and their connections with epigenetic regulation to shape transcriptional programs of stemness and neural differentiation. A comprehensive understanding of these molecular gears appears fundamental for translational applications in regenerative medicine and personalized therapies for neurological conditions.

Multiphoton fluorescence microscopy for in vivo imaging

Multiphoton fluorescence microscopy (MPFM) has been a game-changer for optical imaging, particularly for studying biological tissues deep within living organisms. MPFM overcomes the strong scattering of light in heterogeneous tissue by utilizing nonlinear excitation that confines fluorescence emission mostly to the microscope focal volume. This enables high-resolution imaging deep within intact tissue and has opened new avenues for structural and functional studies. MPFM has found widespread applications and has led to numerous scientific discoveries and insights into complex biological processes. Today, MPFM is an indispensable tool in many research communities. Its versatility and effectiveness make it a go-to technique for researchers investigating biological phenomena at the cellular and subcellular levels in their native environments. In this Review, the principles, implementations, capabilities, and limitations of MPFM are presented. Three application areas of MPFM, neuroscience, cancer biology, and immunology, are reviewed in detail and serve as examples for applying MPFM to biological research.

Autofluorescence lifetime flow cytometry with time-correlated single photon counting

Autofluorescence lifetime imaging microscopy (FLIM) is sensitive to metabolic changes in single cells based on changes in the protein-binding activities of the metabolic co-enzymes NAD(P)H. However, FLIM typically relies on time-correlated single-photon counting (TCSPC) detection electronics on laser-scanning microscopes, which are expensive, low-throughput, and require substantial post-processing time for cell segmentation and analysis. Here, we present a fluorescence lifetime-sensitive flow cytometer that offers the same TCSPC temporal resolution in a flow geometry, with low-cost single-photon excitation sources, a throughput of tens of cells per second, and real-time single-cell analysis. The system uses a 375 nm picosecond-pulsed diode laser operating at 50 MHz, alkali photomultiplier tubes, an FPGA-based time tagger, and can provide real-time phasor-based classification (i.e., gating) of flowing cells. A CMOS camera produces simultaneous brightfield images using far-red illumination. A second PMT provides two-color analysis. Cells are injected into the microfluidic channel using a syringe pump at 2-5 mm/s with nearly 5 ms integration time per cell, resulting in a light dose of 2.65 J/cm2 that is well below damage thresholds (25 J/cm2 at 375 nm). Our results show that cells remain viable after measurement, and the system is sensitive to autofluorescence lifetime changes in Jurkat T cells with metabolic perturbation (sodium cyanide), quiescent versus activated (CD3/CD28/CD2) primary human T cells, and quiescent versus activated primary adult mouse neural stem cells, consistent with prior studies using multiphoton FLIM. This TCSPC-based autofluorescence lifetime flow cytometer provides a valuable label-free method for real-time analysis of single-cell function and metabolism with higher throughput than laser-scanning microscopy systems.

Research of Pulmonary Fibrosis Lesions Based on FLIM and SHG Imaging Microscopy

Two-photon fluorescence lifetime microscopy (TP-FLIM) is a powerful quantitative imaging technique that characterizes and analyzes the structure and function of biological samples through a combination of intensity and lifetime imaging. Because TP-FLIM is independent of the fluorescence signal intensity and the fluorophore concentration, it is widely used in high-throughput, high-content drug screening and clinical diagnostics. Second harmonic generation (SHG) imaging technology has the advantages of high spatial resolution and imaging depth inherent to nonlinear optical imaging. Second harmonics often appear in noncentrosymmetric structures. Collagen tissue in biological organisms is a good example of these structures, showing strong harmonic effects. Therefore, SHG has been widely used for imaging of specific tissue structure imaging. TP-FLIM technology is highly sensitive for quantitatively detecting changes in microenvironments. The objective of this study is to examine pathological pulmonary fibrosis slices using a combined approach of TP-FLIM and SHG technology. The fluorescence lifetime data of pulmonary collagen fibers are analyzed by using phasor plot analysis methods, and normal collagen fibers and fibrotic collagen fibers are distinguished by calculating the aspect ratio from the SHG images formed by the collagen fibers. Our study provides a new method for a deeper understanding of the pathological mechanisms and clinical diagnosis of pulmonary fibrosis and other collagen fiber-related disorders.

METAPHOR: Metabolic evaluation through phasor-based hyperspectral imaging and organelle recognition for mouse blastocysts and oocytes

Only 30% of embryos from in vitro fertilized oocytes successfully implant and develop to term, leading to repeated transfer cycles. To reduce time-to-pregnancy and stress for patients, there is a need for a diagnostic tool to better select embryos and oocytes based on their physiology. The current standard employs brightfield imaging, which provides limited physiological information. Here, we introduce METAPHOR: Metabolic Evaluation through Phasor-based Hyperspectral Imaging and Organelle Recognition. This non-invasive, label-free imaging method combines two-photon illumination and AI to deliver the metabolic profile of embryos and oocytes based on intrinsic autofluorescence signals. We used it to classify i) mouse blastocysts cultured under standard conditions or with depletion of selected metabolites (glucose, pyruvate, lactate); and ii) oocytes from young and old mouse females, or in vitro-aged oocytes. The imaging process was safe for blastocysts and oocytes. The METAPHOR classification of control vs. metabolites-depleted embryos reached an area under the ROC curve (AUC) of 93.7%, compared to 51% achieved for human grading using brightfield imaging. The binary classification of young vs. old/in vitro-aged oocytes and their blastulation prediction using METAPHOR reached an AUC of 96.2% and 82.2%, respectively. Finally, organelle recognition and segmentation based on the flavin adenine dinucleotide signal revealed that quantification of mitochondria size and distribution can be used as a biomarker to classify oocytes and embryos. The performance and safety of the method highlight the accuracy of noninvasive metabolic imaging as a complementary approach to evaluate oocytes and embryos based on their physiology.

Imaging of colorectal adenomas with pseudoinvasion and malignant polyps using two-photon excitation microscopy

Introduction

Although the incidence and mortality rates of colorectal cancer exhibit significant variability, it remains one of the most prevalent cancers worldwide. Endeavors to prevent colorectal cancer development focus on detecting precursor lesions during colonoscopy. The diagnosis of endoscopically resected polyps relies on hematoxylin and eosin staining examination. For challenging cases like adenomatous polyps with epithelial misplacement, additional diagnostic methods could prove beneficial.

Methods

This paper aims to underscore stromal changes observed in malignant polyps and polyps with pseudoinvasion, leveraging two-photon excitation microscopy (TPEM), a technique extensively employed in the medical field in recent years.

Results and discussions

Both the subjective and quantitative analysis of TPEM images revealed distinct distributions and densities of collagen at the invasion front in malignant polyps compared to areas of pseudoinvasion. TPEM holds potential in discerning true invasion in malignant polyps from pseudoinvasion, offering enhanced visualization of local stromal changes.

[The gut, a whistleblower, in the early stages of Parkinson's disease]

The enteric nervous system (ENS), often called the "second brain", plays a crucial role in regulating digestive functions. Dysfunctions of the ENS are associated with several diseases such as Parkinson's disease. Recent studies suggest that early digestive disorders, notably chronic constipation, may be early signs of this neurodegenerative disease. Three-dimensional imaging of the ENS offers new insights into early diagnosis, in particular through the analysis of intestinal biopsies. This new research axis raises questions about the intestinal cause of Parkinson's disease, and opens the door to a better understanding and earlier treatment of this disease.

The polyphenolic compound punicalagin protects skin fibroblasts from UVA radiation oxidative damage

Polyphenols are a class of natural compounds that act as antioxidants, neutralising harmful free radicals that would damage cells and increase the risk of diseases such as cancer, diabetes and heart disease. They also reduce inflammation, which is thought to be at the root of many chronic diseases. We are investigating the photoprotective effects of punicalagin, a type of polyphenolic compound mainly found in pomegranates, against UVA-induced damage in human skin fibroblasts. Punicalagin increases cell viability and reduces the high levels of ROS generated by photooxidative stress through its ability to modulate the Nrf2 transcriptional pathway. Interestingly, activation of the Nrf2 pathway results in an increase in reduced glutathione, NADH, and subsequently protects mitochondrial respiratory capacity. Integrating molecular and imaging approaches, our results demonstrate a potential cytoprotective effect of punicalagin against UVA-induced skin damage through an anti-apoptotic mechanism.

Autofluorescence lifetime flow cytometry with time-correlated single photon counting

Autofluorescence lifetime imaging microscopy (FLIM) is sensitive to metabolic changes in single cells based on changes in the protein-binding activities of the metabolic co-enzymes NAD(P)H. However, FLIM typically relies on time-correlated single-photon counting (TCSPC) detection electronics on laser-scanning microscopes, which are expensive, low-throughput, and require substantial post-processing time for cell segmentation and analysis. Here, we present a fluorescence lifetime-sensitive flow cytometer that offers the same TCSPC temporal resolution in a flow geometry, with low-cost single-photon excitation sources, a throughput of tens of cells per second, and real-time single-cell analysis. The system uses a 375nm picosecond-pulsed diode laser operating at 50MHz, alkali photomultiplier tubes, an FPGA-based time tagger, and can provide real-time phasor-based classification ( i.e ., gating) of flowing cells. A CMOS camera produces simultaneous brightfield images using far-red illumination. A second PMT provides two-color analysis. Cells are injected into the microfluidic channel using a syringe pump at 2-5 mm/s with nearly 5ms integration time per cell, resulting in a light dose of 2.65 J/cm 2 that is well below damage thresholds (25 J/cm 2 at 375 nm). Our results show that cells remain viable after measurement, and the system is sensitive to autofluorescence lifetime changes in Jurkat T cells with metabolic perturbation (sodium cyanide), quiescent vs. activated (CD3/CD28/CD2) primary human T cells, and quiescent vs. activated primary adult mouse neural stem cells, consistent with prior studies using multiphoton FLIM. This TCSPC-based autofluorescence lifetime flow cytometer provides a valuable label-free method for real-time analysis of single-cell function and metabolism with higher throughput than laser-scanning microscopy systems.

Improving the diagnosis of ductal carcinoma in situ with microinvasion without immunohistochemistry: An innovative method with H&E-stained and multiphoton microscopy images

Ductal carcinoma in situ with microinvasion (DCISM) is a challenging subtype of breast cancer with controversial invasiveness and prognosis. Accurate diagnosis of DCISM from ductal carcinoma in situ (DCIS) is crucial for optimal treatment and improved clinical outcomes. However, there are often some suspicious small cancer nests in DCIS, and it is difficult to diagnose the presence of intact myoepithelium by conventional hematoxylin and eosin (H&E) stained images. Although a variety of biomarkers are available for immunohistochemical (IHC) staining of myoepithelial cells, no single biomarker is consistently sensitive to all tumor lesions. Here, we introduced a new diagnostic method that provides rapid and accurate diagnosis of DCISM using multiphoton microscopy (MPM). Suspicious foci in H&E-stained images were labeled as regions of interest (ROIs), and the nuclei within these ROIs were segmented using a deep learning model. MPM was used to capture images of the ROIs in H&E-stained sections. The intensity of two-photon excitation fluorescence (TPEF) in the myoepithelium was significantly different from that in tumor parenchyma and tumor stroma. Through the use of MPM, the myoepithelium and basement membrane can be easily observed via TPEF and second-harmonic generation (SHG), respectively. By fusing the nuclei in H&E-stained images with MPM images, DCISM can be differentiated from suspicious small cancer clusters in DCIS. The proposed method demonstrated good consistency with the cytokeratin 5/6 (CK5/6) myoepithelial staining method (kappa coefficient = 0.818).

Molecular histopathology of matrix proteins through autofluorescence super-resolution microscopy

Extracellular matrix diseases like fibrosis are elusive to diagnose early on, to avoid complete loss of organ function or even cancer progression, making early diagnosis crucial. Imaging the matrix densities of proteins like collagen in fixed tissue sections with suitable stains and labels is a standard for diagnosis and staging. However, fine changes in matrix density are difficult to realize by conventional histological staining and microscopy as the matrix fibrils are finer than the resolving capacity of these microscopes. The dyes further blur the outline of the matrix and add a background that bottlenecks high-precision early diagnosis of matrix diseases. Here we demonstrate the multiple signal classification method-MUSICAL-otherwise a computational super-resolution microscopy technique to precisely estimate matrix density in fixed tissue sections using fibril autofluorescence with image stacks acquired on a conventional epifluorescence microscope. We validated the diagnostic and staging performance of the method in extracted collagen fibrils, mouse skin during repair, and pre-cancers in human oral mucosa. The method enables early high-precision label-free diagnosis of matrix-associated fibrotic diseases without needing additional infrastructure or rigorous clinical training.

Quantifying in vivo collagen reorganization during immunotherapy in murine melanoma with second harmonic generation imaging

Significance

Increased collagen linearization and deposition during tumorigenesis can impede immune cell infiltration and lead to tumor metastasis. Although melanoma is well studied in immunotherapy research, studies that quantify collagen changes during melanoma progression and treatment are lacking.

Aim

We aim to image in vivo collagen in preclinical melanoma models during immunotherapy and quantify the collagen phenotype in treated and control mice.

Approach

Second-harmonic generation imaging of collagen was performed in mouse melanoma tumors in vivo over a treatment time course. Animals were treated with a curative radiation and immunotherapy combination. Collagen morphology was quantified over time at an image and single-fiber level using CurveAlign and CT-FIRE software.

Results

In immunotherapy-treated mice, collagen was reorganized toward a healthy phenotype, including shorter, wider, curlier collagen fibers, with modestly higher collagen density. Temporally, collagen fiber straightness and length changed late in treatment (days 9 and 12), while width and density changed early (day 6) compared with control mice. Single-fiber collagen features calculated in CT-FIRE were the most sensitive to the changes among treatment groups compared with bulk collagen features.

Conclusions

Quantitative second-harmonic generation imaging can provide insight into collagen dynamics in vivo during immunotherapy, with key implications in improving immunotherapy response in melanoma and other cancers.

Analysis of age-related changes in the left ventricular myocardium with multiphoton microscopy

Aging induces cardiac remodeling, resulting in an increase in the risk of suffering heart diseases, including heart failure. Collagen deposition increases with age and, together with sarcomeric changes in cardiomyocytes, may lead to ventricular stiffness. Multiphoton (MP) microscopy is a useful technique to visualize and detect variations in cardiac structures in a label free fashion. Here, we propose a method based on MP imaging (both two-photon excitation fluorescence (TPEF) and second harmonic generation (SHG) modalities) to explore and objectively quantify age-related structural differences in various components of cardiac tissues. Results in transmural porcine left ventricle (LV) sections reveal significant differences when comparing samples from young and old animals. Collagen and myosin SHG signals in old specimens are respectively 3.8x and >6-fold larger than in young ones. Differences in TPEF signals from cardiomyocyte were ∼3x. Moreover, the increased amount of collagen in old specimens results in a more organized pattern when compared to young LV tissues. Since changes in collagen and myosin are associated with cardiac dysfunction, the technique used herein might be a useful tool to accurately predict and measure changes associated with age-related myocardium fibrosis, tissue remodeling and sarcomeric alterations, with potential implications in preventing heart disease.

The use of fluorescence lifetime imaging (FLIM) for in situ microbial detection in complex mineral substrates

The utility of fluorescence lifetime imaging microscopy (FLIM) for identifying bacteria in complex mineral matrices was investigated. Baseline signals from unlabelled Bacillus subtilis and Euglena gracilis, and Bacillus subtilis labelled with SYTO 9 were obtained using two-photon excitation at 730, 750 and 800 nm, identifying characteristic lifetimes of photosynthetic pigments, unpigmented cellular autofluorescence, and SYTO 9. Labelled and unlabelled B. subtilis were seeded onto marble and gypsum samples containing endolithic photosynthetic cyanobacteria and the ability to distinguish cells from mineral autofluorescence and nonspecific dye staining was examined in parallel with ordinary multichannel confocal imaging. It was found that FLIM enabled discrimination of SYTO 9 labelled cells from background, but that the lifetime of SYTO 9 was shorter in cells on minerals than in pure culture under our conditions. Photosynthetic microorganisms were easily observed using both FLIM and confocal. Unlabelled, nonpigmented bacteria showed weak signals that were difficult to distinguish from background when minerals were present, though cellular autofluorescence consistent with NAD(P)H could be seen in pure cultures, and phasor analysis permitted detection on rocks. Gypsum and marble samples showed similar autofluorescence profiles, with little autofluorescence in the yellow-to-red range. Lifetime or time-gated imaging may prove a useful tool for environmental microbiology. LAY DESCRIPTION: The standard method of bacterial enumeration is to label the cells with a fluorescent dye and count them under high-power fluorescence microscopy. However, this can be difficult when the cells are embedded in soil and rock due to fluorescence from the surrounding minerals and dye binding to ambiguous features of the substrate. The use of fluorescence lifetime imaging (FLIM) can disambiguate these signals and allow for improved detection of bacteria in environmental samples.

Label-free assessment of pathological changes in pancreatic intraepithelial neoplasia by biomedical multiphoton microscopy

Pancreatic intraepithelial neoplasia (PanIN) is the most common precursor lesion that has the potential to progress to invasive pancreatic cancer, and early and rapid detection may offer patients a chance for treatment before the development of invasive carcinoma. Therefore, the identification of PanIN holds significant clinical importance. In this study, we first used multiphoton microscopy (MPM) combining two-photon excitation fluorescence and second-harmonic generation imaging to label-free detect PanIN and attempted to differentiate between normal pancreatic ducts and different grades of PanIN. Then, we also developed an automatic image processing strategy to extract eight morphological features of collagen fibers from MPM images to quantify the changes in collagen fibers surrounding the ducts. Experimental results demonstrate that the combination of MPM and quantitative information can accurately identify normal pancreatic ducts and different grades of PanIN. This study may contribute to the rapid diagnosis of pancreatic diseases and may lay the foundation for further clinical application of MPM.

Multiplexed 3D Analysis of Immune States and Niches in Human Tissue

Tissue homeostasis and the emergence of disease are controlled by changes in the proportions of resident and recruited cells, their organization into cellular neighbourhoods, and their interactions with acellular tissue components. Highly multiplexed tissue profiling (spatial omics)1 makes it possible to study this microenvironment in situ, usually in 4-5 micron thick sections (the standard histopathology format)2. Microscopy-based tissue profiling is commonly performed at a resolution sufficient to determine cell types but not to detect subtle morphological features associated with cytoskeletal reorganisation, juxtracrine signalling, or membrane trafficking3. Here we describe a high-resolution 3D imaging approach able to characterize a wide variety of organelles and structures at sub-micron scale while simultaneously quantifying millimetre-scale spatial features. This approach combines cyclic immunofluorescence (CyCIF) imaging4 of over 50 markers with confocal microscopy of archival human tissue thick enough (30-40 microns) to fully encompass two or more layers of intact cells. 3D imaging of entire cell volumes substantially improves the accuracy of cell phenotyping and allows cell proximity to be scored using plasma membrane apposition, not just nuclear position. In pre-invasive melanoma in situ5, precise phenotyping shows that adjacent melanocytic cells are plastic in state and participate in tightly localised niches of interferon signalling near sites of initial invasion into the underlying dermis. In this and metastatic melanoma, mature and precursor T cells engage in an unexpectedly diverse array of juxtracrine and membrane-membrane interactions as well as looser "neighbourhood" associations6 whose morphologies reveal functional states. These data provide new insight into the transitions occurring during early tumour formation and immunoediting and demonstrate the potential for phenotyping of tissues at a level of detail previously restricted to cultured cells and organoids.

More than double the fun with two-photon excitation microscopy

For generations researchers have been observing the dynamic processes of life through the lens of a microscope. This has offered tremendous insights into biological phenomena that span multiple orders of time- and length-scales ranging from the pure magic of molecular reorganization at the membrane of immune cells, to cell migration and differentiation during development or wound healing. Standard fluorescence microscopy techniques offer glimpses at such processes in vitro, however, when applied in intact systems, they are challenged by reduced signal strengths and signal-to-noise ratios that result from deeper imaging. As a remedy, two-photon excitation (TPE) microscopy takes a special place, because it allows us to investigate processes in vivo, in their natural environment, even in a living animal. Here, we review the fundamental principles underlying TPE aimed at basic and advanced microscopy users interested in adopting TPE for intravital imaging. We focus on applications in neurobiology, present current trends towards faster, wider and deeper imaging, discuss the combination with photon counting technologies for metabolic imaging and spectroscopy, as well as highlight outstanding issues and drawbacks in development and application of these methodologies.

Open-top Bessel beam two-photon light sheet microscopy for three-dimensional pathology

Nondestructive pathology based on three-dimensional (3D) optical microscopy holds promise as a complement to traditional destructive hematoxylin and eosin (H&E) stained slide-based pathology by providing cellular information in high throughput manner. However, conventional techniques provided superficial information only due to shallow imaging depths. Herein, we developed open-top two-photon light sheet microscopy (OT-TP-LSM) for intraoperative 3D pathology. An extended depth of field two-photon excitation light sheet was generated by scanning a nondiffractive Bessel beam, and selective planar imaging was conducted with cameras at 400 frames/s max during the lateral translation of tissue specimens. Intrinsic second harmonic generation was collected for additional extracellular matrix (ECM) visualization. OT-TP-LSM was tested in various human cancer specimens including skin, pancreas, and prostate. High imaging depths were achieved owing to long excitation wavelengths and long wavelength fluorophores. 3D visualization of both cells and ECM enhanced the ability of cancer detection. Furthermore, an unsupervised deep learning network was employed for the style transfer of OT-TP-LSM images to virtual H&E images. The virtual H&E images exhibited comparable histological characteristics to real ones. OT-TP-LSM may have the potential for histopathological examination in surgical and biopsy applications by rapidly providing 3D information.

Supercontinuum intrinsic fluorescence imaging heralds free view of living systems

Optimal imaging strategies remain underdeveloped to maximize information for fluorescence microscopy while minimizing the harm to fragile living systems. Taking hint from the supercontinuum generation in ultrafast laser physics, we generated supercontinuum fluorescence from untreated unlabeled live samples before nonlinear photodamage onset. Our imaging achieved high-content cell phenotyping and tissue histology, identified bovine embryo polarization, quantified aging-related stress across cell types and species, demystified embryogenesis before and after implantation, sensed drug cytotoxicity in real-time, scanned brain area for targeted patching, optimized machine learning to track small moving organisms, induced two-photon phototropism of leaf chloroplasts under two-photon photosynthesis, unraveled microscopic origin of autumn colors, and interrogated intestinal microbiome. The results enable a facility-type microscope to freely explore vital molecular biology across life sciences.

SLAM medical imaging enabled by pre-chirp and gain jointly managed Yb-fiber laser

We demonstrate a pre-chirp and gain jointly managed Yb-fiber laser that drives simultaneous label-free autofluorescence-multiharmonic (SLAM) medical imaging. We show that a gain managed Yb-fiber amplifier produces high-quality compressed pulses when the seeding pulses exhibit proper negative pre-chirp. The resulting laser source can generate 43-MHz, 34-fs pulses centered at 1110 nm with more than 90-nJ energy. We apply this ultrafast source to SLAM imaging of cellular and extracellular components in various human tissues of intestinal adenocarcinoma, lung adenocarcinoma, and liver.

Mapping of individual sensory nerve axons from digits to spinal cord with the transparent embedding solvent system

Achieving uniform optical resolution for a large tissue sample is a major challenge for deep imaging. For conventional tissue clearing methods, loss of resolution and quality in deep regions is inevitable due to limited transparency. Here we describe the Transparent Embedding Solvent System (TESOS) method, which combines tissue clearing, transparent embedding, sectioning and block-face imaging. We used TESOS to acquire volumetric images of uniform resolution for an adult mouse whole-body sample. The TESOS method is highly versatile and can be combined with different microscopy systems to achieve uniformly high resolution. With a light sheet microscope, we imaged the whole body of an adult mouse, including skin, at a uniform 0.8 × 0.8 × 3.5 μm3 voxel resolution within 120 h. With a confocal microscope and a 40×/1.3 numerical aperture objective, we achieved a uniform sub-micron resolution in the whole sample to reveal a complete projection of individual nerve axons within the central or peripheral nervous system. Furthermore, TESOS allowed the first mesoscale connectome mapping of individual sensory neuron axons spanning 5 cm from adult mouse digits to the spinal cord at a uniform sub-micron resolution.

Simultaneous label-free autofluorescence multi-harmonic microscopy driven by the supercontinuum generated from a bulk nonlinear crystal

Nonlinear microscopy encompasses several imaging techniques that leverage laser technology to probe intrinsic molecules of biological specimens. These native molecules produce optical fingerprints that allow nonlinear microscopes to reveal the chemical composition and structure of cells and tissues in a label-free and non-destructive fashion, information that enables a plethora of applications, e.g., real-time digital histopathology or image-guided surgery. Because state-of-the-art lasers exhibit either a limited bandwidth or reduced wavelength tunability, nonlinear microscopes lack the spectral support to probe different biomolecules simultaneously, thus losing analytical potential. Therefore, a conventional nonlinear microscope requires multiple or tunable lasers to individually excite endogenous molecules, increasing both the cost and complexity of the system. A solution to this problem is supercontinuum generation, a nonlinear optical phenomenon that supplies broadband femtosecond radiation, granting a wide spectrum for concurrent molecular excitation. This study introduces a source for nonlinear multiphoton microscopy based on the supercontinuum generation from a yttrium aluminum garnet (YAG) crystal, an approach that allows simultaneous label-free autofluorescence multi-harmonic imaging of biological samples and offers a practical and compact alternative for the clinical translation of nonlinear microscopy. While this supercontinuum covered the visible spectrum (550-900 nm) and the near-infrared region (950-1200 nm), the pulses within 1030-1150 nm produced label-free volumetric chemical images of ex vivo chinchilla kidney, thus validating the supercontinuum from bulk crystals as a powerful source for multimodal nonlinear microscopy.

Multidimensional Widefield Infrared-Encoded Spontaneous Emission Microscopy: Distinguishing Chromophores by Ultrashort Infrared Pulses

Photoluminescence (PL) imaging has broad applications in visualizing biological activities, detecting chemical species, and characterizing materials. However, the chemical information encoded in the PL images is often limited by the overlapping emission spectra of chromophores. Here, we report a PL microscopy based on the nonlinear interactions between mid-infrared and visible excitations on matters, which we termed MultiDimensional Widefield Infrared-encoded Spontaneous Emission (MD-WISE) microscopy. MD-WISE microscopy can distinguish chromophores that possess nearly identical emission spectra via conditions in a multidimensional space formed by three independent variables: the temporal delay between the infrared and the visible pulses (t), the wavelength of visible pulses (λvis), and the frequencies of the infrared pulses (ωIR). This method is enabled by two mechanisms: (1) modulating the optical absorption cross sections of molecular dyes by exciting specific vibrational functional groups and (2) reducing the PL quantum yield of semiconductor nanocrystals, which was achieved through strong field ionization of excitons. Importantly, MD-WISE microscopy operates under widefield imaging conditions with a field of view of tens of microns, other than the confocal configuration adopted by most nonlinear optical microscopies, which require focusing the optical beams tightly. By demonstrating the capacity of registering multidimensional information into PL images, MD-WISE microscopy has the potential of expanding the number of species and processes that can be simultaneously tracked in high-speed widefield imaging applications.

Comparison of Retinal Metabolic Activity and Structural Development between rd10 Mice and Normal Mice Using Multiphoton Fluorescence Lifetime Imaging Microscopy

Fluorescence lifetime imaging microscopy (FLIM) is a technique that analyzes the metabolic state of tissues based on the spatial distribution of fluorescence lifetimes of certain interacting molecules. We used multiphoton FLIM to study the metabolic state of developing C57BL6/J and rd10 retinas based on the fluorescence lifetimes of free versus bound nicotinamide adenine dinucleotide and nicotinamide adenine dinucleotide phosphate (NAD(P)H), with free NAD(P)H percentages suggesting increased glycolysis and bound NAD(P)H percentages indicating oxidative phosphorylation. The mice were sacrificed and enucleated at various time points throughout their first 3 months of life. The isolated eyecups were fixed, sectioned using a polyacrylamide gel embedding technique, and then analyzed with FLIM. The results suggested that in both C57BL6/J mice and rd10 mice, oxidative phosphorylation initially decreased and then increased, plateauing over time. This trend, however, was accelerated in rd10 mice, with its turning point occurring at p10 versus the p30 turning point in C57BL6/J mice. There was also a noticeable difference in oxidative phosphorylation rates between the outer and inner retinas in both strains, with greater oxidative phosphorylation present in the latter. A greater understanding of rd10 and WT metabolic changes during retinal development may provide deeper insights into retinal degeneration and facilitate the development of future treatments.

Label-free single-cell live imaging reveals fast metabolic switch in T lymphocytes

T-cell activation induces a metabolic switch generating energy for proliferation, survival, and functions. We used noninvasive label-free two-photon fluorescence lifetime microscopy (2P-FLIM) to map the spatial and temporal dynamics of the metabolic NAD(P)H co-enzyme during T lymphocyte activation. This provides a readout of the OXPHOS and glycolysis rates at a single-cell level. Analyzes were performed in the CD4+ leukemic T cell line Jurkat, and in human CD4+ primary T cells. Cells were activated on glass surfaces coated with activating antibodies mimicking immune synapse formation. Comparing the fraction of bound NAD(P)H between resting and activated T cells, we show that T-cell activation induces a rapid switch toward glycolysis. This occurs after 10 min and remains stable for one hour. Three-dimensional analyzes revealed that the intracellular distribution of fraction of bound NAD(P)H increases at the immune synapse in activated cells. Finally, we show that fraction of bound NAD(P)H tends to negatively correlate with spreading of activated T cells, suggesting a link between actin remodeling and metabolic changes. This study highlights that 2P-FLIM measurement of fraction of bound NAD(P)H is well suited to follow a fast metabolic switch in three dimensions, in single T lymphocytes with subcellular resolution.

Label-free multimodal imaging with simultaneous two-photon and three-photon microscopy and kernel-based nonlinear scaling denoising

We report on a compact multimodal imaging system that can acquire two-photon microscopy (2PM) and three-photon microscopy (3PM) images simultaneously. With dual excitation wavelengths, multiple contrasts including two-photon-excitation-fluorescence (2PEF), second harmonic generation (SHG), and third harmonic generation (THG) are acquired simultaneously from cells, collagen fibers, and interfaces, all label-free. Challenges related to the excitation by two wavelengths and the effective separation of 2PM and 3PM signals are discussed and addressed. The data processing challenge where multiple contrasts can have significantly varying signal levels is also addressed. A kernel-based nonlinear scaling (KNS) denoising method is introduced to reduce noise from ultra-low signal images and generate high-quality multimodal images. Simultaneous 2PM and 3PM imaging is demonstrated on various tissue samples. The simultaneous acquisition speeds up the imaging process and minimizes the commonly encountered problem of motion artifacts and mechanical drift in sequential acquisition. Multimodal imaging with simultaneous 2PM and 3PM will have great potential for label-free in-vivo imaging of biological tissues.

Digital pathology for nonalcoholic steatohepatitis assessment

Histological assessment of nonalcoholic fatty liver disease (NAFLD) has anchored knowledge development about the phenotypes of the condition, their natural history and their clinical course. This fact has led to the use of histological assessment as a reference standard for the evaluation of efficacy of drug interventions for nonalcoholic steatohepatitis (NASH) - the more histologically active form of NAFLD. However, certain limitations of conventional histological assessment systems pose challenges in drug development. These limitations have spurred intense scientific and commercial development of machine learning and digital approaches towards the assessment of liver histology in patients with NAFLD. This research field remains an area in rapid evolution. In this Perspective article, we summarize the current conventional assessment of NASH and its limitations, the use of specific digital approaches for histological assessment, and their application to the study of NASH and its response to therapy. Although this is not a comprehensive review, the leading tools currently used to assess therapeutic efficacy in drug development are specifically discussed. The potential translation of these approaches to support routine clinical assessment of NAFLD and an agenda for future research are also discussed.

Implications for cumulative and prolonged clinical improvement induced by cross-linked hyaluronic acid: An in vivo biochemical/microscopic study in humans

In photoaged human skin, type I collagen fragmentation impairs dermal extracellular matrix (ECM) integrity, resulting in collapsed/contracted fibroblasts with reduced type I procollagen synthesis. Injections of cross-linked hyaluronic acid (CL-HA) reverse these deleterious changes. To investigate the time course and effects of biochemical changes induced by injected CL-HA, particularly whether fibroblast activation leads to accumulation/deposition of dermal collagen, we injected CL-HA into photoaged skin of human participants over 60 years-old and performed biochemical/microscopic analyses of skin samples. Beginning 1 week post-injection and lasting 6-9 months, fibroblasts exhibited activation, including increased immunostaining and gene expression of markers of type I collagen synthesis, such as heat shock protein 47 and components of the transforming growth factor-β pathway. At 1 week post-injection, multiphoton microscopy revealed elongation/stretching of fibroblasts, indicating enhanced dermal mechanical support. At 4 weeks, second-harmonic generation microscopy revealed thick collagen bundles densely packed around pools of injected CL-HA. At 12 months, accumulation of thick collagen bundles was observed and injected CL-HA remained present in substantial amounts. Thus, by occupying space in the dermal ECM, injected CL-HA rapidly and durably enhances mechanical support, stimulating fibroblast elongation and activation, which results in thick, densely packed type I collagen bundles accumulating as early as 4 weeks post-injection and continuing for at least a year. These observations indicate that early and prolonged clinical improvement following CL-HA injection results from space-filling and collagen deposition. As type I collagen has an estimated half-life of 15 years, our data provide the foundations for optimizing the timing/frequency of repeat CL-HA injections.

Multimodal label-free imaging of murine hepatocellular carcinoma with a subcellular resolution

We demonstrate label-free imaging of genetically induced hepatocellular carcinoma (HCC) in a murine model provided by two- and three-photon fluorescence microscopy of endogenous fluorophores excited at the central wavelengths of 790, 980 and 1250 nm and reinforced by second and third harmonic generation microscopy. We show, that autofluorescence imaging presents abundant information about cell arrangement and lipid accumulation in hepatocytes and hepatic stellate cells (HSCs), harmonics generation microscopy provides a versatile tool for fibrogenesis and steatosis study. Multimodal images may be performed by a single ultrafast laser source at 1250 nm falling in tissue transparency window. Various grades of HCC are examined revealing fibrosis, steatosis, liver cell dysplasia, activation of HSCs and hepatocyte necrosis, that shows a great ability of multimodal label-free microscopy to intravital visualization of liver pathology development.

Multimodal Imaging of Pancreatic Cancer Microenvironment in Response to an Antiglycolytic Drug

Lipid metabolism and glycolysis play crucial roles in the progression and metastasis of cancer, and the use of 3-bromopyruvate (3-BP) as an antiglycolytic agent has shown promise in killing pancreatic cancer cells. However, developing an effective strategy to avoid chemoresistance requires the ability to probe the interaction of cancer drugs with complex tumor-associated microenvironments (TAMs). Unfortunately, no robust and multiplexed molecular imaging technology is currently available to analyze TAMs. In this study, the simultaneous profiling of three protein biomarkers using SERS nanotags and antibody-functionalized nanoparticles in a syngeneic mouse model of pancreatic cancer (PC) is demonstrated. This allows for comprehensive information about biomarkers and TAM alterations before and after treatment. These multimodal imaging techniques include surface-enhanced Raman spectroscopy (SERS), immunohistochemistry (IHC), polarized light microscopy, second harmonic generation (SHG) microscopy, fluorescence lifetime imaging microscopy (FLIM), and untargeted liquid chromatography and mass spectrometry (LC-MS) analysis. The study reveals the efficacy of 3-BP in treating pancreatic cancer and identifies drug treatment-induced lipid species remodeling and associated pathways through bioinformatics analysis.

Quantifying in vivo collagen reorganization during immunotherapy in murine melanoma with second harmonic generation imaging

Significance

Increased collagen linearization and deposition during tumorigenesis can impede immune cell infiltration and lead to tumor metastasis. Although melanoma is well studied in immunotherapy research, studies that quantify collagen changes during melanoma progression and treatment are lacking.

Aim

Image in vivo collagen in preclinical melanoma models during immunotherapy and quantify the collagen phenotype in treated and control mice.

Approach

Second harmonic generation imaging of collagen was performed in mouse melanoma tumors in vivo over a treatment time-course. Animals were treated with a curative radiation and immunotherapy combination. Collagen morphology was quantified over time at an image and single fiber level using CurveAlign and CT-FIRE software.

Results

In immunotherapy-treated mice, collagen reorganized toward a healthy phenotype, including shorter, wider, curlier collagen fibers, with modestly higher collagen density. Temporally, collagen fiber straightness and length changed late in treatment (Day 9 and 12) while width and density changed early (Day 6) compared to control mice. Single fiber level collagen analysis was most sensitive to the changes between treatment groups compared to image level analysis.

Conclusions

Quantitative second harmonic generation imaging can provide insight into collagen dynamics in vivo during immunotherapy, with key implications in improving immunotherapy response in melanoma and other cancers.