Altered Expression of Protamine-like and Their DNA Binding Induced by Cr(VI): A Possible Risk to Spermatogenesis?

Chromium (VI) is the most dangerous oxidation state among the stable forms of chromium. In this work, we evaluated the effect of exposing Mytilus galloprovincialis for 24 h to 1, 10, and 100 nM chromium (VI) on the properties of Protamine-like (PLs) and their gene levels in the gonads. Specifically, we analyzed, by AU-PAGE and SDS-PAGE, PLs extracted from unexposed and exposed mussels. In addition, via EMSA, we evaluated the ability of PLs to bind DNA and also verified their potential to protect DNA from oxidative damage. Finally, we assessed possible alterations in gonadal expression of mt10, hsp70, and genes encoding for PLs-II/PL-IV and PL-III. We found that for all experimental approaches the most relevant alterations occurred after exposure to 1 nM Cr(VI). In particular, a comigration of PL-II with PL-III was observed by SDS-PAGE; and a reduced ability of PLs to bind and protect DNA from oxidative damage was recorded. This dose of chromium (VI) exposure was also the one that produced the greatest alterations in the expression of both mt10 and PL-II/PL-IV encoding genes. All of these changes suggest that this dose of chromium (VI) exposure could affect the reproductive health of Mytilus galloprovincialis

The Use of Artificial Intelligence Approaches for Performance Improvement of Low-Cost Integrated Navigation Systems

In this paper, the authors investigate the possibility of applying artificial intelligence algorithms to the outputs of a low-cost Kalman filter-based navigation solution in order to achieve performance similar to that of high-end MEMS inertial sensors. To further improve the results of the prototype and simultaneously lighten filter requirements, different AI models are compared in this paper to determine their performance in terms of complexity and accuracy. By overcoming some known limitations (e.g., sensitivity on the dimension of input data from inertial sensors) and starting from Kalman filter applications (whose raw noise parameter estimates were obtained from a simple analysis of sensor specifications), such a solution presents an intermediate behavior compared to the current state of the art. It allows the exploitation of the power of AI models. Different Neural Network models have been taken into account and compared in terms of measurement accuracy and a number of model parameters; in particular, Dense, 1-Dimension Convolutional, and Long Short Term Memory Neural networks. As can be excepted, the higher the NN complexity, the higher the measurement accuracy; the models’ performance has been assessed by means of the root-mean-square error (RMSE) between the target and predicted values of all the navigation parameters

Developing practical recommendations for preventative healthcare consultations involving dogs and cats using a Delphi technique

© © British Veterinary Association 2019. Re-use permitted under CC BY-NC. No commercial re-use. Published by BMJ. Preventive healthcare is the focus of a large proportion of UK small animal veterinary consultations. The evidence base for how to optimise these consultations is limited. Therefore, evidence-based practical recommendations are needed for veterinary surgeons conducting these consultations. The aim of this study was to use an evidence-based methodology to develop the first consensus recommendations to improve dog and cat preventative healthcare consultations (PHCs). Evidence from multiple sources was systematically examined to generate a list of 18 recommendations. Veterinary surgeons and pet owners with extensive experience of PHCs were recruited to an anonymous panel to obtain consensus on whether these recommendations would improve PHCs. A Delphi technique was followed during three rounds of online questionnaire, with consensus set at 80 per cent agreement or disagreement with each recommendation. Thirteen of the original 18 recommendations reached consensus (>80per cent agreement), while the five remaining recommendations did not reach consensus. Globally, these are the first evidence-based recommendations developed specifically in relation to small animal general practice PHCs, generated via a Delphi panel including both veterinary surgeons and pet owners. Future work is needed to understand how these recommendations can be implemented in a range of veterinary practice settings

Improving the accuracy of industrial robots via iterative reference trajectory modification

In this paper, a novel repetitive control (RC) scheme is presented and discussed. The general framework is the control of repetitive tasks of robotic systems or, more in general, of automatic machines. The key idea of the proposed scheme consists in modifying the reference trajectory provided to the plant in order to compensate for external loads or unmodeled dynamics that cyclically affect it. By exploiting the fact that uniform B-spline trajectories can be generated by means of dynamic filters, the trajectory planning phase has been integrated within an RC scheme that is able to modify in real time the reference signal in order to nullify the tracking errors occurring at the desired via-points. Because of this mechanism, the control scheme is very suitable for the application to industrial plants with off-the-shelf, unmodifiable controllers. Experimental results obtained with a standard industrial manipulator both in joint space and in workspace show the effectiveness of the proposed method