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To clarify the detailed molecular mechanisms underlying the development of asthma, we assessed the potential immune effects of prenatal osteoprotegerin (OPG) inhibition in the pathogenesis of asthma. The effects of OPG deficiency on the development of asthma were evaluated using an ovalbumin-induced asthma model in OPG knockout mice. Histological analysis demonstrated that OPG was mainly detected in airway epithelial cells in wild type mice. After ovalbumin sensitization and challenge, accumulation of inflammatory cells, gene expression of T helper 2-related cytokines and mucus hypersecretion in lung tissues were inhibited by OPG deficiency. Importantly, the serum level of IgE was not increased in OPG KO mice after ovalbumin sensitization and challenge. Based on these findings, OPG knockout mice were protected against methacholine-induced airway hyperresponsiveness. OPG expression is thought to be essential for induction of the allergic immune response in asthma.

Abdominal aortic aneurysm (AAA) is considered to be a potent life-threatening disorder in elderly individuals. Although many patients with a small AAA are detected during routine abdominal screening, there is no effective therapeutic option to prevent the progression or regression of AAA in the clinical setting. Recent advances in molecular biology have led to the identification of several important molecules, including microRNA and transcription factor, in the process of AAA formation. Regulation of these factors using nucleic acid drugs is expected to be a novel therapeutic option for AAA. Nucleic acid drugs can bind to target factors, mRNA, microRNA, and transcription factors in a sequence-specific fashion, resulting in a loss of function of the target molecule at the transcriptional or posttranscriptional level. Of note, inhibition of a transcription factor using a decoy strategy effectively suppresses experimental AAA formation, by regulating the expression of several genes associated with the disease progression. This review focuses on recent advances in molecular therapy of using nucleic acid drugs to treat AAA.

Transactivation of inflammatory and immune mediators in asthma is tightly regulated by nuclear factor κB (NF-κB) and signal transducer and activator of transcription 6 (STAT6). Therefore, we investigated the efficacy of simultaneous inhibition of NF-κB and STAT6 using a chimeric decoy strategy to prevent asthma exacerbation. The effects of decoy oligodeoxynucleotides were evaluated using an ovalbumin-induced mouse asthma model. Ovalbumin-sensitized mice received intratracheal administration of decoy oligodeoxynucleotides 3 days before ovalbumin challenge. Fluorescent-dye-labeled decoy oligodeoxynucleotides could be detected in lymphocytes and macrophages in the lung, and activation of NF-κB and STAT6 was inhibited by chimeric decoy oligodeoxynucleotide transfer. Consequently, treatment with chimeric or NF-κB decoy oligodeoxynucleotides protected against methacholine-induced airway hyperresponsiveness, whereas the effect of chimeric decoy oligodeoxynucleotides was significantly greater than that of NF-κB decoy oligodeoxynucleotides. Treatment with chimeric decoy oligodeoxynucleotides suppressed airway inflammation through inhibition of overexpression of interleukin-4 (IL-4), IL-5, and IL-13 and inflammatory infiltrates. Histamine levels in the lung were reduced via suppression of mast cell accumulation. A significant reduction in mucin secretion was observed due to suppression of MUC5AC gene expression. Interestingly, the inhibitory effects on IL-5, IL-13, and histamine secretion were achieved by transfer of chimeric decoy oligodeoxynucleotides only. This novel therapeutic approach could be useful to treat patients with various types of asthma., Graphical Abstract

Angiotensin II is thought to participate in aneurysm formation, because of its ability to induce and perpetuate inflammation in the aortic wall. Because activation of renin is the first step of the renin–angiotensin system, renin inhibition could inhibit all components of this system effectively. Therefore, we examined the hypothesis that direct inhibition of renin activity could decrease the expansion of aortic aneurysm using a rabbit model. Aortic dilatation was induced by incubation with elastase around the rabbit abdominal aorta. Continuous administration of a direct renin inhibitor, aliskiren, was started at 1 week before incubation with elastase and continued for 5 weeks. Treatment with aliskiren markedly inhibited tissue renin activation and resulted in a significant reduction in angiotensin I and II production in the aneurysm wall. Consequently, the inhibition of renin activity prevented the expansion of experimental aortic aneurysm associated with preservation of the medial layer, independent of its blood pressure–lowering effect. Administration of aliskiren led to the inhibition of activation of NF-κB (nuclear factor-κB), AP-1 (activator protein-1), and CREB (cAMP response element–binding protein), which are thought to cooperatively regulate the inflammatory gene expression profile associated with aneurysm formation. As a result, treatment with aliskiren inhibited macrophage accumulation through suppression of MCP-1 (monocyte chemoattractant protein-1) and CCL4 (C-C motif chemokine ligand 4) expression, and TNF-α (tumor necrosis factor-α) production and activation of MMP-2 (matrix metalloproteinase-2) and MMP-9 (matrix metalloproteinase-9) were also suppressed in the aneurysm wall. In addition, inhibition of (pro)renin receptor elevation was also observed after treatment with aliskiren. Direct inhibition of renin activity using aliskiren prevented the progression of aortic aneurysm, suggesting it as a therapeutic option to treat abdominal aortic aneurysm.

Bridge inspection usually is done visually on the spot. For this reason, inspection is very difficult in the case where humans can not enter, and it has become a problem. Therefore, in order to overcome this problem, we propose a new method in which pictures are taken by Drone and cracks are detected by image processing using a wavelet transform. Since bridge crack include many directional components, the characteristics of directional selection is useful for feature extraction. In this study, a 2-Dimensional Complex Discrete Wavelet Packet Transform with excellent directional selection is applied to bridge floor crack detection, and encouraging results are obtained.

The main drawback of abnormality diagnosis using the wavelet transform (WT) is that it needs much time. In order to improve this problem, a new real signal mother wavelet (RMW) that is made from all objective frequency components has been suggested. Thus the RMW can be greatly shorten the WT calculation time, and this WT is named the Wavelet Instantaneous Correlation (WIC). However, in order to construct the conventional RMW, it is essential to gather the target sounds, namely “sound samples” beforehand. In general, these are gathered by professionals using sensors. Furthermore it is possible that the abnormality diagnosis accuracy may decrease, because of a frequency component difference between the actual sound and the “sound sample”. In this study, therefore, we propose an improved method in which the expected characteristic frequency is extracted from actual sounds automatically, without requiring the “sound sample” to be obtained by professionals.

In our vehicle driving, it is important to take appropriate evasive action based on the recognition of the hazardous events as one of driver's ability. There is a concept of "Risk perception" that makes effect to both driver's ability sides of the behavioral and acceptance with their controllability. In the previous study, the relation of Risk perception with the number of traffic accidents have been shown, however, the quantification of the Risk perception have not been performed in addition to driving knowledge and behavior. In this study, driving knowledge and driving behavior are quantified, and an analysis method for it is constructed. In order to obtain the knowledge and ability, the experiments with subject driver were designed and conducted. By using obtained data, validation for proposed analysis method was also carried out. As a result of correlated with driving tendency, classification possibility of hazard sensitivity based on the individual characteristics had been confirmed.

This paper discusses the problem of human motion analysis from inertial sensor (accelerometer and gyroscope) data, which is the time sequence data obtained from human motion. The inertial sensors are widely used in the wearable sensing field for understanding human activities. Human motion can be divided into simple movements, such as swinging the arms or legs. These simple movements are fundamentally periodic, and they can be modeled with dynamical systems having periodic attractors. On the other hand, more complex motion like walking can be represented as a sequence of simple movements. To address the problem of analyzing human motion data, we propose a new framework based on a dynamical system. The human motions observed by the inertial sensors are divided into simple movements, and they can be often described as periodical signals. The periodical signals are described by a dynamical system, which can store the periodical or transitional trajectory in a state space by using basin of attraction. The attractors abstract a kind of proto-symbol. The dynamical system having periodical attractors is shown to characterize human motion effectively by exploiting spatiotemporal continuity, because it describes the flow of its transitions into the state space. Moreover, in the designed symbol space from the attractors, the information of human motion dynamics is described in the placement of the points. Thus, each point or transition between points in the symbol space corresponds to a specific type of motion; it can act as a notation method of motion characteristics.

It is well Known that the conventional method to detect presence and strength of the knocking by the ion current using the band pass filter is effective up to now. However, as compression ratio increases, there is a stationary wave in the ion current waveform and its frequency components and amplitude of the waveform are almost same as that of the knocking. Therefore the distinction of knocking and the standing wave becomes difficult by the conventional detection method. In this study, a new knocking detection technique which based on the difference of time-frequency properties of knocking and the standing wave was proposed. It first constitutes two band-pass complex real-signal mother wavelets (BC-RMW), and then thereby takes out the knocking ingredient and detects a change share of the wavelet coefficient of the knocking by using them. Furthermore, the proposed method was applied to the distinction of knocking and the standing wave and its effectiveness was inspected.

In production line, pose estimation of 3D object of products is needed beforehand. In order to perform shape measurement of the objects corresponding to speed of the mass production lines before the contact measurement is done, the information of object pose and matching is become required. In this paper, we conducted a study on the performance of model based and view based pose estimation method using image sequence of a rotating 3D object. In model based, we used object feature points from center of gravity and in view based method, the subspace calculation by block diagonalization of matrix represents a transformation an image to another image. We have confirmed the both method performance and it’s considered useful for pose estimation.

In this study, a novel direction selection method using the two-dimensional complex discrete wavelet transform (2D-CDWT) is proposed. In order to achieve arbitrary direction selection, the directional filters are first designed. Calculation procedure of directional selection can be shown as follows: (1) The 16 sub-images are generally generated from the original image by the 2D-CDWT without a down-sampling process and the 12 sub-images that correspond to the high-frequency components are selected. (2) The 12 sub-images are filtered by using the designed directional filter. (3) The down-sampling process is carried out and the resulting images are obtained. Furthermore, this method is applied to the surface analysis of a wafer, and it is confirmed that our method is effective in detecting irregular direction components.

Independent component analysis (ICA) is a useful method for blind source separation of two or more signals. We have previously proposed a new method combining ICA with the complex discrete wavelet transform (CDWT), in which voice and noise signals were separated using a new method. At that time, we used a simulated signal. In this study, we analyze measured biological signals by using a new method, and discuss its effectiveness. As an experiment, we try to separate an electromyogram (EMG) signal from an electrocardiogram (ECG) signal.

The pose estimation of 3D object of products in production line is needed beforehand. In order to perform shape measurement of objects corresponding to speed of the mass production lines before the contact measurement is done, the information of shape representation and matching of object is required. Objects are compared with its descriptor. The descriptor conceptually subtracted from each other to form a scalar metric. If the value difference is smaller, the object shape is considered closer to each other. The rotation object from its original pose can produce the information to estimate its rotation pose by using the boundary. In this paper, we proposed the method to measure 3D object pose from the designing stage of 3D CAD data.

We restore a blurred image caused by defocus of a lens using the shift-invariant wavelet transform created using RI-Spline wavelets.In a defocus blurred image,the blurring kernel varies depending on its position in the image,so a positional frequency representation,such as a wavelet space,is required in order to deblur it.To restore the defocus blur,we assume that the blurring kernel can be obtained regardless of its position in an image.In experiments we conducted using synthesized images,our method using the shift-invariant wavelet transform showed better deblurring performance than that of the ordinary wavelet transform.We also show that our method can be applied to real images if additional range data is used.

In this study, in order to improve effectiveness of the abnormal signal detection, the technique of constituting an Average Real signal Mother Wavelet (A-RMW) from two or more real signals has been proposed and its effectiveness has been confirmed. The main results obtained can be summarized as follows : (1) For constructing A-RMW by two or more signals, the Symmetric Complex Real signal Mother Wavelet (SCRMW) first was constructed respectively and then the average SCRMW was obtained by adding them. Finally the average SCRMW obtained above was normalized and the A-RMW was obtained. (2) The proposed constructing method of the SCRMW is different from the traditional Complex Real signal Mother Wavelet that the phase information of all the frequency components has been cut off and symmetric property can be obtained. (3) The proposal method is applied to the rattle noise source detection of a car, and its effectiveness is examined.

Water leaks cause the ground to cave in by the outflow of the soil, shutting down infrastructure. So investigation of water leaks is an important issue. However it is difficult to detect all leak points, because it depends on the engineer's skill, and the pipe's natural frequency is varies with its diameter, material and amount of flowing water. In order to improve this situation it is necessary to develop a sensor-based monitoring system of water leaks. Recently the Fourier transform (FT) has been used, but it is insufficient when a sound signal changes in terms of time, like water leak sound signals. In this study, we propose a new method that combines Wavelet Instantaneous Cross-correlation (WICC) and statistical techniques, and confirm its effectiveness by using actual water leak sound data.

It is well known that the continuous wavelet transform using the Gabor wavelet is useful and has high precision. However, its calculation amount is very large, and generally, its practical calculation is discretized depending on experience. In this paper, we consider the discretization method for the continuous wavelet transform using the Gabor wavelet set, and propose some approximate tight wavelet frames using the Gabor wavelet set, and based on them, we propose how to thin the Gabor wavelets in the continuous wavelet transform.

Currently, it is said that potential sufferers of Sleep Apnea Syndrome (SAS) account for up up to about 2% of the population in Japan. Not only does SAS cause lack of concentration during the day, it may also cause complications such as hypertension and heart failure, and it has been called a modern disease. However, there is a problem that it is impossible to decide if one suffers from it And diagnosis is difficult if a patient does not go to hospital, because diagnosis requires many resources. Therefore, we propose a method that can easily diagnose SAS by the continuous wavelet transform (CWT) using a vocal sound signal, and obtain encouraging results.

Background— Despite the advent of drug-eluting stents, restenosis after endovascular intervention is still a major limitation in the treatment of cardiovascular disease. To regulate the multiple biological mechanisms underlying restenosis, we focused on inhibition of an important transcription factor, nuclear factor-kappaB (NFκB), using a decoy strategy. Methods and Results— For site-specific application of NFκB decoy oligodeoxynucleotides into target vessels during angioplasty, we developed a balloon catheter–based delivery system combined with biocompatible nanoparticles as oligodeoxynucleotides carriers. To clarify the therapeutic effect at the site of neointima, balloon angioplasty of the rabbit carotid arteries was performed at 4 weeks after initial endothelial denudation. This delivery system exhibited successful transfer of fluorescence-labeled nanospheres into the neointima in short-term contact with target vessels, and fluorescence could be detected ≥1 week after angioplasty. Consistently, local application of NFκB decoy oligodeoxynucleotides -loaded nanospheres resulted in significant inhibition of neointimal formation, associated with inhibition of NFκB binding activity in the injured arteries. The therapeutic effects were caused by inhibition of macrophage recruitment through the suppression of monocyte chemoattractant protein-1, vascular cell adhesion molecule-1, and CC chemokine ligand 4 expression and inhibition of vascular smooth muscle cell growth via a decrease in the expression of cyclin A and proliferating cell nuclear antigen. Importantly, application of NFκB nanospheres accelerated restoration of the endothelial cell monolayer, associated with enhanced expression of phosphorylated Bcl-2 in endothelial cells. Conclusions— A drug-coated balloon catheter using NFκB decoy oligodeoxynucleotides significantly inhibited the development of neointimal hyperplasia in rabbits. The present study indicates the possibility of a novel therapeutic option to prevent restenosis after angioplasty.

Recently, much research regarding time-frequency analysis using wavelet transformation, WT, has been focused on analyzing wavelets, AW's that are derived form a mathematical approach. In the analysis in this study, the measured signal is adopted as the AW. In a general way, this method is applicable to inquiry of noise in industrial instrument and analysis of sounds, vibrations and biological signals. In an application of the proposed system, the correlation between brain waves of healthy elderly people and of senile dementia sufferers is analyzed. Brain waves are complex and non-stationary signals. To apply this method to time-varying signals such as brain waves, a new concept of instantaneous correlation factor, ICF, is introduced. This method uses WT by employing the measured signal as the AW. In this study, we use brain waves as the AW. As a conclusion, it is proved that a dominant feature of the correlation can be estimated by the ICF. Time-varying correlation is effective in the analysis of brain waves and will be useful in the diagnosis of senile dementia.

In this paper, we propose a presentation system of virtual 3D shape information for visually handicapped persons. For displaying a virtual 3D shape, an industrial robot arm is used. A user of the proposed system touches a small plate that is attached to a tip of the robot arm by one hand and drives the arm by moving another hand freely on a guide plane. As the hand moves on the guide plane, the plate successively displays a tangential plane of a 3D shape that is stored in the PC beforehand. Since users can move the hand freely, they can perceive virtual objects with their own will. The experiment was conducted for 22 normal subjects and one visually handicapped with 4 kinds of simple 3D shapes. After the subject touches the virtual shape, it touches a real object and judges whether the two shapes are same or not. The experimental results show that the proposed system is useful for the vision substitute system.

A person can keep an object which moves according to rules in roughly the center of their field of vision at all times. Even if the object is occluded during its movement, the person can continue to track it by estimating its later motion. In this paper, this kind of human system is taken into consideration for an automatic monitoring system, and such a system is constructed using an active vision system with a pan and tilt rotary mechanism. In order to automatically monitor a scene over a wide area at high resolution, the object to be monitored must be tracked while changing the pan and tilt using active vision. The tracking principle used in this system consists of detecting a moving object and estimating its motion. Detection is accomplished by using a background subtraction method which uses a background database, and motion estimation is handled by a Kalman filter. An experiment is performed on a person in a typical room environment, and it is confirmed that the person can be tracked by the proposed system even when occluded. © 2003 Wiley Periodicals, Inc. Syst Comp Jpn, 34(13): 92–102, 2003; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/scj.1222

The complex discrete wavelet transform (CDWT) can be carried out by using a complex mother wavelet that is designed based on the Meyer wavelet, and achieves perfect translation invariance. However, it is calculated by the parallel Multi-resolution algorithm (MRA) using the imaginary part and the real part of the complex mother wavelet and the calculation amount is more than double that of the traditional discrete wavelet transform (DWT). In order to reduce the calculation amount, using the lifting scheme instead of the MRA is considered, although the lifting scheme was only used in the case of the mother wavelet with a compact support. In this research, we design a lifting scheme filter of Meyer wavelet without compact support in order to achieve high-speed computation by application to the CDWT, and have obtained encouraging results.

In our first report, we have proposed a complex type wavelet, the Real-Imaginary Spline Wavelet (RI-Spline wavelet) for the continuous wavelet transform and demonstrated the advantages of our approach. In this study, we develop our RI-Spline wavelet for the Discrete Wavelet Transform (DWT) that uses a fast algorithm based on Multi-resolution analysis. The DWT has a translation variance problem, so it can not catch features of the signals exactly although it has been widely used in signal analysis. In order to overcome this translation variance problem, we first develop a Complex Discrete Wavelet Transform (CDWT) using the RI-Spline wavelet and propose the Coherent Dual-Tree algorithm for the RI-Spline wavelet without increasing the computational cost very much. Then we apply this translation invariant CDWT to translation invariant de-noising. Experimental results show that our method, when applied to ECG data and music data, can obtain better de-noising results than conventional Wavelet Shrinkage.

In this paper, we propose the novel design method of directional selection for three-dimensional complex discrete wavelet transform (3D-CDWT) (hereafter, all abbreviations will be written with capital letters). Previously, the complex discrete wavelet transform has been able to extract directional edges from images using the directional selection property. This can be applied to shape and texture analysis. However the angular range of each directional edge is still unclear and the angular ranges are fixed. Thus, it is difficult to be applied to image processing. Therefore, we firstly clarify the angular range of directional edges by using frequency characteristics. Secondly, we propose a design method for the angular range of directional edges with a desirable angular range. As a result, we can clarify the angular ranges of directional edges and it is possible to obtain the directional edges with arbitrary angular range.

In recent years, senior driver-related traffic accidents have been increasing while the number of deaths in these accidents has been decreasing. This also shows the complexity of the composition ratio of drivers to pedestrians in the traffic environment. In order to ensure traffic safety under this environment, not only is advanced technology for vehicle safety necessary but also traffic safety education of vulnerable road users. As one education method, the use of driving simulators is proposed in this paper, and its validity is evaluated through the application of the proposed method in a special course for high school students in our university. Finally, a questionnaire survey for students was conducted to confirm its effectiveness and the validity of the educational content.

In recent years, in order to reduce traffic accidents, support systems for driving safety have been put to practical use, such as ITS. However, a support system which considers the driver's intentions has not yet been developed. If the system reflects the intentions of the driver in system behavior, important information will be provided at suitable timing. In a previous study, the authors have studied an estimation method for driver intentions, and a reasonable definition method for labeling driver intentions has been proposed based on the assumption of compliance with traffic rules. In this paper, the validity of our proposed method by using a driving simulator is discussed. The system is specially designed to induce driver intention changes by using traffic flow and environmental control. Moreover, in order increase the effectiveness in practical use, a real-time estimation system has also been constructed.

It is well known that a mother wavelet for the discrete wavelet transform (DWT) has the band-pass filter characteristic with octave width in the frequency domain and can be used for octave analysis. However, it is possible that the octave analysis is not necessarily the most suitable to match the analysis signal. In this study, a novel variable-filter band discrete wavelet transform (VFB-DWT) is proposed. It is achieved by using variable-band filters instead of conventional decomposition and reconstruction sequences, which are designed in consideration of the real signal characteristics. Furthermore, the VFB-DWT is applied to the fetal electrocardiogram de-noising and good performance has ben obtained.

Previously, Discrete wavelet Transform(DWT) is well known for useful image processing method. Complex Discrete Wavelet Transform(CDWT) is one of the DWT and has the function called directional selection. This is the expected to be applied into shape and texture analysis. But the principle of directional selection is still not clear. In this paper, we consider the principle of directional selection. After that, we propose the evaluation method for directional selection based on the principle. Finally, we confirm the validity of evaluation method.

A vehicle's steering wheel is a special interface because it needs to be grasped by the driver's hand while driving. This is very useful from the viewpoint of biological instrumentation. This may achieve steady instrumentation for biological information, and by using this information, an estimate of the driver's state can also be made. In past research, a steering wheel sensor system was proposed by the authors. It has 28 pressure sensor points, and several of its characteristics have been analyzed. In this paper, an estimation method of grasp behavior is proposed based on the distribution of grasp pressure data. Four kinds of steering wheel grasp states are defined. Finally, the estimation method and its results are evaluated experimentally.

Today, Virtual Reality (VR) technology has been applied in various fields, and the effects of inducing VR contents in humans have been studied. Generally, VR contents mainly consist of visual stimulation and it is considered that it influences the recognition mechanisms in the human brain, the behaviors in the human body and so on. In this research, in order to construct a methodology of VR content production with higher realism, an analysis method for behaviors in the human body induced by visual stimulation is studied. It is known that the sensation induced by visual stimulation affects the human behavior with a specific frequency component. If this kind of behavior can be modeled by using simple model parameters, it has the possibility to control the human behavior using visual stimulation or to increase its realism. In previous research, a parameterized first-order human behavior model has been proposed. The validity of the proposed model and its parameters has been confirmed through the analysis of verification experimental results. In this research, long-term experiments have been conducted to check the validity of the proposed analysis method. In addition, the possibility of applying the method as a time series modeling method to postural sway analysis is also considered.

This paper presents an evaluation of driving attentiveness by using Fuzzy Inference based on the driver's gaze when driving. Two cameras are used respectively to capture images in front of the driving car and to capture images of the driver's face in order to calculate the coordinates of the objects in front of the car and the driver's eye sight angle by using image processing. There are many kinds of inattentive driving such as loss of concentration on the objects in front of the vehicle, looking aside or idly thinking of some other things while driving, where we are able to detect the inattentive driving by evaluating the movement of the driver's gaze. Driving data with and without task were taken through offline mode experiment by using driving simulator. The tasks are to influence the concentration of the driver when driving. As a result, with the Fuzzy Inference that we proposed, inattentive driving can be detected due to the significant difference evaluation result between attentive driving and inattentive driving.

Allergic asthma is a common inflammatory disease of the airways characterized by reversible airflow obstruction and airway hyperresponsiveness (AHR) to bronchoconstrictor stimuli. The pathophysiology in asthma mainly occurs as a consequence of overexpression of the TH2 cytokines. These inflammatory factors are tightly regulated by a transcriptional network system. Nuclear factor kappaB (NFkB) and STAT6 are well known to regulate a set of gene associated with inflammatory and immune responses, and is thought to play an important role in the induction of allergic asthma. Therefore, we focused on the simultaneous inhibition of these important transcription factors using a decoy strategy to develop a novel therapeutic approach for treating asthma. For increased efficacy of decoy oligodeoxynucleotides (ODN) in vivo, we employed chimeric decoy ODN containing consensus sequences of both NFkB and STAT6 binding sites. In addition, two strands of decoy ODN were combined by the chemical spacer to increase its resistance to endonuclease for intratracheal administration. The therapeutic effect of chimeric decoy ODN was investigated using OVA-induced experimental asthma in mice. Mice were sensitized by intraperitoneal injections of 20 ug of ovalbumin (OVA) and 2 mg aluminum hydroxide constituted in 0.1 ml of saline on days 0 and 14. On days 21, 22 and 23, mice were challenged with 1% OVA aerosol for 20 min. At 24 hours after the last challenge, AHR was measured by methacholine-induced airflow obstruction. Intratracheal administration of decoy ODN was performed in OVA-sensitized mice at 3 days before the first challenge with aerosolized OVA. FITC-labeled chimeric decoy ODN could be detected in macrophages and monocytes migrating into the lung and airway, and NFkB and STAT6 activity were simultaneously inhibited by chimeric decoy ODN. Twenty-four hours after the last OVA challenge, treatment with chimeric or single transfection of NFkB decoy ODN was protected from methacholine-induced AHR, while mice treated with scrambled decoy ODN or saline developed a significantly increase in airway reactivity to methacholine. Importantly, this inhibitory effect of chimeric decoy ODN on airway hyperresponsiveness was significantly greater than that of NFkB decoy ODN. Treatment with chimeric decoy ODN markedly suppressed airway inflammation after OVA sensitization and challenge as compared with control and scrambled decoy ODN treatment. Inflammatory infiltrate, such as macrophage, was significantly inhibited by chimeric decoy ODN through suppression of ICAM-1 and eotaxin expression. In addition, secretion of Th2 cytokines including IL-4, IL-5 and IL-13 in BALF, and histamine in the whole lung were reduced by chimeric decoy ODN. Furthermore, a significant reduction of mucin secretion was observed by chimeric decoy ODN treatment accompanied by a suppression of MUC5AC gene expression. However, intratracheal administration of chimeric decoy ODN did not affected IgE synthesis. The present study provides a novel strategy for treating bronchial asthma by the simultaneous inhibition of both NFkB and STAT6 using chimeric decoy ODN. Further modification of chimeric decoy ODN would be useful to treat asthma as a decoy-based therapy.

Studies are underway for the development of cutoff sheets (CH-200) for use at final disposal yards, which are capable of preventing the expansion of perforations and of self-repair. The study reported here was concerned with the basic properties of these cutoff sheets, in terms of the effects of water pressure, temperature and quality, as well as the structure of the sheets themselves, on their capacity for self-repair. It was found that the capacity for self-repair could be maintained under water pressure of up to 3kgf/cm2, and at the temperatures normally encountered in groundwater and waste.