Estimations of length-weight relationships and consumption rates of odontocetes in the Mediterranean Sea from stranding data

Stranding data provide fundamental information on biometric traits of cetaceans useful to increase knowledge on ecological traits and their consumption patterns. In this study, the length weight (L-W) relationships through the power regression model (W = a ×Lb ) were calculated for three dolphin species (the striped dolphin, the common bottlenose dolphin and the Risso’s dolphin) in several Mediterranean subregions and at the scale of the entire basin. Length (L) and weight (W) data were collected from stranding records during the period from 1983 to 2021 acquired from several databases and the literature. Starting from L-W relationships, a bootstrap method was applied to estimate the mean body weights, the daily ingested biomass (IB) and annual food consumption (AFC) rates of different dolphin species. In particular, four different equations were used to estimate the IB rates. Prey consumption by dolphin species was calculated through AFC rates and the available diet information (expressed in weight fractions) of dolphin species for different Mediterranean subregions. Considering the L-W relationships in the Mediterranean Sea, b coefficient values were equal to 2.578, 2.975 and 2.988 for the striped, the common bottlenose and the Risso’s dolphin, respectively. At the Mediterranean scale, the AFC values estimated were 3913 kg (CI 2469–5306) for the Risso’s dolphin, 2571 kg (1372–3963) for the common bottlenose dolphin and 1118 kg (531–1570) for the striped dolphin. Prey consumption pattern showed a clear partitioning among the investigated species, where the common bottlenose dolphin exploits neritic demersal and pelagic fishes (e.g. eel fishes, sparids), the striped dolphin exploits mesopelagic fishes and myctophids, and the Risso’s dolphin was specialized on bathyal cephalopods of Histioteuthidae family. The results obtained in this study provide new information for the investigated species in several Mediterranean subregions providing a first consistent baseline to support the population dynamics modelling. At the same time, the wide uncertainty ranges of some parameters, as well as the lack of information for some species, stress the necessity of improving the data collection associated to stranding events, especially in the southern Mediterranean areas

Managing multiple pressures for cetaceans’ conservation with an Ecosystem-Based Marine Spatial Planning approach

Despite the recognized important ecological role that cetaceans play in the marine environment, their protection is still scarcely enforced in the Mediterranean Sea even though this area is strongly threatened by local human pressures and climate change. The piecemeal of knowledge related to cetaceans' ecology and distribution in the basin undermines the capacity of addressing cetaceans' protection and identifying effective conservation strategies. In this study, an Ecosystem-Based Marine Spatial Planning (EB-MSP) approach is applied to assess human pressures on cetaceans and guide the designation of a conservation area in the Gulf of Taranto, Northern Ionian Sea (Central-eastern Mediterranean Sea). The Gulf of Taranto hosts different cetacean species that accomplish important phases of their life in the area. Despite this fact, the gulf does not fall within any area-based management tools (ABMTs) for cetacean conservation. We pin down the Gulf of Taranto being eligible for the designation of diverse ABMTs for conservation, both legally and non-legally binding. Through a risk-based approach, this study explores the cause-effect relationships that link any human activities and pressures exerted in the study area to potential effects on cetaceans, by identifying major drivers of potential impacts. These were found to be underwater noise, marine litter, ship collision, and competition and disturbance on preys. We draw some recommendations based on different sources of available knowledge produced so far in the area (i.e., empirical evidence, scientific and grey literature, and expert judgement) to boost cetaceans’ conservation. Finally, we stress the need of sectoral coordination for the management of human activities by applying an EB-MSP approach and valuing the establishment of an ABMT in the Gulf of Taranto

A possible role of fzd10 delivering exosomes derived from colon cancers cell lines in inducing activation of epithelial–mesenchymal transition in normal colon epithelial cell line

Exosomes belong to the family of extracellular vesicles released by every type of cell both in normal and pathological conditions. Growing interest in studies indicates that extracellular vesicles, in particular, the fraction named exosomes containing lipids, proteins and nucleic acid, represent an efficient way to transfer functional cargoes between cells, thus combining all the other cell–cell interaction mechanisms known so far. Only a few decades ago, the involvement of exosomes in the carcinogenesis in different tissues was discovered, and very recently it was also observed how they carry and modulate the presence of Wnt pathway proteins, involved in the carcinogenesis of gastrointestinal tissues, such as Frizzled 10 protein (FZD10), a membrane receptor for Wnt. Here, we report the in vitro study on the capability of tumor-derived exosomes to induce neoplastic features in normal cells. Exosomes derived from two different colon cancer cell lines, namely the non-metastatic CaCo-2 and the metastatic SW620, were found to deliver, in both cases, FZD10, thus demonstrating the ability to reprogram normal colonic epithelial cell line (HCEC-1CT). Indeed, the acquisition of specific mesenchymal characteristics, such as migration capability and expression of FZD10 and markers of mesenchymal cells, was observed. The exosomes derived from the metastatic cell line, characterized by a level of FZD10 higher than the exosomes extracted from the non-metastatic cells, were also more efficient in stimulating EMT activation. The overall results suggest that FZD10, delivered by circulating tumor-derived exosomes, can play a relevant role in promoting the CRC carcinogenesis and propagation

Application of a multi-species bio-economic modelling approach to explore fishing traits within eligible cetacean conservation areas in the Northern Ionian Sea (Central Mediterranean Sea)

The assessment of the spatial overlap between eligible cetacean conservation areas (CCAs) and fishing grounds could be a strategic element in the implementation of effective conservation measures in the pelagic offshore areas. A multi-species bio-economic modelling approach has been applied to estimate the fishing traits in eligible CCAs in the Northern Ionian Sea (NIS, Central Mediterranean Sea) between 10-800 m of depth, adopting the Spatial MAnagement of demersal Resources for Trawl fisheries model (SMART). Four possible CCAs were defined according to the distribution of cetacean species, their bio-ecological needs, as well as socio-economic needs of human activities, identifying a Blue, Red, Orange and Green CCAs in the NIS. SMART spatial domain was a grid with 500 square cells (15x15 NM). The analysis was conducted for the period 2016-2019, considering the Otter Trawl Bottom (OTB) fleet activities in the study areas through the Vessel Monitoring System. The spatial extension of fishing activities, hourly fishing effort (h), landings (tons) and economic value (euros) for each CCA and the NIS were estimated as yearly median values. Fishing activities were absent in the Blue CCA, where the presence of the submarine canyon head does not offer accessible fishing grounds. The hourly fishing effort in the Green area accounted for about 22% (3443 h) of the total hourly effort of the NIS, while the Orange and Red areas were about 8% (1226 h) and 2% (295 h), respectively. The Green CCA corresponded to about 14% (36 tons) of the total landings in the NIS, whereas the Orange and Red areas represented about 9% (22 tons) and 6% (16 tons), respectively. The Green CCA accounted for about 13% (156 thousand euros) of the total economic value of the NIS, while the Orange and Red areas represented about 6% (69 thousand euros) and 4% (44thousand euros), respectively. Results showed no or negligible negative effects on trawl activities by potential spatial restrictions due to the establishment of CCAs highlighting the importance to consider spatially integrated information during the establishment process of conservation areas for cetacean biodiversity according to the principles of Ecosystem Based Management

Top-down cascading effects driven by the odontocetes in the Gulf of Taranto (Northern Ionian Sea, Central Mediterranean Sea)

An investigation of the marine food web in the Gulf of Taranto (Northern Ionian Sea, Central Mediterranean Sea) was carried out to explore the top-down cascading effects driven by the Odontocetes. The food web was analysed by a mass-balance model using 51 functional groups and detailing the trophic impacts of the striped and common bottlenose dolphins, the Risso's dolphin and the sperm whale during the period 2010-2014. Odontocetes resulted top-predators with the highest TL estimated for the Risso's dolphin (TL=5.40) and the lowest for the common bottlenose dolphin (TL=4.47). The striped dolphin played the highest top-down control, showing cascading effects up to the 3rd TL. The Risso's dolphin and the sperm whale played similar cascading effects, but weaker than the striped dolphin. Understanding pattern and strengthen of trophic controls played by the Odontocetes within the food web could contribute to identify the basal mechanisms involved in the ecosystem functioning

Identification of subgroups of early breast cancer patients at high risk of nonadherence to adjuvant hormone therapy: results of an italian survey.

The aim of this study was the identification of subgroups of patients at higher risk of nonadherence to adjuvant hormone therapy for breast cancer. Using recursive partitioning and amalgamation (RECPAM) analysis, the highest risk was observed in the group of unmarried, employed women, or housewives. This result might be functional in designing tailored intervention studies aimed at improvement of adherence. Background: Adherence to adjuvant endocrine therapy (HT) is suboptimal among breast cancer patients. A high rate of nonadherence might explain differences in survival between clinical trial and clinical practice. Tailored interventions aimed at improving adherence can only be implemented if subgroups of patients at higher risk of poor adherence are identified. Because no data are available for Italy, we undertook a large survey on adherence among women taking adjuvant HT for breast cancer. Patients and Methods: Patients were recruited from 10 cancer clinics in central Italy. All patients taking HT for at least 1 year were invited, during one of their follow-up visit, to fill a confidential questionnaire. The association of sociodemographic and clinical characteristics of participants with adherence was assessed using logistic regression. The RECPAM method was used to evaluate interactions among variables and to identify subgroups of patients at different risk of nonadherence. Results: A total of 939 patients joined the study and 18.6% of them were classified as nonadherers. Among possible predictors, only age, working status, and switching from tamoxifen to an aromatase inhibitor were predictive of nonadherence in multivariate analysis. RECPAM analysis led to the identification of 4 classes of patients with a different likelihood of nonadherence to therapy, the lowest being observed in retired women with a low level of education, the highest in the group of unmarried, employed women, or housewives. Conclusion: The identification of these subgroups of “real life” patients with a high prevalence of nonadherers might be functional in designing intervention studies aimed at improving adherenc

Patient{'}s adherence on pharmacological therapy for benign prostatic hyperplasia (BPH)-associated lower urinary tract symptoms (LUTS) is different: Is combination therapy better than monotherapy

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Addressing cetacean–fishery interactions to inform a deep-sea ecosystem-based management in the Gulf of Taranto (Northern Ionian Sea, Central Mediterranean Sea)

Understanding of cetaceans’ trophic role and the quantification of their impacts on the food web is a critical task, especially when data on their prey are linked to deep-sea ecosystems, which are often exposed to excessive exploitation of fishery resources due to poor management. This aspect represents one of the major issues in marine resource management, and trade-offs are needed to simultaneously support the conservation of cetaceans and their irreplaceable ecological role, together with sustainable fishing yield. In that regard, food web models can represent useful tools to support decision-making processes according to an ecosystem-based management (EBM) approach. This study provides a focus on the feeding activity occurrence and the trophic interactions between odontocetes and the fishery in the marine food web of the Gulf of Taranto (Northern Ionian Sea, Central Mediterranean Sea), by zooming in on cetaceans’ prey of commercial interest. In particular, the quantification of trophic impacts is estimated using a food web mass-balance model that integrates information on the bathymetric displacement of both cetaceans’ prey and fishing activity. The results are discussed from a management perspective to guide future research and knowledge enhancement activities as well as support the implementation of an EBM approach

Environmental variables and machine learning models to predict cetacean abundance in the Central-eastern Mediterranean Sea

: Although the Mediterranean Sea is a crucial hotspot in marine biodiversity, it has been threatened by numerous anthropogenic pressures. As flagship species, Cetaceans are exposed to those anthropogenic impacts and global changes. Assessing their conservation status becomes strategic to set effective management plans. The aim of this paper is to understand the habitat requirements of cetaceans, exploiting the advantages of a machine-learning framework. To this end, 28 physical and biogeochemical variables were identified as environmental predictors related to the abundance of three odontocete species in the Northern Ionian Sea (Central-eastern Mediterranean Sea). In fact, habitat models were built using sighting data collected for striped dolphins Stenella coeruleoalba, common bottlenose dolphins Tursiops truncatus, and Risso's dolphins Grampus griseus between July 2009 and October 2021. Random Forest was a suitable machine learning algorithm for the cetacean abundance estimation. Nitrate, phytoplankton carbon biomass, temperature, and salinity were the most common influential predictors, followed by latitude, 3D-chlorophyll and density. The habitat models proposed here were validated using sighting data acquired during 2022 in the study area, confirming the good performance of the strategy. This study provides valuable information to support management decisions and conservation measures in the EU marine spatial planning context