Spontaneous Raman Spectroscopy Research Articles

Multimodal method of tissue differentiation in neurooncology using Raman spectroscopy, fluorescence and diffuse reflectance spectroscopy

There is a need to expand the possibilities of urgent analysis of intracranial tumor type during resection. These measures are necessary to improve resection quality with preservation of intact tissues and avoiding recurrence and neurological impairment in postoperative period. To create optical-spectral method for differentiating the intracranial tumor types. We used a combination of certain methods such as fluorescence spectroscopy to analyze the content of endogenous and exogenous fluorophores in samples, diffuse reflectance spectroscopy to analyze structural integrity of tissues according to light scattering and blood filling according to hemoglobin spectrum absorption, as well as spontaneous Raman spectroscopy detecting individual molecular components of tissues. The study was conducted at the Laboratory of Neurosurgical Anatomy and Conservation of Biological Materials of the Burdenko Neurosurgical Center and included 93 tissue samples from 60 patients diagnosed with glioblastoma (n=28), meningioma (n=12), astrocytoma (n=9), oligodendroglioma (n=5), and metastasis (n=6). Different types of intracranial tumors that cannot be differentiated using one of the considered spectroscopy modes can be distinguished in another one. Thus, we can conclude possible advantages of combined optical-spectral approach.

Multimodal method of tissue differentiation in neurooncology using Raman spectroscopy, fluorescence and diffuse reflectance spectroscopy

There is a need to expand the possibilities of urgent analysis of intracranial tumor type during resection. These measures are necessary to improve resection quality with preservation of intact tissues and avoiding recurrence and neurological impairment in postoperative period. To create optical-spectral method for differentiating the intracranial tumor types. We used a combination of certain methods such as fluorescence spectroscopy to analyze the content of endogenous and exogenous fluorophores in samples, diffuse reflectance spectroscopy to analyze structural integrity of tissues according to light scattering and blood filling according to hemoglobin spectrum absorption, as well as spontaneous Raman spectroscopy detecting individual molecular components of tissues. The study was conducted at the Laboratory of Neurosurgical Anatomy and Conservation of Biological Materials of the Burdenko Neurosurgical Center and included 93 tissue samples from 60 patients diagnosed with glioblastoma (n=28), meningioma (n=12), astrocytoma (n=9), oligodendroglioma (n=5), and metastasis (n=6). Different types of intracranial tumors that cannot be differentiated using one of the considered spectroscopy modes can be distinguished in another one. Thus, we can conclude possible advantages of combined optical-spectral approach.

Broadband coherent anti-Stokes Raman scattering for crystalline materials

Broadband coherent anti-Stokes Raman scattering (B-CARS) has emerged in recent years as a promising chemosensitive high-speed imaging technique. B-CARS allows for the detection of vibrational sample properties in analogy to spontaneous Raman spectroscopy, but also makes electronic sample environments accessible due to its resonant excitation mechanism. Nevertheless, this technique has only gained interest in the biomedical field so far, whereas CARS investigations on solid-state materials are rare and concentrate on layered, two-dimensional materials such as graphene and hexagonal boron nitride . In this work, we discuss the specific properties of this technique when applied to single-crystalline samples, with respect to signal generation, phase matching, and selection rules in the model systems lithium niobate and lithium tantalate. Via polarized B-CARS measurements and subsequent phase retrieval, we validate the predicted selection rules, unequivocally assign the phonons of the ${\mathrm{A}}_{1}$(TO), E(TO) and ${\mathrm{A}}_{1}$(LO) branches to the detected CARS peaks, and address differences in spontaneous Raman spectroscopy concerning peak frequencies and scattering efficiencies. We thus establish this technique for future investigations of solid-state materials, specifically in the field of ferroelectric single crystals.

Alcoholic Fermentation Monitoring and pH Prediction in Red and White Wine by Combining Spontaneous Raman Spectroscopy and Machine Learning Algorithms

In the following study, total sugar concentrations before and during alcoholic fermentation, as well as ethanol concentrations and pH levels after fermentation, of red and white wine grapes were successfully predicted using Raman spectroscopy. Fluorescing compounds such as anthocyanins and pigmented phenolics found in red wine present one of the primary limitations of enological analysis using Raman spectroscopy. Unlike the spontaneous Raman effect, fluorescence is a highly efficient process and consequently emits a much stronger signal than spontaneous Raman scattering. For this reason, many enological applications of Raman spectroscopy are impractical as the more subtle Raman spectrum of any red wine sample is in large part masked by fluorescing compounds present in the wine. This work employs a simple extraction method to mitigate fluorescence in finished red wines. Ethanol and total sugars (fructose plus glucose) of wines made from red (Cabernet Sauvignon) and white (Chardonnay, Sauvignon Blanc, and Gruner Veltliner) varieties were modeled using support vector regression (SVR), partial least squares regression (PLSR) and Ridge regression (RR). The results, which compared the predicted to measured total sugar concentrations before and during fermentation, were excellent (R2SVR = 0.96, R2PLSR = 0.95, R2RR = 0.95, RMSESVR = 1.59, RMSEPLSR = 1.57, RMSERR = 1.57), as were the ethanol and pH predictions for finished wines after phenolic stripping with polyvinylpolypyrrolidone (R2SVR = 0.98, R2PLSR = 0.99, R2RR = 0.99, RMSESVR = 0.23, RMSEPLSR = 0.21, RMSERR = 0.23). The results suggest that Raman spectroscopy is a viable tool for rapid and trustworthy fermentation monitoring.

Current and Future Advancements of Raman Spectroscopy Techniques in Cancer Nanomedicine.

Raman scattering is one of the most used spectroscopy and imaging techniques in cancer nanomedicine due to its high spatial resolution, high chemical specificity, and multiplexity modalities. The flexibility of Raman techniques has led, in the past few years, to the rapid development of Raman spectroscopy and imaging for nanodiagnostics, nanotherapy, and nanotheranostics. This review focuses on the applications of spontaneous Raman spectroscopy and bioimaging to cancer nanotheranostics and their coupling to a variety of diagnostic/therapy methods to create nanoparticle-free theranostic systems for cancer diagnostics and therapy. Recent implementations of confocal Raman spectroscopy that led to the development of platforms for monitoring the therapeutic effects of anticancer drugs in vitro and in vivo are also reviewed. Another Raman technique that is largely employed in cancer nanomedicine, due to its ability to enhance the Raman signal, is surface-enhanced Raman spectroscopy (SERS). This review also explores the applications of the different types of SERS, such as SERRS and SORS, to cancer diagnosis through SERS nanoprobes and the detection of small-size biomarkers, such as exosomes. SERS cancer immunotherapy and immuno-SERS (iSERS) microscopy are reviewed.

Vibrational line shape effects in plasmon-enhanced stimulated Raman spectroscopies.

A density matrix treatment of plasmon-enhanced (PE) stimulated Raman spectroscopies is developed. Specifically, PE stimulated Raman Gain/Loss (PE-SRG/L) and coherent anti-Stokes Raman scattering (PE-CARS) due to monochromatic excitation and PE femtosecond stimulated Raman spectroscopy (PE-FSRS) are considered. A Lorentz oscillator model is used to explicitly describe the time dependence of plasmon-enhanced optical fields. These temporal characteristics are required for a density matrix based description of all plasmon-enhanced nonlinear molecular spectroscopies. Dispersive vibrational line shapes in PE-SRG/L and PE-FSRS spectra are shown to result primarily from terms proportional to the square of the complex optical field enhancement factor. The dependence on the plasmon resonance, picosecond and femtosecond pulse characteristics, and molecular vibrational properties are evident in the density matrix derived PE-FSRS intensity expression. The difference in signal detection mechanisms accounts for the lack of dispersive line shapes in PE spontaneous Raman spectroscopy. This density matrix treatment of PE-FSRS line shapes is compared with prior coupled wave results.

Watching soot inception via online Raman spectroscopy

In this work, online spontaneous Raman spectroscopy was applied to study the soot inception and growth zones of a low pressure premixed ethylene/oxygen flame. Firstly, we measured online Raman spectrum of aerosol soot extracted from the flame. The spectrum was compared to ex situ Raman measurements of the same soot after being deposited on a window. In the aerosol soot particles, the presence of an abundant sp hybridized carbon chain component is inferred accompanying a polycyclic aromatic component. Both cumulenic and polyynic chains are affected by the deposition under vacuum and by the pressure as it is raised to atmospheric, revealing that the sp phase is no longer visible in the ex situ characterization of the sampled soot. Secondly, we monitored the Raman spectra of aerosol soot as a function of the height above the burner. Comparing spectral differences of by-products along the blue to orange zone of the flame permitted the soot formation and evolution to be probed. The online spectra, by avoiding structural modifications of the real soot structures by deposition, highlight the role of unsaturated carbon chains in the chemical condensation scenario.

Calculation of an Enhanced A_{1g} Symmetry Mode Induced by Higgs Oscillations in the Raman Spectrum of High-Temperature Cuprate Superconductors.

In superconductors the Anderson-Higgs mechanism allows for the existence of a collective amplitude (Higgs) mode which can couple to eV light mainly in a nonlinear Raman-like process. The experimental nonequilibrium results on isotropic superconductors have been explained going beyond the BCS theory including the Higgs mode. Furthermore, in anisotropic d-wave superconductors strong interaction effects with other modes are expected. Here we calculate the Raman contribution of the Higgs mode from a new perspective, including many-body Higgs oscillations effects and their consequences in conventional, spontaneous Raman spectroscopy. Our results suggest a significant contribution to the intensity of the A_{1g} symmetry Raman spectrum in d-wave superconductors. In order to test our theory, we predict the presence of measurable characteristic oscillations in THz quench-optical probe time-dependent reflectivity experiments.

Detection of pancreatic cancer by convolutional-neural-network-assisted spontaneous Raman spectroscopy with critical feature visualization

Pancreatic cancer is the deadliest cancer type with a five-year survival rate of less than 9%. Detection of tumor margins plays an essential role in the success of surgical resection. However, histopathological assessment is time-consuming, expensive, and labor-intensive. We constructed a lab-designed, hand-held Raman spectroscopic system that could enable intraoperative tissue diagnosis using convolutional neural network (CNN) models to efficiently distinguish between cancerous and normal pancreatic tissue. To our best knowledge, this is the first reported effort to diagnose pancreatic cancer by CNN-aided spontaneous Raman scattering with a lab-developed system designed for intraoperative applications. Classification based on the original one-dimensional (1D) Raman, two-dimensional (2D) Raman images, and the first principal component (PC1) from the principal component analysis on the 2D image, could all achieve high performance: the testing sensitivity, specificity, and accuracy were over 95%, and the area under the curve approached 0.99. Although CNN models often show great success in classification, it has always been challenging to visualize the CNN features in these models, which has never been achieved in the Raman spectroscopy application in cancer diagnosis. By studying individual Raman regions and by extracting and visualizing CNN features from max-pooling layers, we identified critical Raman peaks that could aid in the classification of cancerous and noncancerous tissues. 2D Raman PC1 yielded more critical peaks for pancreatic cancer identification than that of 1D Raman, as the Raman intensity was amplified by 2D Raman PC1. To our best knowledge, the feature visualization was achieved for the first time in the field of CNN-aided spontaneous Raman spectroscopy for cancer diagnosis. Based on these CNN feature peaks and their frequency at specific wavenumbers, pancreatic cancerous tissue was found to contain more biochemical components related to the protein contents (particularly collagen), whereas normal pancreatic tissue was found to contain more lipids and nucleic acid (particularly deoxyribonucleic acid/ribonucleic acid). Overall, the CNN model in combination with Raman spectroscopy could serve as a useful tool for the extraction of key features that can help differentiate pancreatic cancer from a normal pancreas.

Enhanced Sensitivity for Quantifying Disease Markers via Raman and Machine-Learning of Circulating Biofluids in Optofluidic Chips

We demonstrate novel instrumentation for spontaneous Raman spectroscopy in biofluids, enabling development of a portable, automated, reliable diagnostics technique requiring minimal operator expertise to quantify disease markers. Label-free Raman analysis of biofluids at physiologically-relevant sensitivities is achieved using a microfluidic-embedded liquid-core-waveguide augmented with a unique circulation approach: thermal damage and spectrum variance is minimized, eliminating conventional limits on integration time for excellent signal-to-noise ratio and temporal stability. Machine-learning then optimizes spectrum processing, yielding quantitative results independent of end-user proficiency. Sub-mM accuracy is achieved in solutions of both high and low turbidity, surpassing the sensitivity of previous techniques for analytes with a small scattering cross-section, such as glucose. We attain a new record for label-free glucose measurements in an artificial whole-blood, achieving an accuracy up to 0.14 mM, well-exceeding the 0.78 mM accuracy required for diabetic monitoring, establishing our technique's potential to significantly facilitate portable Raman for complex biofluid analysis.

Noninvasive Detection of Ischemic Vascular Damage in a Pig Model of Liver Donation After Circulatory Death.

Liver graft quality is evaluated by visual inspection prior to transplantation, a process highly dependent on the surgeon's experience. We present an objective, noninvasive, quantitative way of assessing liver quality in real time using Raman spectroscopy, a laser-based tool for analyzing biomolecular composition. A porcine model of donation after circulatory death (DCD) with normothermic regional perfusion (NRP) allowed assessment of liver quality premortem, during warm ischemia (WI) and post-NRP. Ten percent of circulating blood volume was removed in half of experiments to simulate blood recovery for DCD heart removal. Left median lobe biopsies were obtained before circulatory arrest, after 45minutes of WI, and after 2hours of NRP and analyzed using spontaneous Raman spectroscopy, stimulated Raman spectroscopy (SRS), and staining. Measurements were also taken in situ from the porcine liver using a handheld Raman spectrometer at these time points from left median and right lateral lobes. Raman microspectroscopy detected congestion during WI by measurement of the intrinsic Raman signal of hemoglobin in red blood cells (RBCs), eliminating the need for exogenous labels. Critically, this microvascular damage was not observed during WI when 10% of circulating blood was removed before cardiac arrest. Two hours of NRP effectively cleared RBCs from congested livers. Intact RBCs were visualized rapidly at high resolution using SRS. Optical properties of ischemic livers were significantly different from preischemic and post-NRP livers as measured using a handheld Raman spectrometer. Raman spectroscopy is an effective tool for detecting microvascular damage which could assist the decision to use marginal livers for transplantation. Reducing the volume of circulating blood before circulatory arrest in DCD may help reduce microvascular damage.

Coherent Anti-Stokes Raman Scattering Spectroscopy Using a Double-Wavelength-Emission Electronically Tuned Ti:Sapphire Laser.

Coherent anti-Stokes Raman scattering (CARS) spectroscopy is a powerful tool for Raman imaging technology. In contrast, conventional spontaneous Raman spectroscopy is often used for biological analysis with multivariate analysis. This study develops a new type of CARS instrument with a double-wavelength-emission, background-free, electronically tuned Ti:sapphire laser (DW-ETL). DW-ETL generates two laser pulses with different wavelengths simultaneously within its single resonator. The pulse wavelength and buildup time are regulated by acousto-optical tunable filter in the resonator. The present DW-ETL CARS system is free from any mechanical movement to measure a CARS spectrum by controlling each laser pulse of the emission throughout the fingerprint region. Consequently, it is theoretically able to provide stable CARS spectra to apply multivariate analysis in biological applications. The present study demonstrates that the DW-ETL CARS system provides spectra of biomedical samples in the full finger-print region, and the stability and controllability of the system are evaluated.

Surface-Enhanced Raman Spectroscopy to Characterize Different Fractions of Extracellular Vesicles from Control and Prostate Cancer Patients.

Extracellular vesicles (EVs) are membrane-enclosed structures ranging in size from about 60 to 800 nm that are released by the cells into the extracellular space; they have attracted interest as easily available biomarkers for cancer diagnostics. In this study, EVs from plasma of control and prostate cancer patients were fractionated by differential centrifugation at 5000× g, 12,000× g and 120,000× g. The remaining supernatants were purified by ultrafiltration to produce EV-depleted free-circulating (fc) fractions. Spontaneous Raman and surface-enhanced Raman spectroscopy (SERS) at 785 nm excitation using silver nanoparticles (AgNPs) were employed as label-free techniques to collect fingerprint spectra and identify the fractions that best discriminate between control and cancer patients. SERS spectra from 10 µL droplets showed an enhanced Raman signature of EV-enriched fractions that were much more intense for cancer patients than controls. The Raman spectra of dehydrated pellets of EV-enriched fractions without AgNPs were dominated by spectral contributions of proteins and showed variations in S-S stretch, tryptophan and protein secondary structure bands between control and cancer fractions. We conclude that the AgNPs-mediated SERS effect strongly enhances Raman bands in EV-enriched fractions, and the fractions, EV12 and EV120 provide the best separation of cancer and control patients by Raman and SERS spectra.

Very Selective Detection of Low Physiopathological Glucose Levels by Spontaneous Raman Spectroscopy with Univariate Data Analysis

After decades of research on non-invasive glucose monitoring, invasive devices based on finger blood sampling are still the predominant reference for diabetic patients for accurately measuring blood glucose levels. Meanwhile, research continues improving point-of-care technology toward the development of painless and more accurate devices. Raman spectroscopy is well-known as a potentially valuable and painless approach for measuring glucose levels. However, previous Raman studies deal with glucose concentrations that are still order of magnitudes away with respect to human tissues’ physiological concentrations, or they propose enhancement methodologies either invasive or much complex to assure sufficient sensitivity in the physiological range. Instead, this study proposes an alternative non-enhanced Raman spectroscopy approach sensitive to glucose concentrations from 1 to 5 mmol/l, which correspond to the lowest physiopathological glucose level in human blood. Our findings suggest a very selective detection of glucose with respect to other typical metabolites, usually interfering with Raman spectroscopy’s glucose detection. We validate the proposed univariate sensing methodology on glucose solutions mixed with lactate and urea, the two most common molecules found in human serum with concentrations similar to glucose and similar features in the Raman spectra. Our findings clearly illustrate that reliable detection of glucose by Raman spectroscopy is feasible by exploiting the shifted peak at 1125 ± 10 cm–1 within physiopathological ranges.

In Vivo Fiber Optic Raman Spectroscopy of Muscle in Preclinical Models of Amyotrophic Lateral Sclerosis and Duchenne Muscular Dystrophy.

Neuromuscular diseases result in muscle weakness, disability, and, in many instances, death. Preclinical models form the bedrock of research into these disorders, and the development of in vivo and potentially translational biomarkers for the accurate identification of disease is crucial. Spontaneous Raman spectroscopy can provide a rapid, label-free, and highly specific molecular fingerprint of tissue, making it an attractive potential biomarker. In this study, we have developed and tested an in vivo intramuscular fiber optic Raman technique in two mouse models of devastating human neuromuscular diseases, amyotrophic lateral sclerosis, and Duchenne muscular dystrophy (SOD1G93A and mdx, respectively). The method identified diseased and healthy muscle with high classification accuracies (area under the receiver operating characteristic curves (AUROC): 0.76–0.92). In addition, changes in diseased muscle over time were also identified (AUROCs 0.89–0.97). Key spectral changes related to proteins and the loss of α-helix protein structure. Importantly, in vivo recording did not cause functional motor impairment and only a limited, resolving tissue injury was seen on high-resolution magnetic resonance imaging. Lastly, we demonstrate that ex vivo muscle from human patients with these conditions produced similar spectra to those observed in mice. We conclude that spontaneous Raman spectroscopy of muscle shows promise as a translational research tool.

Raman Spectroscopic Assessment of Myocardial Viability in Langendorff-Perfused Ischemic Rat Hearts.

Spontaneous Raman spectroscopy, which senses changes in cellular contents of reduced cytochrome c, could be a powerful tool for label-free evaluation of ischemic hearts. However, undetermined is whether it is applicable to evaluation of myocardial viability in ischemic hearts. To address this issue, we investigated sequential changes in Raman spectra of the subepicardial myocardium in the Langendorff-perfused rat heart before and during ligation of the left coronary artery and its subsequent release and re-ligation. Under 532-nm wavelength excitation, the Raman peak intensity of reduced cytochrome c at 747 cm−1 increased quickly after the coronary ligation, and reached a quasi-steady state within 30 min. Subsequent reperfusion of the heart after a short-term (30-min) ligation that simulates reversible conditions resulted in quick recovery of the peak intensity to the baseline. Further re-ligation resulted in resurgence of the peak intensity to nearly the identical value to the first ischemia value. In contrast, reperfusion after prolonged (120-min) ligation that assumes irreversible states resulted in incomplete recovery of the peak intensity, and re-ligation resulted in inadequate resurgence. Electron microscopic observations confirmed the spectral findings. Together, the Raman spectroscopic measurement for cytochrome c could be applicable to evaluation of viability of the ischemic myocardium without labeling.

Microcalcification-Based Tumor Malignancy Evaluation in Fresh Breast Biopsies with Hyperspectral Stimulated Raman Scattering.

Precise evaluation of breast tumor malignancy based on tissue calcifications has important practical value in the disease diagnosis, as well as the understanding of tumor development. Traditional X-ray mammography provides the overall morphologies of the calcifications but lacks intrinsic chemical information. In contrast, spontaneous Raman spectroscopy offers detailed chemical analysis but lacks the spatial profiles. Here, we applied hyperspectral stimulated Raman scattering (SRS) microscopy to extract both the chemical and morphological features of the microcalcifications, based on the spectral and spatial domain analysis. A total of 211 calcification sites from 23 patients were imaged with SRS, and the results were analyzed with a support vector machine (SVM) based classification algorithm. With optimized combinations of chemical and geometrical features of microcalcifications, we were able to reach a precision of 98.21% and recall of 100.00% for classifying benign and malignant cases, significantly improved from the pure spectroscopy or imaging based methods. Our findings may provide a rapid means to accurately evaluate breast tumor malignancy based on fresh tissue biopsies.

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

Simple SummaryRaman spectroscopy and imaging are label-free, non-destructive techniques to study cellular metabolism with subcellular spatial resolution. This review focuses on applications of Raman-based methods in a combination of stable isotope probing on cancer metabolism and cancer imaging.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.

Raman Spectroscopy and Machine Learning for Prediction and Characterization of Stem Cells during IPS Reprogramming

A number of investigations has addressed the use of label-free spontaneous Raman spectroscopy to monitor the differentiation process in stem cells as an alternative to destructive or invasive methods. In this study, using label-free imaging Raman spectroscopy combined with intelligent algorithms, we analysed the reprograming process in an isogenic mouse cell line and compared reprogrammed cells with the original embryonic stem cells (ES) and differentiated cells. Neural network, regression models, and ratiometric analyses were used to discriminate the cell states and extract several important biomarkers specific to differentiation or reprogramming. After appropriate processing, the spectral signatures of single living cells were used as an input of neural network model. Results show a high accuracy in predicting the ES cells, neuronal cells, and cells after 10 or 20 days of reprogramming (with sensitivity and specificity scores of 92% or more). By contrast, an intermediate cell state (5 days of reprogramming) exhibited a lower predictive accuracy (66%) which suggest this population is highly variable in terms of metabolic signatures. Linear regression models and ratiometric analyses confirmed this result and allowed us to extract several spectral wavelengths to characterize and predict the different states. Interestingly, our results make a strong case for substantial differences between stem cells (ES) and cells undergoing reprogramming, notably through the contribution of the lipid band at 1445 cm−1 which is associated to synthesis of fatty acids. This difference was seen even in cells after 20 days of reprogramming which are positive for pluripotency markers (Nanog, Oct4, Sox2 and SSEA-1). Finally, we also showed that the laser does not damage living cells, underlying the technical advantage of our method.

Multiphoton imaging and Raman spectroscopy of the bovine vertebral endplate.

The interface between the intervertebral disc and the vertebral body is important to the discs' biomechanics and physiology, and is widely implicated in its pathology. This study aimed to explore biochemically and structurally the bony endplate, cartilage endplate and intervertebral disc, below the nucleus and below the annulus in healthy bovine tails. Multiphoton imaging and spontaneous Raman spectroscopy were employed. Raman spectroscopy provided relative quantification of mineral and matrix components across the vertebral endplate and its adjacent areas with microscopic spatial resolution. Microscopy utilising second-harmonic generation (SHG) and two-photon fluorescence (TPF) allowed for the structural identification of distinct endplate regions. The cartilage endplate was revealed as structurally distinct from both the bone and disc, supporting its biomechanical function as a transition zone between the soft and hard tissue components. The collagen fibres were continuous across the tidemark which defines the interface between the mineralised and non-mineralised regions of the endplate. Raman spectroscopy revealed gradients in phosphate and carbonate content through the depth of the endplate and also differences beneath the nucleus and annulus consistent with a higher rate of remodelling under the annulus.