Qualifications of intracellular structure were performed for the first time using the gray-level co-occurrence matrix (GLCM) method for images of cells obtained by resolution-enhanced photothermal imaging. The GLCM method has been used to extract five parameters of texture features for five different types of cells in mouse brain; pyramidal neurons and glial cells in the basal nucleus (BGl), dentate gyrus granule cells, cerebellar Purkinje cells, and cerebellar granule cells. The parameters are correlation, contrast, angular second moment (ASM), inverse difference moment (IDM), and entropy for the images of cells of interest in a mouse brain. The parameters vary depending on the pixel distance taken in the analysis method. Based on the obtained results, we identified that the most suitable GLCM parameter is IDM for pyramidal neurons and BGI, granule cells in the dentate gyrus, Purkinje cells and granule cells in the cerebellum. It was also found that the ASM is the most appropriate for neurons in the basal nucleus.
Simultaneous two-color subtraction microscopy using mode multiplexing is realized experimentally. The samples are irradiated with single laser diode at wavelength of 445 nm. Then the beam split laser spots generate separate solid and donut spatial modes and are multiplexed with modulators for simultaneous excitation. The produced fluorescence signals are back collected and further divided into two color bands with dichroic mirrors. Then they are detected with two photomultipliers and demultiplexed in four lock-in amplifiers. Four fluorescence images are recorded in every scan and resolution enhanced images are obtained in two color channels after applying the subtraction strategy. With this method, imaging results of microspheres stained with organic dyes and mesenteric lymph nodes of a mouse labeled with quantum dots (Q525/650) are realized. Improvement of 20% ~ 30% in resolving power of the two color channels compared with confocal microscopy is achieved in with corresponding subtraction factor of about 0.3.
Multi-color fluorescence imaging of tissue samples has been an urgent requirement in current biology. As far as fluorescence signals should be isolated by optical bandpass filter-sets, rareness of the combination of chromophores with little spectral overlap has hampered to satisfy this demand. Additivity of signals in a fluorescence image accepts applying linear unmixing of superposed spectra based on singular value decomposition, hence complete separation of the fluorescence signals fairly overlapping each other. We have developed 7-color fluorescence imaging based on this principle and applied the method to the investigation of mouse spleen. Not only rough structural features in a spleen such as red pulp, marginal zone, and white pulp, but also fine structures of them, periarteriolar lymphocyte sheath (PALS), follicle, and germinal center were clearly pictured simultaneously. The distributions of subsets of dendritic cells (DC) and macrophages (M(phi) ) markers such as BM8, F4/80, MOMA2 and Mac3 around the marginal zone were imagined simultaneously. Their inhomogeneous expressions were clearly demonstrated. These results show the usefulness of the method in the study of the structure that consists of many kinds of cells and in the identification of cells characterized by multiple markers.
The object of the experiment described in this paper was to demonstrate that cells stained with multiple fluorophores could be identified and quantified simultaneously. Hyperspectral imaging was used to classify spleen cells of a Balb/c mouse, with the anti-mouse CD4 antibody conjugated with Alexa 488, 532, 546 and 568. It was found that the system was able to identify the specific fluorophore present and map their location in the cells. The system also provided relative signal strength data. Spectral libraries were constructed with color-coded spectra that enabled automatic spectral identification in subsequent acquisitions.