High-Speed Coherent Raman Fingerprint Imaging of Biological Tissues

Estimation of biological variance in coherent Raman microscopy data of two cell lines using chemometrics

Broadband Coherent Anti-Stokes Raman Scattering (BCARS) is a valuable spectroscopic imaging tool for visualizing cellular structures and lipid distributions in biomedical applications. However, the inevitable biological changes in the samples (cells/tissues/lipids) introduce spectral variations in BCARS data and make analysis challenging. In this work, we conducted a systematic study to estimate the biological variance in BCARS data of two commonly used cell lines (HEK293 and HepG2) in biomedical research. The BCARS data were acquired from two different experimental setups (Leibniz Institute of Photonics Technology (IPHT) in Jena and Politecnico di Milano (POLIMI) in Milano) to evaluate the reproducibility of results. Also, spontaneous Raman data were independently acquired at POLIMI to validate those results. First, Kramers-Kronig (KK) algorithm was utilized to retrieve Raman-like signals from the BCARS data, and a pre-processing pipeline was subsequently used to standardize the data. Principal component analysis - Linear discriminant analysis (PCA-LDA) was performed using two cross-validation (CV) methods: batch-out CV and 10-fold CV. Additionally, the analysis was repeated, considering different spectral regions of the data as input to the PCA-LDA. Finally, the classification accuracies of the two BCARS datasets were compared with the results of spontaneous Raman data. The results demonstrated that the CH band region (2770-3070 cm-1) and spectral data in the 1500-1800 cm-1 region have significantly contributed to the classification. A maximum of 100% balanced accuracies were obtained for the 10-fold CV for both BCARS setups. However, in the case of batch-out CV, it is 92.4% for the IPHT dataset and 98.8% for the POLIMI dataset. This study offers a comprehensive overview for estimating biological variance in biomedical applications. The insights gained from this analysis hold promise for improving the reliability of BCARS measurements in biomedical applications, paving the way for more accurate and meaningful spectroscopic analyses in the study of biological systems.

Ultrabroadband two-beam coherent anti-Stokes Raman scattering and spontaneous Raman spectroscopy of organic fluids: A comparative study

Spontaneous Raman spectroscopy is a well-established diagnostic tool, allowing for the identification of all Raman active species with a single measurement. Yet, it may suffer from low-signal intensity and fluorescent background. In contrast, coherent anti-Stokes Raman scattering (CARS) offers laser-like signals, but the traditional approach lacks the multiplex capability of spontaneous Raman spectroscopy. We present an ultrabroadband CARS setup which aims at exciting the full spectrum (300-3700 cm-1) of biological molecules. A dual-output optical parametric amplifier provides a ~7 fs pump/Stokes and a ~700 fs probe pulse. CARS spectra of DMSO, ethanol, and methanol show great agreement with spontaneous Raman spectroscopy and superiority in fluorescent environments. The spectral resolution proves sufficient to differentiate between the complex spectra of L-proline and hydroxyproline. Moreover, decay constants in the sub picosecond range are determined for individual Raman transitions, providing an additional approach for sample characterization.

A Dual-Modal, Label-Free Raman Imaging Method for Rapid Virtual Staining of Large-Area Breast Cancer Tissue Sections

As one of the most common cancers, accurate, rapid, and simple histopathological diagnosis is very important for breast cancer. Raman imaging is a powerful technique for label-free analysis of tissue composition and histopathology, but it suffers from slow speed when applied to large-area tissue sections. In this study, we propose a dual-modal Raman imaging method that combines Raman mapping data with microscopy bright-field images to achieve virtual staining of breast cancer tissue sections. We validate our method on various breast tissue sections with different morphologies and biomarker expressions and compare it with the golden standard of histopathological methods. The results demonstrate that our method can effectively distinguish various types and components of tissues, and provide staining images comparable to stained tissue sections. Moreover, our method can improve imaging speed by up to 65 times compared to general spontaneous Raman imaging methods. It is simple, fast, and suitable for clinical applications.

Frequency-Domain Low-Wavenumber Hyperspectral Stimulated Raman Scattering Microscopy

In recent years, stimulated Raman scattering (SRS) microscopy has experienced rapid technological advancements and has found widespread applications in chemical analysis. Hyperspectral SRS (hSRS) microscopy further enhances the chemical selectivity in imaging by providing a Raman spectrum for each pixel. Time-domain hSRS techniques often require interferometry and ultrashort femtosecond laser pulses. They are especially suited to measuring low-wavenumber Raman transitions but are susceptible to scattering-induced distortions. Frequency-domain hSRS microscopy, on the other hand, offers a simpler optical configuration and demonstrates high tolerance to sample scattering but typically operates within the spectral range of 400-4000 cm-1. Conventional frequency-domain hSRS microscopy is widely employed in biological applications but falls short in detecting chemical bonds with a weaker vibrational energy. In this work, we extend the spectral coverage of picosecond spectral-focusing hSRS microscopy to below 100 cm-1. This frequency-domain low-wavenumber hSRS approach can measure the weaker vibrational energy from the sample and has a strong tolerance to sample scattering. By expanding spectral coverage to 100-4000 cm-1, this development enhances the capability of spectral-domain SRS microscopy for chemical imaging.

Label-free optical imaging for brain cancer assessment

Advances in label-free optical imaging offer a promising avenue for brain cancer assessment, providing high-resolution, real-time insights without the need for radiation or exogeneous agents. These cost-effective and intricately detailed techniques overcome the limitations inherent in magnetic resonance imaging (MRI), computed tomography (CT), and positron emission tomography (PET) scans by offering superior resolution and more readily accessible imaging options. This comprehensive review explores a variety of such methods, including photoacoustic imaging (PAI), optical coherence tomography (OCT), Raman imaging, and IR microscopy. It focuses on their roles in the detection, diagnosis, and management of brain tumors. By highlighting recent advances in these imaging techniques, the review aims to underscore the importance of label-free optical imaging in enhancing early detection and refining therapeutic strategies for brain cancer.

Collagen organization and structure in FBLN5-/- mice using label-free microscopy: implications for pelvic organ prolapse

Pelvic organ prolapse (POP) is a gynecological disorder described by the descent of superior pelvic organs into or out of the vagina as a consequence of disrupted muscles and tissue. A thorough understanding of the etiology of POP is limited by the availability of clinically relevant samples, restricting longitudinal POP studies on soft-tissue biomechanics and structure to POP-induced models such as fibulin-5 knockout (FBLN5-/- ) mice. Despite being a principal constituent in the extracellular matrix, little is known about structural perturbations to collagen networks in the FBLN5-/- mouse cervix. We identify significantly different collagen network populations in normal and prolapsed cervical cross-sections using two label-free, nonlinear microscopy techniques. Collagen in the prolapsed mouse cervix tends to be more isotropic, and displays reduced alignment persistence via 2-D Fourier transform analysis of images acquired using second harmonic generation microscopy. Furthermore, coherent Raman hyperspectral imaging revealed elevated disorder in the secondary structure of collagen in prolapsed tissues. Our results underscore the need for in situ multimodal monitoring of collagen organization to improve POP predictive capabilities.

Temporally optimized and spectrally shaped hyperspectral coherent anti-Stokes Raman scattering microscopy

Coherent anti-Stokes Raman scattering (CARS) microscopy offers label-free chemical contrasts based on molecular vibrations. Hyperspectral CARS (HS-CARS) microscopy enables comprehensive microscale chemical characterization of biological samples. Various HS-CARS methods have been developed with individual advantages and disadvantages. We present what we believe to be a new temporally optimized and spectrally shaped (TOSS) HS-CARS method to overcome the limitations of existing techniques by providing precise control of the spatial and temporal profiles of the excitation beams for efficient and accurate measurements. This method uniquely uses Fourier transform pulse shaping based on a two-dimensional spatial light modulator to control the phase and amplitude of the excitation beams. TOSS-HS-CARS achieves fast, stable, and flexible acquisition, minimizes photodamage, and is highly adaptable to a multimodal multiphoton imaging system.

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.

Spectral effects and enhancement quantification in healthy human saliva with surface-enhanced Raman spectroscopy using silver nanopillar substrates

OBJECTIVES

Raman spectroscopy as a diagnostic tool for biofluid applications is limited by low inelastic scattering contributions compared to the fluorescence background from biomolecules. Surface-enhanced Raman spectroscopy (SERS) can increase Raman scattering signals, thereby offering the potential to reduce imaging times. We aimed to evaluate the enhancement related to the plasmonic effect and quantify the improvements in terms of spectral quality associated with SERS measurements in human saliva.

METHODS

Dried human saliva was characterized using spontaneous Raman spectroscopy and SERS. A fabrication protocol was implemented leading to the production of silver (Ag) nanopillar substrates by glancing angle deposition. Two different imaging systems were used to interrogate saliva from 161 healthy donors: a custom single-point macroscopic system and a Raman micro-spectroscopy instrument. Quantitative metrics were established to compare spontaneous RS and SERS measurements: the Raman spectroscopy quality factor (QF), the photonic count rate (PR), the signal-to-background ratio (SBR).

RESULTS

SERS measurements acquired with an excitation energy four times smaller than with spontaneous RS resulted in improved QF, PR values an order of magnitude larger and a SBR twice as large. The SERS enhancement reached 100×, depending on which Raman bands were considered.

CONCLUSIONS

Single-point measurement of dried saliva with silver nanopillars substrates led to reproducible SERS measurements, paving the way to real-time tools of diagnosis in human biofluids.

Collagen organization and structure in FLBN5-/- mice using label-free microscopy: implications for pelvic organ prolapse

Pelvic organ prolapse (POP) is a gynecological disorder described by the descent of superior pelvic organs into or out of the vagina as a consequence of disrupted muscles and tissue. A thorough understanding of the etiology of POP is limited by the availability of clinically relevant samples, restricting longitudinal POP studies on soft-tissue biomechanics and structure to POP-induced models such as fibulin-5 knockout (FBLN5-/-) mice. Despite being a principal constituent in the extracellular matrix, little is known about structural perturbations to collagen networks in the FBLN5-/- mouse cervix. We identify significantly different collagen network populations in normal and prolapsed cervical cross-sections using two label-free, nonlinear microscopy techniques. Collagen in the prolapsed mouse cervix tends to be more isotropic, and displays reduced alignment persistence via 2-D Fourier Transform analysis of images acquired using second harmonic generation microscopy. Furthermore, coherent Raman hyperspectral imaging revealed elevated disorder in the secondary structure of collagen in prolapsed tissues. Our results underscore the need for in situ multimodal monitoring of collagen organization to improve POP predictive capabilities.

High-content stimulated Raman histology of human breast cancer

Histological examination is crucial for cancer diagnosis, however, the labor-intensive sample preparation involved in the histology impedes the speed of diagnosis. Recently developed two-color stimulated Raman histology could bypass the complex tissue processing to generates result close to hematoxylin and eosin staining, which is one of the golden standards in cancer histology. Yet, the underlying chemical features are not revealed in two-color stimulated Raman histology, compromising the effectiveness of prognostic stratification. Here, we present a high-content stimulated Raman histology (HC-SRH) platform that provides both morphological and chemical information for cancer diagnosis based on un-stained breast tissues. Methods: By utilizing both hyperspectral SRS imaging in the C-H vibration window and sparsity-penalized unmixing of overlapped spectral profiles, HC-SRH enabled high-content chemical mapping of saturated lipids, unsaturated lipids, cellular protein, extracellular matrix (ECM), and water. Spectral selective sampling was further implemented to boost the speed of HC-SRH. To show the potential for clinical use, HC-SRH using a compact fiber laser-based stimulated Raman microscope was demonstrated. Harnessing the wide and rapid tuning capability of the fiber laser, both C-H and fingerprint vibration windows were accessed. Results: HC-SRH successfully mapped unsaturated lipids, cellular protein, extracellular matrix, saturated lipid, and water in breast tissue. With these five chemical maps, HC-SRH provided distinct contrast for tissue components including duct, stroma, fat cell, necrosis, and vessel. With selective spectral sampling, the speed of HC-SRH was improved by one order of magnitude. The fiber-laser-based HC-SRH produced the same image quality in the C-H window as the state-of-the-art solid laser. In the fingerprint window, nucleic acid and solid-state ester contrast was demonstrated. Conclusions: HC-SRH provides both morphological and chemical information of tissue in a label-free manner. The chemical information detected is beyond the reach of traditional hematoxylin and eosin staining and heralds the potential of HC-SRH for biomarker discovery.

Compressive Raman imaging by combining scattering-projection interleaving with context-aware excitation

Exciting an object with a laser-focus array and randomly interleaving its scattering projection has been proved to be an effective strategy for speeding up Raman imaging. The so-called scattering interleaved Raman imaging (SIRI) method allows Raman hyperspectral imaging with a single snapshot and exhibits excellent reconstruction fidelity and signal-to-noise ratios (SNRs). Here, we show that the performance of SIRI is significantly improved when combined with context-aware excitation. The experiments on micro-plastics demonstrate that the restriction of Raman excitation within a smaller region of interest as guided by bright-field microscopy improves the signal intensity and the SNR, and it is surprising that the spectral resolution is also significantly improved. The context-aware SIRI method is successfully used for imaging of lipid-producing yeast cells, suggesting that it is a promising analytical tool for studying live cells or tissues.

Enhanced double resonance Raman scattering in multilayer graphene with broadband coherent anti-Stokes Raman spectroscopy

Graphene's unique gapless band structure and remarkably large third-order optical susceptibility have drawn significant attention to its nonlinear optical response, particularly in the context of coherent anti-Stokes Raman scattering (CARS). Under the combined influence of phononic and electronic resonances, the CARS response of graphene has been observed to exhibit a distinctive feature of time-resolved dip-to-peak evolution. Here, we report a greatly enhanced double resonance Raman mode beyond the G mode of multi-layer graphene with broadband CARS measurements. The significant difference in the intensity ratio between CARS and SR for this mode may be attributed to the preferential activation of low-frequency phonons in the impulsive stimulated Raman scattering process (ISRS) and a lower dephasing rate. Our results build on a foundation towards a deeper exploration of the coherent Raman response of two-dimensional materials.

Rapid single-particle chemical imaging of nanoplastics by SRS microscopy

Plastics are now omnipresent in our daily lives. The existence of microplastics (1 µm to 5 mm in length) and possibly even nanoplastics (<1 μm) has recently raised health concerns. In particular, nanoplastics are believed to be more toxic since their smaller size renders them much more amenable, compared to microplastics, to enter the human body. However, detecting nanoplastics imposes tremendous analytical challenges on both the nano-level sensitivity and the plastic-identifying specificity, leading to a knowledge gap in this mysterious nanoworld surrounding us. To address these challenges, we developed a hyperspectral stimulated Raman scattering (SRS) imaging platform with an automated plastic identification algorithm that allows micro-nano plastic analysis at the single-particle level with high chemical specificity and throughput. We first validated the sensitivity enhancement of the narrow band of SRS to enable high-speed single nanoplastic detection below 100 nm. We then devised a data-driven spectral matching algorithm to address spectral identification challenges imposed by sensitive narrow-band hyperspectral imaging and achieve robust determination of common plastic polymers. With the established technique, we studied the micro-nano plastics from bottled water as a model system. We successfully detected and identified nanoplastics from major plastic types. Micro-nano plastics concentrations were estimated to be about 2.4 ± 1.3 × 105 particles per liter of bottled water, about 90% of which are nanoplastics. This is orders of magnitude more than the microplastic abundance reported previously in bottled water. High-throughput single-particle counting revealed extraordinary particle heterogeneity and nonorthogonality between plastic composition and morphologies; the resulting multidimensional profiling sheds light on the science of nanoplastics.

Fluorescence Microscopy: a statistics-optics perspective

Fundamental properties of light unavoidably impose features on images collected using fluorescence microscopes. Modeling these features is ever more important in quantitatively interpreting microscopy images collected at scales on par or smaller than light's wavelength. Here we review the optics responsible for generating fluorescent images, fluorophore properties, microscopy modalities leveraging properties of both light and fluorophores, in addition to the necessarily probabilistic modeling tools imposed by the stochastic nature of light and measurement.

Profiling single cancer cell metabolism via high-content SRS imaging with chemical sparsity

Metabolic reprogramming in a subpopulation of cancer cells is a hallmark of tumor chemoresistance. However, single-cell metabolic profiling is difficult because of the lack of a method that can simultaneously detect multiple metabolites at the single-cell level. In this study, through hyperspectral stimulated Raman scattering (hSRS) imaging in the carbon-hydrogen (C-H) window and sparsity-driven hyperspectral image decomposition, we demonstrate a high-content hSRS (h2SRS) imaging approach that enables the simultaneous mapping of five major biomolecules, including proteins, carbohydrates, fatty acids, cholesterol, and nucleic acids at the single-cell level. h2SRS imaging of brain and pancreatic cancer cells under chemotherapy revealed acute and adapted chemotherapy-induced metabolic reprogramming and the unique metabolic features of chemoresistance. Our approach is expected to facilitate the discovery of therapeutic targets to combat chemoresistance. This study illustrates a high-content, label-free chemical imaging approach that measures metabolic profiles at the single-cell level and warrants further research on cellular metabolism.

Removing non-resonant background from broadband CARS using a physics-informed neural network

Broadband coherent anti-Stokes Raman scattering (BCARS) is capable of producing high-quality Raman spectra spanning broad bandwidths, 400-4000 cm-1, with millisecond acquisition times. Raw BCARS spectra, however, are a coherent combination of vibrationally resonant (Raman) and non-resonant (electronic) components that may challenge or degrade chemical analyses. Recently, we demonstrated a deep convolutional autoencoder network, trained on pairs of simulated BCARS-Raman datasets, which could retrieve the Raman signal with high quality under ideal conditions. In this work, we present a new computational system that incorporates experimental measurements of the laser system spectral and temporal properties, combined with simulated susceptibilities. Thus, the neural network learns the mapping between the susceptibility and the measured response for a specific BCARS system. The network is tested on simulated and measured experimental results taken with our BCARS system.

Air-laser-based coherent Raman spectroscopy of atmospheric molecules in a filamentary plasma grating

Coherent Raman spectroscopy (CRS) with air-laser-based hybrid femtosecond/picosecond (fs/ps) pulses has shown promising potential for remote detection and surveillance of atmospheric species with high temporal and frequency resolution. Here, to enhance the sensitivity and extend the detection distance, we generate the CRS spectra of air molecules in situ in a filamentary plasma grating, and show that the grating can efficiently enhance the intensities of the coherent vibrational Raman lines of N2, O2, and N2 + by 2-3 orders of magnitude at an extended distance. By examining the intensities of the Raman lines, fs-pulsed supercontinuum, and ps-pulsed air laser produced under different grating conditions, we reveal that the optimization of the Raman lines is achieved by the dynamic balance between the supercontinuum-induced vibrational coherence and air-laser-induced polarization of the air species.

Intense and Superflat White Laser with 700-nm 3-dB Bandwidth and 1-mJ Pulse Energy Enabling Single-Shot Subpicosecond Pulse Laser Spectroscopy

An optical spectrometer is a basic spectral instrument that probes microscopic physical and chemical properties of macroscopic objects but generally suffers from difficulty in broadband time-resolved measurement. In this work, we report the creation of ultrabroadband white-light laser with a 3-dB bandwidth covering 385 to 1,080 nm, pulse energy of 1.07 mJ, and pulse duration of several hundred femtoseconds by passing 3-mJ pulse energy, 50-fs pulse duration Ti:Sapphire pulse laser through a cascaded fused silica plate and chirped periodically poled lithium niobate crystal. We utilize this unprecedented superflat, ultrabroadband, and intense femtosecond laser light source to build a single-shot (i.e., single-pulse) subpicosecond pulse laser ultraviolet-visible-near-infrared spectrometer and successfully measure various atomic and molecular absorption spectra. The single-shot ultrafast spectrometer may open up a frontier to monitor simultaneously the ultrafast dynamics of multiple physical and chemical processes in various microscopic systems.

Monitoring and modelling the glutamine metabolic pathway: a review and future perspectives

BACKGROUND

Analysis of the glutamine metabolic pathway has taken a special place in metabolomics research in recent years, given its important role in cell biosynthesis and bioenergetics across several disorders, especially in cancer cell survival. The science of metabolomics addresses the intricate intracellular metabolic network by exploring and understanding how cells function and respond to external or internal perturbations to identify potential therapeutic targets. However, despite recent advances in metabolomics, monitoring the kinetics of a metabolic pathway in a living cell in situ, real-time and holistically remains a significant challenge.

AIM

This review paper explores the range of analytical approaches for monitoring metabolic pathways, as well as physicochemical modeling techniques, with a focus on glutamine metabolism. We discuss the advantages and disadvantages of each method and explore the potential of label-free Raman microspectroscopy, in conjunction with kinetic modeling, to enable real-time and in situ monitoring of the cellular kinetics of the glutamine metabolic pathway.

KEY SCIENTIFIC CONCEPTS

Given its important role in cell metabolism, the ability to monitor and model the glutamine metabolic pathways are highlighted. Novel, label free approaches have the potential to revolutionise metabolic biosensing, laying the foundation for a new paradigm in metabolomics research and addressing the challenges in monitoring metabolic pathways in living cells.

Raman Imaging Reveals Insights into Membrane Phase Biophysics in Cells

Cellular membranes are essential components of all living organisms. They are composed of a complex mixture of lipids with diverse chemical structures and crucial biological functions. The dynamic and heterogeneous nature of cellular membranes presents a challenge for studying their biophysical properties and organization in vivo. Raman imaging, particularly coherent Raman scattering techniques such as stimulated Raman scattering (SRS) microscopy, have emerged as powerful tools for studying cellular membranes with high spatial and temporal resolution and minimal perturbation. In this Review, we discuss the scientific importance and technical challenges of characterizing membrane composition in cellular contexts and how the advances of Raman imaging can provide unique insights into membrane phase behavior and organization. We also highlight recent applications of Raman imaging in studying cellular membranes and implications in diseases. In particular, the discovery of phase separation and a solid-phase intracellular membrane on endoplasmic reticulum is reviewed in detail, shedding light on the biology of lipotoxicity.

Label-free mid-infrared photothermal live-cell imaging beyond video rate

Advancement in mid-infrared (MIR) technology has led to promising biomedical applications of MIR spectroscopy, such as liquid biopsy or breath diagnosis. On the contrary, MIR microscopy has been rarely used for live biological samples in an aqueous environment due to the lack of spatial resolution and the large water absorption background. Recently, mid-infrared photothermal (MIP) imaging has proven to be applicable to 2D and 3D single-cell imaging with high spatial resolution inherited from visible light. However, the maximum measurement rate has been limited to several frames s^-1, limiting its range of use. Here, we develop a significantly improved wide-field MIP quantitative phase microscope with two orders-of-magnitude higher signal-to-noise ratio than previous MIP imaging techniques and demonstrate live-cell imaging beyond video rate. We first derive optimal system design by numerically simulating thermal conduction following the photothermal effect. Then, we develop the designed system with a homemade nanosecond MIR optical parametric oscillator and a high full-well-capacity image sensor. Our high-speed and high-spatial-resolution MIR microscope has great potential to become a new tool for life science, in particular for live-cell analysis.

The Emerging Role of Raman Spectroscopy as an Omics Approach for Metabolic Profiling and Biomarker Detection toward Precision Medicine

Omics technologies have rapidly evolved with the unprecedented potential to shape precision medicine. Novel omics approaches are imperative toallow rapid and accurate data collection and integration with clinical information and enable a new era of healthcare. In this comprehensive review, we highlight the utility of Raman spectroscopy (RS) as an emerging omics technology for clinically relevant applications using clinically significant samples and models. We discuss the use of RS both as a label-free approach for probing the intrinsic metabolites of biological materials, and as a labeled approach where signal from Raman reporters conjugated to nanoparticles (NPs) serve as an indirect measure for tracking protein biomarkers in vivo and for high throughout proteomics. We summarize the use of machine learning algorithms for processing RS data to allow accurate detection and evaluation of treatment response specifically focusing on cancer, cardiac, gastrointestinal, and neurodegenerative diseases. We also highlight the integration of RS with established omics approaches for holistic diagnostic information. Further, we elaborate on metal-free NPs that leverage the biological Raman-silent region overcoming the challenges of traditional metal NPs. We conclude the review with an outlook on future directions that will ultimately allow the adaptation of RS as a clinical approach and revolutionize precision medicine.

Single-shot detection of bacterial spores with Yb-laser-based CARS spectroscopy

We present a system based on a high-energy femtosecond ytterbium laser seeding an optical parametric amplifier and a photonic crystal hollow core fiber (PCHCF) compressor for coherent anti-Stokes Raman scattering (CARS) spectroscopy. The PCHCF provides spectral broadening of the Stokes pulse which is then compressed to a duration matched to that of the pump pulse. In these conditions, the excitation efficiency of vibrational levels in the target molecules is largely improved, as the time gating effect due to the mismatch between the durations of the pump and Stokes pulses is avoided. Experiments are presented along with a theoretical model to quantify expected improvement of sensitivity. The system is used to detect bacterial spores deposited on a surface with a single laser shot at unprecedented signal-to-noise ratio.

Toward Gene-Correlated Spatially Resolved Metabolomics with Fingerprint Coherent Raman Imaging

Raman spectroscopy has long been known to provide sufficient information to discriminate distinct cell phenotypes. Underlying this discriminating capability is that Raman spectra provide an overall readout of the metabolic profiles that change with transcriptomic activity. Robustly associating Raman spectral changes with the regulation of specific signaling pathways may be possible, but the spectral signals of interest may be weak and vary somewhat among individuals. Establishing a Raman-to-transcriptome mapping will thus require tightly controlled and easily manipulated biological systems and high-throughput spectral acquisition. We attempt to meet these requirements using broadband coherent anti-Stokes Raman scattering (BCARS) microscopy to spatio-spectrally map the C. elegans hermaphrodite gonad in vivo at subcellular resolution. The C. elegans hermaphrodite gonad is an ideal model system with a sequential, continuous process of highly regulated spatiotemporal cellular events. We demonstrate that the BCARS spatio-spectral signatures correlate with gene expression profiles in the gonad, evincing that BCARS has potential as a spatially resolved omics surrogate.

Nanoscale bond-selective imaging by computational fusion of atomic force microscopy and coherent anti-Stokes Raman scattering microscopy

Vibrational microscopy based on coherent Raman scattering is a powerful tool for high-speed chemical imaging, but its lateral resolution is bound to the optical diffraction limit. On the other hand, atomic force microscopy (AFM) provides nano-scale spatial resolution, yet with lower chemical specificity. In this study, we leverage a computational approach called pan-sharpening to merge AFM topography images and coherent anti-Stokes Raman scattering (CARS) images. The hybrid system combines the advantages of both modalities, providing informative chemical mapping with ∼20 nm spatial resolution. CARS and AFM images were sequentially acquired on a single multimodal platform, which facilitates image co-localization. Our image fusion approach allowed for discerning merged neighboring features previously invisible due to the diffraction limit and identifying subtle unobservable structures with the input from AFM images. Compared to tip-enhanced CARS measurement, sequential acquisition of CARS and AFM images enables higher laser power to be used and avoids any tip damage caused by the incident laser beams, resulting in a significantly improved CARS image quality. Together, our work suggests a new direction for achieving super-resolution coherent Raman scattering imaging of materials through a computational approach.

Analytical Techniques for Single-Cell Biochemical Assays of Lipids

Lipids are essential cellular components forming membranes, serving as energy reserves, and acting as chemical messengers. Dysfunction in lipid metabolism and signaling is associated with a wide range of diseases including cancer and autoimmunity. Heterogeneity in cell behavior including lipid signaling is increasingly recognized as a driver of disease and drug resistance. This diversity in cellular responses as well as the roles of lipids in health and disease drive the need to quantify lipids within single cells. Single-cell lipid assays are challenging due to the small size of cells (∼1 pL) and the large numbers of lipid species present at concentrations spanning orders of magnitude. A growing number of methodologies enable assay of large numbers of lipid analytes, perform high-resolution spatial measurements, or permit highly sensitive lipid assays in single cells. Covered in this review are mass spectrometry, Raman imaging, and fluorescence-based assays including microscopy and microseparations.

The marriage of coherent Raman scattering imaging and advanced computational tools

Coherent Raman scattering microscopy can provide high-contrast tissue and single-cell images based on the inherent molecular vibrations of the sample. However, conventional techniques face a three-way trade-off between Raman spectral bandwidth, imaging speed, and image fidelity. Although currently challenging to address via optical design, this trade-off can be overcome via emerging computational tools such as compressive sensing and machine learning.

A Fano-resonance plasmonic assembly for broadband-enhanced coherent anti-Stokes Raman scattering

Surface-enhanced coherent anti-Stokes Raman scattering (SECARS) technique has triggered huge interests due to the significant signal enhancement for high-sensitivity detection. Previous SECARS work has tended to focus only on the enhancement effect at a certain combination of frequencies, more suitable for single-frequency CARS. In this work, based on the enhancement factor for broadband SECARS excitation process, a novel Fano resonance plasmonic nanostructure for SECARS is studied. In addition to the 12 orders of magnitude enhancement effect that can be realized under single-frequency CARS, this structure also shows huge enhancement under broadband CARS in a wide wavenumber region, covering most of the fingerprint region. This geometrically-tunable Fano plasmonic nanostructure provides a way to realize broadband-enhanced CARS, with potentials in single-molecular monitoring and high-selectivity biochemical detection.

High-Speed Stimulated Raman Scattering Microscopy Using Inertia-Free AOD Scanning

High-throughput stimulated Raman scattering (SRS) microscopy is highly desired for large tissue imaging with chemical specificity. However, the mapping speed remains as the major short board of conventional SRS, primarily owing to the mechanical inertia existing in galvanometers or other laser scanning alternatives. Here, we developed inertia-free acousto-optic deflector (AOD)-based high-speed large-field stimulated Raman scattering microscopy, in which both the speed and integration time are ensured by immune of the mechanical response time. To avoid laser beam distortion induced by the intrinsic spatial dispersion of AODs, two spectral compression systems are implemented to compress the broad-band femtosecond pulse to picosecond laser. We achieved an SRS imaging of a 12 × 8 mm² mouse brain slice in only 8 min at an image resolution of approximately 1 μm and 32 slices from a whole brain in 12 h. The AOD-based inertia-free SRS mapping can be much faster after further upgrading and allow broad-spectrum applications of chemical imaging in the future.

Toward the Next Frontiers of Vibrational Bioimaging

Chemical imaging based on vibrational contrasts can extract molecular information entangled in complex biological systems. To this end, nonlinear Raman scattering microscopy, mid-infrared photothermal (MIP) microscopy, and atomic force microscopy (AFM)-based force-detected photothermal microscopies are emerging with better chemical sensitivity, molecular specificity, and spatial resolution than conventional vibrational methods. Their utilization in bioimaging applications has provided biological knowledge in unprecedented detail. This Perspective outlines key methodological developments, bioimaging applications, and recent technical innovations of the three techniques. Representative biological demonstrations are also highlighted to exemplify the unique advantages of obtaining vibrational contrasts. With years of effort, these three methods compose an expanding vibrational bioimaging toolbox to tackle specific bioimaging needs, benefiting many biological investigations with rich information in both label-free and labeling manners. Each technique will be discussed and compared in the outlook, leading to possible future directions to accommodate growing needs in vibrational bioimaging.

Birefringence based multi-focus fs/ps-CARS spectroscopy for thermometry and hyperspectral microscopy

We present a multi-focus fs/ps-CARS scheme to perform spectroscopy on multiple points simultaneously for gas phase measurements and microscopy, using a single birefringence crystal or a combination of birefringent stacks. CARS performances are first reported for 1 kHz single-shot N₂ spectroscopy on two points set few millimeters apart, allowing thermometry measurements to be carried out in the vicinity of a flame. Then, simultaneous acquisition of toluene spectra is demonstrated on two points set 14 µm apart in a microscope setup. Finally, two-point and four-point hyperspectral imaging of PMMA microbeads in water is performed, demonstrating a proportional increase in acquisition speed.

Ultrafast Spectral Tuning of a Fiber Laser for Time-Encoded Multiplex Coherent Raman Scattering Microscopy

Coherent Raman scattering microscopy utilizing bioorthogonal tagging approaches like isotope or alkyne labeling allows for a targeted monitoring of spatial distribution and dynamics of small molecules of interest in cells, tissues, and other complex biological matrices. To fully exploit this approach in terms of real-time monitoring of several Raman tags, e.g., to study drug uptake dynamics, extremely fast tunable lasers are needed. Here, we present a laser concept without moving parts and fully electronically controlled for the quasi-simultaneous acquisition of coherent anti-Stokes Raman scattering images at multiple Raman resonances. The laser concept is based on the combination of a low noise and spectrally narrow Fourier domain mode-locked laser seeding a compact four wave mixing-based high-power fiber-based optical parametric amplifier.

Stimulated Raman Scattering Imaging Sheds New Light on Lipid Droplet Biology

A lipid droplet (LD) is a dynamic organelle closely associated with cellular functions and energy homeostasis. Dysregulated LD biology underlies an increasing number of human diseases, including metabolic disease, cancer, and neurodegenerative disorder. Commonly used lipid staining and analytical tools have difficulty providing the information regarding LD distribution and composition at the same time. To address this problem, stimulated Raman scattering (SRS) microscopy uses the intrinsic chemical contrast of biomolecules to achieve both direct visualization of LD dynamics and quantitative analysis of LD composition with high molecular selectivity at the subcellular level. Recent developments of Raman tags have further enhanced sensitivity and specificity of SRS imaging without perturbing molecular activity. With these advantages, SRS microscopy has offered great promise for deciphering LD metabolism in single live cells. This article overviews and discusses the latest applications of SRS microscopy as an emerging platform to dissect LD biology in health and disease.

High-throughput line-illumination Raman microscopy with multislit detection

Raman microscopy is an emerging tool for molecular imaging and analysis of living samples. Use of Raman microscopy in life sciences is, however, still limited because of its slow measurement speed for spectral imaging and analysis. We developed a multiline-illumination Raman microscope to achieve ultrafast Raman spectral imaging. A spectrophotometer equipped with a periodic array of confocal slits detects Raman spectra from a sample irradiated by multiple line illuminations. A comb-like Raman hyperspectral image is formed on a two-dimensional detector in the spectrophotometer, and a hyperspectral Raman image is acquired by scanning the sample with multiline illumination array. By irradiating a sample with 21 simultaneous illumination lines, we achieved high-throughput Raman hyperspectral imaging of mouse brain tissue, acquiring 1108800 spectra in 11.4 min. We also measured mouse kidney and liver tissue as well as conducted label-free live-cell molecular imaging. The ultrafast Raman hyperspectral imaging enabled by the presented technique will expand the possible applications of Raman microscopy in biological and medical fields.

Rapid coherent Raman hyperspectral imaging based on delay-spectral focusing dual-comb method and deep learning algorithm

Rapid coherent Raman hyperspectral imaging shows great promise for applications in sensing, medical diagnostics, and dynamic metabolism monitoring. However, the spectral acquisition speed of current multiplex coherent anti-Stokes Raman scattering (CARS) microscopy is generally limited by the spectrometer integration time, and as the detection speed increases, the signal-to-noise ratio (SNR) of single spectrum will decrease, leading to a terrible imaging quality. In this Letter, we report a dual-comb coherent Raman hyperspectral microscopy imaging system developed by integrating two approaches, a rapid delay-spectral focusing method and deep learning. The spectral refresh rate is exploited by focusing the relative delay scanning in the effective Raman excitation region, enabling a spectral acquisition speed of 36 kHz, ≈4 frames/s, for a pixel resolution of 95 × 95 pixels and a spectral bandwidth no less than 200 cm^-1. To improve the spectral SNR and imaging quality, the deep learning models are designed for spectral preprocessing and automatic unsupervised feature extraction. In addition, by changing the relative delay focusing region of the comb pairs, the detected spectral wavenumber region can be flexibly tuned to the high SNR region of the spectrum.

High power ytterbium rod-type fiber laser delivering tunable picosecond pulses

We designed an all-normal dispersion ytterbium rod-type fiber laser oscillator delivering picosecond pulses which are continuously tunable both in central wavelength and pulse duration. This system delivers self-mode-locked pulses with an average power up to 25 W. At a repetition rate of 78 MHz, it yields picosecond laser pulses, of which the central wavelength and pulse duration can be tuned between 1010 nm - 1060 nm and 4.5 ps - 1.8 ps, respectively. The tunability is obtained by adjusting the position and the width of a slit which acts as a spectral bandwidth filter, placed close to the center of a 4f-folded zero dispersion line inserted in the laser cavity. This oscillator delivers nearly Fourier limited pulses with at most a 1.2 time-bandwidth product. A numerical model accounts well for the behavior of this all-normal dispersion fiber oscillator.

Super-resolved Raman imaging via galvo-painted structured line illumination

Traditional line-scan Raman imaging features a rapid imaging speed while preserving complete spectral information, yet has diffraction-limited resolution. Sinusoidally structured line excitation can yield an improvement in the lateral resolution of the Raman image along the line's direction. However, given the need for the line and spectrometer slit to be aligned, the resolution in the perpendicular direction remains diffraction limited. To overcome this, we present here a galvo-modulated structured line imaging system, where a system of three galvos can arbitrarily orient the structured line on the sample plane, while keeping the beam aligned to the spectrometer slit in the detection plane. Thus, a two-fold isotropic improvement in the lateral resolution fold is possible. We demonstrate the feasibility using mixtures of microspheres as chemical and size standards. The results prove an improvement in the lateral resolution of 1.8-fold (limited by line contrast at higher frequencies), while preserving complete spectral information of the sample.

Raman Spectroscopy for Chemical Biology Research

In chemical biology research, various fluorescent probes have been developed and used to visualize target proteins or molecules in living cells and tissues, yet there are limitations to this technology, such as the limited number of colors that can be detected simultaneously. Recently, Raman spectroscopy has been applied in chemical biology to overcome such limitations. Raman spectroscopy detects the molecular vibrations reflecting the structures and chemical conditions of molecules in a sample and was originally used to directly visualize the chemical responses of endogenous molecules. However, our initial research to develop "Raman tags" opens a new avenue for the application of Raman spectroscopy in chemical biology. In this Perspective, we first introduce the label-free Raman imaging of biomolecules, illustrating the biological applications of Raman spectroscopy. Next, we highlight the application of Raman imaging of small molecules using Raman tags for chemical biology research. Finally, we discuss the development and potential of Raman probes, which represent the next-generation probes in chemical biology.

Coherent Raman spectroscopy on hydrogen with in-situ generation, in-situ use, and in-situ referencing of the ultrabroadband excitation

Time-resolved spectroscopy can provide valuable insights in hydrogen chemistry, with applications ranging from fundamental physics to the use of hydrogen as a commercial fuel. This work represents the first-ever demonstration of in-situ femtosecond laser-induced filamentation to generate a compressed supercontinuum behind a thick optical window, and its in-situ use to perform femtosecond/picosecond coherent Raman spectroscopy (CRS) on molecular hydrogen (H₂). The ultrabroadband coherent excitation of Raman active molecules in measurement scenarios within an enclosed space has been hindered thus far by the window material imparting temporal stretch to the pulse. We overcome this challenge and present the simultaneous single-shot detection of the rotational H₂ and the non-resonant CRS spectra in a laminar H₂/air diffusion flame. Implementing an in-situ referencing protocol, the non-resonant spectrum measures the spectral phase of the supercontinuum pulse and maps the efficiency of the ultrabroadband coherent excitation achieved behind the window. This approach provides a straightforward path for the implementation of ultrabroadband H₂ CRS in enclosed environment such as next-generation hydrogen combustors and reforming reactors.

A bimodal type of AgPd Plasmonic Blackbody Nanozyme with boosted catalytic efficacy and synergized photothermal therapy for efficacious tumor treatment in the second biological window

Nanozymes are promising for precise cancer treatment, but are typically limited in terms of the low catalytic efficiency and the complexity in tumor microenvironment (TME). Herein, we describe a bimodal type of AgPd plasmonic blackbody (AgPd PB) nanozyme of compact sizes (< 30 nm), which presents not only boosted enzyme efficacy but also efficient photothermal therapy (PTT) for synergized therapy through tissue-penetrating light in the second biological window (1000–1700 nm). The synthesized hyperbranched AgPd PB nanozymes possess intense and broadband localized surface plasmonic resonance absorption of 400–1300 nm, entailing prominent photothermal efficiency (η = 45.1% at 1064 nm) for PTT. Importantly, PTT was found to significantly boost the nanozyme efficacy of both catalase (CAT) and peroxidase (POD) processes, which correspondingly decompose H₂O₂ to into O₂ to relieve tumor hypoxia, and activate H₂O₂ to generate oxidative •OH radical. While the generated •OH was found to be able to minimize heat shock proteins (HSPs), which plays a vital role to counterbalance PTT effect both in vitro and in vivo. As compared to control ground without treatment, the synergized nanozyme and PTT activities resulted in about 7-fold reduction of tumor volume, thus elevating the survival rate from 0 to 80% at 30 days posttreatment. Besides the synergistic therapy, the AgPd PB nanozyme were shown to own fluorescence, computed tomography (CT), and photoacoustic (PA) imaging abilities, thus having implications for uses in imaging-guided precise cancer therapy. This study provides a paradigm of TME responsive theranostics under NIR-II light irradiation.

Fingerprint multiplex CARS at high speed based on supercontinuum generation in bulk media and deep learning spectral denoising

We introduce a broadband coherent anti-Stokes Raman scattering (CARS) microscope based on a 2-MHz repetition rate ytterbium laser generating 1035-nm high-energy (≈µJ level) femtosecond pulses. These features of the driving laser allow producing broadband red-shifted Stokes pulses, covering the whole fingerprint region (400-1800 cm^-1), employing supercontinuum generation in a bulk crystal. Our system reaches state-of-the-art acquisition speed (<1 ms/pixel) and unprecedented sensitivity of ≈14.1 mmol/L when detecting dimethyl sulfoxide in water. To further improve the performance of the system and to enhance the signal-to-noise ratio of the CARS spectra, we designed a convolutional neural network for spectral denoising, coupled with a post-processing pipeline to distinguish different chemical species of biological tissues.

Raman signal extraction from CARS spectra using a learned-matrix representation of the discrete Hilbert transform

Removing distortions in coherent anti-Stokes Raman scattering (CARS) spectra due to interference with the nonresonant background (NRB) is vital for quantitative analysis. Popular computational approaches, the Kramers-Kronig relation and the maximum entropy method, have demonstrated success but may generate significant errors due to peaks that extend in any part beyond the recording window. In this work, we present a learned matrix approach to the discrete Hilbert transform that is easy to implement, fast, and dramatically improves accuracy of Raman retrieval using the Kramers-Kronig approach.

Bringing Vibrational Imaging to Chemical Biology with Molecular Probes

As an emerging optical imaging modality, stimulated Raman scattering (SRS) microscopy provides invaluable opportunities for chemical biology studies using its rich chemical information. Through rapid progress over the past decade, the development of Raman probes harnessing the chemical biology toolbox has proven to play a key role in advancing SRS microscopy and expanding biological applications. In this perspective, we first discuss the development of biorthogonal SRS imaging using small tagging of triple bonds or isotopes and highlight their unique advantages for metabolic pathway analysis and microbiology investigations. Potential opportunities for chemical biology studies integrating small tagging with SRS imaging are also proposed. We next summarize the current designs of highly sensitive and super-multiplexed SRS probes, as well as provide future directions and considerations for next-generation functional probe design. These rationally designed SRS probes are envisioned to bridge the gap between SRS microscopy and chemical biology research and should benefit their mutual development.

Discriminating cell line specific features of antibiotic-resistant strains of Escherichia coli from Raman spectra via machine learning analysis

While Raman spectroscopy can provide label-free discrimination between highly similar biological species, the discrimination is often marginal, and optimal use of spectral information is imperative. Here, we compare two machine learning models, an artificial neural network and a support vector machine, for discriminating between Raman spectra of 11 bacterial mutants of Escherichia coli MDS42. While we find that both models discriminate the 11 bacterial strains with similarly high accuracy, sensitivity and specificity, it is clear that the models form different class boundaries. By extracting strain-specific (and function-specific) spectral features utilized by the models, we find that both models utilize a small subset of high intensity peaks while separate subsets of lower intensity peaks are utilized by only one method or the other. This analysis highlights the need for methods to use the complete spectral information more effectively, beginning with a better understanding of the distinct information gained from each model.

Polarization-perceptual anisotropic two-dimensional ReS2 neuro-transistor with reconfigurable neuromorphic vision

Polarization is a common and unique phenomenon in nature, which reveals more camouflage features of objects. However, current polarization-perceptual devices based on conventional physical architectures face enormous challenges for high-performance computation due to the traditional von Neumann bottleneck. In this work, a novel polarization-perceptual neuro-transistor with reconfigurable anisotropic vision is proposed based on a two-dimensional ReS₂ phototransistor. The device exhibits excellent photodetection ability and superior polarization sensitivity due to its direct band gap semiconductor property and strong anisotropic crystal structure, respectively. The fascinating polarization-sensitive neuromorphic behavior, such as polarization memory consolidation and reconfigurable visual imaging, are successfully realized. In particular, the regulated polarization responsivity and dichroic ratio are successfully emulated through our artificial compound eyes. More importantly, two intriguing polarization-perceptual applications for polarized navigation with reconfigurable adaptive learning abilities and three-dimensional visual polarization imaging are also experimentally demonstrated. The proposed device may provide a promising opportunity for future polarization perception systems in intelligent humanoid robots and autonomous vehicles.

Intraoperative imaging in pathology-assisted surgery

The pathological assessment of surgical specimens during surgery can reduce the incidence of positive resection margins, which otherwise can result in additional surgeries or aggressive therapeutic regimens. To improve patient outcomes, intraoperative spectroscopic, fluorescence-based, structural, optoacoustic and radiological imaging techniques are being tested on freshly excised tissue. The specific clinical setting and tumour type largely determine whether endogenous or exogenous contrast is to be detected and whether the tumour specificity of the detected biomarker, image resolution, image-acquisition times or penetration depth are to be prioritized. In this Perspective, we describe current clinical standards for intraoperative tissue analysis and discuss how intraoperative imaging is being implemented. We also discuss potential implementations of intraoperative pathology-assisted surgery for clinical decision-making.