Depth-resolved mid-infrared photothermal imaging of living cells and organisms with submicrometer spatial resolution

O-PTIR spectroscopy for characterizing active pharmaceutical ingredient specific particle size distributions of nasal spray suspension products

Evaluation of the particle size distribution (PSD) of active pharmaceutical ingredients (APIs) in nasal suspension products is challenging due to the presence of both API and excipients. To characterize these intricate formulations, it is essential to have sophisticated analytical methods that offer high spatial resolution and the ability to chemically pinpoint and map out the presence of API particles. However, such advanced techniques have not been documented for nasal formulations yet. In this proof-of-concept study, we investigated the utility of optical photothermal infrared spectroscopy (O-PTIR) to analyze the PSD of commercially available Nasonex® and its generic Azonaire® nasal mometasone furoate (MM) suspensions. Simultaneous O-PTIR and Raman spectra, as well as IR chemical maps, were collected from the particles in both formulations. Spatially resolved spectra from the particles confirmed the presence of peaks related to MM (1727 cm-1, 1661 cm-1, and 1122 cm-1) and excipient microcrystalline cellulose (MCC) (1061 cm-1). The PSD of MM particles was characterized using chemical maps specific to MM (1661 cm-1) and automated imaging. Results confirmed that the PSD of both formulations were comparable. Spectral analysis also revealed the presence of free MM, free MCC, and particles containing co-localized MM and MCC. For suspension-based nasal products, O-PTIR enables the measurement of API PSD, which is critical for formulators in developing nasal suspension products. This approach holds potential as an innovative complimentary analytical tool that could diminish the need for extensive clinical endpoint bioequivalence studies when evaluating the comparability of generic and brand-name nasal suspension products.

Rapid Hyperspectral Photothermal Mid-Infrared Spectroscopic Imaging from Sparse Data for Gynecologic Cancer Tissue Subtyping

Ovarian cancer detection has traditionally relied on a multistep process that includes biopsy, tissue staining, and morphological analysis by experienced pathologists. While widely practiced, this conventional approach suffers from several drawbacks: it is qualitative, time-intensive, and heavily dependent on the quality of staining. Mid-infrared (MIR) hyperspectral photothermal imaging is a label-free, biochemically quantitative technology that, when combined with machine learning algorithms, can eliminate the need for staining and provide quantitative results comparable to traditional histology. However, this technology is slow. This work presents a novel approach to MIR photothermal imaging that enhances its speed by an order of magnitude. This method resolves the longstanding trade-off between imaging resolution and data collection speed, enabling the reconstruction of high-quality, high-resolution images from undersampled data sets and achieving a 10X improvement in data acquisition time. We assessed the performance of our sparse imaging methodology using a variety of quantitative metrics, including mean squared error (MSE), structural similarity index (SSIM), and tissue subtype classification accuracies, employing both random forest and convolutional neural network (CNN) models, accompanied by Receiver Operating Characteristic (ROC) curves. Our statistically robust analysis, based on data from 100 ovarian cancer patient samples and over 65 million data points, demonstrates the method's capability to produce superior image quality and accurately distinguish between different gynecological tissue types with segmentation accuracy exceeding 95%. Our work demonstrates the feasibility of integrating rapid MIR hyperspectral photothermal imaging with machine learning in enhancing ovarian cancer tissue characterization, paving the way for quantitative, label-free, automated histopathology.

Cervical Cancer Tissue Analysis Using Photothermal Midinfrared Spectroscopic Imaging

Hyperspectral photothermal mid-infrared spectroscopic imaging (HP-MIRSI) is an emerging technology with promising applications in cervical cancer diagnosis and quantitative, label-free histopathology. This study pioneers the application of HP-MIRSI to the evaluation of clinical cervical cancer tissues, achieving excellent tissue type segmentation accuracy of over 95%. This achievement stems from an integrated approach of optimized data acquisition, computational data reconstruction, and the application of machine learning algorithms. The results are statistically robust, drawing from tissue samples of 98 cervical cancer patients and incorporating over 40 million data points. Traditional cervical cancer diagnosis methods entail biopsy, staining, and visual evaluation by a pathologist. This process is qualitative, subject to variations in staining and subjective interpretations, and requires extensive tissue processing, making it costly and time-consuming. In contrast, our proposed alternative can produce images comparable to those from histological analyses without the need for staining or complex sample preparation. This label-free, quantitative method utilizes biochemical data from HP-MIRSI and employs machine-learning algorithms for the rapid and precise segmentation of cervical tissue subtypes. This approach can potentially transform histopathological analysis by offering a more accurate and label-free alternative to conventional diagnostic processes.

Optical photothermal infrared imaging using metabolic probes in biological systems

Infrared spectroscopy is a powerful tool for identifying biomolecules. In biological systems, infrared spectra provide information on structure, reaction mechanisms, and conformational change of biomolecules. However, the promise of applying infrared imaging to biological systems has been hampered by low spatial resolution and the overwhelming water background arising from the aqueous nature of in cell and in vivo work. Recently, optical photothermal infrared microscopy (OPTIR) has overcome these barriers and achieved both spatially and spectrally resolved images of live cells and organisms. Here, we determine the most effective modes of collection for work in biological samples. We examine three cell lines (Huh-7, differentiated 3T3-L1, and U2OS) and three organisms ( E. coli , tardigrades, and zebrafish). Our results suggest that the information provided by multifrequency imaging is comparable to hyperspectral imaging while reducing imaging times twenty-fold. We also explore the utility of IR active probes, including global and site-specific probes, for tracking metabolic pathways and protein localization, structure, and local environment. Our findings illustrate the versatility of OPTIR, and together, provide a direction for future dynamic imaging of living cells and organisms.

Mid-infrared chemical imaging of living cells enabled by plasmonic metasurfaces

Mid-Infrared (MIR) chemical imaging provides rich chemical information of biological samples in a label-free and non-destructive manner. Yet, its adoption to live-cell analysis is limited by the strong attenuation of MIR light in water, often necessitating cell culture geometries that are incompatible with the prolonged viability of cells and with standard high-throughput workflow. Here, we introduce a new approach to MIR microscopy, where cells are imaged through their localized near-field interaction with a plasmonic metasurface. Chemical contrast of distinct molecular groups provided sub-cellular resolution images of the proteins, lipids, and nucleic acids in the cells that were collected using an inverted MIR microscope. Time-lapse imaging of living cells demonstrated that their behaviors, including motility, viability, and substrate adhesion, can be monitored over extended periods of time using low-power MIR light. The presented approach provides a method for the non-perturbative MIR imaging of living cells, which is well-suited for integration with modern high-throughput screening technologies for the label-free, high-content chemical imaging of living cells.

Benchtop IR Imaging of Live Cells: Monitoring the Total Mass of Biomolecules in Single Cells

Absolute quantity imaging of biomolecules on a single cell level is critical for measurement assurance in biosciences and bioindustries. While infrared (IR) transmission microscopy is a powerful label-free imaging modality capable of chemical quantification, its applicability to hydrated biological samples remains challenging due to the strong IR absorption by water. Traditional IR imaging of hydrated cells relies on powerful light sources, such as synchrotrons, to mitigate the light absorption by water. However, we overcome this challenge by applying a solvent absorption compensation (SAC) technique to a home-built benchtop IR microscope based on an external-cavity quantum cascade laser. SAC-IR microscopy adjusts the incident light using a pair of polarizers to precompensate the IR absorption by water while retaining the full dynamic range. Integrating the IR absorbance over a cell yields the total mass of biomolecules per cell. We monitor the total mass of the biomolecules of live fibroblast cells over 12 h, demonstrating promise for advancing our understanding of the biomolecular processes occurring in live cells on the single-cell level.

3D micro-CT and O-PTIR spectroscopy bring new understanding of the influence of filler content in dental resin composites

BACKGROUND

Dental resin composites' performance is intricately linked to their polymerisation shrinkage characteristics. This study compares polymerisation shrinkage using advanced 3D micro-computed tomography (micro-CT) and traditional 2D linear assessments. It delves into the crucial role of filler content on shrinkage and the degree of conversion in dental resin composites, providing valuable insights for the field.

METHODS

Five experimental dental composite materials were prepared with increasing filler contents (55-75 wt%) and analysed using either 3D micro-CT for volumetric shrinkage or a custom-designed linometer for 2D linear shrinkage. The degree of conversion was assessed using Optical Photothermal Infrared (O-PTIR) and Fourier-Transform Infrared (FTIR) spectroscopy. Light transmittance through a 2-mm layer was evaluated using a NIST-calibrated spectrometer. Scanning Electron Microscopy (SEM) and Energy-Dispersive X-ray Spectroscopy (EDX) examined surface morphology and elemental distribution. Correlation between the investigated parameters was determined using Spearman correlation analyses.

RESULTS

The study found significant differences in polymerisation-related properties among different filler content categories, with volumetric shrinkage consistently demonstrating higher mean values than linear shrinkage across most groups. Volumetric shrinkage decreased with increasing curing depth, showing no direct correlation between filler content and shrinkage levels at different curing depths. The results highlighted a strong negative correlation between filler content and degree of conversion, volumetric and linear shrinkage, as well as maximum shrinkage rate. Light transmittance showed a moderate correlation with the filler content and a weak correlation with other tested parameters.

CONCLUSIONS

This study underscores the importance of considering both volumetric and linear shrinkage in the design and analysis of dental composite materials. The findings advocate optimising filler content to minimise shrinkage and enhance material performance. Integrating micro-CT and O-PTIR techniques offers novel insights into dental composites' polymerisation behaviour, providing a foundation for future research to develop materials with improved clinical outcomes.

Machine learning-assisted mid-infrared spectrochemical fibrillar collagen imaging in clinical tissues

Significance

Label-free multimodal imaging methods that can provide complementary structural and chemical information from the same sample are critical for comprehensive tissue analyses. These methods are specifically needed to study the complex tumor-microenvironment where fibrillar collagen's architectural changes are associated with cancer progression. To address this need, we present a multimodal computational imaging method where mid-infrared spectral imaging (MIRSI) is employed with second harmonic generation (SHG) microscopy to identify fibrillar collagen in biological tissues.

Aim

To demonstrate a multimodal approach where a morphology-specific contrast mechanism guides an MIRSI method to detect fibrillar collagen based on its chemical signatures.

Approach

We trained a supervised machine learning (ML) model using SHG images as ground truth collagen labels to classify fibrillar collagen in biological tissues based on their mid-infrared hyperspectral images. Five human pancreatic tissue samples (sizes are in the order of millimeters) were imaged by both MIRSI and SHG microscopes. In total, 2.8 million MIRSI spectra were used to train a random forest (RF) model. The other 68 million spectra were used to validate the collagen images generated by the RF-MIRSI model in terms of collagen segmentation, orientation, and alignment.

Results

Compared with the SHG ground truth, the generated RF-MIRSI collagen images achieved a high average boundary F -score (0.8 at 4-pixel thresholds) in the collagen distribution, high correlation (Pearson's R 0.82) in the collagen orientation, and similarly high correlation (Pearson's R 0.66) in the collagen alignment.

Conclusions

We showed the potential of ML-aided label-free mid-infrared hyperspectral imaging for collagen fiber and tumor microenvironment analysis in tumor pathology samples.

A tutorial on optical photothermal infrared (O-PTIR) microscopy

This tutorial reviews the rapidly growing field of optical photothermal infrared (O-PTIR) spectroscopy and chemical imaging. O-PTIR is an infrared super-resolution measurement technique where a shorter wavelength visible probe is used to measure and map infrared (IR) absorption with spatial resolution up to 30× better than conventional techniques such as Fourier transform infrared and direct IR laser imaging systems. This article reviews key limitations of conventional IR instruments, the O-PTIR technology breakthroughs, and their origins that have overcome the prior limitations. This article also discusses recent developments in expanding multi-modal O-PTIR approaches that enable complementary Raman spectroscopy and fluorescence microscopy imaging, including wide-field O-PTIR imaging with fluorescence-based detection of IR absorption. Various practical subjects are covered, including sample preparation techniques, optimal measurement configurations, use of IR tags/labels and techniques for data analysis, and visualization. Key O-PTIR applications are reviewed in many areas, including biological and biomedical sciences, environmental and microplastics research, (bio)pharmaceuticals, materials science, cultural heritage, forensics, photonics, and failure analysis.

Structural Mapping of Protein Aggregates in Live Cells Modeling Huntington's Disease

While protein aggregation is a hallmark of many neurodegenerative diseases, acquiring structural information on protein aggregates inside live cells remains challenging. Traditional microscopy does not provide structural information on protein systems. Routinely used fluorescent protein tags, such as Green Fluorescent Protein (GFP), might perturb native structures. Here, we report a counter-propagating mid-infrared photothermal imaging approach enabling mapping of secondary structure of protein aggregates in live cells modeling Huntington's disease. By comparing mid-infrared photothermal spectra of label-free and GFP-tagged huntingtin inclusions, we demonstrate that GFP fusions indeed perturb the secondary structure of aggregates. By implementing spectra with small spatial step for dissecting spectral features within sub-micrometer distances, we reveal that huntingtin inclusions partition into a β-sheet-rich core and a ɑ-helix-rich shell. We further demonstrate that this structural partition exists only in cells with the [RNQ+] prion state, while [rnq-] cells only carry smaller β-rich non-toxic aggregates. Collectively, our methodology has the potential to unveil detailed structural information on protein assemblies in live cells, enabling high-throughput structural screenings of macromolecular assemblies.

Click-free imaging of carbohydrate trafficking in live cells using an azido photothermal probe

Real-time tracking of intracellular carbohydrates remains challenging. While click chemistry allows bio-orthogonal tagging with fluorescent probes, the reaction permanently alters the target molecule and only allows a single snapshot. Here, we demonstrate click-free mid-infrared photothermal (MIP) imaging of azide-tagged carbohydrates in live cells. Leveraging the micromolar detection sensitivity for 6-azido-trehalose (TreAz) and the 300-nm spatial resolution of MIP imaging, the trehalose recycling pathway in single mycobacteria, from cytoplasmic uptake to membrane localization, is directly visualized. A peak shift of azide in MIP spectrum further uncovers interactions between TreAz and intracellular protein. MIP mapping of unreacted azide after click reaction reveals click chemistry heterogeneity within a bacterium. Broader applications of azido photothermal probes to visualize the initial steps of the Leloir pathway in yeasts and the newly synthesized glycans in mammalian cells are demonstrated.

Benchmarking classification abilities of novel optical photothermal IR spectroscopy at the single-cell level with bulk FTIR measurements

Fourier-transform infrared (FTIR) spectroscopy is a simple, fast and inexpensive method with a history of use for bacterial analysis. However, due to the limitations placed on spatial resolution inherent to infrared wavelengths, analysis has generally been performed on bulk samples, leading to biological variance among individual cells to be buried in averaged spectra. This also increases the bacterial load necessary for analysis, which can be problematic in clinical settings where limiting incubation time is valuable. Optical photothermal-induced resonance (O-PTIR) spectroscopy is a novel method aiming to bypass this limitation using a secondary lower wavelength laser, allowing for infrared measurements of a single bacterium. Here, using Staphylococcus capitis, Staphylococcus epidermidis and Micrococcus luteus strains as a model and FTIR as a benchmark, we examined O-PTIR's ability to discriminate single-cell samples at the intergenetic, interspecific and intraspecific levels. When combined with chemometric analysis, we showed that O-PTIR is capable of discriminating different between genera, species and strains within species to a degree comparable with FTIR. Furthermore, small variations in the amide bands associated with differences in the protein structure can still be seen in spite of smaller sample sizes. This demonstrates the potential of O-PTIR for single-cell bacterial analysis and classification.

Spectroscopic and Interferometric Sum-Frequency Imaging of Strongly Coupled Phonon Polaritons in SiC Metasurfaces

Phonon polaritons enable waveguiding and localization of infrared light with extreme confinement and low losses. The spatial propagation and spectral resonances of such polaritons are usually probed with complementary techniques such as near-field optical microscopy and far-field reflection spectroscopy. Here, infrared-visible sum-frequency spectro-microscopy is introduced as a tool for spectroscopic imaging of phonon polaritons. The technique simultaneously provides sub-wavelength spatial resolution and highly-resolved spectral resonance information. This is implemented by resonantly exciting polaritons using a tunable infrared laser and wide-field microscopic detection of the upconverted light. The technique is employed to image hybridization and strong coupling of localized and propagating surface phonon polaritons in a metasurface of SiC micropillars. Spectro-microscopy allows to measure the polariton dispersion simultaneously in momentum space by angle-dependent resonance imaging, and in real space by polariton interferometry. Notably, it is possible to directly image how strong coupling affects the spatial localization of polaritons, inaccessible with conventional spectroscopic techniques. The formation of edge states is observed at excitation frequencies where strong coupling prevents polariton propagation into the metasurface. The technique is applicable to the wide range of polaritonic materials with broken inversion symmetry and can be used as a fast and non-perturbative tool to image polariton hybridization and propagation.

Surface-enhanced optical-mid-infrared photothermal microscopy using shortened colloidal silver nanowires: a noble approach for mid-infrared surface sensing

We propose surface-enhanced optical-mid-infrared photothermal (MIP) microscopy using highly crystalline silver nanowires, acting as a Fabry-Perot resonator, and demonstrate its applicability to enhanced mid-infrared surface sensing of thin polymer layers as thin as 20 nm.

An end-to-end approach for single-cell infrared absorption spectroscopy of bacterial inclusion bodies: from AFM-IR measurement to data interpretation of large sample sets

BACKGROUND

Inclusion bodies (IBs) are well-known subcellular structures in bacteria where protein aggregates are collected. Various methods have probed their structure, but single-cell spectroscopy remains challenging. Atomic Force Microscopy-based Infrared Spectroscopy (AFM-IR) is a novel technology with high potential for the characterisation of biomaterials such as IBs.

RESULTS

We present a detailed investigation using AFM-IR, revealing the substructure of IBs and their variation at the single-cell level, including a rigorous optimisation of data collection parameters and addressing issues such as laser power, pulse frequency, and sample drift. An analysis pipeline was developed tailored to AFM-IR image data, allowing high-throughput, label-free imaging of more than 3500 IBs in 12,000 bacterial cells. We examined IBs generated in Escherichia coli under different stress conditions. Dimensionality reduction analysis of the resulting spectra suggested distinct clustering of stress conditions, aligning with the nature and severity of the applied stresses. Correlation analyses revealed intricate relationships between the physical and morphological properties of IBs.

CONCLUSIONS

Our study highlights the power and limitations of AFM-IR, revealing structural heterogeneity within and between IBs. We show that it is possible to perform quantitative analyses of AFM-IR maps over a large collection of different samples and determine how to control for various technical artefacts.

Overtone photothermal microscopy for high-resolution and high-sensitivity vibrational imaging

Photothermal microscopy is a highly sensitive pump-probe method for mapping nanostructures and molecules through the detection of local thermal gradients. While visible photothermal microscopy and mid-infrared photothermal microscopy techniques have been developed, they possess inherent limitations. These techniques either lack chemical specificity or encounter significant light attenuation caused by water absorption. Here, we present an overtone photothermal (OPT) microscopy technique that offers high chemical specificity, detection sensitivity, and spatial resolution by employing a visible probe for local heat detection in the C-H overtone region. We demonstrate its capability for high-fidelity chemical imaging of polymer nanostructures, depth-resolved intracellular chemical mapping of cancer cells, and imaging of multicellular C. elegans organisms and highly scattering brain tissues. By bridging the gap between visible and mid-infrared photothermal microscopy, OPT establishes a new modality for high-resolution and high-sensitivity chemical imaging. This advancement complements large-scale shortwave infrared imaging approaches, facilitating multiscale structural and chemical investigations of materials and biological metabolism.

Widefield Super-Resolution Infrared Spectroscopy and Imaging of Autofluorescent Biological Materials and Photosynthetic Microorganisms Using Fluorescence Detected Photothermal Infrared (FL-PTIR)

We have demonstrated high-speed, super-resolution infrared (IR) spectroscopy and chemical imaging of autofluorescent biomaterials and organisms using camera-based widefield photothermal detection that takes advantage of temperature-dependent modulations of autofluorescent emission. A variety of biological materials and photosynthetic organisms exhibit strong autofluorescence emission under ultraviolet excitation and the autofluorescent emission has a very strong temperature dependence, of order 1%/K. Illuminating a sample with pulses of IR light from a wavelength-tunable laser source causes periodic localized sample temperature increases that result in a corresponding transient decrease in autofluorescent emission. A low-cost light-emitting diode-based fluorescence excitation source was used in combination with a conventional fluorescence microscopy camera to detect localized variations in autofluorescent emission over a wide area as an indicator of localized IR absorption. IR absorption image stacks were acquired over a range of IR wavelengths, including the fingerprint spectral range, enabling extraction of localized IR absorption spectra. We have applied widefield fluorescence detected photothermal IR (FL-PTIR) to an analysis of autofluorescent biological materials including collagen, leaf tissue, and photosynthetic organisms including diatoms and green microalgae cells. We have also demonstrated the FL-PTIR on live microalgae in water, demonstrating the potential for label-free dynamic chemical imaging of autofluorescent cells.

Machine learning assisted mid-infrared spectrochemical fibrillar collagen imaging in clinical tissues

Significance

Label-free multimodal imaging methods that can provide complementary structural and chemical information from the same sample are critical for comprehensive tissue analyses. These methods are specifically needed to study the complex tumor-microenvironment where fibrillar collagen's architectural changes are associated with cancer progression. To address this need, we present a multimodal computational imaging method where mid-infrared spectral imaging (MIRSI) is employed with second harmonic generation (SHG) microscopy to identify fibrillar collagen in biological tissues.

Aim

To demonstrate a multimodal approach where a morphology-specific contrast mechanism guides a mid-infrared spectral imaging method to detect fibrillar collagen based on its chemical signatures.

Approach

We trained a supervised machine learning (ML) model using SHG images as ground truth collagen labels to classify fibrillar collagen in biological tissues based on their mid-infrared hyperspectral images. Five human pancreatic tissue samples (sizes are in the order of millimeters) were imaged by both MIRSI and SHG microscopes. In total, 2.8 million MIRSI spectra were used to train a random forest (RF) model. The remaining 68 million spectra were used to validate the collagen images generated by the RF-MIRSI model in terms of collagen segmentation, orientation, and alignment.

Results

Compared to the SHG ground truth, the generated MIRSI collagen images achieved a high average boundary F-score (0.8 at 4 pixels threshold) in the collagen distribution, high correlation (Pearson's R 0.82) in the collagen orientation, and similarly high correlation (Pearson's R 0.66) in the collagen alignment.

Conclusions

We showed the potential of ML-aided label-free mid-infrared hyperspectral imaging for collagen fiber and tumor microenvironment analysis in tumor pathology samples.

Development of 1 Month Sustained-Release Microspheres Containing Liraglutide for Type 2 Diabetes Treatment

Liraglutide has been extensively applied in the treatment of type 2 diabetes mellitus (T2DM), but its 11-15 h half-life resulted in daily administration, which led to poor patient compliance. This study aimed to solve this problem by developing liraglutide-loaded microspheres with a 1 month sustained release prepared by the W1/O/W2 method combined with the premix membrane emulsification technique to improve therapeutic efficacy. Remarkably, we found that the amphiphilic properties of liraglutide successfully reduced the oil-water interfacial tension, resulting in a stable primary emulsion and decreasing the level of drug leakage into the external water phase. As a result, exceptional drug loading (>8%) and encapsulation efficiency (>85%) of microspheres were achieved. Furthermore, the uniformity in microsphere size facilitated an in-depth exploration of the structural characteristics of liraglutide-loaded microspheres. The results indicated that the dimensions of the internal cavities of the microspheres were significantly influenced by the size of the inner water droplets in the primary emulsion. A denser and more uniform cavity structure decreased the initial burst release, improving the release process of liraglutide from the microspheres. To evaluate the release behavior of liraglutide from microspheres, a set of in vitro release assays and in vivo pharmacodynamics were performed. The liraglutide-loaded microspheres effectively decreased fasting blood glucose (FBG) levels and hemoglobin A1c (HbA1c) levels while enhancing the pancreatic and hepatic functions in db/db mice. In conclusion, liraglutide sustained-release microspheres showed the potential for future clinical applications in the management of T2DM and provided an effective therapeutic approach to overcoming patient compliance issues.

Mid-infrared single-photon upconversion spectroscopy enabled by nonlocal wavelength-to-time mapping

Ultrasensitive spectroscopy is an essential component in mid-infrared (MIR) technology. However, the drawbacks of MIR detectors pose challenges to robust MIR spectroscopy at the single-photon level. We propose an MIR single-photon frequency upconversion spectroscopy nonlocally mapping the MIR information to the time domain. Broadband MIR photons from spontaneous parametric downconversion are frequency-upconverted to the near-infrared band with quantum correlation preservation. Via the group delay of fiber, the MIR spectral information within a 1.18-micrometer bandwidth of 2.76 to 3.94 micrometers is then successfully projected to arrival times of correlated photon pairs. Under the conditions of 6.4 × 106 photons per second illumination, the transmission spectra of polymers with single-photon sensitivity are demonstrated using single-pixel detectors. The developed approach circumvents scanning and frequency selection instability, which stands out for its inherent compatibility for evolving environments and scalability for various wavelengths. Because of its high sensitivity and robustness, characterization of biochemical samples and weak measurement of quantum systems are possible to foresee.

Deep learning empowers photothermal microscopy with super-resolution capabilities

In the past two decades, photothermal microscopy (PTM) has achieved sensitivity at the level of a single particle or molecule and has found applications in the fields of material science and biology. PTM is a far-field imaging method; its resolution is restricted by the diffraction limits. In our previous work, the modulated difference PTM (MDPTM) was proposed to improve the lateral resolution, but its resolution improvement was seriously constrained by information loss and artifacts. In this Letter, a deep learning approach of the cycle generative adversarial network (Cycle GAN) is employed for further improving the resolution of PTM, called DMDPTM. The point spread functions (PSFs) of both PTM and MDPTM are optimized and act as the second generator of Cycle GAN. Besides, the relationship between the sample's volume and the photothermal signal is utilized during dataset construction. The images of both PTM and MDPTM are utilized as the inputs of the Cycle GAN to incorporate more information. In the simulation, DMDPTM quantitatively distinguishes a distance of 60 nm between two nanoparticles (each with a diameter of 60 nm), demonstrating a 4.4-fold resolution enhancement over the conventional PTM. Experimentally, the super-resolution capability of DMDPTM is verified by restored images of Au nanoparticles, achieving the resolution of 114 nm. Finally, the DMDPTM is successfully employed for the imaging of carbon nanotubes. Therefore, the DMDPTM will serve as a powerful tool to improve the lateral resolution of PTM.

Oleic acid differentially affects lipid droplet storage of de novo synthesized lipids in hepatocytes and adipocytes

Lipogenesis is a vital but often dysregulated metabolic pathway. Here we use optical photothermal infrared imaging to quantify lipogenesis rates of isotopically labelled oleic acid and glucose concomitantly in live cells. In hepatocytes, but not adipocytes, we find that oleic acid feeding at 60 μM increases the number and size of lipid droplets (LDs) while simultaneously inhibiting storage of de novo synthesized lipids in LDs. Our results demonstrate alternate regulation of lipogenesis between cell types.

Click-free imaging of carbohydrate trafficking in live cells using an azido photothermal probe

Real-time tracking of intracellular carbohydrates remains challenging. While click chemistry allows bio-orthogonal tagging with fluorescent probes, the reaction permanently alters the target molecule and only allows a single snapshot. Here, we demonstrate click-free mid-infrared photothermal (MIP) imaging of azide-tagged carbohydrates in live cells. Leveraging the micromolar detection sensitivity for 6-azido-trehalose (TreAz) and the 300-nm spatial resolution of MIP imaging, the trehalose recycling pathway in single mycobacteria, from cytoplasmic uptake to membrane localization, is directly visualized. A peak shift of azide in MIP spectrum further uncovers interactions between TreAz and intracellular protein. MIP mapping of unreacted azide after click reaction reveals click chemistry heterogeneity within a bacterium. Broader applications of azido photothermal probes to visualize the initial steps of the Leloir pathway in yeasts and the newly synthesized glycans in mammalian cells are demonstrated.

Rapid hyperspectral photothermal mid-infrared spectroscopic imaging from sparse data for gynecologic cancer tissue subtyping

Ovarian cancer detection has traditionally relied on a multi-step process that includes biopsy, tissue staining, and morphological analysis by experienced pathologists. While widely practiced, this conventional approach suffers from several drawbacks: it is qualitative, time-intensive, and heavily dependent on the quality of staining. Mid-infrared (MIR) hyperspectral photothermal imaging is a label-free, biochemically quantitative technology that, when combined with machine learning algorithms, can eliminate the need for staining and provide quantitative results comparable to traditional histology. However, this technology is slow. This work presents a novel approach to MIR photothermal imaging that enhances its speed by an order of magnitude. Our method significantly accelerates data collection by capturing a combination of highresolution and interleaved, lower-resolution infrared band images and applying computational techniques for data interpolation. We effectively minimize data collection requirements by leveraging sparse data acquisition and employing curvelet-based reconstruction algorithms. This approach enhances imaging speed without compromising image quality and ensures robust tissue segmentation. This method resolves the longstanding trade-off between imaging resolution and data collection speed, enabling the reconstruction of high-quality, high-resolution images from undersampled datasets and achieving a 10X improvement in data acquisition time. We assessed the performance of our sparse imaging methodology using a variety of quantitative metrics, including mean squared error (MSE), structural similarity index (SSIM), and tissue subtype classification accuracies, employing both random forest and convolutional neural network (CNN) models, accompanied by Receiver Operating Characteristic (ROC) curves. Our statistically robust analysis, based on data from 100 ovarian cancer patient samples and over 65 million data points, demonstrates the method's capability to produce superior image quality and accurately distinguish between different gynecological tissue types with segmentation accuracy exceeding 95%. Our work demonstrates the feasibility of integrating rapid MIR hyperspectral photothermal imaging with machine learning in enhancing ovarian cancer tissue characterization, paving the way for quantitative, label-free, automated histopathology. It represents a significant leap forward from traditional histopathological methods, offering profound implications for cancer diagnostics and treatment decision-making.

Dual phase-detected infrared photothermal microscopy

Infrared photothermal microscopy (IPM) has recently gained considerable attention as a versatile analytical platform capable of providing spatially resolved molecular insights across diverse research fields. This technique has led to numerous breakthroughs in the study of compositional variations in functional materials and cellular dynamics in living cells. However, its application to investigate multiple components of temporally dynamic systems, such as living cells and operational devices, has been hampered by the limited information content of the IP signal, which only covers a narrow spectral window (< 1 cm-1). Here, we present a straightforward approach for measuring two distinct IPM images utilizing the orthogonality between the in-phase and quadrature outputs of a lock-in amplifier, called dual-phase IR photothermal (DP-IP) detection. We demonstrate the feasibility of DP-IP detection for IPM in distinguishing two different micro-sized polymer beads.

In Vitro Models for Investigating Intestinal Host-Pathogen Interactions

Infectious diseases are increasingly recognized as a major threat worldwide due to the rise of antimicrobial resistance and the emergence of novel pathogens. In vitro models that can adequately mimic in vivo gastrointestinal physiology are in high demand to elucidate mechanisms behind pathogen infectivity, and to aid the design of effective preventive and therapeutic interventions. There exists a trade-off between simple and high throughput models and those that are more complex and physiologically relevant. The complexity of the model used shall be guided by the biological question to be addressed. This review provides an overview of the structure and function of the intestine and the models that are developed to emulate this. Conventional models are discussed in addition to emerging models which employ engineering principles to equip them with necessary advanced monitoring capabilities for intestinal host-pathogen interrogation. Limitations of current models and future perspectives on the field are presented.

Steam disinfection enhances bioaccessibility of metallic nanoparticles in nano-enabled silicone-rubber baby bottle teats, pacifiers, and teethers

Nano-enabled silicone-rubber articles for feeding or chewing could be a source of metallic nanoparticles (NPs) directly exposed to infants and young children. However, the impact of steam disinfection on release of NPs and the related potential risks to children's health are unknown. Here, we investigated contents and form of Ag and Zn in 57 nano-enabled silicone-rubber baby bottle teats, pacifiers, and teethers of seven countries and examined the impacts of steam disinfection on in vitro bioaccessibility (IVBA) of Ag and Zn in the articles. Nearly 89% articles had a mixture of Ag- and Zn-containing NPs and the teethers had relatively high Ag and Zn contents (up to 501 and 254 µg/g, respectively). Steam disinfection caused rubber decomposition into micro(nano)plastics (0.54-15.7 µm) and NP release from the interior of bulk rubber and micro-sized plastics, thus enhancing the IVBA of Ag and Zn by up to 5.5 times. The findings provide insights into mechanisms for NP release by steam disinfection. Though oral exposure risk assessment suggested low health concerns on individual metal release, our study points out the need to assess the potential health risks of child co-exposure to metallic NPs and micro(nano)plastics.

Mapping enzyme activity in living systems by real-time mid-infrared photothermal imaging of nitrile chameleons

Simultaneous spatial mapping of the activity of multiple enzymes in a living system can elucidate their functions in health and disease. However, methods based on monitoring fluorescent substrates are limited. Here, we report the development of nitrile (C≡N)-tagged enzyme activity reporters, named nitrile chameleons, for the peak shift between substrate and product. To image these reporters in real time, we developed a laser-scanning mid-infrared photothermal imaging system capable of imaging the enzymatic substrates and products at a resolution of 300 nm. We show that when combined, these tools can map the activity distribution of different enzymes and measure their relative catalytic efficiency in living systems such as cancer cells, Caenorhabditis elegans, and brain tissues, and can be used to directly visualize caspase-phosphatase interactions during apoptosis. Our method is generally applicable to a broad category of enzymes and will enable new analyses of enzymes in their native context.

Gene and Photothermal Combination Therapy: Principle, Materials, and Amplified Anticancer Intervention

Gene therapy (GT) and photothermal therapy (PTT) have emerged as promising alternatives to chemotherapy and radiotherapy for cancer treatment, offering noninvasiveness and reduced side effects. However, their efficacy as standalone treatments is limited. GT exhibits slow response rates, while PTT is confined to local tumor ablation. The convergence of GT and PTT, known as GT-PTT, facilitated by photothermal gene nanocarriers, has attracted considerable attention across various disciplines. In this integrated approach, GT reciprocates PTT by sensitizing cellular response to heat, while PTT benefits GT by improving gene translocation, unpacking, and expression. Consequently, this integration presents a unique opportunity for cancer therapy with rapid response and improved effectiveness. Extensive efforts over the past few years have been dedicated to the development of GT-PTT, resulting in notable achievements and rapid progress from the laboratory to potential clinical applications. This comprehensive review outlines recent advances in GT-PTT, including synergistic mechanisms, material systems, imaging-guided therapy, and anticancer applications. It also explores the challenges and future prospects in this nascent field. By presenting innovative ideas and insights into the implementation of GT-PTT for enhanced cancer therapy, this review aims to inspire further progress in this promising area of research.

Monitoring the synthesis of neutral lipids in lipid droplets of living human cancer cells using two-color infrared photothermal microscopy

There has been growing interest in the functions of lipid droplets (LDs) due to recent discoveries regarding their diverse roles. These functions encompass lipid metabolism, regulation of lipotoxicity, and signaling pathways that extend beyond their traditional role in energy storage. Consequently, there is a need to examine the molecular dynamics of LDs at the subcellular level. Two-color infrared photothermal microscopy (2C-IPM) has proven to be a valuable tool for elucidating the molecular dynamics occurring in LDs with sub-micrometer spatial resolution and molecular specificity. In this study, we employed the 2C-IPM to investigate the molecular dynamics of LDs in both fixed and living human cancer cells (U2OS cells) using the isotope labeling method. We investigated the synthesis of neutral lipids occurring in individual LDs over time after exposing the cells to excess saturated fatty acids while simultaneously comparing inherent lipid contents in LDs. We anticipate that these research findings will reveal new opportunities for studying lesser-known biological processes within LDs and other subcellular organelles.

Colocalization of β-Sheets and Carotenoids in Aβ Plaques Revealed with Multimodal Spatially Resolved Vibrational Spectroscopy

The aggregation of amyloid β(Aβ) peptides is at the heart of Alzheimer's disease development and progression. As a result, amyloid aggregates have been studied extensively in vitro, and detailed structural information on fibrillar amyloid aggregates is available. However, forwarding these structural models to amyloid plaques in the human brain is still a major challenge. The chemistry of amyloid plaques, particularly in terms of the protein secondary structure and associated chemical moieties, remains poorly understood. In this report, we use Raman microspectroscopy to identify the presence of carotenoids in amyloid plaques and demonstrate that the abundance of carotenoids is correlated with the overall protein secondary structure of plaques, specifically to the population of β-sheets. While the association of carotenoids with plaques has been previously identified, their correlation with the β structure has never been identified. To further validate these findings, we have used optical photothermal infrared (O-PTIR) spectroscopy, which is a spatially resolved technique that yields complementary infrared contrast to Raman. O-PTIR unequivocally demonstrates the presence of elevated β-sheets in carotenoid-containing plaques and the lack of β structure in noncarotenoid plaques. Our findings underscore the potential link between anti-inflammatory species as carotenoids to specific secondary structural motifs within Aβ plaques and highlight the possible role of chemically distinct plaques in neuroinflammation, which can uncover new mechanistic insights and lead to new therapeutic strategies for AD.

Time-resolved vibrational dynamics: Novel opportunities for sensing and imaging

The evolution of time-resolved spectroscopies has resulted in significant advancements across numerous scientific disciplines, particularly those concerned with molecular electronic states. However, the intricacy of molecular vibrational spectroscopies, which provide comprehensive molecular-level information within complex structures, has presented considerable challenges due to the ultrashort dephasing time. Over recent decades, an increasing focus has been placed on exploring the temporal progression of bond vibrations, thereby facilitating an improved understanding of energy redistribution within and between molecules. This review article focuses on an array of time-resolved detection methodologies, each distinguished by unique technological attributes that offer exclusive capabilities for investigating the physical phenomena propelled by molecular vibrational dynamics. In summary, time-resolved vibrational spectroscopy emerges as a potent instrument for deciphering the dynamic behavior of molecules. Its potential for driving future progress across fields as diverse as biology and materials science is substantial, marking a promising future for this innovative tool.

Bond-selective full-field optical coherence tomography

Optical coherence tomography (OCT) is a label-free, non-invasive 3D imaging tool widely used in both biological research and clinical diagnosis. Conventional OCT modalities can only visualize specimen tomography without chemical information. Here, we report a bond-selective full-field OCT (BS-FF-OCT), in which a pulsed mid-infrared laser is used to modulate the OCT signal through the photothermal effect, achieving label-free bond-selective 3D sectioned imaging of highly scattering samples. We first demonstrate BS-FF-OCT imaging of 1 µm PMMA beads embedded in agarose gel. Next, we show 3D hyperspectral imaging of up to 75 µm of polypropylene fiber mattress from a standard surgical mask. We then demonstrate BS-FF-OCT imaging on biological samples, including cancer cell spheroids and C. elegans. Using an alternative pulse timing configuration, we finally demonstrate the capability of BS-FF-OCT on imaging a highly scattering myelinated axons region in a mouse brain tissue slice.

Roadmap on Label-Free Super-Resolution Imaging

Label-free super-resolution (LFSR) imaging relies on light-scattering processes in nanoscale objects without a need for fluorescent (FL) staining required in super-resolved FL microscopy. The objectives of this Roadmap are to present a comprehensive vision of the developments, the state-of-the-art in this field, and to discuss the resolution boundaries and hurdles which need to be overcome to break the classical diffraction limit of the LFSR imaging. The scope of this Roadmap spans from the advanced interference detection techniques, where the diffraction-limited lateral resolution is combined with unsurpassed axial and temporal resolution, to techniques with true lateral super-resolution capability which are based on understanding resolution as an information science problem, on using novel structured illumination, near-field scanning, and nonlinear optics approaches, and on designing superlenses based on nanoplasmonics, metamaterials, transformation optics, and microsphere-assisted approaches. To this end, this Roadmap brings under the same umbrella researchers from the physics and biomedical optics communities in which such studies have often been developing separately. The ultimate intent of this paper is to create a vision for the current and future developments of LFSR imaging based on its physical mechanisms and to create a great opening for the series of articles in this field.

Label-free biomedical optical imaging

Label-free optical imaging employs natural and nondestructive approaches for the visualisation of biomedical samples for both biological assays and clinical diagnosis. Currently, this field revolves around multiple broad technology-oriented communities, each with a specific focus on a particular modality despite the existence of shared challenges and applications. As a result, biologists or clinical researchers who require label-free imaging are often not aware of the most appropriate modality to use. This manuscript presents a comprehensive review of and comparison among different label-free imaging modalities and discusses common challenges and applications. We expect this review to facilitate collaborative interactions between imaging communities, push the field forward and foster technological advancements, biophysical discoveries, as well as clinical detection, diagnosis, and monitoring of disease.

Time-Resolved Mid-Infrared Photothermal Microscopy for Imaging Water-Embedded Axon Bundles

Few experimental tools exist for performing label-free imaging of biological samples in a water-rich environment due to the high infrared absorption of water, overlapping with major protein and lipid bands. A novel imaging modality based on time-resolved mid-infrared photothermal microscopy is introduced and applied to imaging axon bundles in a saline bath environment. Photothermally induced spatial gradients at the axon bundle membrane interfaces with saline and surrounding biological tissue are observed and temporally characterized by a high-speed boxcar detection system. Localized time profiles with an enhanced signal-to-noise, hyper-temporal image stacks, and two-dimensional mapping of the time decay profiles are acquired without the need for complex post image processing. Axon bundles are found to have a larger distribution of time decay profiles compared to the water background, allowing background differentiation based on these transient dynamics. The quantitative analysis of the signal evolution over time allows characterizing the level of thermal confinement at different regions. When axon bundles are surrounded by complex heterogeneous tissue, which contains smaller features, a stronger thermal confinement is observed compared to a water environment, thus shedding light on the heat transfer dynamics across aqueous biological interfaces.

Label-Free High-Resolution Photothermal Optical Infrared Spectroscopy for Spatiotemporal Chemical Analysis in Fresh, Hydrated Living Tissues and Embryos

Label-free chemical imaging of living and functioning systems is the holy grail of biochemical research. However, existing techniques often require extensive sample preparation to remove interfering molecules such as water, rendering many molecular imaging techniques unsuitable for in situ structural studies. Here, we examined freshly extracted tissue biopsies and living small vertebrates at submicrometer resolution using optical photothermal infrared (O-PTIR) microspectroscopy and demonstrated the following major advances: (1) O-PTIR can be used for submicrometer structural analysis of unprocessed, fully hydrated tissue biopsies extracted from diverse organs, including living brain and lung tissues. (2) O-PTIR imaging can be performed on living organisms, such as salamander embryos, without compromising their further development. (3) Using O-PTIR, we tracked the structural changes of amyloids in functioning brain tissues over time, observing the appearance of newly formed amyloids for the first time. (4) Amyloid structures appeared altered following standard fixation and dehydration procedures. Thus, we demonstrate that O-PTIR enables time-resolved submicrometer in situ investigation of chemical and structural changes in diverse biomolecules in their native conditions, representing a technological breakthrough for in situ molecular imaging of biological samples.

Application of Optical Photothermal Infrared (O-PTIR) Spectroscopy for Assessment of Bone Composition at the Submicron Scale

The molecular basis of bone structure and strength is mineralized collagen fibrils at the submicron scale (∼500 nm). Recent advances in optical photothermal infrared (O-PTIR) spectroscopy allow the investigation of bone composition with unprecedented submicron spatial resolution, which may provide new insights into factors contributing to underlying bone function. Here, we investigated (i) whether O-PTIR-derived spectral parameters correlated to standard attenuated total reflection (ATR) Fourier transform infrared spectroscopy spectral data and (ii) whether O-PTIR-derived spectral parameters, including heterogeneity of tissue, contribute to the prediction of proximal femoral bone stiffness. Analysis of serially demineralized bone powders showed a significant correlation (r = 0.96) between mineral content quantified using ATR and O-PTIR spectroscopy, indicating the validity of this technique in assessing bone mineralization. Using femoral neck sections, the principal component analysis showed that differences between O-PTIR and ATR spectra were primarily attributable to the phosphate ion (PO4) absorbance band, which was typically shifter toward higher wavenumbers in O-PTIR spectra. Additionally, significant correlations were found between hydrogen phosphate (HPO4) content (r = 0.75) and carbonate (CO3) content (r = 0.66) quantified using ATR and O-PTIR spectroscopy, strengthening the validity of this method to assess bone mineral composition. O-PTIR imaging of individual trabeculae at 500 nm pixel resolution illustrated differences in submicron composition in the femoral neck from bones with different stiffness. O-PTIR analysis showed a significant negative correlation (r = -0.71) between bone stiffness and mineral maturity, reflective of newly formed bone being an important contributor to bone function. Finally, partial least squares regression analysis showed that combining multiple O-PTIR parameters (HPO4 content and heterogeneity, collagen integrity, and CO3 content) could significantly predict proximal femoral stiffness (R2 = 0.74, error = 9.7%) more accurately than using ATR parameters. Additionally, we describe new findings in the effects of bone tissue orientation in the O-PTIR spectra. Overall, this study highlights a new application of O-PTIR spectroscopy that may provide new insights into molecular-level factors underlying bone mechanical competence.

Stimulated Raman photothermal microscopy toward ultrasensitive chemical imaging

Stimulated Raman scattering (SRS) microscopy has shown enormous potential in revealing molecular structures, dynamics, and couplings in complex systems. However, the sensitivity of SRS is fundamentally limited to the millimolar level due to shot noise and the small modulation depth. To overcome this barrier, we revisit SRS from the perspective of energy deposition. The SRS process pumps molecules to their vibrationally excited states. The subsequent relaxation heats up the surroundings and induces refractive index changes. By probing the refractive index changes with a laser beam, we introduce stimulated Raman photothermal (SRP) microscopy, where a >500-fold boost of modulation depth is achieved. The versatile applications of SRP microscopy on viral particles, cells, and tissues are demonstrated. SRP microscopy opens a way to perform vibrational spectroscopic imaging with ultrahigh sensitivity.

Single virus fingerprinting by widefield interferometric defocus-enhanced mid-infrared photothermal microscopy

Clinical identification and fundamental study of viruses rely on the detection of viral proteins or viral nucleic acids. Yet, amplification-based and antigen-based methods are not able to provide precise compositional information of individual virions due to small particle size and low-abundance chemical contents (e.g., ~ 5000 proteins in a vesicular stomatitis virus). Here, we report a widefield interferometric defocus-enhanced mid-infrared photothermal (WIDE-MIP) microscope for high-throughput fingerprinting of single viruses. With the identification of feature absorption peaks, WIDE-MIP reveals the contents of viral proteins and nucleic acids in single DNA vaccinia viruses and RNA vesicular stomatitis viruses. Different nucleic acid signatures of thymine and uracil residue vibrations are obtained to differentiate DNA and RNA viruses. WIDE-MIP imaging further reveals an enriched β sheet components in DNA varicella-zoster virus proteins. Together, these advances open a new avenue for compositional analysis of viral vectors and elucidating protein function in an assembled virion.

High-throughput single-cell sorting by stimulated Raman-activated cell ejection

Single-cell sorting is essential to explore cellular heterogeneity in biology and medicine. Recently developed Raman-activated cell sorting (RACS) circumvents the limitations of fluorescence-activated cell sorting, such as the cytotoxicity of labels. However, the sorting throughputs of all forms of RACS are limited by the intrinsically small cross-section of spontaneous Raman scattering. Here, we report a stimulated Raman-activated cell ejection (S-RACE) platform that enables high-throughput single-cell sorting based on high-resolution multi-channel stimulated Raman chemical imaging, in situ image decomposition, and laser-induced cell ejection. The performance of this platform was illustrated by sorting a mixture of 1 μm polymer beads, where 95% yield, 98% purity, and 14 events per second throughput were achieved. Notably, our platform allows live cell ejection, allowing for the growth of single colonies of bacteria and fungi after sorting. To further illustrate the chemical selectivity, lipid-rich Rhodotorula glutinis cells were successfully sorted from a mixture with Saccharomyces cerevisiae, confirmed by downstream quantitative PCR. Furthermore, by integrating a closed-loop feedback control circuit into the system, we realized real-time single-cell imaging and sorting, and applied this method to precisely eject regions of interest from a rat brain tissue section. The reported S-RACE platform opens exciting opportunities for a wide range of single-cell applications in biology and medicine.

Millimeter-deep micron-resolution vibrational imaging by shortwave infrared photothermal microscopy

Deep-tissue chemical imaging plays a vital role in biological and medical applications. Here, we present a shortwave infrared photothermal (SWIP) microscope for millimeter-deep vibrational imaging with sub-micron lateral resolution and nanoparticle detection sensitivity. By pumping the overtone transition of carbon-hydrogen bonds and probing the subsequent photothermal lens with shortwave infrared light, SWIP can obtain chemical contrast from polymer particles located millimeter-deep in a highly scattering phantom. By fast digitization of the optically probed signal, the amplitude of the photothermal signal is shown to be 63 times larger than that of the photoacoustic signal, thus enabling highly sensitive detection of nanoscale objects. SWIP can resolve the intracellular lipids across an intact tumor spheroid and the layered structure in millimeter-thick liver, skin, brain, and breast tissues. Together, SWIP microscopy fills a gap in vibrational imaging with sub-cellular resolution and millimeter-level penetration, which heralds broad potential for life science and clinical applications.

Bond-selective fluorescence imaging with single-molecule sensitivity

Bioimaging harnessing optical contrasts and chemical specificity is of vital importance in probing complex biology. Vibrational spectroscopy based on mid-infrared (mid-IR) excitation can reveal rich chemical information about molecular distributions. However, its full potential for bioimaging is hindered by the achievable sensitivity. Here, we report bond selective fluorescence-detected infrared-excited (BonFIRE) spectral microscopy. BonFIRE employs two-photon excitation in the mid-IR and near-IR to upconvert vibrational excitations to electronic states for fluorescence detection, thus encoding vibrational information into fluorescence. The system utilizes tuneable narrowband picosecond pulses to ensure high sensitivity, biocompatibility, and robustness for bond-selective biological interrogations over a wide spectrum of reporter molecules. We demonstrate BonFIRE spectral imaging in both fingerprint and cell-silent spectroscopic windows with single-molecule sensitivity for common fluorescent dyes. We then demonstrate BonFIRE imaging on various intracellular targets in fixed and live cells, neurons, and tissues, with promises for further vibrational multiplexing. For dynamic bioanalysis in living systems, we implement a high-frequency modulation scheme and demonstrate time-lapse BonFIRE microscopy of live HeLa cells. We expect BonFIRE to expand the bioimaging toolbox by providing a new level of bond-specific vibrational information and facilitate functional imaging and sensing for biological investigations.

Stimulated Raman Photothermal Microscopy towards Ultrasensitive Chemical Imaging

Stimulated Raman scattering (SRS) microscopy has shown enormous potential in revealing molecular structures, dynamics and coupling in a complex system. However, the bond-detection sensitivity of SRS microscopy is fundamentally limited to milli-molar level due to the shot noise and the small modulation depth in either pump or Stokes beam4. Here, to overcome this barrier, we revisit SRS from the perspective of energy deposition. The SRS process pumps molecules to their vibrational excited states. The thereafter relaxation heats up the surrounding and induces a change in refractive index. By probing the refractive index change with a continuous wave beam, we introduce stimulated Raman photothermal (SRP) microscopy, where a >500-fold boost of modulation depth is achieved on dimethyl sulfide with conserved average power. Versatile applications of SRP microscopy on viral particles, cells, and tissues are demonstrated. With much improved signal to noise ratio compared to SRS, SRP microscopy opens a new way to perform vibrational spectroscopic imaging with ultrahigh sensitivity and minimal water absorption.

Coherent Raman scattering microscopy of lipid droplets in cells and tissues

Lipid droplets (LDs) play a key role as the hub for lipid metabolism to maintain cellular metabolic homeostasis. Understanding the functions and changes of LDs in different pathological conditions is crucial for identifying new markers for diagnosis and discovering new targets for treatment. In recent years, coherent Raman scattering (CRS) microscopy has been popularized for the imaging and quantification of LDs in live cells. Compared to spontaneous Raman scattering microscopy, CRS microscopy offers a much higher imaging speed while maintaining similar chemical information. Due to the high lipid density, LDs usually have strong CRS signals and therefore are the most widely studied organelle in the CRS field. In this review, we discuss recent achievements using CRS to study the quantity, distribution, composition, and dynamics of LDs in various systems.

High-speed mid-infrared graphene electro-optical modulator based on suspended germanium slot waveguides

The mid-infrared (MIR) region is attracting increasing interest for on-chip synchronous detection and free-space optical (FSO) communications. For such applications, a high-performance electro-optical modulator is a crucial component. In this regard, we propose and investigate a graphene-based electro-absorption modulator (EAM) and microring modulator (MRM) using the suspended germanium waveguide platform. The modulators are designed for the second atmospheric window (8 to 12 µm). The incorporation of double-layer graphene on the suspended slot waveguide structure allows for the significant enhancement of light-graphene interaction, theoretically achieving a 3-dB bandwidth as high as 78 GHz. The EAM shows a calculated modulation depth of 0.022-0.045 dB/µm for the whole operation wavelength range. The MRM exhibits a calculated extinction ratio as high as 68.9 dB and a modulation efficiency of 0.59 V·cm around 9 µm. These modulators hold promise for constructing high-speed FSO communication and on-chip spectroscopic detection systems in the MIR atmospheric window.

Infrared spectroscopic laser scanning confocal microscopy for whole-slide chemical imaging

Chemical imaging, especially mid-infrared spectroscopic microscopy, enables label-free biomedical analyses while achieving expansive molecular sensitivity. However, its slow speed and poor image quality impede widespread adoption. We present a microscope that provides high-throughput recording, low noise, and high spatial resolution where the bottom-up design of its optical train facilitates dual-axis galvo laser scanning of a diffraction-limited focal point over large areas using custom, compound, infinity-corrected refractive objectives. We demonstrate whole-slide, speckle-free imaging in ~3 min per discrete wavelength at 10× magnification (2 μm/pixel) and high-resolution capability with its 20× counterpart (1 μm/pixel), both offering spatial quality at theoretical limits while maintaining high signal-to-noise ratios (>100:1). The data quality enables applications of modern machine learning and capabilities not previously feasible - 3D reconstructions using serial sections, comprehensive assessments of whole model organisms, and histological assessments of disease in time comparable to clinical workflows. Distinct from conventional approaches that focus on morphological investigations or immunostaining techniques, this development makes label-free imaging of minimally processed tissue practical.

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.