Meta-Analysis of a New Georeferenced Database on Polycyclic Aromatic Hydrocarbons in Western and Central Mediterranean Seafood

The aim of this work was to collect and harmonize the results of several studies achieved over the years, in order to obtain a database of georeferenced observations on polycyclic aromatic hydrocarbons (PAHs) in Western and Central Mediterranean seafood. For each observation, some information on the taxonomy and the ecology of the sampled species are reported, as well as details on the investigated hydrocarbon, and spatial and temporal information on sampling. Moreover, two health risk indexes were calculated for each record and included in the database. Through several statistical methods, we conducted a meta‐analysis of the data on some of the species in this database, identifying trends that could be related to the biology of the investigated organisms, as well as to the physico‐chemical properties of each hydrocarbon and to the oceanographic characteristic of this part of the Mediterranean. The analysis of the data showed that, at a consumption rate like the one typical of the Italian population, seafood caught from the area considered in the present work seems to pose a minimal risk to health. However, we also found evidence of an increasing trend of PAH concentrations in Mediterranean mussels, pointing to the need for constant monitoring

Tracking fish abundance by underwater image recognition

Marine cabled video-observatories allow the non-destructive sampling of species at frequencies and durations that have never been attained before. Nevertheless, the lack of appropriate methods to automatically process video imagery limits this technology for the purposes of ecosystem monitoring. Automation is a prerequisite to deal with the huge quantities of video footage captured by cameras, which can then transform these devices into true autonomous sensors. In this study, we have developed a novel methodology that is based on genetic programming for content-based image analysis. Our aim was to capture the temporal dynamics of fish abundance. We processed more than 20,000 images that were acquired in a challenging real-world coastal scenario at the OBSEA-EMSO testing-site. The images were collected at 30-min. frequency, continuously for two years, over day and night. The highly variable environmental conditions allowed us to test the effectiveness of our approach under changing light radiation, water turbidity, background confusion, and bio-fouling growth on the camera housing. The automated recognition results were highly correlated with the manual counts and they were highly reliable when used to track fish variations at different hourly, daily, and monthly time scales. In addition, our methodology could be easily transferred to other cabled video-observatories.Peer ReviewedPostprint (published version

Video Image Enhancement and Machine Learning Pipeline for Underwater Animal Detection and Classification at Cabled Observatories

Corrección de una afiliación en Sensors 2023, 23, 16. https://doi.org/10.3390/s23010016An understanding of marine ecosystems and their biodiversity is relevant to sustainable use of the goods and services they offer. Since marine areas host complex ecosystems, it is important to develop spatially widespread monitoring networks capable of providing large amounts of multiparametric information, encompassing both biotic and abiotic variables, and describing the ecological dynamics of the observed species. In this context, imaging devices are valuable tools that complement other biological and oceanographic monitoring devices. Nevertheless, large amounts of images or movies cannot all be manually processed, and autonomous routines for recognizing the relevant content, classification, and tagging are urgently needed. In this work, we propose a pipeline for the analysis of visual data that integrates video/image annotation tools for defining, training, and validation of datasets with video/image enhancement and machine and deep learning approaches. Such a pipeline is required to achieve good performance in the recognition and classification tasks of mobile and sessile megafauna, in order to obtain integrated information on spatial distribution and temporal dynamics. A prototype implementation of the analysis pipeline is provided in the context of deep-sea videos taken by one of the fixed cameras at the LoVe Ocean Observatory network of Lofoten Islands (Norway) at 260 m depth, in the Barents Sea, which has shown good classification results on an independent test dataset with an accuracy value of 76.18% and an area under the curve (AUC) value of 87.59%.This work was developed within the framework of the Tecnoterra (ICM-CSIC/UPC) and the following project activities: ARIM (Autonomous Robotic Sea-Floor Infrastructure for Benthopelagic Monitoring; MarTERA ERA-Net Cofound) and RESBIO (TEC2017-87861-R; Ministerio de Ciencia, Innovación y Universidades)

Towards Naples Ecological REsearch for Augmented Observatories (NEREA): The NEREA-Fix module, a stand-alone platform for long-term deep-sea ecosystem monitoring

Deep-sea ecological monitoring is increasingly recognized as indispensable for the comprehension of the largest biome on Earth, but at the same time it is subjected to growing human impacts for the exploitation of biotic and abiotic resources. Here, we present the Naples Ecological REsearch (NEREA) stand-alone observatory concept (NEREA-fix), an integrated observatory with a modular, adaptive structure, characterized by a multiparametric video-platform to be deployed in the Dohrn canyon (Gulf of Naples, Tyrrhenian Sea) at ca. 650 m depth. The observatory integrates a seabed platform with optoacoustic and oceanographic/geochemical sensors connected to a surface transmission buoy, plus a mooring line (also equipped with depth-staged environmental sensors). This reinforced high-frequency and long-lasting ecological monitoring will integrate the historical data conducted over 40 years for the Long-Term Ecological Research (LTER) at the station “Mare Chiara”, and ongoing vessel-assisted plankton (and future environmental DNA-eDNA) sampling. NEREA aims at expanding the observational capacity in a key area of the Mediterranean Sea, representing a first step towards the establishment of a bentho-pelagic network to enforce an end-to-end transdisciplinary approach for the monitoring of marine ecosystems across a wide range of animal sizes (from bacteria to megafauna).This research was funded by PON “Iniziative in supporto al consolidamento e potenziamento dell’infrastruttura EMSO e delle sue attività (InSEA)” - European Union - Italian Ministry of University and Research, grant number PIR01_00030.Peer ReviewedPostprint (published version

Annual rhythms of temporal niche partitioning in the Sparidae family are correlated to different environmental variables

none11siopenSbragaglia, Valerio; Nuñez, Jesús D.; Dominoni, Davide; Coco, Salvatore; Fanelli, Emanuela; Azzurro, Ernesto; Marini, Simone; Nogueras, Marc; Ponti, Massimo; del Rio Fernandez, Joaquin; Aguzzi, JacopoSbragaglia, Valerio; Nuñez, Jesús D.; Dominoni, Davide; Coco, Salvatore; Fanelli, Emanuela; Azzurro, Ernesto; Marini, Simone; Nogueras, Marc; Ponti, Massimo; del Rio Fernandez, Joaquin; Aguzzi, Jacop

Attenuation of Listeria monocytogenes Virulence by Cannabis sativa L. Essential Oil

Anti-virulence strategies are being explored as a novel approach to combat pathogens. Such strategies include inhibition of surface adhesion, tissue invasion, toxin production, and/or interference with the gene regulation of other virulence traits. Listeria monocytogenes, the causative agent of listeriosis, is a facultative intracellular food pathogen characterized by a wide distribution in the environment. Its ability to persist within biofilms and to develop resistance to sanitizers is the cause of significant problems in food processing plants and of steep costs for the food industry. In humans, the treatment of listeriosis is hampered by the intracellular location of listeriae and the poor intracellular penetration of some antibiotics. Eleven L. monocytogenes isolates from patients who were diagnosed with invasive listeriosis in Italy in 2014–2016 were studied. This in vitro and in vivo study explored the antibacterial and anti-virulence properties of a steam-distilled essential oil of Cannabis sativa L., which is being intensively investigated for its high content in powerful bioactive phytochemicals. Susceptibility experiments demonstrated a moderate bactericidal activity of the essential oil (Minimum Bactericidal Concentration > 2048 μg/mL). Assessment of the effects of sublethal concentrations of the essential oil on L. monocytogenes virulence traits demonstrated a significant action on motility. Listeriae were non-motile after exposure to the essential oil. Light and scanning electron microscopy documented aggregates of listeriae with the flagella trapped inside the cluster. Real-time RT-PCR experiments showed downregulation of flagellar motility genes and of the regulatory gene prfA. The ability to form biofilm and to invade Caco-2 cells was also significantly reduced. Galleria mellonella larvae infected with L. monocytogenes grown in presence of sublethal concentrations of the essential oil showed much higher survival rates compared with controls, suggesting that the extract inhibited tissue invasion. Food contamination with L. monocytogenes is a major concern for the food industry, particularly for plants making ready-to-eat and processed food. The present work provides a baseline in the study of the anti-virulence properties of the C. sativa essential oil against L. monocytogenes. Further studies are needed to understand if it could be used as an alternative agent for the control of L. monocytogenes in food processing plants

Genetic Inhibition of the Ubiquitin Ligase Rnf5 Attenuates Phenotypes Associated to F508del Cystic Fibrosis Mutation

Cystic fibrosis (CF) is caused by mutations in the CFTR chloride channel. Deletion of phenylalanine 508 (F508del), the most frequent CF mutation, impairs CFTR trafficking and gating. F508del-CFTR mistrafficking may be corrected by acting directly on mutant CFTR itself or by modulating expression/activity of CFTR-interacting proteins, that may thus represent potential drug targets. To evaluate possible candidates for F508del-CFTR rescue, we screened a siRNA library targeting known CFTR interactors. Our analysis identified RNF5 as a protein whose inhibition promoted significant F508del-CFTR rescue and displayed an additive effect with the investigational drug VX-809. Significantly, RNF5 loss in F508del-CFTR transgenic animals ameliorated intestinal malabsorption and concomitantly led to an increase in CFTR activity in intestinal epithelial cells. In addition, we found that RNF5 is differentially expressed in human bronchial epithelia from CF vs. control patients. Our results identify RNF5 as a target for therapeutic modalities to antagonize mutant CFTR proteins