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Hideaki Mori

Publications and source records attributed to Hideaki Mori.

21 records · Page 2Linked to original sources

Complexities in ETS-domain transcription factor function and regulation: lessons from the TCF (ternary complex factor) subfamily. The Colworth Medal Lecture.

The ETS-domain transcription factor family can be divided into a series of subfamilies. Elk-1 represents the founding member of the ternary complex factor (TCF) subfamily. By focusing on the TCF subfamily, we can demonstrate the complexities that exist in the function and regulation of ETS-domain transcription factors. This article focuses on Elk-1 in detail and summarizes the functions of other TCFs. The key themes covered include the domain structure of the TCFs, the mechanisms of complex formation with serum response factor, regulation of TCFs by mitogen-activated protein kinase cascades, and transcriptional regulatory properties of the TCFs. Finally, the emerging role of the TCFs in vivo is discussed. A picture is developing indicating that, while these proteins exhibit significant sequence and functional conservation, key differences in their structure and regulation are being identified which may relate to unique functions of these proteins in vivo.

Amino Acid Sequence↗

[Fundamental evaluation of segmented attenuation correction method for clinical FDG-PET studies: simulation of pulmonary mass lesions in phantom studies].

OBJECTIVE: Both the segmented attenuation correction (SAC) method and post-injection transmission scanning are useful and widespread in clinical whole-body FDG-PET studies. The SAC method usually accomplishes smoothing of the transmission data. This calculation segments a micro -map into three degrees (lung, soft tissue, and bone) of attenuation coefficient. This method is used to reduce transmission scan time without deteriorating the quality of PET images. However, the SAC method has a tendency to underestimate the attenuation coefficient, resulting lower detectability for lung field mass lesions. We therefore evaluated the quantitative accuracy of the SAC method using transmission scanning and emission scanning data in a phantom study. METHODS: A dedicated 3D PET scanner, the Siemens ECAT EXACT HR+, was used to scan images of two types of phantoms, a spherical phantom (Japan Radioisotope Association phantom) and a cylindrical phantom (20 cm in diameter). We evaluated differences between transmission images ( micro -map) of the SAC method and measured attenuation correction (MAC) method, these two kinds of attenuation-corrected emission data (emission + SAC method, emission + MAC method), and emission data only (without attenuation correction). RESULTS: In the micro -map, recovery coefficient (RC) values at 10 mm in diameter were 0.27 and 0.00 in the MAC and SAC methods, respectively, in the spherical hot area. For the emission data, the emission + SAC method and emission + MAC method showed almost the same RC values for all sizes of hot area diameter. The SAC method, however, resulted in 20% underestimation for all sizes of hot area diameter as compared with the MAC method. CONCLUSION: In pulmonary mass lesions, it is necessary to correct for the partial volume effect in quantitative PET measurement. However, from our data, the SAC method is not appropriate for partial volume effect correction.

Evaluation Studies as Topic↗

[Measurement of left ventricular chamber and myocardial volume in hypertrophic cardiomyopathy patients by ECG-gated myocardial perfusion SPECT: application of a newly developed edge-detection algorithm].

Quantitative gated SPECT (QGS) software has been reported to demonstrate inaccurate edge detection in the left ventricular chamber in hypertrophic cardiomyopathy patients. In this study we developed a method to calculate left ventricular volume (LVV) and left myocardial volume (LMV) from gated SPECT data using a newly developed edge-detection algorithm, and we compared it with the QGS method of calculating LVV and LMV in a phantom study. Our method gave more accurate measurements LVV and LMV whereas the QGS method underestimated LMV. Compared with QGS LVV and LMV, our method yielded better results in the phantom study.

Algorithms↗