Developments in spontaneous and coherent Raman scattering microscopic imaging for biomedical applications

Raman spectrometer with vertical flow method for solutions containing organic solvents

The vertical flow (VF) method improves generation and collection efficiency in Raman spectroscopy. It enhances all Raman signals, including undesired signals of organic solvents having a considerably large Raman cross section. We constructed a Raman spectrometer using the VF method to overcome this drawback and introduced a spatial line rejection mask to eliminate unnecessary bands. In addition, the design of the VF unit was improved to resist organic solvents. A VF unit with a 60-µm pinhole enhanced the signal 168 times. The spatial mask effectively eliminated the large Raman bands of the solvent and enabled a longer exposure time. The increase in the dynamic range improved the signal-to-noise ratio by 10 % in methanol and acetonitrile measurements. Raman spectrometer with the VF method and spatial mask enables us to record the Raman spectrum of solute molecules without the disturbance of solvent bands.

Label-free morpho-molecular phenotyping of living cancer cells by combined Raman spectroscopy and phase tomography

Accurate, rapid and non-invasive cancer cell phenotyping is a pressing concern across the life sciences, as standard immuno-chemical imaging and omics require extended sample manipulation. Here we combine Raman micro-spectroscopy and phase tomography to achieve label-free morpho-molecular profiling of human colon cancer cells, following the adenoma, carcinoma, and metastasis disease progression, in living and unperturbed conditions. We describe how to decode and interpret quantitative chemical and co-registered morphological cell traits from Raman fingerprint spectra and refractive index tomograms. Our multimodal imaging strategy rapidly distinguishes cancer phenotypes, limiting observations to a low number of pristine cells in culture. This synergistic dataset allows us to study independent or correlated information in spectral and tomographic maps, and how it benefits cell type inference. This method is a valuable asset in biomedical research, particularly when biological material is in short supply, and it holds the potential for non-invasive monitoring of cancer progression in living organisms.

Real-Time Signal Analysis with Wider Dynamic Range and Enhanced Sensitivity in Multiplex Colorimetric Immunoassays Using Encoded Hydrogel Microparticles

The simultaneous quantification of multiple proteins is crucial for accurate medical diagnostics. A promising technology, the multiplex colorimetric immunoassay using encoded hydrogel microparticles, has garnered attention, due to its simplicity and multiplex capabilities. However, it encounters challenges related to its dynamic range, as it relies solely on the colorimetric signal analysis of encoded hydrogel microparticles at the specific time point (i.e., end-point analysis). This necessitates the precise determination of the optimal time point for the termination of the colorimetric reaction. In this study, we introduce real-time signal analysis to quantify proteins by observing the continuous colorimetric signal change within the encoded hydrogel microparticles. Real-time signal analysis measures the "slope", the rate of the colorimetric signal generation, by focusing on the kinetics of the accumulation of colorimetric products instead of the colorimetric signal that appears at the end point. By developing a deep learning-based automatic analysis program that automatically reads the code of the graphically encoded hydrogel microparticles and obtains the slope by continuously tracking the colorimetric signal, we achieved high accuracy and high throughput analysis. This technology has secured a dynamic range more than twice as wide as that of the conventional end-point signal analysis, simultaneously achieving a sensitivity that is 4-10 times higher. Finally, as a demonstration of application, we performed multiplex colorimetric immunoassays using real-time signal analysis covering a wide concentration range of protein targets associated with pre-eclampsia.

Transient stimulated Raman scattering spectroscopy and imaging

Stimulated Raman scattering (SRS) has been developed as an essential quantitative contrast for chemical imaging in recent years. However, while spectral lines near the natural linewidth limit can be routinely achieved by state-of-the-art spontaneous Raman microscopes, spectral broadening is inevitable for current mainstream SRS imaging methods. This is because those SRS signals are all measured in the frequency domain. There is a compromise between sensitivity and spectral resolution: as the nonlinear process benefits from pulsed excitations, the fundamental time-energy uncertainty limits the spectral resolution. Besides, the spectral range and acquisition speed are mutually restricted. Here we report transient stimulated Raman scattering (T-SRS), an alternative time-domain strategy that bypasses all these fundamental conjugations. T-SRS is achieved by quantum coherence manipulation: we encode the vibrational oscillations in the stimulated Raman loss (SRL) signal by femtosecond pulse-pair sequence excited vibrational wave packet interference. The Raman spectrum was then achieved by Fourier transform of the time-domain SRL signal. Since all Raman modes are impulsively and simultaneously excited, T-SRS features the natural-linewidth-limit spectral line shapes, laser-bandwidth-determined spectral range, and improved sensitivity. With ~150-fs laser pulses, we boost the sensitivity of typical Raman modes to the sub-mM level. With all-plane-mirror high-speed time-delay scanning, we further demonstrated hyperspectral SRS imaging of live-cell metabolism and high-density multiplexed imaging with the natural-linewidth-limit spectral resolution. T-SRS shall find valuable applications for advanced Raman imaging.

Rapid, label-free classification of glioblastoma differentiation status combining confocal Raman spectroscopy and machine learning

Label-free identification of tumor cells using spectroscopic assays has emerged as a technological innovation with a proven ability for rapid implementation in clinical care. Machine learning facilitates the optimization of processing and interpretation of extensive data, such as various spectroscopy data obtained from surgical samples. The here-described preclinical work investigates the potential of machine learning algorithms combining confocal Raman spectroscopy to distinguish non-differentiated glioblastoma cells and their respective isogenic differentiated phenotype by means of confocal ultra-rapid measurements. For this purpose, we measured and correlated modalities of 1146 intracellular single-point measurements and sustainingly clustered cell components to predict tumor stem cell existence. By further narrowing a few selected peaks, we found indicative evidence that using our computational imaging technology is a powerful approach to detect tumor stem cells in vitro with an accuracy of 91.7% in distinct cell compartments, mainly because of greater lipid content and putative different protein structures. We also demonstrate that the presented technology can overcome intra- and intertumoral cellular heterogeneity of our disease models, verifying the elevated physiological relevance of our applied disease modeling technology despite intracellular noise limitations for future translational evaluation.

In-situ quantification of lipids in live cells through imaging approaches

Lipids are important molecules that are widely distributed within the cell, and they play a crucial role in several biological processes such as cell membrane formation, signaling, cell motility and division. Monitoring the spatiotemporal dynamics of cellular lipids in real-time and quantifying their concentrations in situ is crucial since the local concentration of lipids initiates various signaling pathways that regulate cellular processes. In this review, we first introduced the historical background of lipid quantification methods. We then delve into the current state of the art of in situ lipid quantification, including the establishment and utility of fluorescence imaging techniques based on sensors of lipid-binding domains labeled with organic dyes or fluorescent proteins, and Raman and magnetic resonance imaging (MRI) techniques that do not require lipid labeling. Next, we highlighted the biological applications of live-cell lipid quantification techniques in the study of in situ lipid distribution, lipid transformation, and lipid-mediated signaling pathways. Finally, we discussed the technical challenges and prospects for the development of lipid quantification in live cells, with the aim of promoting the development of in situ lipid quantification in live cells, which may have a profound impact on the biological and medical fields.

Feasibility studies of multimodal nonlinear endoscopy using multicore fiber bundles for remote scanning from tissue sections to bulk organs

Here, we report on the development and application of a compact multi-core fiber optical probe for multimodal non-linear imaging, combining the label-free modalities of Coherent Anti-Stokes Raman Scattering, Second Harmonic Generation, and Two-Photon Excited Fluorescence. Probes of this multi-core fiber design avoid moving and voltage-carrying parts at the distal end, thus providing promising improved compatibility with clinical requirements over competing implementations. The performance characteristics of the probe are established using thin cryo-sections and artificial targets before the applicability to clinically relevant samples is evaluated using ex vivo bulk human and porcine intestine tissues. After image reconstruction to counteract the data's inherently pixelated nature, the recorded images show high image quality and morpho-chemical conformity on the tissue level compared to multimodal non-linear images obtained with a laser-scanning microscope using a standard microscope objective. Furthermore, a simple yet effective reconstruction procedure is presented and demonstrated to yield satisfactory results. Finally, a clear pathway for further developments to facilitate a translation of the multimodal fiber probe into real-world clinical evaluation and application is outlined.

Conjugated Polymeric Materials in Biological Imaging and Cancer Therapy

Conjugated polymers (CPs) have attracted much attention in the fields of chemistry, medicine, life science, and material science. Researchers have carried out a series of innovative researches and have made significant research progress regarding the unique photochemical and photophysical properties of CPs, expanding the application range of polymers. CPs are polymers formed by the conjugation of multiple repeating light-emitting units. Through precise control of their structure, functional molecules with different properties can be obtained. Fluorescence probes with different absorption and emission wavelengths can be obtained by changing the main chain structure. By modifying the side chain structure with water-soluble groups or selective recognition molecules, electrostatic interaction or specific binding with specific targets can be achieved; subsequently, the purpose of selective recognition can be achieved. This article reviews the research work of CPs in cell imaging, tumor diagnosis, and treatment in recent years, summarizes the latest progress in the application of CPs in imaging, tumor diagnosis, and treatment, and discusses the future development direction of CPs in cell imaging, tumor diagnosis, and treatment.

Toward next-generation endoscopes integrating biomimetic video systems, nonlinear optical microscopy, and deep learning

According to the World Health Organization, the proportion of the world's population over 60 years will approximately double by 2050. This progressive increase in the elderly population will lead to a dramatic growth of age-related diseases, resulting in tremendous pressure on the sustainability of healthcare systems globally. In this context, finding more efficient ways to address cancers, a set of diseases whose incidence is correlated with age, is of utmost importance. Prevention of cancers to decrease morbidity relies on the identification of precursor lesions before the onset of the disease, or at least diagnosis at an early stage. In this article, after briefly discussing some of the most prominent endoscopic approaches for gastric cancer diagnostics, we review relevant progress in three emerging technologies that have significant potential to play pivotal roles in next-generation endoscopy systems: biomimetic vision (with special focus on compound eye cameras), non-linear optical microscopies, and Deep Learning. Such systems are urgently needed to enhance the three major steps required for the successful diagnostics of gastrointestinal cancers: detection, characterization, and confirmation of suspicious lesions. In the final part, we discuss challenges that lie en route to translating these technologies to next-generation endoscopes that could enhance gastrointestinal imaging, and depict a possible configuration of a system capable of (i) biomimetic endoscopic vision enabling easier detection of lesions, (ii) label-free in vivo tissue characterization, and (iii) intelligently automated gastrointestinal cancer diagnostic.

Fundamentals and Applications of Raman-Based Techniques for the Design and Development of Active Biomedical Materials

Raman spectroscopy is an analytical method based on light-matter interactions that can interrogate the vibrational modes of matter and provide representative molecular fingerprints. Mediated by its label-free, non-invasive nature, and high molecular specificity, Raman-based techniques have become ubiquitous tools for in situ characterization of materials. This review comprehensively describes the theoretical and practical background of Raman spectroscopy and its advanced variants. The numerous facets of material characterization that Raman scattering can reveal, including biomolecular identification, solid-to-solid phase transitions, and spatial mapping of biomolecular species in bioactive materials, are highlighted. The review illustrates the potential of these techniques in the context of active biomedical material design and development by highlighting representative studies from the literature. These studies cover the use of Raman spectroscopy for the characterization of both natural and synthetic biomaterials, including engineered tissue constructs, biopolymer systems, ceramics, and nanoparticle formulations, among others. To increase the accessibility and adoption of these techniques, the present review also provides the reader with practical recommendations on the integration of Raman techniques into the experimental laboratory toolbox. Finally, perspectives on how recent developments in plasmon- and coherently-enhanced Raman spectroscopy can propel Raman from underutilized to critical for biomaterial development are provided.

Label-free structural and functional volumetric imaging by dual-modality optical-Raman projection tomography

Mesoscale volumetric imaging is of great importance for the study of bio-organisms. Among others, optical projection tomography provides unprecedented structural details of specimens, but it requires fluorescence label for chemical targeting. Raman spectroscopic imaging is able to identify chemical components in a label-free manner but lacks microstructure. Here, we present a dual-modality optical-Raman projection tomography (ORPT) technology, which enables label-free three-dimensional imaging of microstructures and components of millimeter-sized samples with a micron-level spatial resolution on the same device. We validate the feasibility of our ORPT system using images of polystyrene beads in a volume, followed by detecting biomolecules of zebrafish and Arabidopsis, demonstrating that fused three-dimensional images of the microstructure and molecular components of bio-samples could be achieved. Last, we observe the fat body of Drosophila melanogaster at different developmental stages. Our proposed technology enables bimodal label-free volumetric imaging of the structure and function of biomolecules in a large sample.

Quantifying Inflammatory Response and Drug-Aided Resolution in an Atopic Dermatitis model with Deep Learning

Noninvasive quantification of dermal diseases aids efficacy studies and paves the way for broader enrollment in clinical studies across varied demographics. Related to atopic dermatitis, accurate quantification of the onset and resolution of inflammatory flare-ups in the skin remains challenging, as the commonly used macroscale cues do not necessarily represent the underlying inflammation at the cellular level. Although atopic dermatitis affects over 10% of Americans, the genetic underpinnings and cellular level phenomena causing the physical manifestation of the disease require more clarity. Current gold standards of quantification are often invasive, requiring biopsies followed by laboratory analysis. This represents a gap in our ability to diagnose and study skin inflammatory disease, as well as develop improved topical therapeutic treatments. This need can be addressed through noninvasive imaging methods and the use of modern quantitative approaches to streamline the generation of relevant insights. This work reports the nonin- vasive image-based quantification of inflammation in an atopic dermatitis mouse model based on cellular-level deep learning analysis of coherent anti-Stokes Raman scattering and stimulated Raman scattering imaging. This quantifica- tion method allows for timepoint-specific disease scores using morphological and physiological measurements. The outcomes we demonstrate set the stage for applying this workflow to future clinical studies.

Optical tweezers and Raman spectroscopy for single-cell classification of drug resistance in acute lymphoblastic leukemia

Laser Tweezers Raman Spectroscopy (LTRS) is a combination of laser tweezers and Raman spectroscopy. It is a physical tool based on the mechanical effects of the laser, which can be used to study single living cells in suspension in a fast and non-destructive way. Our work aims to establish a methodology system based on LTRS to rapidly and non-destructively detect the resistance of acute lymphoblastic leukemia (ALL) cells and to provide a new idea for the evaluation of the resistance of ALL cells. Two specific adriamycin-resistant and parental ALL cells BALL-1 and Nalm6 were included in this study. Adriamycin resistant cells can induce the spectral differences, which can be detected by LTRS initially. To ensure the accuracy of the results, we use the principal components analysis (PCA) as well as the classification and regression trees (CRT) algorithms, which show that the specificity and sensitivity of LTRS are above 90%. In addition, to further clarify the chemoresistance status of ALL cells, we used the CRT models and receiver operating characteristic (ROC) curves which are based on the band data to look for some important bands and band intensity ratios that have strong pointing significance. Our work proves that LTRS analysis combined with multivariate statistical analyses have great potential to be a novel analytical strategy at the single-cell level for rapidly evaluating the chemoresistance status of ALL cells.

Concentration Quantification of the Low-Complexity Domain of Fused in Sarcoma inside a Single Droplet and Effects of Solution Parameters

Liquid-liquid phase separation (LLPS) is an important phenomenon in biology, and it is desirable to develop quantitative methods to analyze protein droplets generated by LLPS. This study quantified the change in protein concentration in a droplet in label-free and single-droplet conditions using Raman imaging and the Raman band of water as an intensity standard. Small changes in the protein concentration with variations in pH and salt concentration were observed, and it was shown that the concentration in the droplet decreases as the conditions become less favorable for droplet formation. The effect of exposure to 1,6-hexanediol was also examined, and this additive was found to decrease the protein concentration in the droplet. A model can be proposed in which the addition of 1,6-hexanediol reduces the protein concentration in the droplet, and the droplet disappears when the concentration falls below a certain threshold value.

Estimating the Analytical Performance of Raman Spectroscopy for Quantification of Active Ingredients in Human Stratum Corneum

Confocal Raman microscopy (CRM) has become a versatile technique that can be applied routinely to monitor skin penetration of active molecules. In the present study, CRM coupled to multivariate analysis (namely PLSR—partial least squares regression) is used for the quantitative measurement of an active ingredient (AI) applied to isolated (ex vivo) human stratum corneum (SC), using systematically varied doses of resorcinol, as model compound, and the performance is quantified according to key figures of merit defined by regulatory bodies (ICH, FDA, and EMA). A methodology is thus demonstrated to establish the limit of detection (LOD), precision, accuracy, sensitivity (SEN), and selectivity (SEL) of the technique, and the performance according to these key figures of merit is compared to that of similar established methodologies, based on studies available in literature. First, principal components analysis (PCA) was used to examine the variability within the spectral data set collected. Second, ratios calculated from the area under the curve (AUC) of characteristic resorcinol and proteins/lipids bands (1400–1500 cm⁻¹) were used to perform linear regression analysis of the Raman spectra. Third, cross-validated PLSR analysis was applied to perform quantitative analysis in the fingerprint region. The AUC results show clearly that the intensities of Raman features in the spectra collected are linearly correlated to resorcinol concentrations in the SC (R² = 0.999) despite a heterogeneity in the distribution of the active molecule in the samples. The Root Mean Square Error of Cross-Validation (RMSECV) (0.017 mg resorcinol/mg SC), The Root Mean Square of Prediction (RMSEP) (0.015 mg resorcinol/mg SC), and R² (0.971) demonstrate the reliability of the linear regression constructed, enabling accurate quantification of resorcinol. Furthermore, the results have enabled the determination, for the first time, of numerical criteria to estimate analytical performances of CRM, including LOD, precision using bias corrected mean square error prediction (BCMSEP), sensitivity, and selectivity, for quantification of the performance of the analytical technique. This is one step further towards demonstrating that Raman spectroscopy complies with international guidelines and to establishing the technique as a reference and approved tool for permeation studies.

Clinical Spectroscopy: Lost in Translation?

This Focal Point Review paper discusses the developments of biomedical Raman and infrared spectroscopy, and the recent strive towards these technologies being regarded as reliable clinical tools. The promise of vibrational spectroscopy in the field of biomedical science, alongside the development of computational methods for spectral analysis, has driven a plethora of proof-of-concept studies which convey the potential of various spectroscopic approaches. Here we report a brief review of the literature published over the past few decades, with a focus on the current technical, clinical, and economic barriers to translation, namely the limitations of many of the early studies, and the lack of understanding of clinical pathways, health technology assessments, regulatory approval, clinical feasibility, and funding applications. The field of biomedical vibrational spectroscopy must acknowledge and overcome these hurdles in order to achieve clinical efficacy. Current prospects have been overviewed with comment on the advised future direction of spectroscopic technologies, with the aspiration that many of these innovative approaches can ultimately reach the frontier of medical diagnostics and many clinical applications.

Looking Inside Non-Destructively: Label-Free, Raman-Based Visualization of Intracellular Coxiella burnetii

The life cycle of intracellular pathogens is often complex and can include different morphoforms. Treatment of intracellular infections and unperturbed studying of the pathogen inside the host cell are frequently challenging. Here, we present a Raman-based, label-free, non-invasive, and non-destructive method to localize, visualize, and even quantify intracellular bacteria in 3D within intact host cells in a Coxiella burnetii infection model. C. burnetii is a zoonotic obligate intracellular pathogen that causes infections in ruminant livestock and humans with an acute disease known as Q fever. Using statistical data analysis, no isolation is necessary to gain detailed information on the intracellular pathogen's metabolic state. High-quality false color image stacks with diffraction-limited spatial resolution enable a 3D spatially resolved single host cell analysis that shows excellent agreement with results from transmission electron microscopy. Quantitative analysis at different time points post infection allows to follow the infection cycle with the transition from the large cell variant (LCV) to the small cell variant (SCV) at around day 6 and a gradual change in the lipid composition during vacuole maturation. Spectral characteristics of intracellular LCV and SCV reveal a higher lipid content of the metabolically active LCV.

Stimulated Raman scattering microscopy with spectral phasor analysis: applications in assessing drug-cell interactions

Statins have displayed significant, although heterogeneous, anti-tumour activity in breast cancer disease progression and recurrence. They offer promise as a class of drugs, normally used for cardiovascular disease control, that could have a significant impact on the treatment of cancer. Understanding their mode of action and accurately assessing their efficacy on live cancer cells is an important and significant challenge. Stimulated Raman scattering (SRS) microscopy is a powerful, label-free imaging technique that can rapidly characterise the biochemical responses of live cell populations following drug treatment. Here, we demonstrate multi-wavelength SRS imaging together with spectral phasor analysis to characterise a panel of breast cancer cell lines (MCF-7, SK-BR-3 and MDA-MB-231 cells) treated with two clinically relevant statins, atorvastatin and rosuvastatin. Label-free SRS imaging within the high wavenumber region of the Raman spectrum (2800–3050 cm⁻¹) revealed the lipid droplet distribution throughout populations of live breast cancer cells using biocompatible imaging conditions. A spectral phasor analysis of the hyperspectral dataset enables rapid differentiation of discrete cellular compartments based on their intrinsic SRS characteristics. Applying the spectral phasor method to studying statin treated cells identified a lipid accumulating phenotype in cell populations which displayed the lowest sensitivity to statin treatment, whilst a weaker lipid accumulating phenotype was associated with a potent reduction in cell viability. This study provides an insight into potential resistance mechanisms of specific cancer cells towards treatment with statins. Label-free SRS imaging provides a novel and innovative technique for phenotypic assessment of drug-induced effects across different cellular populations and enables effective analysis of drug–cell interactions at the subcellular scale.

Stimulated Raman scattering microscopy with spectral phasor analysis provides a label-free approach for phenotypic evaluation of drug-induced effects.

Numerical investigation of the energy limit in a picosecond fiber optic parametric oscillator

Numerical simulation of a fiber optic parametric oscillator to produce picosecond narrowband pulses for coherent anti-Stokes Raman spectroscopy has been performed by an open source Python-based library using an extremely wide range of parameters, such as the pump pulse duration, parametric frequency shift, spectral bandwidth of the pump, and the parametric pulses. It required an extremely large calculation window, both in time and spectral domains. We managed to speed up the simulation 50 times using a graphic processor unit that allowed us to define the areas of stability for different lengths of standard passive (5-100 m) and photonic crystal (23-100 cm) fibers used in the external linear oscillator cavity. It was shown that highly chirped dissipative solitons at a wavelength about 800 nm can be generated with energy up to 55 nJ, which is limited by the pump depletion and self-phase modulation effects.

Raman Spectroscopy: A Personalized Decision-Making Tool on Clinicians' Hands for In Situ Cancer Diagnosis and Surgery Guidance

Accurate in situ diagnosis and optimal surgical removal of a malignancy constitute key elements in reducing cancer-related morbidity and mortality. In surgical oncology, the accurate discrimination between healthy and cancerous tissues is critical for the postoperative care of the patient. Conventional imaging techniques have attempted to serve as adjuvant tools for in situ biopsy and surgery guidance. However, no single imaging modality has been proven sufficient in terms of specificity, sensitivity, multiplexing capacity, spatial and temporal resolution. Moreover, most techniques are unable to provide information regarding the molecular tissue composition. In this review, we highlight the potential of Raman spectroscopy as a spectroscopic technique with high detection sensitivity and spatial resolution for distinguishing healthy from malignant margins in microscopic scale and in real time. A Raman spectrum constitutes an intrinsic "molecular finger-print" of the tissue and any biochemical alteration related to inflammatory or cancerous tissue state is reflected on its Raman spectral fingerprint. Nowadays, advanced Raman systems coupled with modern instrumentation devices and machine learning methods are entering the clinical arena as adjunct tools towards personalized and optimized efficacy in surgical oncology.

Aggregation-Induced Emission-Active Poly(phenyleneethynylene)s for Fluorescence and Raman Dual-Modal Imaging and Drug-Resistant Bacteria Killing

Poly(phenyleneethynylene) (PPE) is a widely used functional conjugated polymer with applications ranging from organic optoelectronics and fluorescence sensors to optical imaging and theranostics. However, the fluorescence efficiency of PPE in aggregate states is generally not as good as their solution states, which greatly compromises their performance in fluorescence-related applications. Herein, a series of PPE derivatives with typical aggregation-induced emission (AIE) properties is designed and synthesized. In these PPEs, the diethylamino-substituted tetraphenylethene units function as the long-wavelength AIE source and the alkyl side chains serve as the functionalization site. The obtained AIE-active PPEs with large π-conjugation show strong aggregate-state fluorescence, interesting self-assembly behaviors, inherently enhanced alkyne vibrations in the Raman-silent region of cells, and efficient antibacterial activities. The PPE nanoparticles with good cellular uptake capability can clearly and sensitively visualize the tumor region and residual tumors via their fluorescence and Raman signals, respectively, to benefit the precise tumor resection surgery. After post-functionalization, the obtained PPE-based polyelectrolyte can preferentially image bacteria over mammalian cells and possesses efficient photodynamic killing capability against Gram-positive and drug-resistant bacteria. This work provides a feasible design strategy for developing functional conjugated polymers with multimodal imaging capability as well as photodynamic antimicrobial ability.

Translational biophotonics with Raman imaging: clinical applications and beyond

Clinical medicine continues to seek novel rapid non-invasive tools capable of providing greater insight into disease progression and management. Raman scattering based technologies constitute a set of tools under continuing development to address outstanding challenges spanning diagnostic medicine, surgical guidance, therapeutic monitoring, and histopathology. Here we review the mechanisms and clinical applications of Raman scattering, specifically focusing on high-speed imaging methods that can provide spatial context for translational biomedical applications.

A decade of alkyne-tag Raman imaging (ATRI): applications in biological systems

Alkyne functional groups have Raman signatures in a region (1800 cm-1 to 2800 cm-1) that is free from interference from cell components, known as the "silent region", and alkyne signals in this region were first utilized a decade ago to visualize the nuclear localization of a thymidine analogue EdU. Since then, the strategy of Raman imaging of biological samples by using alkyne functional groups, called alkyne-tag Raman imaging (ATRI), has become widely used. This article reviews the applications of ATRI in biological samples ranging from organelles to whole animal models, and briefly discusses the prospects for this technique.

Multimodal nonlinear endomicroscopic imaging probe using a double-core double-clad fiber and focus-combining micro-optical concept

Multimodal non-linear microscopy combining coherent anti-Stokes Raman scattering, second harmonic generation, and two-photon excited fluorescence has proved to be a versatile and powerful tool enabling the label-free investigation of tissue structure, molecular composition, and correlation with function and disease status. For a routine medical application, the implementation of this approach into an in vivo imaging endoscope is required. However, this is a difficult task due to the requirements of a multicolour ultrashort laser delivery from a compact and robust laser source through a fiber with low losses and temporal synchronization, the efficient signal collection in epi-direction, the need for small-diameter but highly corrected endomicroobjectives of high numerical aperture and compact scanners. Here, we introduce an ultra-compact fiber-scanning endoscope platform for multimodal non-linear endomicroscopy in combination with a compact four-wave mixing based fiber laser. The heart of this fiber-scanning endoscope is an in-house custom-designed, single mode, double clad, double core pure silica fiber in combination with a 2.4 mm diameter NIR-dual-waveband corrected endomicroscopic objective of 0.55 numerical aperture and 180 µm field of view for non-linear imaging, allowing a background free, low-loss, high peak power laser delivery, and an efficient signal collection in backward direction. A linear diffractive optical grating overlays pump and Stokes laser foci across the full field of view, such that diffraction-limited performance is demonstrated for tissue imaging at one frame per second with sub-micron spatial resolution and at a high transmission of 65% from the laser to the specimen using a distal resonant fiber scanner.

Multimodal Scanning Microscope Combining Optical Coherence Tomography, Raman Spectroscopy and Fluorescence Lifetime Microscopy for Mesoscale Label-Free Imaging of Tissue

Multimodal optical imaging of tissue has significant potential to become an indispensable diagnostic tool in clinical pathology. Conventional bright-field microscopy provides contrast based on attenuation or reflectance of light, having no depth-related information and no molecular specificity. Recent developments in biomedical optics have introduced a variety of optical modalities, such as Raman spectroscopy (RS), fluorescence lifetime imaging microscopy (FLIM) of endogenous fluorophores, optical coherence tomography (OCT), and others, which provide a distinct characteristic, i.e., molecular, chemical, and morphological information, of the sample. To harvest the full analytical potential of those modalities, we have developed a novel multimodal imaging system, which allows the co-registered acquisition of OCT/FLIM/RS on a single device. The present implementation allows the investigation of biological tissues in the mesoscale range, 0.1-5 mm in a correlated manner. Due to the co-registered acquisition of the modalities, it is possible to directly compare and evaluate the corresponding information between the three modalities. Moreover, by additionally preparing and characterizing entire pathological hematoxylin and eosin (H&E) slides of head and neck biopsies, it is also possible to correlate the multimodal spectroscopic information to any location of the ground truth H&E information. To the best of our knowledge, this is the first development and implementation of a compact and clinically applicable multimodal scanning microscope, which combines OCT, FLIM, and RS together with the possibility for co-registering H&E information for a morpho-chemical tissue characterization and a correlation with the pathological ground truth (H&E) of the underlying signal origin directly in a clinical environment.

Looking for a perfect match: multimodal combinations of Raman spectroscopy for biomedical applications

Raman spectroscopy has shown very promising results in medical diagnostics by providing label-free and highly specific molecular information of pathological tissue ex vivo and in vivo. Nevertheless, the high specificity of Raman spectroscopy comes at a price, i.e., low acquisition rate, no direct access to depth information, and limited sampling areas. However, a similar case regarding advantages and disadvantages can also be made for other highly regarded optical modalities, such as optical coherence tomography, autofluorescence imaging and fluorescence spectroscopy, fluorescence lifetime microscopy, second-harmonic generation, and others. While in these modalities the acquisition speed is significantly higher, they have no or only limited molecular specificity and are only sensitive to a small group of molecules. It can be safely stated that a single modality provides only a limited view on a specific aspect of a biological specimen and cannot assess the entire complexity of a sample. To solve this issue, multimodal optical systems, which combine different optical modalities tailored to a particular need, become more and more common in translational research and will be indispensable diagnostic tools in clinical pathology in the near future. These systems can assess different and partially complementary aspects of a sample and provide a distinct set of independent biomarkers. Here, we want to give an overview on the development of multimodal systems that use RS in combination with other optical modalities to improve the diagnostic performance.

The Role of Raman Spectroscopy Within Quantitative Metabolomics

Ninety-four years have passed since the discovery of the Raman effect, and there are currently more than 25 different types of Raman-based techniques. The past two decades have witnessed the blossoming of Raman spectroscopy as a powerful physicochemical technique with broad applications within the life sciences. In this review, we critique the use of Raman spectroscopy as a tool for quantitative metabolomics. We overview recent developments of Raman spectroscopy for identification and quantification of disease biomarkers in liquid biopsies, with a focus on the recent advances within surface-enhanced Raman scattering-based methods. Ultimately, we discuss the applications of imaging modalities based on Raman scattering as label-free methods to study the abundance and distribution of biomolecules in cells and tissues, including mammalian, algal, and bacterial cells.

The Progress of Label-Free Optical Imaging in Alzheimer's Disease Screening and Diagnosis

As the major neurodegenerative disease of dementia, Alzheimer's disease (AD) has caused an enormous social and economic burden on society. Currently, AD has neither clear pathogenesis nor effective treatments. Positron emission tomography (PET) and magnetic resonance imaging (MRI) have been verified as potential tools for diagnosing and monitoring Alzheimer's disease. However, the high costs, low spatial resolution, and long acquisition time limit their broad clinical utilization. The gold standard of AD diagnosis routinely used in research is imaging AD biomarkers with dyes or other reagents, which are unsuitable for in vivo studies owing to their potential toxicity and prolonged and costly process of the U.S. Food and Drug Administration (FDA) approval for human use. Furthermore, these exogenous reagents might bring unwarranted interference to mechanistic studies, causing unreliable results. Several label-free optical imaging techniques, such as infrared spectroscopic imaging (IRSI), Raman spectroscopic imaging (RSI), optical coherence tomography (OCT), autofluorescence imaging (AFI), optical harmonic generation imaging (OHGI), etc., have been developed to circumvent this issue and made it possible to offer an accurate and detailed analysis of AD biomarkers. In this review, we present the emerging label-free optical imaging techniques and their applications in AD, along with their potential and challenges in AD diagnosis.

Time-encoded stimulated Raman scattering microscopy of tumorous human pharynx tissue in the fingerprint region from 1500-1800 cm-1

Stimulated Raman scattering (SRS) microscopy for biomedical analysis can provide a molecular localization map to infer pathological tissue changes. Compared to spontaneous Raman, SRS achieves much faster imaging speeds at reduced spectral coverage. By targeting spectral features in the information dense fingerprint region, SRS allows fast and reliable imaging. We present time-encoded (TICO) SRS microscopy of unstained head-and-neck biopsies in the fingerprint region with molecular contrast. We combine a Fourier-domain mode-locked (FDML) laser with a master oscillator power amplifier (MOPA) to cover Raman transitions from 1500-1800cm^-1. Both lasers are fiber-based and electronically programmable making this fingerprint TICO system robust and reliable. The results of our TICO approach were cross-checked with a spontaneous Raman micro-spectrometer and show good agreement, paving the way toward clinical applications.

Advances in Application of Azobenzene as a Trigger in Biomedicine: Molecular Design and Spontaneous Assembly

Azobenzene is a well-known derivative of stimulus-responsive molecular switches and has shown superior performance as a functional material in biomedical applications. The results of multiple studies have led to the development of light/hypoxia-responsive azobenzene for biomedical use. In recent years, long-wavelength-responsive azobenzene has been developed. Matching the longer wavelength absorption and hypoxia-response characteristics of the azobenzene switch unit to the bio-optical window results in a large and effective stimulus response. In addition, azobenzene has been used as a hypoxia-sensitive connector via biological cleavage under appropriate stimulus conditions. This has resulted in on/off state switching of properties such as pharmacology and fluorescence activity. Herein, recent advances in the design and fabrication of azobenzene as a trigger in biomedicine are summarized.

Spontaneous Raman and Surface-Enhanced Raman Scattering Bioimaging

Raman spectroscopy is a specific, noninvasive and nondestructive optical technique and is able to obtain chemical information from molecules. Optical imaging based on Raman spectroscopy has been a powerful technique for monitoring minute chemical changes of biological samples and generating images through direct or indirect strategies. Two widely applied Raman imaging techniques include spontaneous Raman and surface-enhanced Raman scattering (SERS) imaging. In this chapter, we introduce the basic principles including the physics behind Raman and SERS imaging, design of Raman/SERS labels or probes, and current strategies for further improvements. The progress in the use of spontaneous Raman and SERS spectroscopy for bioimaging is discussed, either in fundamental studies or in biomedical theranostics. In addition, we give insights into the challenges and opportunities for improving Raman imaging performance.

Azo-Enhanced Raman Scattering for Enhancing the Sensitivity and Tuning the Frequency of Molecular Vibrations

Raman scattering provides stable narrow-banded signals that potentially allow for multicolor microscopic imaging. The major obstacle for the applications of Raman spectroscopy and microscopy is the small cross section of Raman scattering that results in low sensitivity. Here, we report a new concept of azo-enhanced Raman scattering (AERS) by designing the intrinsic molecular structures using resonance Raman and concomitant fluorescence quenching strategies. Based on the selection of vibrational modes and the enhancing unit of azobenzenes, we obtained a library of AERS molecules with specific Raman signals in the fingerprint and silent frequency regions. The spectral characterization and molecular simulation revealed that the azobenzene unit conjugated to the vibrational modes significantly enhanced Raman signals due to the mechanism of extending the conjugation system, coupling the electronic-vibrational transitions, and improving the symmetry of vibrational modes. The nonradiative decay of azobenzene from the excited state quenched the commitment fluorescence, thus providing a clean background for identifying Raman scattering. The most sensitive AERS molecules produced Raman signals of more than 4 orders of magnitude compared to 5-ethynyl-2'-deoxyuridine (EdU). In addition, a frequency tunability of 10 distinct Raman bands was achieved by selecting different types of vibrational modes. This methodology of AERS allows for designing small-molecule Raman probes to visualize various entities in complex systems by multicolor spontaneous Raman imaging. It will open new prospects to explore innovative applications of AERS in interdisciplinary research fields.

Monitoring Deuterium Uptake in Single Bacterial Cells via Two-Dimensional Raman Correlation Spectroscopy

Raman-stable isotope labeling using heavy water (Raman-D₂O) is attracting great interest as a fast technique with various applications ranging from the identification of pathogens in medical samples to the determination of microbial activity in the environment. Despite its widespread applications, little is known about the fundamental processes of hydrogen-deuterium (H/D) exchange, which are crucial for understanding molecular interactions in microorganisms. By combining two-dimensional (2D) correlation spectroscopy and Raman deuterium labeling, we have investigated H/D exchange in bacterial cells under time dependence. Most C-H stretching signals decreased in intensity over time, prior to the formation of the C-D stretching vibration signals. The intensity of the C-D signal gradually increased over time, and the shape of the C-D signal was more uniform after longer incubation times. Deuterium uptake showed high variability between the bacterial genera and mainly led to an observable labeling of methylene and methyl groups. Thus, the C-D signal encompassed a combination of symmetric and antisymmetric CD₂ and CD₃ stretching vibrations, depending on the bacterial genera. The present study allowed for the determination of the sequential order of deuterium incorporation into the functional groups of proteins, lipids, and nucleic acids and hence understanding the process of biomolecule synthesis and the growth strategies of different bacterial taxa. We present the combination of Raman-D₂O labeling and 2D correlation spectroscopy as a promising approach to gain a fundamental understanding of molecular interactions in biological systems.

Morpho-molecular signal correlation between optical coherence tomography and Raman spectroscopy for superior image interpretation and clinical diagnosis

The combination of manifold optical imaging modalities resulting in multimodal optical systems allows to discover a larger number of biomarkers than using a single modality. The goal of multimodal imaging systems is to increase the diagnostic performance through the combination of complementary modalities, e.g. optical coherence tomography (OCT) and Raman spectroscopy (RS). The physical signal origins of OCT and RS are distinctly different, i.e. in OCT it is elastic back scattering of photons, due to a change in refractive index, while in RS it is the inelastic scattering between photons and molecules. Despite those diverse characteristics both modalities are also linked via scattering properties and molecular composition of tissue. Here, we investigate for the first time the relation of co-registered OCT and RS signals of human bladder tissue, to demonstrate that the signals of these complementary modalities are inherently intertwined, enabling a direct but more importantly improved interpretation and better understanding of the other modality. This work demonstrates that the benefit for using two complementary imaging approaches is, not only the increased diagnostic value, but the increased information and better understanding of the signal origins of both modalities. This evaluation confirms the advantages for using multimodal imaging systems and also paves the way for significant further improved understanding and clinically interpretation of both modalities in the future.

Super-resolution vibrational microscopy by stimulated Raman excited fluorescence

Inspired by the revolutionary impact of super-resolution fluorescence microscopy, super-resolution Raman imaging has been long pursued because of its much higher chemical specificity than the fluorescence counterpart. However, vibrational contrasts are intrinsically less sensitive compared with fluorescence, resulting in only mild resolution enhancement beyond the diffraction limit even with strong laser excitation power. As such, it is still a great challenge to achieve biocompatible super-resolution vibrational imaging in the optical far-field. In 2019 Stimulated Raman Excited Fluorescence (SREF) was discovered as an ultrasensitive vibrational spectroscopy that combines the high chemical specificity of Raman scattering and the superb sensitivity of fluorescence detection. Herein we developed a novel super-resolution vibrational imaging method by harnessing SREF as the contrast mechanism. We first identified the undesired role of anti-Stokes fluorescence background in preventing direct adoption of super-resolution fluorescence technique. We then devised a frequency-modulation (FM) strategy to remove the broadband backgrounds and achieved high-contrast SREF imaging. Assisted by newly synthesized SREF dyes, we realized multicolor FM-SREF imaging with nanometer spectral resolution. Finally, by integrating stimulated emission depletion (STED) with background-free FM-SREF, we accomplished high-contrast super-resolution vibrational imaging with STED-FM-SREF whose spatial resolution is only determined by the signal-to-noise ratio. In our proof-of-principle demonstration, more than two times of resolution improvement is achieved in biological systems with moderate laser excitation power, which shall be further refined with optimized instrumentation and imaging probes. With its super resolution, high sensitivity, vibrational contrast, and mild laser excitation power, STED-FM-SREF microscopy is envisioned to aid a wide variety of applications.

Reduction of excess intensity noise of picosecond Yb soliton fiber lasers in a >10-mW power regime

We demonstrate that excess intensity noise of soliton fiber lasers in the average power regime exceeding 10 mW can be reduced by increasing the intracavity dispersion and reducing the pump power. Based on this strategy, we present a polarization-maintaining picosecond Yb fiber laser mode-locked by a nonlinear amplifying loop mirror whose excess noise is equal to the shot noise at an optical power of >10 mW.

Detection and Classification of Multi-Type Cells by Using Confocal Raman Spectroscopy

Tumor cells circulating in the peripheral blood are the prime cause of cancer metastasis and death, thus the identification and discrimination of these rare cells are crucial in the diagnostic of cancer. As a label-free detection method without invasion, Raman spectroscopy has already been indicated as a promising method for cell identification. This study uses a confocal Raman spectrometer with 532 nm laser excitation to obtain the Raman spectrum of living cells from the kidney, liver, lung, skin, and breast. Multivariate statistical methods are applied to classify the Raman spectra of these cells. The results validate that these cells can be distinguished from each other. Among the models built to predict unknown cell types, the quadratic discriminant analysis model had the highest accuracy. The demonstrated analysis model, based on the Raman spectrum of cells, is propitious and has great potential in the field of biomedical for classifying circulating tumor cells in the future.

Unveiling Cancer Metabolism through Spontaneous and Coherent Raman Spectroscopy and Stable Isotope Probing

Metabolic reprogramming is a common hallmark in cancer. The high complexity and heterogeneity in cancer render it challenging for scientists to study cancer metabolism. Despite the recent advances in single-cell metabolomics based on mass spectrometry, the analysis of metabolites is still a destructive process, thus limiting in vivo investigations. Being label-free and nonperturbative, Raman spectroscopy offers intrinsic information for elucidating active biochemical processes at subcellular level. This review summarizes recent applications of Raman-based techniques, including spontaneous Raman spectroscopy and imaging, coherent Raman imaging, and Raman-stable isotope probing, in contribution to the molecular understanding of the complex biological processes in the disease. In addition, this review discusses possible future directions of Raman-based technologies in cancer research.

Combined total internal reflection AF spectral-imaging and Raman spectroscopy for fast assessment of surgical margins during breast cancer surgery

The standard treatment for breast cancer is surgical removal mainly through breast-conserving surgery (BCS). We developed a new technique based on auto-fluorescence (AF) spectral imaging and Raman spectroscopy for fast intraoperative assessment of excision margins in BCS. A new wide-field AF imaging unit based on total internal reflection (TIR) was combined with a Raman spectroscopy microscope equipped with a 785 nm laser. The wavelength of the AF excitation was optimized to 365 nm in order to maximize the discrimination of adipose tissue. This approach allows for the non-adipose regions of tissue, which are at a higher risk of containing a tumor, to be targeted more efficiently by the Raman spectroscopy measurements. The integrated TIR-AF-Raman was tested on small tissue samples as well as fresh wide local excisions, delivering the analysis of the entire cruciate surface of BCS specimens (5.1 × 7.6 cm²) in less than 45 minutes and also providing information regarding the location of the tumor in the specimen. Full automation of the instrument and selection of a faster translation stage would allow for the measurement of BCS specimens within an intraoperative time scale (20 minutes). This study demonstrates that the TIR-AF Raman microscope represents a feasible step towards the development of a technique for intraoperative assessment of large WLE within intraoperative timescales.

Raman Imaging: An Impending Approach Towards Cancer Diagnosis

In accordance with the recent studies, Raman spectroscopy is well experimented as a highly sensitive analytical and imaging technique in biomedical research, mainly for various disease diagnosis including cancer. In comparison with other imaging modalities, Raman spectroscopy facilitate numerous assistances owing to its low background signal, immense spatial resolution, high chemical specificity, multiplexing capability, excellent photo stability and non-invasive detection capability. In cancer diagnosis Raman imaging intervened as a promising investigative tool to provide molecular level information to differentiate the cancerous vs non-cancerous cells, tissues and even in body fluids. Anciently, spontaneous Raman scattering is very feeble due to its low signal intensity and long acquisition time but new advanced techniques like coherent Raman scattering (CRS) and surface enhanced Raman scattering (SERS) gradually superseded these issues. So, the present review focuses on the recent developments and applications of Raman spectroscopy-based imaging techniques for cancer diagnosis.

Toward rapid infectious disease diagnosis with advances in surface-enhanced Raman spectroscopy

In a pandemic era, rapid infectious disease diagnosis is essential. Surface-enhanced Raman spectroscopy (SERS) promises sensitive and specific diagnosis including rapid point-of-care detection and drug susceptibility testing. SERS utilizes inelastic light scattering arising from the interaction of incident photons with molecular vibrations, enhanced by orders of magnitude with resonant metallic or dielectric nanostructures. While SERS provides a spectral fingerprint of the sample, clinical translation is lagged due to challenges in consistency of spectral enhancement, complexity in spectral interpretation, insufficient specificity and sensitivity, and inefficient workflow from patient sample collection to spectral acquisition. Here, we highlight the recent, complementary advances that address these shortcomings, including (1) design of label-free SERS substrates and data processing algorithms that improve spectral signal and interpretability, essential for broad pathogen screening assays; (2) development of new capture and affinity agents, such as aptamers and polymers, critical for determining the presence or absence of particular pathogens; and (3) microfluidic and bioprinting platforms for efficient clinical sample processing. We also describe the development of low-cost, point-of-care, optical SERS hardware. Our paper focuses on SERS for viral and bacterial detection, in hopes of accelerating infectious disease diagnosis, monitoring, and vaccine development. With advances in SERS substrates, machine learning, and microfluidics and bioprinting, the specificity, sensitivity, and speed of SERS can be readily translated from laboratory bench to patient bedside, accelerating point-of-care diagnosis, personalized medicine, and precision health.

Biophotonic technologies for assessment of breast tumor surgical margins-A review

Breast conserving surgery (BCS) offering similar surgical outcomes as mastectomy while retaining breast cosmesis is becoming increasingly popular for the management of early stage breast cancers. However, its association with reoperation rates of 20% to 40% following incomplete tumor removal warrants the need for a fast and accurate intraoperative surgical margin assessment tool that offers cellular, structural and molecular information of the whole specimen surface to a clinically relevant depth. Biophotonic technologies are evolving to qualify as such an intraoperative tool for clinical assessment of breast cancer surgical margins at the microscopic and macroscopic scale. Herein, we review the current research in the application of biophotonic technologies such as photoacoustic imaging, Raman spectroscopy, multimodal multiphoton imaging, diffuse optical imaging and fluorescence imaging using medically approved dyes for breast cancer detection and/or tumor subtype differentiation toward intraoperative assessment of surgical margins in BCS specimens, and possible challenges in their route to clinical translation.

Introduction to Infrared and Raman-Based Biomedical Molecular Imaging and Comparison with Other Modalities

Molecular imaging has rapidly developed to answer the need of image contrast in medical diagnostic imaging to go beyond morphological information to include functional differences in imaged tissues at the cellular and molecular levels. Vibrational (infrared (IR) and Raman) imaging has rapidly emerged among the molecular imaging modalities available, due to its label-free combination of high spatial resolution with chemical specificity. This article presents the physical basis of vibrational spectroscopy and imaging, followed by illustration of their preclinical in vitro applications in body fluids and cells, ex vivo tissues and in vivo small animals and ending with a brief discussion of their clinical translation. After comparing the advantages and disadvantages of IR/Raman imaging with the other main modalities, such as magnetic resonance imaging (MRI), computed tomography (CT), positron emission tomography/single-photon emission-computed tomography (PET/SPECT), ultrasound (US) and photoacoustic imaging (PAI), the design of multimodal probes combining vibrational imaging with other modalities is discussed, illustrated by some preclinical proof-of-concept examples.