Search

Background: The optimal antithrombotic (antiplatelet or anticoagulant) treatment of patients undergoing extracranial carotid artery interventions is a subject of debate. The aim of this multidisciplinary document was to critically review the recommendations of current guidelines, taking into consideration the results of recendy published studies. Methods:The various antithrombotic strategies reported were evaluated for asymptomatic and symptomatic patients undergoing extracranial carotid artery interventions (endarterectomy, transfemoral carotid artery stenting [CAS] or transcarotid artery revascularization [TCAR]). Based on a critical review, a series of recommendations were formulated by an international expert panel. Results: For asymptomatic patients, we recommend low-dose aspirin (75-100 ing/day) or dopidogrel (75 mg/day) with the primary goal to reduce the risk of myocardial infarction and cardiovascular event rates rather than to reduce the risk of stroke. For symptomatic patients, we recommend dual antiplatelet treatment (DAFT) initiated within 24 h of the index event to reduce the risk of recurrent events. We suggest that following transfemoral CAS or TCAR, patients continue DAFT for 1 month after which a single antiplatelet agent is used. High level of evidence to support anticoagulant treatment for patients with carotid artery disease is lacking. Condusions: The antithrombotic treatment offered to carotid patients should be individualized, taking into account the presence of symptoms, the type of intervention and the goal of the treatment. The duration and type of DAFr (ticagrelor instead of dopidogrel) should be evaluated in future trials. [ABSTRACT FROM AUTHOR]

International guidelines strongly recommend statins alone or in combination with other lipid-lowering agents to lower low-density lipoprotein cholesterol (LDL-C) levels for patients with asymptomatic/symptomatic carotid stenosis (AsxCS/SCS). Lowering LDL-C levels is associated with significant reductions in transient ischemic attack, stroke, cardiovascular (CV) event and death rates. The aim of this multi-disciplinary overview is to summarize the benefits and risks associated with lowering LDL-C with statins or non-statin medications for Asx/SCS patients. The cerebrovascular and CV beneficial effects associated with statins, proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors and other non-statin lipid-lowering agents (e.g. fibrates, ezetimibe) are reviewed. The use of statins and PCSK9 inhibitors is associated with several beneficial effects for Asx/SCS patients, including carotid plaque stabilization and reduction of stroke rates. Ezetimibe and fibrates are associated with smaller reductions in stroke rates. The side-effects resulting from statin and PCSK9 inhibitor use are also highlighted. The benefits associated with lowering LDL-C with statins or non-statin lipid lowering agents (e.g. PCSK9 inhibitors) outweigh the risks and potential side-effects. Irrespective of their LDL-C levels, all Asx/SCS patients should receive high-dose statin treatment±ezetimibe or PCSK9 inhibitors for reduction not only of LDL-C levels, but also of stroke, cardiovascular mortality and coronary event rates. [ABSTRACT FROM AUTHOR]

The competition for marine space is a recognized challenge, and the implementation of new activities, such as those emerging from Blue Growth initiatives, may amplify this competition. The marine spatial planning (MSP) framework requires decision makers to analyse spatially explicit environmental and socio-economic data to determine where user conflicts are or might emerge and consider several potential management scenarios. In the present research, a spatially explicit Bayesian belief network (BBN) was applied for this purpose. The BBN was developed to analyse the potential reallocation of artisanal fishing effort to alternative sites due to the introduction of a new, non-take area: an offshore aquaculture site along the Basque continental shelf. The constructed model combined discrete, operational fisheries data, continuous environmental data, and expert judgment to produce fishing activity suitability maps for three different métiers (longlines, nets and traps). The BBN was run with various effort reallocation scenarios for each metier, and the best alternative fishing locations were identified based on environmental suitability, past revenue, and past fishing presence. The closure had a lesser effect on net and longline activity, displacing 10% and 7% of local fishing effort respectively. Comparatively, 50% of all local effort by traps took place within the closed grounds, and few alternative sites were identified. Nets were found to have the greatest number of alternative fishing grounds surrounding the aquaculture site. The present research demonstrates how BBNs can support spatially explicit scenario building and user-user conflict analysis for sustainable and successful ecosystem-based marine spatial planning. [ABSTRACT FROM AUTHOR]

Semi-automated classification of zooplankton allows increasing the number of processed samples cost-effectively, albeit with a relatively limited taxonomic accuracy, partly because cost-efficiency trade-off but also due to technological limitations that might be overcome in the future. The present study tests the suitability of using a cost-efficient semi-automated classification methodology as a tool to assess zooplankton indicators for the purpose of the EU Marine Strategy Framework Directive, using samples collected in the Baltic Sea. In this brackish ecosystem the zooplankton individuals are small-bodied and therefore their identification with semi-automated classification is challenging. However, results show that semi-automated zooplankton classification provides a taxonomic classification level that is sufficient for a number of proposed indicators. This analysis also points out weakness of the methodology and proposes already proved solutions based on the latest development of these methodologies applied to zooplankton classification. As proved in the Baltic Sea, complementing manual zooplankton analyses with the semi-automated classification offers new advantages for marine environment assessment. [ABSTRACT FROM AUTHOR]

Maritime transport and shipping are impacted negatively by biofouling, which can result in increased fuel consumption. Thus, costs for fouling reduction can be considered an investment to reduce fuel consumption. Anti-fouling measures also reduce the rate of introduction of non-indigenous species (NIS). Further mitigation measures to reduce the transport of NIS within ballast water and sediments impose additional costs. The estimated operational cost of NIS mitigation measures may represent between 1.6% and 4% of the annual operational cost for a ship operating on European seas, with the higher proportional costs in small ships. However, fouling by NIS may affect fuel consumption more than fouling by native species due to differences in species’ life-history traits and their resistance to antifouling coatings and pollution. Therefore, it is possible that the cost of NIS mitigation measures could be smaller than the cost from higher fuel consumption arising from fouling by NIS. [ABSTRACT FROM AUTHOR]

Ecosystems consist of complex dynamic interactions among species and the environment, the understanding of which has implications for predicting the environmental response to changes in climate and biodiversity. However, with the recent adoption of more explorative tools, like Bayesian networks, in predictive ecology, few assumptions can be made about the data and complex, spatially varying interactions can be recovered from collected field data. In this study, we compare Bayesian network modelling approaches accounting for latent effects to reveal species dynamics for 7 geographically and temporally varied areas within the North Sea. We also apply structure learning techniques to identify functional relationships such as prey–predator between trophic groups of species that vary across space and time. We examine if the use of a general hidden variable can reflect overall changes in the trophic dynamics of each spatial system and whether the inclusion of a specific hidden variable can model unmeasured group of species. The general hidden variable appears to capture changes in the variance of different groups of species biomass. Models that include both general and specific hidden variables resulted in identifying similarity with the underlying food web dynamics and modelling spatial unmeasured effect. We predict the biomass of the trophic groups and find that predictive accuracy varies with the models' features and across the different spatial areas thus proposing a model that allows for spatial autocorrelation and two hidden variables. Our proposed model was able to produce novel insights on this ecosystem's dynamics and ecological interactions mainly because we account for the heterogeneous nature of the driving factors within each area and their changes over time. Our findings demonstrate that accounting for additional sources of variation, by combining structure learning from data and experts' knowledge in the model architecture, has the potential for gaining deeper insights into the structure and stability of ecosystems. Finally, we were able to discover meaningful functional networks that were spatially and temporally differentiated with the particular mechanisms varying from trophic associations through interactions with climate and commercial fisheries. [ABSTRACT FROM AUTHOR]

The effect of different factors (spawning biomass, environmental conditions) on recruitment is a subject of great importance in the management of fisheries, recovery plans and scenario exploration. In this study, recently proposed supervised classification techniques, tested by the machine-learning community, are applied to forecast the recruitment of seven fish species of North East Atlantic (anchovy, sardine, mackerel, horse mackerel, hake, blue whiting and albacore), using spawning, environmental and climatic data. In addition, the use of the probabilistic flexible naive Bayes classifier (FNBC) is proposed as modelling approach in order to reduce uncertainty for fisheries management purposes. Those improvements aim is to improve probability estimations of each possible outcome (low, medium and high recruitment) based in kernel density estimation, which is crucial for informed management decision making with high uncertainty. Finally, a comparison between goodness-of-fit and generalization power is provided, in order to assess the reliability of the final forecasting models. It is found that in most cases the proposed methodology provides useful information for management whereas the case of horse mackerel is an example of the limitations of the approach. The proposed improvements allow for a better probabilistic estimation of the different scenarios, i.e. to reduce the uncertainty in the provided forecasts. [ABSTRACT FROM AUTHOR]

Fishery monitoring programs are essential for effective management of marine resources, as they provide scientists and managers with the necessary data for both the preparation of scientific advice and fisheries control and surveillance. The monitoring is generally done by human observers, both in port and onboard, with a high cost involved. Consequently, some Regional Fisheries Management Organizations (RFMO) are opting for electronic monitoring (EM) as an alternative or complement to human observers in certain fisheries. This is the case of the tropical tuna purse seine fishery operating in the Indian and Atlantic oceans, which started an EM program on a voluntary basis in 2017. However, even when the monitoring is conducted though EM, the image analysis is a tedious task manually performed by experts. In this paper, we propose a cost-effective methodology for the automatic processing of the images already being collected by cameras onboard tropical tuna purse seiners. Firstly, the images are preprocessed to homogenize them across all vessels and facilitate subsequent steps. Secondly, the fish are individually segmented using a deep neural network (Mask R-CNN). Then, all segments are passed through other deep neural network (ResNet50V2) to classify them by species and estimate their size distribution. For the classification of fish, we achieved an accuracy for all species of over 70%, i.e., about 3 out of 4 individuals are correctly classified to their corresponding species. The size distribution estimates are aligned with official port measurements but calculated using a larger number of individuals. Finally, we also propose improvements to the current image capture systems which can facilitate the work of the proposed automation methodology. [ABSTRACT FROM AUTHOR]

The recommendations of international guidelines for the management of asymptomatic carotid stenosis (ACS) often vary considerably and extend from a conservative approach with risk factor modification and best medical treatment (BMT) alone, to a more aggressive approach with a carotid intervention plus BMT. The aim of the current multispecialty position statement is to reconcile the conflicting views on the topic. A literature review was performed with a focus on data from recent studies. Several clinical and imaging high-risk features have been identified that are associated with an increased long-term ipsilateral ischemic stroke risk in patients with ACS. Such high-risk clinical/imaging features include intraplaque hemorrhage, impaired cerebrovascular reserve, carotid plaque echolucency/ulceration/ neovascularization, a lipid-rich necrotic core, a thin or ruptured fibrous cap, silent brain infarction, a contralateral transient ischemic attack/stroke episode, male patients < 75 years and microembolic signals on transcranial Doppler. There is growing evidence that 80–99% ACS indicate a higher stroke risk than 50–79% stenoses. Although aggressive risk factor control and BMT should be implemented in all ACS patients, several high-risk features that may increase the risk of a future cerebrovascular event are now documented. Consequently, some guidelines recommend a prophylactic carotid intervention in high-risk patients to prevent future cerebrovascular events. Until the results of the much-anticipated randomized controlled trials emerge, the jury is still out regarding the optimal management of ACS patients. [ABSTRACT FROM AUTHOR]

Objectives: The recommendations of international guidelines for the management of asymptomatic carotid stenosis (ACS) often vary considerably and extend from a conservative approach with risk factor modification and best medical treatment (BMT) alone, to a more aggressive approach with a carotid intervention plus BMT. The aim of the current multispecialty position statement is to reconcile the conflicting views on the topic.Materials and Methods: A literature review was performed with a focus on data from recent studies.Results: Several clinical and imaging high-risk features have been identified that are associated with an increased long-term ipsilateral ischemic stroke risk in patients with ACS. Such high-risk clinical/imaging features include intraplaque hemorrhage, impaired cerebrovascular reserve, carotid plaque echolucency/ulceration/ neovascularization, a lipid-rich necrotic core, a thin or ruptured fibrous cap, silent brain infarction, a contralateral transient ischemic attack/stroke episode, male patients < 75 years and microembolic signals on transcranial Doppler. There is growing evidence that 80-99% ACS indicate a higher stroke risk than 50-79% stenoses.Conclusions: Although aggressive risk factor control and BMT should be implemented in all ACS patients, several high-risk features that may increase the risk of a future cerebrovascular event are now documented. Consequently, some guidelines recommend a prophylactic carotid intervention in high-risk patients to prevent future cerebrovascular events. Until the results of the much-anticipated randomized controlled trials emerge, the jury is still out regarding the optimal management of ACS patients. [ABSTRACT FROM AUTHOR]