Nanoplastics Detected in Commercial Sea Salt.

People of all ages consume salt every day, but is it really just salt? Plastic nanoparticles [nanoplastics (NPs)] pose an increasing environmental threat and have begun to contaminate everyday salt in consumer goods. Herein, we developed a combined surface enhanced Raman scattering (SERS) and stimulated Raman scattering (SRS) approach that can realize the filtration, enrichment, and detection of NPs in commercial salt. The Au-loaded (50 nm) anodic alumina oxide substrate was used as the SERS substrate to explore the potential types of NP contaminants in salts. SRS was used to conduct imaging and quantify the presence of the NPs. SRS detection was successfully established through standard plastics, and NPs were identified through the match of the hydrocarbon group of the nanoparticles. Simultaneously, the NPs were quantified based on the high spatial resolution and rapid imaging of the SRS imaging platform. NPs in sea salts produced in Asia, Australasia, Europe, and the Atlantic were studied. We estimate that, depending on the location, an average person could be ingesting as many as 6 million NPs per year through the consumption of sea salt alone. The potential health hazards associated with NP ingestion should not be underestimated.

Virtual formalin-fixed and paraffin-embedded staining of fresh brain tissue via stimulated Raman CycleGAN model.

Intraoperative histology is essential for surgical guidance and decision-making. However, frozen-sectioned hematoxylin and eosin (H&E) staining suffers from degraded accuracy, whereas the gold-standard formalin-fixed and paraffin-embedded (FFPE) H&E is too lengthy for intraoperative use. Stimulated Raman scattering (SRS) microscopy has shown rapid histology of brain tissue with lipid/protein contrast but is challenging to yield images identical to nucleic acid-/protein-based FFPE stains interpretable to pathologists. Here, we report the development of a semi-supervised stimulated Raman CycleGAN model to convert fresh-tissue SRS images to H&E stains using unpaired training data. Within 3 minutes, stimulated Raman virtual histology (SRVH) results that matched perfectly with true H&E could be generated. A blind validation indicated that board-certified neuropathologists are able to differentiate histologic subtypes of human glioma on SRVH but hardly on conventional SRS images. SRVH may provide intraoperative diagnosis superior to frozen H&E in both speed and accuracy, extendable to other types of solid tumors.

High-content stimulated Raman histology of human breast cancer.

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

Significantly Accelerated Photochemical Perfluorooctanoic Acid Decomposition at the Air-Water Interface of Microdroplets.

The efficient elimination of per- and polyfluoroalkyl substances (PFASs) from the environment remains a huge challenge and requires advanced technologies. Herein, we demonstrate that perfluorooctanoic acid (PFOA) photochemical decomposition could be significantly accelerated by simply carrying out this process in microdroplets. The almost complete removal of 100 and 500 µg/L PFOA was observed after 20 min of irradiation in microdroplets, while this was achieved after about 2 h in the corresponding bulk phase counterpart. To better compare the defluorination ratio, 10 mg/L PFOA was used typically, and the defluorination rates in microdroplets were tens of times faster than that in the bulk phase reaction system. The high performances in actual water matrices, universality, and scale-up applicability were demonstrated as well. We revealed in-depth that the great acceleration is due to the abundance of the air-water interface in microdroplets, where the reactants concentration enrichment, ultrahigh interfacial electric field, and partial solvation effects synergistically promoted photoreactions responsible for PFOA decomposition, as evidenced by simulated Raman scattering microscopy imaging, vibrational Stark effect measurement, and DFT calculation. This study provides an effective approach and highlights the important roles of air-water interface of microdroplets in PFASs treatment.

Evaluating Differentiation Status of Mesenchymal Stem Cells by Label-Free Microscopy System and Machine Learning.

Mesenchymal stem cells (MSCs) play a crucial role in tissue engineering, as their differentiation status directly affects the quality of the final cultured tissue, which is critical to the success of transplantation therapy. Furthermore, the precise control of MSC differentiation is essential for stem cell therapy in clinical settings, as low-purity stem cells can lead to tumorigenic problems. Therefore, to address the heterogeneity of MSCs during their differentiation into adipogenic or osteogenic lineages, numerous label-free microscopic images were acquired using fluorescence lifetime imaging microscopy (FLIM) and stimulated Raman scattering (SRS), and an automated evaluation model for the differentiation status of MSCs was built based on the K-means machine learning algorithm. The model is capable of highly sensitive analysis of individual cell differentiation status, so it has great potential for stem cell differentiation research.

Imaging of pH distribution inside individual microdroplet by stimulated Raman microscopy.

Aerosol microdroplets as microreactors for many important atmospheric reactions are ubiquitous in the atmosphere. pH largely regulates the chemical processes within them; however, how pH and chemical species spatially distribute within an atmospheric microdroplet is still under intense debate. The challenge is to measure pH distribution within a tiny volume without affecting the chemical species distribution. We demonstrate a method based on stimulated Raman scattering microscopy to visualize the three-dimensional pH distribution inside single microdroplets of varying sizes. We find that the surface of all microdroplets is more acidic, and a monotonic trend of pH decreasing is observed in the 2.9-µm aerosol microdroplet from center to edge, which is well supported by molecular dynamics simulation. However, bigger cloud microdroplet differs from small aerosol for pH distribution. This size-dependent pH distribution in microdroplets can be related to the surface-to-volume ratio. This work presents noncontact measurement and chemical imaging of pH distribution in microdroplets, filling the gap in our understanding of spatial pH in atmospheric aerosol.

Histological diagnosis of unprocessed breast core-needle biopsy via stimulated Raman scattering microscopy and multi-instance learning.

Core-needle biopsy (CNB) plays a vital role in the initial diagnosis of breast cancer. However, the complex tissue processing and global shortage of pathologists have hindered traditional histopathology from timely diagnosis on fresh biopsies. In this work, we developed a full digital platform by integrating label-free stimulated Raman scattering (SRS) microscopy with weakly-supervised learning for rapid and automated cancer diagnosis on un-labelled breast CNB. Methods: We first compared the results of SRS imaging with standard hematoxylin and eosin (H&E) staining on adjacent frozen tissue sections. Then fresh unprocessed biopsy tissues were imaged by SRS to reveal diagnostic histoarchitectures. Next, weakly-supervised learning, i.e., the multi-instance learning (MIL) model was conducted to evaluate the ability to differentiate between benign and malignant cases, and compared with the performance of supervised learning model. Finally, gradient-weighted class activation mapping (Grad-CAM) and semantic segmentation were performed to spatially resolve benign/malignant areas with high efficiency. Results: We verified the ability of SRS in revealing essential histological hallmarks of breast cancer in both thin frozen sections and fresh unprocessed biopsy, generating histoarchitectures well correlated with H&E staining. Moreover, we demonstrated that weakly-supervised MIL model could achieve superior classification performance to supervised learnings, reaching diagnostic accuracy of 95% on 61 biopsy specimens. Furthermore, Grad-CAM allowed the trained MIL model to visualize the histological heterogeneity within the CNB. Conclusion: Our results indicate that MIL-assisted SRS microscopy provides rapid and accurate diagnosis on histologically heterogeneous breast CNB, and could potentially help the subsequent management of patients.

Stimulated Raman Scattering Microscopy Enables Gleason Scoring of Prostate Core Needle Biopsy by a Convolutional Neural Network.

Focal therapy (FT) has been proposed as an approach to eradicate clinically significant prostate cancer while preserving the normal surrounding tissues to minimize treatment-related toxicity. Rapid histology of core needle biopsies is essential to ensure the precise FT for localized lesions and to determine tumor grades. However, it is difficult to achieve both high accuracy and speed with currently available histopathology methods. Here, we demonstrated that stimulated Raman scattering (SRS) microscopy could reveal the largely heterogeneous histologic features of fresh prostatic biopsy tissues in a label-free and near real-time manner. A diagnostic convolutional neural network (CNN) built based on images from 61 patients could classify Gleason patterns of prostate cancer with an accuracy of 85.7%. An additional 22 independent cases introduced as external test dataset validated the CNN performance with 84.4% accuracy. Gleason scores of core needle biopsies from 21 cases were calculated using the deep learning SRS system and showed a 71% diagnostic consistency with grading from three pathologists. This study demonstrates the potential of a deep learning-assisted SRS platform in evaluating the tumor grade of prostate cancer, which could help simplify the diagnostic workflow and provide timely histopathology compatible with FT treatment. SIGNIFICANCE: A platform combining stimulated Raman scattering microscopy and a convolutional neural network provides rapid histopathology and automated Gleason scoring on fresh prostate core needle biopsies without complex tissue processing.

Significantly Accelerated Hydroxyl Radical Generation by Fe(III)-Oxalate Photochemistry in Aerosol Droplets.

Fe(III)-oxalate complexes are ubiquitous in atmospheric environments, which can release reactive oxygen species (ROS) such as H2O2, O•2-, and OH• under light irradiation. Although Fe(III)-oxalate photochemistry has been investigated extensively, the understanding of its involvement in authentic atmospheric environments such as aerosol droplets is far from enough, since the current available knowledge has mainly been obtained in bulk-phase studies. Here, we find that the production of OH• by Fe(III)-oxalate in aerosol microdroplets is about 10-fold greater than that of its bulk-phase counterpart. In addition, in the presence of Fe(III)-oxalate complexes, the rate of photo-oxidation from SO2 to sulfate in microdroplets was about 19-fold faster than that in the bulk phase. The availability of efficient reactants and mass transfer due to droplet effects made dominant contributions to the accelerated OH• and SO42- formation. This work highlights the necessary consideration of droplet effects in atmospheric laboratory studies and model simulations.

Instant diagnosis of gastroscopic biopsy via deep-learned single-shot femtosecond stimulated Raman histology.

Gastroscopic biopsy provides the only effective method for gastric cancer diagnosis, but the gold standard histopathology is time-consuming and incompatible with gastroscopy. Conventional stimulated Raman scattering (SRS) microscopy has shown promise in label-free diagnosis on human tissues, yet it requires the tuning of picosecond lasers to achieve chemical specificity at the cost of time and complexity. Here, we demonstrate that single-shot femtosecond SRS (femto-SRS) reaches the maximum speed and sensitivity with preserved chemical resolution by integrating with U-Net. Fresh gastroscopic biopsy is imaged in <60 s, revealing essential histoarchitectural hallmarks perfectly agreed with standard histopathology. Moreover, a diagnostic neural network (CNN) is constructed based on images from 279 patients that predicts gastric cancer with accuracy >96%. We further demonstrate semantic segmentation of intratumor heterogeneity and evaluation of resection margins of endoscopic submucosal dissection (ESD) tissues to simulate rapid and automated intraoperative diagnosis. Our method holds potential for synchronizing gastroscopy and histopathological diagnosis.

Generation of broadband parabolic pulses based on a pre-chirper free, core-pumped nonlinear fiber amplifier for coherent anti-Stokes Raman imaging.

We report the generation of parabolic pulses with broadband spectrum from a core-pumped Yb-doped fiber amplifier seeded by a dispersion managed fiber oscillator. The net cavity dispersion of Yb-doped oscillator was continuously changed from 0.074 to -0.170 ps2, which enabled us to achieve dissipative soliton, stretched pulse and soliton mode-locking operations. Spectral evolution processes in the core-pumped nonlinear fiber amplifier seeded by various input solitons were investigated experimentally and theoretically. Our finding indicates that cavity dispersion of oscillator can be used to engineer the input pulse parameter for amplifier, thus forming a pre-chirper free fiber amplification structure. In the experiment, we obtained 410-mW parabolic pulses with spectral bandwidth up to 56 nm. In combination with a passively synchronized frequency-doubled Er-doped fiber laser, we have demonstrated coherent anti-Stokes Raman imaging. The compact dual-color fiber laser source may facilitate practical applications of nonlinear biomedical imaging beyond the laboratory environment.

Switchable stimulated Raman scattering microscopy with photochromic vibrational probes.

Photochromic probes with reversible fluorescence have revolutionized the fields of single molecule spectroscopy and super-resolution microscopy, but lack sufficient chemical specificity. In contrast, Raman probes with stimulated Raman scattering (SRS) microscopy provides superb chemical resolution for super-multiplexed imaging, but are relatively inert. Here we report vibrational photochromism by engineering alkyne tagged diarylethene to realize photo-switchable SRS imaging. The narrow Raman peak of the alkyne group shifts reversibly upon photoisomerization of the conjugated diarylethene when irradiated by ultraviolet (UV) or visible light, yielding "on" or "off" SRS images taken at the photoactive Raman frequency. We demonstrated photo-rewritable patterning and encryption on thin films, painting/erasing of cells with labelled alkyne-diarylethene, as well as pulse-chase experiments of mitochondria diffusion in living cells. The design principle provides potentials for super-resolution microscopy, optical memories and switches with vibrational specificity.

Highly specific and label-free histological identification of microcrystals in fresh human gout tissues with stimulated Raman scattering.

Gout is a common metabolic disease with growing burden, caused by monosodium urate (MSU) microcrystal deposition. In situ and chemical-specific histological identification of MSU is crucial in the diagnosis and management of gout, yet it remains inaccessible for current histological methods. Methods: Stimulated Raman scattering (SRS) microscopy was utilized to image MSU based on its fingerprint Raman spectra. We first tested SRS for the diagnosis capability of gout and the differentiation power from pseudogout with rat models of acute gout arthritis, calcium pyrophosphate deposition disease (CPDD) and comorbidity. Then, human synovial fluid and surgical specimens (n=120) were were imaged with SRS to obtain the histopathology of MSU and collagen fibers. Finally, quantitative SRS analysis was performed in gout tissue of different physiological phases (n=120) to correlate with traditional histopathology including H&E and immunohistochemistry staining. Results: We demonstrated that SRS is capable of early diagnosis of gout, rapid detection of MSU in synovial fluid and fresh unprocessed surgical tissues, and accurate differentiation of gout from pseudogout in various pathophysiological conditions. Furthermore, quantitative SRS analysis revealed the optical characteristics of MSU deposition at different pathophysiological stages, which were found to matched well with corresponding immunofluorescence histochemistry features. Conclusion: Our work demonstrated the potential of SRS microscopy for rapid intraoperative diagnosis of gout and may facilitate future fundamental researches of MSU-based diseases.

Passively synchronized mode-locked fiber lasers for coherent anti-Stokes Raman imaging.

We have proposed and implemented a polarization-maintaining passively synchronized fiber laser system, which could deliver tunable dual-color picosecond pulses by including a frequency-doubling module and a spectral broadening module. Specifically, the output from the involved Er-doped fiber laser were used to generate second-harmonic pulses at 790 nm with a quadratic nonlinear crystal. In parallel, the amplified pulses from the synchronized Yb-doped fiber laser were launched into a 150-m single mode fiber, which resulted in not only substantial spectral bandwidth broadening from 0.1 to 20.1 nm, but also a significant Raman-induced signal around 1080 nm. Consequently, narrow spectra from 1018-1051 nm and 1070-1095 nm could be continuously tuned via a tunable bandpass filter, corresponding to Raman bonds from 2835-3143 cm-1 and 3312-3525 cm-1. Finally, the achieved tunable synchronized pulses enabled us to microscopically examine mouse ear samples based on coherent anti-Stokes Raman and second harmonic generation imaging. Therefore, our tunable passively-synchronized fiber laser system would be promising to provide a simple and compact laser source for subsequent coherent Raman microscopy.