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[IEEE 2019 Conference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC) - Munich, Germany (2019.6.23-2019.6.27)] 2019 Conference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC) - Quantitative Phase Microscopy with Molecular Vibrational Sensitivity
摘要： Quantitative phase imaging (QPI) has become a valuable tool for studying optically transparent samples such as biological cells and tissues. It yields the sample-specific optical path-length delay at each spatial point of the field of view with a nanometer resolution, enabling high-contrast and objective analysis. The major advantage of QPI is its wide-field, label-free measurement capability of the transparent morphology. This allows for high-speed imaging limited by the image sensor’s frame rate while reducing optical and/or chemical damages to the sample which are troublesome in other imaging techniques such as fluorescence and Raman imaging. To date, QPI has been used for pathology diagnosis, phenotyping of live cancer cells, non-destructive measurement of cellular volume and dry-mass, study of cellular membrane dynamics, to just name a few. However, QPI lacks chemical sensitivity which limits its application to morphology-based diagnosis. Here, we report on our wide-field label-free molecular-vibrational (MV) microscopy method realized in the framework of QPI utilizing mid-infrared (MIR) photothermal effect. We measure local changes in the optical phase delay occurring upon absorption of the MIR light in the vicinity of the MV-resonant molecules, which is called photothermal effect, by means of QPI. This imaging scheme yields high-molecular-detection sensitivity based on MV-resonant MIR absorption having ~8 orders of magnitude larger cross-section compared to Raman scattering. Meanwhile, it also maintains the visible-light spatial resolution, high temporal resolution limited by the image sensor’s frame rate, and low photodamage to the sample with the wide-field, low-fluence optical illumination. Notably, our wide-field, parallelized detection scheme could even surpass the imaging speed of conventional label-free imaging methods such as coherent Raman imaging by an order of magnitude, as they typically employ a point-scanning mechanism for image synthesis. Our MV-sensitive QPI (MV-QPI) could offer new insights for optically-transparent complex dynamics by enabling high-speed, label-free cross-correlative analysis based on the quantitative morphology and the MV-spectroscopic chemical contrasts.
关键词： molecular-vibrational microscopy,Quantitative phase imaging,chemical sensitivity,label-free imaging,mid-infrared photothermal effect
更新于2025-09-12 10:27:22
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Label-Free Super-Resolution Imaging of Transparent Dielectric Objects Assembled on Silver Film by a Microsphere-Assisted Microscope
摘要： In optical microscopy, label-free imaging transparent dielectric objects with sub-wavelength features is still a challenge. We propose a method to super-resolution image a label-free transparent periodic object using the microsphere-assisted bright-field microscope. A two-dimensional array of label-free hexagonally close-packed polystyrene (PS) nanoparticles with a diameter of 250 nm assembled on a silver film coated glass slide can be discerned by coupling a classical optical microscope with a 30-μm-diameter BaTiO3 glass (BTG) microsphere. However, when the PS nanoparticle array with the same diameter is assembled on either a glass slide or a high-reflectance dielectric multilayer coated glass slide, it cannot be resolved. We propose that period plasmonic near-field illumination is generated due to the excitation of surface plasmon polarition modes on periodically structured interfaces. More high-frequency information of the object is coupled into the BTG microsphere lens, resulting in the improvement of imaging resolution.
关键词： transparent dielectric objects,surface plasmon polarition modes,microsphere-assisted microscope,label-free imaging,super-resolution
更新于2025-09-12 10:27:22
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Label-free imaging of amyloid plaques in Alzheimer’s disease with stimulated Raman scattering microscopy
摘要： One of the key pathological features of Alzheimer’s disease (AD) is the existence of extracellular deposition of amyloid plaques formed with misfolded amyloid-β (Aβ). The conformational change of proteins leads to enriched contents of β sheets, resulting in remarkable changes of vibrational spectra, especially the spectral shifts of the amide I mode. Here, we applied stimulated Raman scattering (SRS) microscopy to image amyloid plaques in the brain tissue of an AD mouse model. We have demonstrated the capability of SRS microscopy as a rapid, label-free imaging modality to differentiate misfolded from normal proteins based on the blue shift (~10 cm?1) of amide I SRS spectra. Furthermore, SRS imaging of Aβ plaques was verified by antibody staining of frozen thin sections and fluorescence imaging of fresh tissues. Our method may provide a new approach for studies of AD pathology, as well as other neurodegenerative diseases associated with protein misfolding.
关键词： amyloid plaques,protein misfolding,Alzheimer’s disease,stimulated Raman scattering microscopy,label-free imaging
更新于2025-09-09 09:28:46
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Label-Free Identification of Lymphocyte Subtypes Using Three-Dimensional Quantitative Phase Imaging and Machine Learning
摘要： We describe here a protocol for the label-free identification of lymphocyte subtypes using quantitative phase imaging and machine learning. Identification of lymphocyte subtypes is important for the study of immunology as well as diagnosis and treatment of various diseases. Currently, standard methods for classifying lymphocyte types rely on labeling specific membrane proteins via antigen-antibody reactions. However, these labeling techniques carry the potential risks of altering cellular functions. The protocol described here overcomes these challenges by exploiting intrinsic optical contrasts measured by 3D quantitative phase imaging and a machine learning algorithm. Measurement of 3D refractive index (RI) tomograms of lymphocytes provides quantitative information about 3D morphology and phenotypes of individual cells. The biophysical parameters extracted from the measured 3D RI tomograms are then quantitatively analyzed with a machine learning algorithm, enabling label-free identification of lymphocyte types at a single-cell level. We measure the 3D RI tomograms of B, CD4+ T, and CD8+ T lymphocytes and identified their cell types with over 80% accuracy. In this protocol, we describe the detailed steps for lymphocyte isolation, 3D quantitative phase imaging, and machine learning for identifying lymphocyte types.
关键词： lymphocyte identification,machine learning,holotomography,immune cell,immunology,Immunology and Infection,Quantitative phase imaging,optical diffraction tomography,holographic microscopy,label-free imaging
更新于2025-09-04 15:30:14
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Motility-based label-free detection of parasites in bodily fluids using holographic speckle analysis and deep learning
摘要： Parasitic infections constitute a major global public health issue. Existing screening methods that are based on manual microscopic examination often struggle to provide sufficient volumetric throughput and sensitivity to facilitate early diagnosis. Here, we demonstrate a motility-based label-free computational imaging platform to rapidly detect motile parasites in optically dense bodily fluids by utilizing the locomotion of the parasites as a specific biomarker and endogenous contrast mechanism. Based on this principle, a cost-effective and mobile instrument, which rapidly screens ~3.2 mL of fluid sample in three dimensions, was built to automatically detect and count motile microorganisms using their holographic time-lapse speckle patterns. We demonstrate the capabilities of our platform by detecting trypanosomes, which are motile protozoan parasites, with various species that cause deadly diseases affecting millions of people worldwide. Using a holographic speckle analysis algorithm combined with deep learning-based classification, we demonstrate sensitive and label-free detection of trypanosomes within spiked whole blood and artificial cerebrospinal fluid (CSF) samples, achieving a limit of detection of ten trypanosomes per mL of whole blood (~five-fold better than the current state-of-the-art parasitological method) and three trypanosomes per mL of CSF. We further demonstrate that this platform can be applied to detect other motile parasites by imaging Trichomonas vaginalis, the causative agent of trichomoniasis, which affects 275 million people worldwide. With its cost-effective, portable design and rapid screening time, this unique platform has the potential to be applied for sensitive and timely diagnosis of neglected tropical diseases caused by motile parasites and other parasitic infections in resource-limited regions.
关键词： parasitic infections,holographic speckle analysis,trypanosomes,resource-limited settings,deep learning,Trichomonas vaginalis,label-free imaging,motility-based detection
更新于2025-09-04 15:30:14