Biomedical subjects

Jun-ichi Inoue

Publications and source records attributed to Jun-ichi Inoue.

3 recordsLinked to original sources

PubMed2002

Novel point mutation in the cardiac transcription factor CSX/NKX2.5 associated with congenital heart disease.

The homeobox transcription factor CSX/NKX2.5, which is a vertebrate homologue of the Drosophila gene tinman, is essential for cardiac development. It is expressed in the early cardiac mesoderm and in heart muscle lineage throughout life. Homozygous deletion of CSX/NKX2.5 causes early embryonic lethality in mice because cardiac development is arrested at the linear heart tube stage. Heterozygous mutation of human CSX/NKX2.5 has been associated with various congenital heart diseases such as atrial septal defect (ASD), ventricular septal defect, tetralogy of Fallot, and tricuspid valve abnormalities, including Ebstein's anomaly. Additionally, CSX/NKX2.5 mutation causes atrioventricular (AV) conduction block with or without associated congenital heart diseases. Ten different heterozygous mutations have been already reported and a new point mutation, which is a C-to-A transition (Cys264ter) at nucleotide 901 of CSX/NKX2.5, results in the production of a truncated protein occurring COOH-terminal to the homeodomain of CSX/NKX2.5. The mutation was found in a patient with familial ASD and first-degree AV block; 4 members from 3 generations had secundum-type ASD and first-degree AV block.

Cysteine↗

PubMed2001

Dynamics of the maximum marginal likelihood hyperparameter estimation in image restoration: gradient descent versus expectation and maximization algorithm.

Dynamical properties of image restoration and hyperparameter estimation are investigated by means of statistical mechanics. We introduce an exactly solvable model for image restoration and derive differential equations with respect to macroscopic quantities. From these equations, we evaluate relaxation processes of the system to the equilibrium state. Our statistical mechanical approach also enables us to investigate the hyperparameter estimation by means of maximization of the marginal likelihood by using gradient descent and the expectation and maximization algorithm from the dynamical point of view.

Journal Article↗

PubMed2001

Multistate image restoration by transmission of bit-decomposed data.

We report on the restoration of gray-scale image when it is decomposed into a binary form before transmission. We assume that a gray-scale image expressed by a set of Q-Ising spins is first decomposed into an expression using Ising (binary) spins by means of the threshold division, namely, we produce (Q-1) binary Ising spins from a Q-Ising spin by the function F(sigma(i)-m)=1 if the input data sigma(i)in[0,...,Q-1] is sigma(i)> or =m and 0 otherwise, where m in [1,...,Q-1] is the threshold value. The effects of noise are different from the case where the raw Q-Ising values are sent. We investigate whether it is more effective to use the binary data for transmission, or to send the raw Q-Ising values. By using the mean-field model, we analyze the performance of our method quantitatively. In order to investigate what kind of original picture is efficiently restored by our method, the standard image in two dimensions is simulated by the mean-field annealing, and we compare the performance of our method with that using the Q-Ising form. We show that our method is more efficient than the one using the Q-Ising form when the original picture has large parts in which the nearest-neighboring pixels take close values.

Journal Article↗