Bilateral ibotenic acid lesions of the lateral, but not the medial, parabrachial nucleus (PBN) blocked conditioned taste aversion (CTA) induced by morphine but not conditioned place preference induced by morphine. The same lateral PBN lesions also blocked conditioned place aversion produced by low intraperitoneal doses of morphine (shown to produce aversion, instead of preference, due to a restricted action on gut opiate receptors). Lateral PBN lesions did not block CTA produced by LiCl. Cerebral peduncle lesions that destroyed the direct descending projections from the visceral cortex to the PBN did not block CTA induced by morphine, nor did ibotenic acid lesions of the tegmental pedunculopontine nuclei (shown to block place preference produced by even high morphine doses). It is suggested that the lateral PBN is a critical link in the neural pathway carrying the aversive motivational effects of opiates from the gut into the central nervous system, independent of the neural pathway carrying the rewarding motivational effects of morphine.

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<p>Marine litter is a growing problem that advances parallel to economic and industrial development and seriously affects ecosystems. One of the most abundant pollutants are plastics. The BEWATS project focuses on innovative tools for remote marine litter control and management through satellite and UAV’s. The areas of study are currently at the Vigo coast in Galicia (North-West of Spain). In this area, there are many high natural value beaches including Nature Reserve and part of a National Park. These beaches are receiving an increasing amount of marine litter, mainly plastic, helped by strong currents in the area. Every few months, these beaches are clean and the collected litter information tracked. In this context, the BEWATS project concentrates on tracking the possible path through which marine litter reaches the area of interest. In this presentation, we will discuss how this is achieved by data fusion from UAV imagery, marine dynamics model simulations and Earth-observation satellite data (Sentinel-2). To detect possible marine litter, we have developed a novel synthetic data-based approach to marine litter detection using Sentinel-2 images and machine learning techniques. Within this approach, one can classify and quantify according to pixel-level litter fraction present. We have validated our approach with existing open-sourced available datasets.  </p><p>The BEWATS project is led by Vigo University, which provides UAV’s imagery, and the Spanish Research Council (CSIC) provides marine dynamics models for tracking waste routes and delineation of waste concentration zones. In this context, GMV provides Earth observation based solution of detecting marine litter. BEWATS is founded by the Biodiversity Foundation of the Spanish Ministry for the Ecological Transition and the Demographic Challenge.</p>

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