Medaka has been developed as a model animal that can be used to apply both forward and reverse genetic approaches. Large-scale mutagenesis screening for developmental processes, full-length cDNA/Expressed sequence Tag(EST) sequencing and genome sequencing projects have made it possible to use medaka as an effective model for research studies using a forward genetic approach. Currently, it is possible to identify the causal genes in medaka mutants within one to two years. Moreover, the TILLING library and high-throughput screening of mutations by highresolution melting (HRM) facilitate the identification of mutations in a particular gene and can produce medaka with mutations in the particular gene of interest. In addition to this reverse genetics approach, genome editing with the use of engineered nucleases, such as TALEN and CRISPR/CAS9, can be applicable to medaka. Recently, knock-in expression with a GFP cassette at the de novo locus was reported in zebrafish, and this can also be applied to medaka. Therefore, most methods for forward and reverse genetic approaches are equivalent or easier with the medaka model than other animal models such as the mouse and rat.

Although constant environments (fixed temperature and day/night cycle) are the general condition for animal experiments, organisms in nature live in fluctuating environments. Thus, studies on phenotype/genotype interactions in fluctuating environments represent the future for the biological and biomedical sciences. In this context, numerous features of medaka, such as their adaptability to variable temperature (4 to 40 ℃), tolerance to high-salinity environments without acclimatization, ability to measure the light/dark cycle and adaptation to seasonal change, can provide important information for analyses of phenotype, genotype and environmental interaction. For these reasons, we believe that medaka, a model animal established in Japan, is a good candidate for experimental animal studies of phenotype and genotype interactions in changing environments.

Medaka (Oryzias latipes) is an old but new model animal in the life sciences. Recently, numerous mutants have been produced in which orthologs of human disease genes have been knocked out. These new human disease models require methods for examining the whole-body histology of the mutant medaka. We therefore serially sectioned the whole body of adult medaka to microscopically examine all of the tissues and organs at the cellular level, and to identify any abnormalities resulting from gene knockout. In order to promote discussion of the histological and pathological findings, virtual slides of the serial whole-body sections of the medaka were prepared and shared among the authors via the internet. We also developed a tracking system with which to digitize the movements of the medaka over a 24- hour period. The system can be used to accurately clarify the circadian rhythms of medaka. We consider that the whole body sectioning and the 24-hour tracking system will be useful for comprehensively examining disease-gene knockout in medaka, and that the methods described here may open a new field of research examining the global relationships between gene functioning and physiological significance.

Image processing is a crucial step in the quantitative interpretation of biomedical images acquired from the various biomedical modalities, such as mammography, X-ray computed tomography, magnetic resonance imaging and light and electron microscopy. One of the most important purposes of the image processing is to derive meaningful information for utilizing the shape analysis.The process of shape analysis consists of two main steps: (1) the extraction of image components of the target (e.g., area, boundary, network pattern and skeleton), (2) the description of the shape features (e.g., size, perimeter, circularity and compactness). In this study, a target region extraction approach based on a new type of mathematical morphology is introduced. Mathematical morphology is a nonlinear image processing method based on the set theory and is useful for the extraction of the image components from an image. It can be used as a fundamental tool to analyze the biomedical images. However, conventional morphological processing has a common drawback that a unique type of artifact might appear in the processed image, depending on a fixed scanning direction of the structuring element (SE). Since biomedical images consist of delicate shape features which have directional variations, the artifact is caused by the insufficient morphological processing with the limitation of the SE scanning direction.To overcome this problem, an extension of conventional morphological operation has been proposed. The algorithm of this new type morphological operation uses a single SE to a series of rotations of the original image. Since the algorithm enables isotropic processing, it causes a considerable reduction in this type of artifact. In this paper, the new algorithm of the image processing method is applied to extraction of nuclei regions in histological sections of Medaka testis image for quantification of the number and the size of nuclei.

Optogenetics is a new tool for neuroscience field using photoactive biomolecules and light, in which the biomolecules are driven by molecular biological technique and are activated by optimum wavelength. On the other hand, we developed another tool which uses infrared light to induce a target gene expression named IR-LEGO, infrared laser evoked gene operator. Almost all orgasms have a stress response to recover the damage by heat, so called heat shock response. The IR-LEGO method utilizes this system as a biological principle, while the method requires a microscope to heat single cells in vivo by focusing the IR beam. Recently, we applied the methods to clarify biological questions with many researchers in the fields of developmental biology, neuroscience and so on. In this review, I will introduce the principal of this method and applications for animals and plants. Furthermore, I will discuss notice in practical experiments, and describe weak points and merits about the method.

Since the Committee for Proprietary Medicinal Products (CPMP) of the European Union issued in 1997 a “points to consider” document for the assessment of the potential for QT interval prolongation by non-cardiovascular agents to predict drug-induced torsades de pointes (TdP), the QT liability has become the critical safety issue in the development of pharmaceuticals. As TdP is usually linked to delayed cardiac repolarization, international guideline (ICH S7B) has advocated the standard repolarization assays such as in vitro I_Kr (hERG current) and in vivo QT interval, or in vitro APD (as a follow up) as the best biomarkers for predicting the TdP risk. However, the recent increasing evidence suggests that the currently used above biomarkers and/or assays are not fully predictive for TdP, and also does not address potential arrhythmia (VT and/or VF) induced by other mechanisms including the selective disruption of hERG protein trafficking, the interaction with other ion channels, pumps, exchangers, or transporters, and dysfunction of exciting-contraction coupling and cellular damage. There is, therefore, an urgent need for other surrogate markers or assays that can predict a wide range of cardiac toxicity potential of drug candidates. A recent advance in technology for large-scale production of human stem cell derived cardiomyocytes (hiPS/hESCM) has encouraged us to develop the new platform over traditional cell and ex vivo animal models for cardiac safety assessment. Indeed, the combination with modified analytical techniques such as multi-electrode array, patch clamp, impedance, motion vector, or optical imaging and hiPS/hES-CM offer new comprehensive pre-clinical human models capable of predicting a wide range of cardiac liability and their mechanisms. The platforms will open novel opportunities for a reliable, cost- and time-effective, and translational research in human cardiac toxicity during early development phase.

We review here flow cytometric gating methods, which were newly established and named “HAS-Flow,” to analyze ATL (adult T-cell leukemia/lymphoma) cells. Using CD7 vs. CD3 or CADM1 plots of CD4-positive lymphocytes, HTLV1- infected ATL cells can be specifically separated from other normal T-cells. These plots are different among subtypes of ATL, and reflect the disease progression from HTLV-1 infection through indolent ATL to aggressive ATL. Moreover, the change of the plots after chemotherapy could distinguish chemo-sensitive cases and predict prognosis. We are now advancing their clinical applications. For example, recurrence of ATL and engraftment after HSCT (hematopoietic stem cell transplantation) can be monitored simultaneously by combining HAS-Flow with HLA-Flow, which can analyze mixed chimerism among various cell populations after HSCT.

Understanding proliferative status of samples from precancerous lesions can be difficult when proliferating cells are mixed among majority of normal cells. Here, we report a novel flow cytometry method to enable detection of proliferative cell populations. Using flow cytometry, we found a high correlation between microsphere diameter to the width of the forward scattered signal (FSC_W) and the fluorescent microsphere diameter to the width of the side fluorescent signal (RFL_W). In addition, the amount of fluorescent intensity of fluorochrome-stained DNA highly correlated to that of the calculated intensities of side fluorescent signals (RFL_A). Next, human buccal cells and human umbilical vein endothelial cells (HUVECs) were measured by flow cytometry to calculate the ratios of nuclear and cell diameters (N/C ratio) of individual cells using the FSC_W and RFL_W values, as these values correspond to the lengths of the cell and nucleus, respectively. By drawing scattergrams of cell lengths and N/C ratios using measurement values of buccal cells and HUVECs, respectively, these cells could be discriminated as low-N/C ratio group (buccal cells) and high-N/C ratio group (HUVECs). In addition, cell cycle analyses of HUVECs, which exhibited high-N/C ratio were performed to obtain the cell proliferation index (CPIx), an original index that represents the proliferative characteristics of cell populations. CPIx values of HUVECs well represented the proliferative conditions of each cell culture. Finally, when low-proliferative HUVECs and high-proliferative Hela cells were mixed and measured in this system, CPIx values of mixed samples were well correlated with the proportion of Hela cells, suggesting that CPIx quantitatively represents proliferative status of samples. Therefore, this method is expected to substantially contribute to improvements in cancer testing such as cervical cancer screening.