Using complementary optical microscopy techniques provides more detailed insight into biological samples. However, misinterpretation can occur by temporal discrepancies due to differences in temporal resolution and switching imaging modalities. Here, we demonstrated multimodal imaging of cryofixed cells using Raman and fluorescence structured illumination microscopy (SIM). Cryofixation preserves structures and chemical states of samples in their near-native states, allowing multimodal imaging without artifacts caused by temporal discrepancy. We demonstrated multimodal imaging of cryofixed HeLa cells stained with an actin probe, where Raman microscope visualized cytochromes, proteins and lipids, and SIM visualized fluorescence-labelled actin filaments.
We developed a fast Raman spectroscopic discrimination system based on a slit-scanning confocal microscope and machine learning. The speed of discrimination was improved by reducing the number of measurements, without measuring all points in the field of view. During discrimination, the system continues to evaluate the spectra already obtained, which guarantees the accuracy of the discrimination and enables early detection of anomalies by optimizing the measurement positions. We performed discrimination using a mixture of polystyrene (PS) and polymethyl methacrylate (PMMA) microbeads as a sample to mimic cancer tissue and that of fatty liver tissue using mouse liver tissue samples. The results showed that the discrimination was about 2-11 times faster than that by slit scanning confocal microscopy.
Spontaneous Raman flow cytometers and cell sorters typically have cell or particle throughputs less than 5 event/s due to long signal integration times. Here we report an up to 10x increase in throughput by coupling constant illumination along the flow path with time delay integration, a technique that counteracts sample motion by matching it to the charge transfer velocity of a CCD device. This allows longer signal integration times while also multiplexing acquisition along the flow path. We demonstrate high spectral bandwidth (600 – 3200 cm-1) Raman acquisitions from flowing particles and mammalian cells at throughputs up to 50 events/s.
We investigated the photophysical property of Yellow Cameleon 3.60 (YC3.60), a fluorescent calcium-ion (Ca2+) indicator based on Förster resonance energy transfer (FRET), under cryogenic conditions. By measuring the fluorescence intensity ratio of the donor and accepter at various Ca2+ concentrations under room and cryogenic temperatures, we confirmed that YC3.60 exhibits a Ca2+-dependent FRET efficiency. Although slight differences were observed in the fluorescence lifetime and spectral shape at the cryogenic temperature, which can affect the FRET efficiency, our measurement suggested that YC3.60 can be employed for quantitative Ca2+ measurement and imaging under cryogenic conditions with improved photostability and quantum yield.
KEYWORDS: Raman spectroscopy, Light sources and illumination, Machine learning, Medical research, Random forests, Microscopy, Microscopes, Engineering, Diagnostics, Decision trees
We propose a method that combines high-speed Raman imaging with a machine learning technique, multi-armed bandit, to achieve rapid and accurate identification of samples under observation. First, our method dvides the field of view of the sample into small sections, and it returns either ’positive’ or ’negative’ based on whether the sections with high anomaly indices exceed a certain proportion. Moreover, the points to be measured are determined dynamically and automatically generating a series of optimal illumination patterns.
Saturated-excitation (SAX) microscopy can provide theoretically unlimited improvement of spatial resolution in laser scanning microscopy. However, in practice, the signal-to-noise ratio (SNR) limits its capability. In this research, we introduced image scanning microscopy (ISM) into SAX microscopy to improve the SNR.
We developed spontaneous Raman microscopy using Bandit algorithm to realize fast diagnosis of the existence of anomalies or not with guaranteeing accuracy. The algorithm evaluates obtained Raman spectra during measurement to judge if the diagnosis is completed with ensuring an allowance error rate that users decided and also to generate optimal illumination patterns for the next irradiation which are optimized to accelerate the detection of anomaly. We present our simulation and experimental studies to show that our system can accelerate more than a few tens times faster than line-scanning Raman microscopy which requires full scanning over all pixels.
We present our recent study combined multi-armed Bandits algorithm in reinforcement learning with spontaneous Raman microscope for the acceleration of the measurements by designing and generating optimal illumination pattern “on the fly” during the measurements while keeping the accuracy of diagnosis. We present our simulation and experimental studies using Raman images in the diagnosis of follicular thyroid carcinoma and non-alcoholic fatty liver disease, and show that this protocol can accelerate more than a few tens times in speedy and accurate diagnoses faster than line-scanning Raman microscope that requires the full detailed scanning over all pixels.
The on-the-fly Raman image microscopy designs to accelerate measurements by combining one of reinforcement machine learning techniques, bandit algorithm utilized in the Monte Carlo tree search in alpha-GO, and a programmable illumination system. Given a descriptor based on Raman signals to quantify the likelihood of the predefined quantity to be evaluated, e.g., the degree of cancers, the on-the-fly Raman image microscopy evaluates the upper and lower confidence bounds in addition to the sample average of that quantity based on finite point/line illuminations, and then the bandit algorithm feedbacks the desired illumination pattern to accelerate the detection of the anomaly, during the measurement to the microscope.
Most conventional bandit algorithms assume that infinite number of measurements or samples provides us with 100% accuracy. However, in Raman measurements we should develop both a Raman descriptor to quantify the degree of anomaly, and a new algorithm to take into account the finite accuracy lower than 100%. This microscope can also be applied to other problems, besides detection of cancer cells, such as anomaly or defects of materials. The algorithm itself is also beneficial and transferrable to the other microscopes such as infrared image microscope.
We propose the use of visible-wavelength two-photon excitation (v2PE) for activation of reversibly photo-switchable fluorescent proteins (RSFPs) and successive confocal detection to achieve super-resolution imaging. In this method, three photons interact with the sample molecules in total, which provides imaging properties equivalent to using third-order nonlinearity in fluorescence response. Because this technique uses visible light, it can achieve higher spatial resolution than confocal microscopy. In this study, we performed experimental investigations to confirm the activation of negative RSFPs by v2PE and demonstrated super-resolution imaging of live cells.
Saturated-excitation (SAX) improves the spatial resolution of laser scanning microscopy in three dimensions by inducing nonlinear fluorescence signals that localize within a focus spot. However, the spatial resolution of SAX microscopy is practically limited by the signal-to-noise ratio (SNR). In this research, we introduce image scanning microscopy (ISM) to improve the SNR of SAX microscopy. The improvement of the SNR by ISM enables the detection of weak nonlinear signal components and contributes to the improvement of the spatial resolution of SAX microscopy in practice.
Visible-wavelength two-photon excitation (v2PE) is a powerful technique for simultaneous multicolor fluorescence imaging via simultaneous excitation of fluorescent proteins (FPs) with different emission wavelengths. We implemented v2PE into a slit-scanning confocal microscope in order to realize faster simultaneous multicolor fluorescence imaging with utilizing the capability of spectral detection. We demonstrated simultaneous multicolor imaging of living HeLa cells with expressing three types of FPs with different emission wavelengths localized at different intracellular structures. Linear un-mixing of hyperspectral images successfully separated the distribution of multiple FPs expressed in the sample.
Specimen induced aberrations can have detrimental effects in all types of high-resolution microscope. In this study, we present a sensorless technique that uses a deformable mirror (DM) to correct aberrations of both the system and sample. Using a laser-free confocal microscope, with patterned disk illumination and detection. The system is based on a commercial confocal module (Clarity, Aurox Ltd., UK) that uses Light Emitting Diode (LED) illumination to obtain optically sectioned 3D images. The results obtained show that the setup was able to correct aberrations of biological samples used in the study. These systems will help researchers working on various biological systems to obtain improved quality images when focussing deep into thick specimens.
KEYWORDS: Microscopy, Luminescence, Spatial resolution, 3D image processing, Confocal microscopy, Two photon excitation microscopy, Stereoscopy, Point spread functions, Objectives, Time lapse microscopy
Two-photon excitation microscopy is one of the key techniques used to observe three-dimensional (3-D) structures in biological samples. We utilized a visible-wavelength laser beam for two-photon excitation in a multifocus confocal scanning system to improve the spatial resolution and image contrast in 3-D live-cell imaging. Experimental and numerical analyses revealed that the axial resolution has improved for a wide range of pinhole sizes used for confocal detection. We observed the 3-D movements of the Golgi bodies in living HeLa cells with an imaging speed of 2 s per volume. We also confirmed that the time-lapse observation up to 8 min did not cause significant cell damage in two-photon excitation experiments using wavelengths in the visible light range. These results demonstrate that multifocus, two-photon excitation microscopy with the use of a visible wavelength can constitute a simple technique for 3-D visualization of living cells with high spatial resolution and image contrast.
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