This PDF file contains the front matter associated with SPIE Proceedings Volume 12855, including the Title Page, Copyright information, Table of Contents, and Conference Committee information.

Stimulated Raman scattering (SRS) techniques enable label-free detection of the vibrational modes of molecules with high chemical specificity. However, its practical application to material characterization and bioimaging has been limited by sensitivity accompanied with the low Raman cross-section issue, resulting from typical far electronic resonance excitation. To address this limitation, the electronic pre-resonance (EPR) SRS technique has been developed to enhance Raman signals through bringing the excitation frequency close enough to the absorption peaks of examined molecules. However, a significant weakness of previous demonstrations was the lack of dual-wavelength tunability, restricting EPR-SRS to only a limited number of species in a proof-of-concept experiment. In this study, we present EPR-SRS spectromicroscopy driven by a multiple-plate continuum (MPC) light source. The MPC light source enables the examination of a single vibration mode with independent adjustment of both pump and Stokes wavelengths. As a proof-of-concept experiment, we interrogated the C=C vibration mode of Alexa 635 by continuously scanning the pump-to-absorption frequency detuning across the entire EPR region. The results exhibit a remarkable 150-fold enhancement in SRS signal and demonstrate good agreement with the Albrecht A-term pre-resonance model. Moreover, we observed signal enhancement in EPR-SRS bioimages of Drosophila brains stained with Alexa 635. Leveraging the improved sensitivity and potential to implement hyperspectral measurement, we envision that this technique holds great promise for advancing our understanding of biological systems and facilitating multiplex chemical characterization.

Super-resolution vibrational microscopy holds great promise for enhancing the multiplexing capabilities of nanometer-scale biological imaging due to the narrower spectral linewidth of molecular vibrations compared to fluorescence. However, current super-resolution vibrational microscopy techniques are plagued by several limitations, such as the requirement for cell fixation, high power consumption, or complex detection setups. Here we describe our recent demonstration of reversible saturable optical Raman transitions (RESORT) microscopy, which addresses these limitations by utilizing photoswitchable stimulated Raman scattering (SRS). To realize RESORT, we developed a bright photoswitchable Raman probe (DAE620). Leveraging the signal depletion capability of DAE620 through a donut-shaped beam, we successfully demonstrate super-resolution vibrational imaging of mammalian cells. This approach provides excellent chemical specificity and achieves spatial resolution beyond the optical diffraction limit. The present results indicate the potential of RESORT microscopy for multiplexed super-resolution imaging of live cells.

Raman spectroscopy reflects molecular vibrational fingerprints of highly narrow bands. Thus Raman microscopy is well-known for offering an attractive solution to multiplex cellular imaging. However, despite the multiplex capability, Raman imaging has never gotten close to the dream of observing high-speed cellular dynamics that are truly significant for biological studies, due to the fundamental bottleneck of low strength of Raman scattering signals. Even with highly advanced Raman techniques, such as stimulated Raman scattering (SRS) microscopy, researchers have rarely achieved dynamic imaging or at the cost of high laser powers and complex systems, along with sacrificing the full-spectrum information that is the major advantage of Raman spectroscopy. This manuscript summarized our efforts on the improvement of high quality spontaneous Raman imaging, which were recently published on the high-impact journals. We combined novel azo-enhanced Raman scattering (AERS) probes with a highly efficient and speed-optimized line-scan Raman imaging system. The AERS probes targeted cellular organelles and featured back-ground free Raman signals with strength 4 orders of magnitude larger than the traditional Raman probes, e.g. 5-ethynyl-2’-deoxyuridine (EdU), without resorting to the complex coherent Raman approaches. The dynamic azo-enhanced Raman imaging (DAERI) system was able to obtain Raman images of live cells at the temporal resolution of 3.5 s per frame and the confocal spatial resolution of ~270 nm using a low power density of 75 μW/μm². Empowered by this performance, we demonstrated DAERI of lysosomal and mitochondrial dynamics within live cells. In particular, DAERI’ s preservation of the full-spectrum information utilized the hallmark of spontaneous Raman signals in fingerprint region and allowed us to easily and accurately unmix triple-stained cell images by resolving individual organelles clearly in a single image scan.

We have developed a novel methodology to capture images of various biomolecules at a resolution surpassing the traditional diffraction limit of optical microscopy. By harnessing a multimodal imaging platform that combines stimulated Raman scattering (SRS), multiphoton fluorescence (MPF), and second harmonic generation (SHG), together with sophisticated image deconvolution algorithms, we have successfully generated super-resolution images that reveal the details of biomolecular metabolism. These images enable us to explore the intricate associations between metabolic activities and the spatial distribution of metabolites within breast cancer tissues. To enhance the accuracy of this measurement technique, in this study, we designed a pre-processing workflow that incorporates both denoising and drift correction processes. Our cutting-edge, nonlinear multimodal imaging approach, when applied in a super-resolution context with new workflow, holds significant promise for advancing early detection of breast cancer, prognostication, evaluation of therapeutic outcomes, and deepening our mechanistic understanding of diseases.

High throughput wide-field second harmonic imaging enables the label-free imaging of interfacial (< 3 nm thick) water, with a spatial resolution of ~370 nm using ~100 ms acquisition times per image. The obtained interfacial orientational order of water can be used to create spatiotemporal transmembrane potential maps of free-standing lipid membranes, giant unilamellar vesicles or living cells. These maps are then used to uniquely quantify membrane-water interactions, which show surprisingly heterogeneous behavior which sheds new light on processes such as ion transport, ion channel operation and membrane deformation.

vibrational motion of a molecule is intrinsically linked to its structure and composition, which provides a way to identify it. Raman spectroscopy, utilizing the inelastic scattering of light, investigates these molecular vibrations. While Raman shifts exceeding 200 cm⁻¹ primarily capture intramolecular vibrations, lower Raman shifts ( < 200 cm⁻¹) provide insights into the collective motion of molecules, thereby revealing valuable structural information. Although frequency domain imaging effectively addresses higher Raman shifts, a time domain approach proves more practical for lower Raman shifts. Impulsive Stimulated Raman Scattering (ISRS) is a time domain technique that employs a pump pulse to instantaneously excite a molecule, activating all modes within its bandwidth and inducing a transient refractive index modulation. This modulation can be probed by a second pulse, enabling analysis of spatial profile, spectrum, and polarization changes. In this study, we elucidate the implementation of transient vibrational refractive index detection for the acquisition of ultrafast hyperspectral images, including the integration of a random access delay line into the existing setup that enables scanning windows of up to 50 picoseconds at random time delays.

Achieving accurate resections is crucial for confirming the success of surgical procedures during the operation. However, the time-consuming histologic analysis lacks the ability to provide real-time diagnoses, resulting in delays in surgical procedures. As a result, there is an urgent need for real-time assessment of both healthy and cancerous soft tissue. In this study, Raman spectral data from diverse bovine tissue were acquired using a 785 nm fiber-optic Raman probe system and utilized for classification through a Random Forest (RF) classifier. The study entailed a quantitative and experimental analysis, utilizing locally collected bovine samples, including muscle, fat, bone, and bone marrow, with Raman spectra obtained from 1200 sites across 24 samples. The Random Forest analysis demonstrated significant potential for distinguishing between various types of bovine tissue, achieving an average accuracy of approximately 99.5%, specificity of about 99.7%, and sensitivity of about 99.1%. The integration of machine learning techniques with Raman sensing technology shows immense potential in facilitating real-time, intraoperative, in vivo evaluations of soft tissues.

Heterodyne coherent anti-Stokes Raman scattering is presented with a single and compact fiber-based light source only, providing the pump and Stokes as well as local oscillator pulses with a fixed phase relation. The interferometrically superimposed pulses of the CARS signal and the local oscillator generated heterodyne gain, scaling with the LO power, and amplifying the weak CARS signal at the detection site. The functionality of this heterodyne CARS setup was verified by measurements of the heterodyne amplification, the sample concentration, and the phase dependence of the signal. Additionally, 10-fold suppression of non-resonant signal was achieved for background correction.

Three-dimensional (3D) quantitative localization of multiple biomolecular components within their native cellular context holds immense promise across various areas of biomedicine. While confocal Raman spectral imaging allows label-free detection of biomolecules within the 3D biological samples, achieving quantitative 3D mapping of multiple biomolecules has proven challenging. To address this limitation, we present an integrated quantitative bio-analytical methodology designed to elevate semi-quantitative volumetric Raman imaging analysis to a fully quantitative level, enabling precise visualization and assessment of the 3D distribution of multiple key biomolecular components in biological samples. We herein showcased the utility of quantitative Raman analysis in chemometric phenotyping of 3D human engineered cartilage, including the compositional changes during the maturation process of chondrocytes in hydrogels which mimics the development of native human cartilage. The structural changes of cartilage from week 3 to week 15 were analysed to investigate the changes in the localisation of different kinds of extracellular matrices. By employing spectral-unmixing techniques, we performed simultaneous analysis and comparison of six biological components within the human engineered cartilage, using the native human cartilage sample as the positive control. Our results demonstrate a progressive maturation of the engineered cartilage towards native human cartilage, characterized by significant differences in the levels of elastin and glycogen. These findings hold crucial implications for the viability and survival of tissue-engineered cartilage following implantation into human patients. This innovative approach opens new avenues for in-depth investigations of tissue development, disease progression, and therapeutic interventions.

Amino acids, renowned as essential metabolic building blocks, play an important role in fundamental processes such as protein synthesis, while the non-invasive visualization of their subcellular distribution has remained a challenge. In this study, we introduce a method for monitoring the intracellular uptake of specific amino acids, including Methionine, within live cells and tissues using stimulated Raman scattering (SRS) microscopy combined with deuterium labeling. Our approach employs a straightforward background subtraction technique to detect the SRS signal of methionine enriched with eight deuterium atoms (d₈-Met). Notably, our findings indicate that d₈-Met metabolism appears to be minimally invasive and yields a more robust signal when compared to the previously employed alkyne-labeled methionine analog, homopropargyl glycine (Hpg). This enhanced performance can be attributed to the minimally disruptive labeling characteristics of deuterium, making it a promising biorthogonal probe with potential applications for long-term imaging. Furthermore, we extend the applicability of this technique by introducing a synthetic diet containing d₈-Met to living Drosophila, enabling us to visualize systemic incorporation of d₈-Met. Our imaging efforts encompass various dissected tissues, including the brain, wing disc, fat body, and gut, revealing systemic integration within the organism. These results unveil the capability of SRS imaging to discern previously unseen variations in methionine distribution at a subcellular level within tissues, shedding light on cell-to-cell heterogeneity. In conclusion, d₈-Met and analogous deuterated biomolecules hold significant potential for investigating metabolism and molecular fate at subcellular resolutions.

Second harmonic generation imaging is a powerful tool for visualizing molecular structures in living organisms without the need for exogenous dyes. However, SHG signal lacks molecular specificity in identifying the source. This study aimed at molecular identification of SHG sources in the mouse brain using a multimodal imaging technique combining SHG and multiplex coherent anti Stokes Raman scattering (CARS) spectroscopy. We performed multimodal imaging in two different regions, the surface and dentate gyrus of the brain tissue. For the brain surface, the SHG signal was recognized through CARS spectrum analysis, indicating its origin in collagen. In the dentate gyrus, CARS images did not unveil corresponding molecular origins; however, morphologically, the SHG signal likely originated from Rootletin within neurons. Overall, Multimodal imaging approach to molecular identification of SHG has the potential to contribute to a comprehensive understanding of the molecular and structural features of the mouse brain. These findings advance label-free imaging techniques and have implications for brain tissue analysis and functional mapping research.