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Isoniazid (INH), a widely used first-line antitubercular drug, has been noted to be associated with hepatotoxicity. In spite of extensive researches over many decades, the mechanism of INH-induced hepatotoxicity still remains poorly understood. Recently, mitochondrial toxicity has been emerging as a new paradigm for INH-induced hepatotoxicity. In this study, we showed that INH impaired mitochondrial biogenesis and dynamics in human hepatocarcinoma HepG2 cells. INH reduced mitochondrial membrane potential (MMP) and induced mitochondria swelling. INH also inhibited the protein expressions of three major mitochondrial biogenesis regulators, SIRT1, PGC1α and NRF1, along with increased acetylation of PGC1α. Meanwhile, INH decreased the number of mitochondria, accompanied by decreased expression of mitochondrial protein COX IV. INH caused mitochondrial fragmentation involving decreased levels of the fusion protein MFN2 as well as the fission protein DRP1. INH-reduced DRP1 expression was associated with the increase of apoptosis, suggesting the existence of pro-survival fission and its involvement in mitochondrial quality control. INH activated p38 MAPK, whereas inhibition of p38 MAPK aggravated INH-induced decreases of SIRT1, PGC1α, NRF1, COX IV and DRP1 expressions. P38 MAPK inhibition also further up-regulated the acetylation of PGC1α and exacerbated INH-induced MMP loss, mitochondrial swelling and apoptosis. Taken together, INH-activated p38 MAPK induced mitochondrial biogenesis to alleviate apoptosis through partly recovering SIRT1-PGC1α pathway activation. In the meantime, p38 MAPK activation by INH promoted protective mitochondrial fission to alleviate apoptosis by partial recovery of DRP1 expression.

In this paper, a vision-guided autonomous quadrotor in an air-ground multi-robot system has been proposed. This quadrotor is equipped with a monocular camera, IMUs and a flight computer, which enables autonomous flights. Two complementary pose/motion estimation methods, respectively marker-based and optical-flow-based, are developed by considering different altitudes in a flight. To achieve smooth take-off, stable tracking and safe landing with respect to a moving ground robot and desired trajectories, appropriate controllers are designed. Additionally, data synchronization and time delay compensation are applied to improve the system performance. Real-time experiments are conducted in both indoor and outdoor environments.

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The mechanism for motion detection in a fly's vision system, known as the Reichardt correlator, suffers from a main shortcoming as a velocity estimator: low accuracy. To enable accurate velocity estimation, responses of the Reichardt correlator to image sequences are analyzed in this paper. An elaborated model with additional preprocessing modules is proposed. The relative error of velocity estimation is significantly reduced by establishing a real-time response-velocity lookup table based on the power spectrum analysis of the input signal. By exploiting the improved velocity estimation accuracy and the simple structure of the Reichardt correlator, a high-speed vision system of 1 kHz is designed and applied for robot yaw-angle control in real-time experiments. The experimental results demonstrate the potential and feasibility of applying insect-inspired motion detection to robot control.

In the Autonomous City Explorer (ACE) project a mobile robot is developed, which is capable of finding its way to a given destination in an unknown urban environment. An exemplary mission is to find the way from our institute to the Marienplatz, a public place in the center of Munich, without any prior knowledge or GPS information. Inspired by the behavior of humans in unknown environments, ACE must find its way by asking pedestrians. The route is about 1.5 kilometers far and includes heavily traveled roads and crowded public places. In order to navigate safely in an unknown urban environment, some challenges arise for the vision system. Robust human detection, tracking and the estimation of human body poses is essential for natural interaction with pedestrians. Furthermore, the robot needs to be able to detect sidewalk and crossroads. A visual odometry system is used to support the conventional navigation. Outdoor experiments were conducted twice successfully. After about 5 hours and interacting with 25 and 38 persons respectively, ACE arrived the Marienplatz. This paper describes both, an architecture of the vision system used for ACE and the algorithms used to deal with the described challenges.

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Motion detection in the fly is extremely fast with low computational requirements. Inspired from the fly's vision system, we focus on a real-time flight control on a miniquadrotor with fast visual feedback. In this work, an elaborated elementary motion detector (EMD) is utilized to detect local optical flow. Combined with novel receptive field templates, the yaw rate of the quadrotor is estimated through a lookup table established with this bioinspired visual sensor. A closed-loop control system with the feedback of yaw rate estimated by EMD is designed. With the motion of the other degrees of freedom stabilized by a camera tracking system, the yaw-rate of the quadrotor during hovering is controlled based on EMD feedback under real-world scenario. The control performance of the proposed approach is compared with that of conventional approach. The experimental results demonstrate the effectiveness of utilizing EMD for quadrotor control.