Assessment of the mineralogenic toxicity of aquatic pollutants

In ecotoxicology a major focus is in the aquatic environment, not only because it presents a great economic value to man but it is an ecosystem widely affected by the growing anthropogenic pollution. Most of the studies performed relate to adverse effects in development, reproductive or endocrine disruption but little is known about the possible effects in bone formation and skeletal development. In this study, we set out to evaluate the effects of 8 aquatic pollutants on the skeletal development using an in vivo system, the zebrafish larvae aged 20 days post-fertilization, through chronic exposure. Several endpoints were considered such as the cumulative mortality, total length, occurrence of skeletal deformities and marker gene expression. We were able to establish LD50 values for some pollutants, like 3-methylcholanthrene, lindane, diclofenac, cobalt and vanadate and found that the total length was not affected by any of the pollutants tested. Cobalt was the most harmful chemical to affect hatching time, severely affecting the ability of the zebrafish embryos to hatch and overall the number of deformities increased upon exposure to tested chemicals but no patterns of deformities were identified. We also propose that 3-methylcholanthrene has an osteogenic effect, affecting osteoblast and osteoclast function and that op levels can act as a mediator of 3-methylcholanthrene toxic stress to the osteoblast. In turn we found naphthalene to probably have a chondrogenic effect. Our results provided new insights into the potential osteotoxicity of environmental pollutants. Future studies should aim at confirming these preliminary data and at determining mechanisms of osteotoxicity.

Biologically Inspired Vision for Indoor Robot Navigation

Ultrasonic, infrared, laser and other sensors are being applied in robotics. Although combinations of these have allowed robots to navigate, they are only suited for specific scenarios, depending on their limitations. Recent advances in computer vision are turning cameras into useful low-cost sensors that can operate in most types of environments. Cameras enable robots to detect obstacles, recognize objects, obtain visual odometry, detect and recognize people and gestures, among other possibilities. In this paper we present a completely biologically inspired vision system for robot navigation. It comprises stereo vision for obstacle detection, and object recognition for landmark-based navigation. We employ a novel keypoint descriptor which codes responses of cortical complex cells. We also present a biologically inspired saliency component, based on disparity and colour.