Forecasting the ongoing invasion of Lagocephalus sceleratus in the Mediterranean Sea

Invasive species from the Suez Canal, also named “Lessepsian species”, often have an ecological and financial impact on marine life, fisheries, human well-being and health in the Mediterranean Sea. Among these, the silver-cheeked toad-fish Lagocephalus sceleratus (Gmelin, 1789) has rapidly colonised the eastern Mediterranean basin and is currently moving westwards. This pufferfish has a highly opportunistic behaviour, it attacks fish captured in nets and lines and seriously damages fishing gears and catch. It is a highly-toxic species with no immediate economic value for the Mediterranean market, although it currently represents 4% of the weight of the total artisanal catches. Consequently, the possible effects on Mediterranean fisheries and health require to enhance our understanding about the future geographical distribution of this pufferfish in the whole basin. In this paper, an overall habitat suitability map and an effective geographical spread map for L. sceleratus at Mediterranean scale are produced by using cloud computing-based algorithms to merge seven machine learning approaches. Further, the potential impact of the species is estimated for several Mediterranean Sea subdivisions: The major fishing areas of the Food and Agriculture Organization of the United Nations, the Economic Exclusive Zones, and the subdivisions of the General Fisheries Commission for the Mediterranean Sea. Our results suggest that without an intervention, L. sceleratus will continue its rapid spread and will likely have a high impact on fisheries. The presented method is generic and can be applied to other invasive species. It is based on an Open Science approach and all processes are freely available as Web services

Deficient NRG1-ERBB signaling alters social approach: relevance to genetic mouse models of schizophrenia

Growth factor Neuregulin 1 (NRG1) plays an essential role in development and organization of the cerebral cortex. NRG1 and its receptors, ERBB3 and ERBB4, have been implicated in genetic susceptibility for schizophrenia. Disease symptoms include asociality and altered social interaction. To investigate the role of NRG1-ERBB signaling in social behavior, mice heterozygous for an Nrg1 null allele (Nrg1+/−), and mice with conditional ablation of Erbb3 or Erbb4 in the central nervous system, were evaluated for sociability and social novelty preference in a three-chambered choice task. Results showed that deficiencies in NRG1 or ERBB3 significantly enhanced sociability. All of the mutant groups demonstrated a lack of social novelty preference, in contrast to their respective wild-type controls. Effects of NRG1, ERBB3, or ERBB4 deficiency on social behavior could not be attributed to general changes in anxiety-like behavior, activity, or loss of olfactory ability. Nrg1+/− pups did not exhibit changes in isolation-induced ultrasonic vocalizations, a measure of emotional reactivity. Overall, these findings provide evidence that social behavior is mediated by NRG1-ERBB signaling

Detecting patterns of climate change in long-term forecasts of marine environmental parameters

Forecasting environmental parameters in the distant future requires complex modelling and large computational resources. Due to the sensitivity and complexity of forecast models, long-term parameter forecasts (e.g. up to 2100) are uncommon and only produced by a few organisations, in heterogeneous formats and based on different assumptions of greenhouse gases emissions. However, data mining techniques can be used to coerce the data to a uniform time and spatial representation, which facilitates their use in many applications. In this paper, streams of big data coming from AquaMaps and NASA collections of 126 long-term forecasts of nine types of environmental parameters are processed through a cloud computing platform in order to (i) standardise and harmonise the data representations, (ii) produce intermediate scenarios and new informative parameters, and (iii) align all sets on a common time and spatial resolution. Time series cross-correlation applied to these aligned datasets reveals patterns of climate change and similarities between parameter trends in 10 marine areas. Our results highlight that (i) the Mediterranean Sea may have a standalone ‘response’ to climate change with respect to other areas, (ii) the Poles are most representative of global forecasted change, and (iii) the trends are generally alarming for most oceans

In Vivo Silencing of MicroRNA-132 Reduces Blood Glucose and Improves Insulin Secretion

Dysfunctional insulin secretion is a hallmark of type 2 diabetes (T2D). Interestingly, several islet microRNAs (miRNAs) are upregulated in T2D, including miR-132. We aimed to investigate whether in vivo treatment with antagomir-132 lowers expression of miR-132 in islets thereby improving insulin secretion and lowering blood glucose. Mice injected with antagomir-132 for 24 h, had reduced expression of miR-132 expression in islets, decreased blood glucose, and increased insulin secretion. In isolated human islets treated with antagomir-132, insulin secretion from four of six donors increased. Target prediction coupled with analysis of miRNA-messenger RNA expression in human islets revealed DESI2, ARIH1, SLC25A28, DIAPH1, and FOXA1 to be targets of miR-132 that are conserved in both species. Increased expression of these targets was validated in mouse islets after antagomir-132 treatment. In conclusion, we identified a post-transcriptional role for miR-132 in insulin secretion, and demonstrated that systemic antagomir-132 treatment in mice can be used to improve insulin secretion and reduce blood glucose in vivo. Our study is a first step towards utilizing antagomirs as therapeutic agents to modulate islet miRNA levels to improve beta cell function