Comparative analyses of site-directed mutagenesis of human melatonin MTNR1A and MTNR1B receptors using a yeast fluorescent biosensor.

Melatonin is an indoleamine neurohormone made by the pineal gland. Its receptors, MTNR1A and MTNR1B, are members of the G-protein-coupled receptor (GPCR) family and are involved in sleep, circadian rhythm, and mood disorders, and in the inhibition of cancer growth. These receptors, therefore, represent significant molecular targets for insomnia, circadian sleep disorders, and cancer. The yeast Saccharomyces cerevisiae is an attractive host for assaying agonistic activity for human GPCR. We previously constructed a GPCR-based biosensor employing a high-sensitivity yeast strain that incorporated both a chimeric yeast-human Gα protein and a bright fluorescent reporter gene (ZsGreen). Similar approaches have been used for simple and convenient measurements of various GPCR activities. In the current study, we constructed a fluorescence-based yeast biosensor for monitoring the signaling activation of human melatonin receptors. We used this system to analyze point mutations, including previously unreported mutations of the consensus sequences of MTNR1A and MTNR1B melatonin receptors and compared their effects. Most mutations in the consensus sequences significantly affected the signaling capacities of both receptors, but several mutations showed differences between these subtype receptors. Thus, this yeast biosensor holds promise for revealing the functions of melatonin receptors.

Visualization of murine lymph vessels using photoacoustic imaging with contrast agents.

Metastasis frequently occurs even in the early stage of breast cancer. This research studied the feasibility of using photoacoustic (PA) imaging for identifying metastasis in the lymph vessels of mice. The photoacoustic efficiency of various contrast agents was investigated, and the influence of scattered light was evaluated by using a lymph vessel phantom. The lymph vessels of mice were then visualized using the selected contrast agents: indocyanine green (ICG) and gold nanorods (AuNR). The attenuation of the PA imaging was -1.90 dB/mm, whereas that of the fluorescence imaging was -4.45 dB/mm. The results indicate the potential of identifying sentinel lymph nodes by using PA imaging with these contrast agents.

Development of Real-Time 3-D Photoacoustic Imaging System Employing Spherically Curved Array Transducer.

Photoacoustic (PA) imaging is a promising imaging modality to visualize specific living tissues based on the light absorption coefficients without dyeing. In this paper, a real-time PA imaging system with a tunable laser was newly developed with an originally designed spherically curved array transducer. Five different series of experiments were conducted to validate the PA measurement system. The peak frequency of the transducer response was 17.7 MHz, and a volume-imaging rate of 3-D volume imaging was 10-20 volumes per second. The spatial resolution of imaging was 90- [Formula: see text] along both the axial and lateral directions. The developed imaging system could measure a difference on an absorption coefficient of gold nanorods. Additionally, the PA imaging could visualize the in vivo microvasculatures of a human hand. This PA imaging system with higher spatial-temporal resolution and the tunable laser further should enhance our understanding of not only basic properties of the photo acoustics but also clinical applications.

3D Gabor wavelet based vessel filtering of photoacoustic images.

Filtering and segmentation of vasculature is an important issue in medical imaging. The visualization of vasculature is crucial for the early diagnosis and therapy in numerous medical applications. This paper investigates the use of Gabor wavelet to enhance the effect of vasculature while eliminating the noise due to size, sensitivity and aperture of the detector in 3D Optical Resolution Photoacoustic Microscopy (OR-PAM). A detailed multi-scale analysis of wavelet filtering and Hessian based method is analyzed for extracting vessels of different sizes since the blood vessels usually vary with in a range of radii. The proposed algorithm first enhances the vasculature in the image and then tubular structures are classified by eigenvalue decomposition of the local Hessian matrix at each voxel in the image. The algorithm is tested on non-invasive experiments, which shows appreciable results to enhance vasculature in photo-acoustic images.