Biomedical subjects

Jun Nakanishi

Publications and source records attributed to Jun Nakanishi.

5 recordsLinked to original sources

PubMed2006

FRET-based monitoring of conformational change of the beta2 adrenergic receptor in living cells.

The beta(2) adrenergic receptor (beta(2)AR) is a G protein-coupled receptor that is selective to epinephrine. We demonstrate herein monitoring of an agonist-induced conformational change of beta(2)AR in living cells. The monitoring method is based on fluorescence resonance energy transfer from a cyan fluorescent protein (CFP) to a biarsenical fluorophore, FlAsH, attached to the C-terminus, and the third intracellular loop (ICL3), respectively. Recombinant beta(2)ARs exhibited agonist-induced increases in the FlAsH/CFP emission ratio, indicating that the ICL3 approached the C-terminus upon activation. Since the emission ratio changes were on a time scale of seconds, the conformational change of beta(2)AR in living cells was more rapid than that of purified beta(2)AR measured in vitro. Interestingly, the direction of the emission ratio change of beta(2)AR was opposite to that of the norepinephrine-responsive alpha(2A) adrenergic receptor reported recently. It was suggested that this discrepancy corresponds directly to the diametric biological functions, i.e., the activation or inactivation of adenylyl cyclase.

Adrenergic beta-2 Receptor Agonists↗

PubMed2005

Composite adaptive control with locally weighted statistical learning.

This paper introduces a probably stable learning adaptive control framework with statistical learning. The proposed algorithm employs nonlinear function approximation with automatic growth of the learning network according to the nonlinearities and the working domain of the control system. The unknown function in the dynamical system is approximated by piecewise linear models using a nonparametric regression technique. Local models are allocated as necessary and their parameters are optimized on-line. Inspired by composite adaptive control methods, the proposed learning adaptive control algorithm uses both the tracking error and the estimation error to update the parameters. We first discuss statistical learning of nonlinear functions, and motivate our choice of the locally weighted learning framework. Second, we begin with a class of first order SISO systems for theoretical development of our learning adaptive control framework, and present a stability proof including a parameter projection method that is needed to avoid potential singularities during adaptation. Then, we generalize our adaptive controller to higher order SISO systems, and discuss further extension to MIMO problems. Finally, we evaluate our theoretical control framework in numerical simulations to illustrate the effectiveness of the proposed learning adaptive controller for rapid convergence and high accuracy of control.

Algorithms↗

PubMed2004

Photoactivation of a substrate for cell adhesion under standard fluorescence microscopes.

Cell-culturing substrates where cell adhesion can be switched on by external stimuli during cell cultivation are useful scaffolds for tissue engineering, cell-based drug screening, and fundamental cellular studies. Here, we show a new strategy for photoactivation of a substrate for cell adhesion under standard fluorescence microscopes. A glass substrate chemically modified with an alkylsiloxane having a photocleavable 2-nitrobenzyl group was coated with bovine serum albumin to prevent cell adhesion. Upon irradiation under a fluorescence microscope, the protein was replaced with fibronectin, which made the irradiated region cell-adhesive. Subsequent seeding of HEK293 or COS7 cells produced patterns corresponding to the irradiated patterns. We succeeded for the first time in positioning single cells in proximity to cultivating single cells. The present method provides a general strategy for positioning single cells of same or different types at any locations on the substrate and will be useful for studying cell-cell interactions.

Animals↗

PubMed2004

Feedback error learning and nonlinear adaptive control.

In this paper, we present our theoretical investigations of the technique of feedback error learning (FEL) from the viewpoint of adaptive control. We first discuss the relationship between FEL and nonlinear adaptive control with adaptive feedback linearization, and show that FEL can be interpreted as a form of nonlinear adaptive control. Second, we present a Lyapunov analysis suggesting that the condition of strictly positive realness (SPR) associated with the tracking error dynamics is a sufficient condition for asymptotic stability of the closed-loop dynamics. Specifically, for a class of second order SISO systems, we show that this condition reduces to K2D > K(P) where K(P) and K(D) are positive position and velocity feedback gains, respectively. Moreover, we provide a 'passivity'-based stability analysis which suggests that SPR of the tracking error dynamics is a necessary and sufficient condition for asymptotic hyperstability. Thus, the condition K2D > K(P) mentioned above is not only a sufficient but also necessary condition to guarantee asymptotic hyperstability of FEL, i.e. the tracking error is bounded and asymptotically converges to zero. As a further point, we explore the adaptive control and FEL framework for feedforward control formulations, and derive an additional sufficient condition for asymptotic stability in the sense of Lyapunov. Finally, we present numerical simulations to illustrate the stability properties of FEL obtained from our mathematical analysis.

Artificial Intelligence↗

PubMed2004

A new protein conformation indicator based on biarsenical fluorescein with an extended benzoic acid moiety.

We demonstrate herein a new protein conformation indicator based on biarsenical fluorescein with an extended benzoic acid moiety. The present indicator is reactive to a genetically introduced tetracysteine motif (Cys-Cys-Xaa-Xaa-Cys-Cys, where Xaa is a noncysteine amino acid) of proteins. Compared to the original biarsenical fluorescein (FlAsH) and the biarsenical Nile red analogue (BArNile), the present indicator exhibited larger fluorescence intensity changes in response to Ca(2+)-induced conformational rearrangements of calmodulin. A calculation of the highest occupied molecular orbital (HOMO) level of the benzoic acid moiety of the indicator molecule supports possible involvement of a photoinduced electron transfer (PET) process. These results indicate that the present indicator is useful for sensitive detection of protein conformational changes.

Benzoic Acid↗