Search results for: Hironori Tsuchiya

Authors: Maki Mizogami, Hironori Tsuchiya, Yoshiroh Hayabuchi, Kenji Shigemi

Abstract:

Since drugs exhibit significant structure-dependent differences in activity and toxicity, their differentiation based on the mechanism of action should have implications for comparative drug efficacy and safety. We aimed to differentiate drug stereoisomers by their stereostructure-selective membrane interactions underlying pharmacological and toxicological effects. Biomimetic lipid bilayer membranes were prepared with phospholipids and sterols (either cholesterol or epicholesterol) to mimic the lipid compositions of neuronal and cardiomyocyte membranes and to provide these membranes with the chirality. The membrane preparations were treated with different classes of stereoisomers at clinically- and pharmacologically-relevant concentrations (25-200 μM), followed by measuring fluorescence polarization to determine the membrane interactivity of drugs to change the physicochemical property of membranes. All the tested drugs acted on lipid bilayers to increase or decrease the membrane fluidity. Drug stereoisomers could not be differentiated when interacting with the membranes consisting of phospholipids alone. However, they stereostructure-selectively interacted with neuro-mimetic and cardio-mimetic membranes containing 40 mol% cholesterol ((3β)-cholest-5-en-3-ol) to show the relative potencies being local anesthetic R(+)-bupivacaine > rac-bupivacaine > S(‒)-bupivacaine, α2-adrenergic agonistic D-medetomidine > rac-medetomidine > L-medetomidine, β-adrenergic antagonistic R(+)-propranolol > rac-propranolol > S(–)-propranolol, NMDA receptor antagonistic S(+)-ketamine > rac-ketamine, analgesic monoterpenoid (+)-menthol > (‒)-menthol, non-steroidal anti-inflammatory S(+)-ibuprofen > rac-ibuprofen > R(‒)-ibuprofen, and bioactive flavonoid (+)-epicatechin > (‒)-epicatechin. All of the order of membrane interactivity were correlated to those of beneficial and adverse effects of the tested stereoisomers. In contrast, the membranes prepared with epicholesterol ((3α)-chotest-5-en-3-ol), an epimeric form of cholesterol, reversed the rank order of membrane interactivity to be S(‒)-enantiomeric > racemic > R(+)-enantiomeric bupivacaine, L-enantiomeric > racemic > D-enantiomeric medetomidine, S(–)-enantiomeric > racemic > R(+)-enantiomeric propranolol, racemic > S(+)-enantiomeric ketamine, (‒)-enantiomeric > (+)-enantiomeric menthol, R(‒)-enantiomeric > racemic > S(+)-enantiomeric ibuprofen, and (‒)-enantiomeric > (+)-enantiomeric epicatechin. The opposite configuration allows drug molecules to interact with chiral sterol membranes enantiomer-selectively. From the comparative results, it is speculated that a 3β-hydroxyl group in cholesterol is responsible for the enantioselective interactions of drugs. In conclusion, the differentiation of drug stereoisomers by their stereostructure-selective membrane interactions would be useful for designing and predicting drugs with higher activity and/or lower toxicity.

Keywords: chiral membrane, differentiation, drug stereoisomer, enantioselective membrane interaction

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Authors: Hironori Karachi, Haruka Yamashita

Abstract:

Recently, the system of quick response (QR) code is getting popular. Many companies introduce new QR code payment services and the services are competing with each other to increase the number of users. For increasing the number of users, we should grasp the difference of feature of the demographic information, usage information, and value of users between services. In this study, we conduct an analysis of real-world data provided by Nomura Research Institute including the demographic data of users and information of users’ usages of two services; LINE Pay, and PayPay. For analyzing such data and interpret the feature of them, Nonnegative Matrix Factorization (NMF) is widely used; however, in case of the target data, there is a problem of the missing data. EM-algorithm NMF (EMNMF) to complete unknown values for understanding the feature of the given data presented by matrix shape. Moreover, for comparing the result of the NMF analysis of two matrices, there is Discriminant NMF (DNMF) shows the difference of users features between two matrices. In this study, we combine EMNMF and DNMF and also analyze the target data. As the interpretation, we show the difference of the features of users between LINE Pay and Paypay.

Keywords: data science, non-negative matrix factorization, missing data, quality of services

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Authors: Ruwani N. Nugara, Masashi Inafuku, Kensaku Takara, Hironori Iwasaki, Hirosuke Oku

Abstract:

Pteryxin from the partially purified hexane phase (HP) of Peucedanum japonicum Thunb (PJT) was identified as the active compound related to anti-obesity. Thus, in this study we investigated the mechanisms related to anti-obesity activity in-vitro. The HP was fractionated, and effect on the triglyceride (TG) content was evaluated in 3T3-L1 and HepG2 cells. Comprehensive spectroscopic analyses were used to identify the structure of the active compound. The dose dependent effect of active constituent on the TG content, and the gene expressions related to adipogenesis, fatty acid catabolism, energy expenditure, lipolysis and lipogenesis (20 μg/mL) were examined in-vitro. Furthermore, higher dosage of pteryxin (50μg/mL) was tested against 20μg/mL in 3T3-L1 adipocytes. The mRNA were subjected to SOLiD next generation sequencer and the obtained data were analyzed by Ingenuity Pathway Analysis (IPA). The active constituent was identified as pteryxin, a known compound in PJT. However, its biological activities against obesity have not been reported previously. Pteryxin dose dependently suppressed TG content in both 3T3-L1 adipocytes and HepG2 hepatocytes (P < 0.05). Sterol regulatory element-binding protein-1 (SREBP1 c), Fatty acid synthase (FASN), and acetyl-CoA carboxylase-1 (ACC1) were downregulated in pteryxin-treated adipocytes (by 18.0, 36.1 and 38.2%; P < 0.05, respectively) and hepatocytes (by 72.3, 62.9 and 38.8%, respectively; P < 0.05) indicating its suppressive effects on fatty acid synthesis. The hormone-sensitive lipase (HSL), a lipid catabolising gene was upregulated (by 15.1%; P < 0.05) in pteryxin-treated adipocytes suggesting improved lipolysis. Concordantly, the adipocyte size marker gene, paternally expressed gene1/mesoderm specific transcript (MEST) was downregulated (by 42.8%; P < 0.05), further accelerating the lipolytic activity. The upregulated trend of uncoupling protein 2 (UCP2; by 77.5%; P < 0.05) reflected the improved energy expenditure due to pteryxin. The 50μg/mL dosage of pteryxin completely suppressed PPARγ, MEST, SREBP 1C, HSL, Adiponectin, Fatty Acid Binding Protein (FABP) 4, and UCP’s in 3T3-L1 adipocytes. The IPA suggested that pteryxin at 20μg/mL and 50μg/mL suppress obesity in two different pathways, whereas the WNT signaling pathway play a key role in the higher dose of pteryxin in preadipocyte stage. Pteryxin in PJT play the key role in regulating lipid metabolism related gene network and improving energy production in vitro. Thus, the results suggests pteryxin as a new natural compound to be used as an anti-obesity drug in pharmaceutical industry.

Keywords: obesity, peucedanum japonicum thunb, pteryxin, food science

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Authors: F. Tang, S. Boskovich, A. Raheja, Z. Aliyazicioglu, S. Bhandari, N. Tsuchiya

Abstract:

Calpoly Autonomous Transportation Experience (CATE) is a driverless vehicle that we are developing to provide safe, accessible, and efficient transportation of passengers throughout the Cal Poly Pomona campus for events such as orientation tours. Unlike the other self-driving vehicles that are usually developed to operate with other vehicles and reside only on the road networks, CATE will operate exclusively on walk-paths of the campus (potentially narrow passages) with pedestrians traveling from multiple locations. Safety becomes paramount as CATE operates within the same environment as pedestrians. As driverless vehicles assume greater roles in today’s transportation, this project will contribute to autonomous driving with pedestrian traffic in a highly dynamic environment. The CATE project requires significant interdisciplinary work. Researchers from mechanical engineering, electrical engineering and computer science are working together to attack the problem from different perspectives (hardware, software and system). In this abstract, we describe the software aspects of the project, with a focus on the requirements and the major components. CATE shall provide a GUI interface for the average user to interact with the car and access its available functionalities, such as selecting a destination from any origin on campus. We have developed an interface that provides an aerial view of the campus map, the current car location, routes, and the goal location. Users can interact with CATE through audio or manual inputs. CATE shall plan routes from the origin to the selected destination for the vehicle to travel. We will use an existing aerial map for the campus and convert it to a spatial graph configuration where the vertices represent the landmarks and edges represent paths that the car should follow with some designated behaviors (such as stay on the right side of the lane or follow an edge). Graph search algorithms such as A* will be implemented as the default path planning algorithm. D* Lite will be explored to efficiently recompute the path when there are any changes to the map. CATE shall avoid any static obstacles and walking pedestrians within some safe distance. Unlike traveling along traditional roadways, CATE’s route directly coexists with pedestrians. To ensure the safety of the pedestrians, we will use sensor fusion techniques that combine data from both lidar and stereo vision for obstacle avoidance while also allowing CATE to operate along its intended route. We will also build prediction models for pedestrian traffic patterns. CATE shall improve its location and work under a GPS-denied situation. CATE relies on its GPS to give its current location, which has a precision of a few meters. We have implemented an Unscented Kalman Filter (UKF) that allows the fusion of data from multiple sensors (such as GPS, IMU, odometry) in order to increase the confidence of localization. We also noticed that GPS signals can easily get degraded or blocked on campus due to high-rise buildings or trees. UKF can also help here to generate a better state estimate. In summary, CATE will provide on-campus transportation experience that coexists with dynamic pedestrian traffic. In future work, we will extend it to multi-vehicle scenarios.

Keywords: driverless vehicle, path planning, sensor fusion, state estimate

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