Satoru Shiono

Control mechanism of JAK/STAT signal transduction pathway.

Suppressor of cytokine signaling‐1 (SOCS1) was identified as the negative regulator of Janus kinase (JAK) and signal transducer and activator of transcription (STAT) signal transduction pathway. However, the kinetics and control mechanism of the pathway have not yet been fully understood. We have developed the computer simulation of the JAK/STAT pathway. Without nuclear phosphatase, SOCS1s binding to JAK did not cause the decrease in nuclear phosphorylated STAT1. However, without SH2 domain‐containing tyrosine phosphatase 2 (SHP‐2) or cytoplasmic phosphatase, it did. So nuclear phosphatase is considered to be the most important in this system. By changing parameters of the model, dynamical characteristics and control mechanism were investigated.

448-Detector optical recording system: development and application to Aplysia gill-withdrawal reflex

The spatial resolution of a fast, multichannel, optical recording apparatus has been improved in an attempt to increase the completeness of optical recordings of neuron activity responsible for the Aplysia gill-withdrawal reflex. A new optical apparatus was developed, increasing the number of pixels to 448. Action potential activity from 168 to 192 neurons could be detected. Hence, the number of optically detected neurons increased about 2.5 times in comparison with a previously used 100- or 124-detector optical apparatus. Because optically detected action potential signals were shown to be due to the cell body of a neuron, it was possible to know its position as well as its approximate size. The distribution of the detected active neurons and those neurons that showed an apparent change in spike frequency to the siphon stimulation were determined.<<ETX>>

Glucose sensor based on a field-effect transistor with a photolithographically patterned glucose oxidase membrane

Abstract A photopolymer solution consisting of polyvinylpyrrolidone and 2,5-bis(4′-azido-2′-sulfobenzal)cyclopentanone is used to make a patterned glucose oxidase membrane for a FET-glucose sensor by photolithography. A small patterned glucose oxidase membrane, 0.2 mm wide and 1 mm long, is made on the gate surface of an ISFET by developing a photocross-linked glucose oxidase membrane with aqueous 1–3% glutaraldehyde solution. The optimum composition of the enzyme/photopolymer solution is described. The sensor with the patterned membrane showed linear response to glucose concentration from 0.3 to 2.2 mM and useful response up to 5 mM.

Electrophoresis of DNA in micro-pillars fabricated in polydimethylsiloxane

We describe the fabrication of a device containing micro-pillars and separation of DNA. It was made of polydimethylsiloxane (PDMS) and made by a replica molding method using a patterned silicon wafer as a mold. The device has a micro-channel in which 15 µm pillars are arranged in a hexagonal lattice with 1 µm spacing. Electrophoresis of DNA in the pillars showed the average speed of DNA migration was dependent on its lengths. The PDMS device not only demonstrates the possibility of rapid DNA separation, but also has an advantage in mass production cost by using the replication method.

Glucose-sensitive field-effect transistor with a membrane containing co-immobilized gluconolactonase and glucose oxidase

Abstract A glucose-sensitive field-effect transistor (FET) with a two-enzyme membrane containing gluconolactonase and glucose oxidase is investigated. The two-enzyme membrane (ca. 1 μm thick) is formed on the ion-sensitive gate of the FET by photopolymerization. The gluconolactonase used was a partially purified product prepared from crude glucose oxidase by gel filtration. A glucose sensor with only purified glucose oxidase has little response for glucose, but the co-immobilization of gluconolactonase and glucose oxidase considerably enhanced the response amplitude of the glucose sensor. The composition of the two-enzyme/photopolymer solution is optimized; gluconolactonase with an activity at least twice that of glucose oxidase is necessary. The linear calibration graph extends from 0.2 to 2 mM glucose.

Information theoretic analysis of action potential trains

A crosscorrelational method of action potential trains has been proposed, based on information theory. Two information theoretic quantities, mutual information and channel capacity, were calculated from a pair of action potential trains for detecting a crosscorrelation and estimating synaptic connectivity. The method was compared with conventional ones, using action potential trains obtained by the simulation of a neuron model. This method was shown to have the advantages to more easily find a weak but significant crosscorrelation and to give better estimation of synaptic connectivity independent of the firing probability of a presynaptic neuron.

Information theoretic analysis of action potential trains. II. Analysis of correlation among n neurons to deduce connection structure

We propose a cross-correlational method based on information theory, which produces a network connection structure to account for observed patterns of action potential activity in multi-unit recordings. Firing probabilities and conditional probabilities are estimated from the action potential trains of n neurons. Two-point mutual information (2pMI) and joint conditional mutual information (JCMI) are calculated by using the estimated probabilities, and then the n-point mutual information (npMI) is calculated. A significant peak of npMI indicates that each neuron is connected to all other neurons at specified time differences, either directly or indirectly. To distinguish between direct and indirect connection, the two-point m-joint conditional mutual information (2pJCMI) is calculated over the peak region for each pair of neurons. A minimum effective connection structure among the n neurons can be deduced in this manner. The procedure for deducing the connection structure for three- and n-neuron networks is described. We apply this method to action potential trains produced by simulated neural networks. Some limitations of the method are also discussed.

Data Processing for Multi-Channel Optical Recording : Action Potential Detection by Neural Network

Using a neural network, we have developed a program for fast and precise detection of action potentials (AP) in raw multi-channel optical recording data. The AP detection was performed in two steps: first, peaks were detected in raw optical data, and, second, the peaks were classified by the neural network into APs, noise and undecided peaks. The network was optimized and trained by the backpropagation learning algorithm, employing some thousands of manually classified peaks. The performance of the optimized network was found to be not completely satisfactory, although it was better than the classification by template matching and nearest-neighbor rules. The addition of a signal-to-noise ratio (SNR) of a peak to the network classification improved the classification performance: in comparison with the manual classification results, 96% of manually classified APs were detected. The causes of classification errors were discussed. In spite of the fact that the program required a slight amount of human intervention for undecided peaks, the program could allow mostly automatic AP detection.

Separation and characterization of by-product oligomers in epoxy resins by reversed-phase high-performance liquid chromatography

Abstract Three series of monoepoxide by-product oligomers in diglycidyl ethers of bisphenol A type epoxy resins were separated by reversed-phase gradient elution high-performance liquid chromatography. The by-product oligomers studied have a functional group other than a 2,3-epoxypropyloxy group as an endgroup: they have a 2,3-dihydroxypropyloxy, a 2-hydroxy-3-methoxypropyloxy or a 2-hydroxy-3- p-tert. -butylphenoxypropyloxy endgroup. Three oligomers of each series of by-products were isolated and characterized by infrared, mass and carbon-13 nuclear magnetic resonance spectrometry.

A flow-through cell for use with an enzyme-modified field effect transistor without polymeric encapsulation and wire bonding

Abstract A new type of flow-through cell for an enzyme-modified field effect transistor (FET) is described. The cell makes it possible to use a FET without polymeric encapsulation and wire bonding. Electrical evaluation of a FET used with the flow cell demonstrates that the flow cell has no practical problems causing sensor malfunctions. The noise and drift levels of tbe FET sensor with the flow cell are shown to be similar to those of an epoxy-encapsulated FET sensor. The application of the flow cell with a urease-modified FET is described. Useful responses are obtained for 0.25–50 mg l−1 urea with relative standard deviations of