Phylogeny and synonymy of Gyrodinium heterostriatum comb. nov. (Dinophyceae), a common unarmored dinoflagellate in the world oceans

© The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Gómez, F., Artigas, L.F., Gast, R.J. Phylogeny and synonymy of Gyrodinium heterostriatum comb. nov. (Dinophyceae), a common unarmored dinoflagellate in the world oceans. Acta Protozoologica, 59 (2), (2020): 77-87, doi: 10.4467/16890027AP.20.007.12675.The North Sea and the English Channel are regions with a long tradition of plankton studies, where the colony-forming haptophyte Phaeocystis globosa dominates the spring phytoplankton blooms. Among its predators, we investigated an abundant unarmored dinoflagellate (~3000 cells per liter) in the North Sea in May 2019. It has been reported in the literature as Gymnodinium heterostriatum or G. striatissimum, and often identified as Gyrodinium spirale. Phylogenetic analyses using the small-, large subunit- and Internal Transcriber Spacers of the ribosomal RNA (SSU-, LSU-, ITS rRNA) gene sequences indicate that our isolates clustered within the Gyrodinium clade. The new sequences formed a sister group with sequences of the freshwater taxon Gyrodinium helveticum, being one of the infrequent marine-freshwater transitions in the microbial world. This isolate is the first characterized member of a clade of numerous environmental sequences widely distributed from cold to tropical seas. This common and abundant taxon has received several names due to its morphological plasticity (changes of size and shape, often deformed after engulfing prey) and the difficulty in discerning surface striation. We conclude that the priority is for the species name Gymnodinium heterostriatum Kofoid & Swezy 1921, a new name that was proposed for Gymnodinium spirale var. obtusum sensu Dogiel 1906. The species Gyrodinium striatissimum (Hulburt 1957) Gert Hansen & Moestrup 2000 and Gymnodinium lucidum D. Ballantine in Parke & Dixon 1964 (=G. hyalinum M. Lebour 1925) are posterior synonyms. We propose Gyrodinium heterostriatum comb. nov. for Gymnodinium heterostriatum.F.G. was partly supported by the convention #2101893310 between CNRS INSU and the French Ministry of Ecology (MTES) for the implementation of the Monitoring Program of the European Marine Strategy Framework directive (MSFD) for pelagic habitats and the descriptor ‘biodiversity’. Samples were collected within the framework of JERICO-NEXT (www.jerico-ri.eu), a European (H2020) project to establish a joint international network of coastal observatories, during a 4-day collaborative monitoring campaign of the Southern North Sea. Part of the infrastructure and data were provided by VLIZ (Flanders Marine Institute) and funded by Research Foundation-Flanders (FWO) as part of the Belgian contribution to the LifeWatch project

Wireless Sensor Networks for Ecosystem Monitoring & Port Surveillance

International audienceProviding a wide variety of the most up - to - date innovations in sensor technology and sensor networks, our current project should achieve two major goals. The first goal covers various issues related to the public maritime transport safety and security, such as the coastal and port surveillance systems. While the second one w ill improve the capacity of public authorities to develop and implement smart environment policies by monitoring the shallow coastal water ecosystems. At this stage of our project, a surveillance platform has been already installed near the "Molène Island" which is a small but the largest island of an archipelago of many islands located off the West coast of Brittany in North Western France. Our final objective is to add various sensors as well as to design, develop and implement new algorithms to extend th e capacity of the existing platform and reach the goals of our project. Finally, this manuscript introduces the identified approaches as well as t he second phase of the project which consists in analyzing living underwater micro - organisms (the population o f Marine Micro - Organisms, i.e. MMOs such as Phytoplankton and Zooplankton micro - zooplankton, but also heterotrophic bacterioplankton) in order to predict the health conditions of the macro - environment s . In addition, this communication discusses developed t echniques and concepts to deal with several practical problems related to our project. Some results are given and the whole system architecture is briefly described. This manuscript will also addresses the national benefit of such projects in the case of t hree different countries (Australia, France and KS

Combination of 'machine learning' methodologies and imaging- in-flow system to detect Harmful Algae semi-automatically

In recent years, improvements in data acquisition techniques have been carried out to sample, characterize and quantify phytoplankton communities at high temporal and geographical resolution, with a special focus on potential harmful algae, during oceanographic campaigns or in the frame of monitoring networks (to support knowledge but also for EU Directives and Regional Sea Convention needs). These acquisition and digitization techniques, including 'imaging-in-flow' systems, allow to process a high number of samples and, consequently, generate an important quantity of data in which the presence of target events might not be detected. Indeed, as for traditional samples analysis with inverted microscope, a full manual quantification of the particles based on a simple visual inspection can be time-consuming, tedious and consequently lead to erroneous or wrong identifications. For this purpose, the ZooImage R-package was and is still being developed to allow greater automation in data classification and analysis while also permitting some user-interaction during the process. The proposed methodology consists in combining few expert knowledge and machine learning algorithms at different levels: (i) to classify particles into different groups based on the definition and the adaptation of a specific training set through the use of 'contextual data'; (ii) to detect and partially validate the 'most suspect' predictions, based on a probability of misclassification; (iii) to estimate the number of cells for each colonial form thanks to the building of specific predictive models. These different semi-automated tools were applied to the in vivo image dataset acquired with the FlowCam instrument during the September-October CAMANOC 2014 (Ifremer) cruise in the English Channel, in order to evaluate their operational ability to monitor the diversity of samples for the microphytoplankton, and especially to detect, track and count the most frequent potentially harmful algae found in this area at that period, like species belonging to Pseudo-nitzschia, Dinophysis, Prorocentrum and Phaeocystis genera. A distribution of these target groups was computed which highlights different sub-regions in the English Channel during the late summer-fall transition

Status of pelagic habitats within the EU-Marine Strategy Framework Directive: Proposals for improving consistency and representativeness of the assessment

Anthropogenic activities have transformed the pelagic habitat in the last decades with profound implications for its essential functions. While the EU-Marine Strategy Framework Directive 2008/56/EC and the Commission Decision (EU) 2017/848 have set criteria and methodological standards for the assessment and determination of Good Environmental Status (GES) for pelagic habitats in EU waters, there is strong evidence that Member States have not yet harmonized the pelagic GES assessment across EU marine waters. Today, pelagic habitats are assessed by evaluating whether good status is achieved by each of the pelagic indicators, but this approach fails to observe the high variability of the pelagic environment. To this end, GES is not estimated at pelagic habitats scale but only for each individual indicator. This paper synthesises the latest developments on pelagic habitats assessment and identifies the main factors limiting the consistency of the assessment across Member States: i) coarse spatial and temporal scales of sampling effort as regards to the pelagic habitat dynamics, ii) little consideration of the whole range of plankton (and, to some extent, of zooplankton) size and trophic spectra, iii) lack of integrated hydro-biogeochemical and biological studies and collaboration among experts from different scientific fields, iv) limited availability of pressure-based indicators, and v) lack of integration methods of the pelagic indicators’ status for the GES determination. This analysis demonstrates the importance of maintaining a consistent sampling frequency and a spatially extensive network of stations across the gradient of anthropogenic pressures, where spatial environmental data can help objectively extrapolating field data.The authors would like to thank the Pelagic Habitats Experts, part of the MSFD Biodiversity Expert Network for the fruitful discussions on the harmonisation of the MSFD assessment and monitoring for pelagic habitats. CM, MP, JND, and AP were funded by the Joint Research Centre of Ispra (Italy). IV wishes to acknowledge support from the program “Monitoring and recording the situation of the marine sub-regions of Greece / Upgrading and functional updating of the MSFD monitoring network”, funded by national and EU funds under National Strategic Reference Framework 2014–2020 (MIS 5010880), and the European project ABIOMMED: Support coherent and coordinated assessment of biodiversity and measures across Mediterranean for the next 6-year cycle of MSFD implementation, funded by DG Environment (11.0661/2020/839620/SUB/ENV.C2), coordinator Dr. Kalliopi Pagou, HCMR.Peer reviewe

The Plankton Lifeform Extraction Tool: a digital tool to increase the discoverability and usability of plankton time-series data

Publication history: Accepted - 25 October 2021; Published online - 6 December 2021.Plankton form the base of the marine food web and are sensitive indicators of environmental change. Plankton time series are therefore an essential part of monitoring progress towards global biodiversity goals, such as the Convention on Biological Diversity Aichi Targets, and for informing ecosystem-based policy, such as the EU Marine Strategy Framework Directive. Multiple plankton monitoring programmes exist in Europe, but differences in sampling and analysis methods prevent the integration of their data, constraining their utility over large spatio-temporal scales. The Plankton Lifeform Extraction Tool brings together disparate European plankton datasets into a central database from which it extracts abundance time series of plankton functional groups, called “lifeforms”, according to shared biological traits. This tool has been designed to make complex plankton datasets accessible and meaningful for policy, public interest, and scientific discovery. It allows examination of large-scale shifts in lifeform abundance or distribution (for example, holoplankton being partially replaced by meroplankton), providing clues to how the marine environment is changing. The lifeform method enables datasets with different plankton sampling and taxonomic analysis methodologies to be used together to provide insights into the response to multiple stressors and robust policy evidence for decision making. Lifeform time series generated with the Plankton Lifeform Extraction Tool currently inform plankton and food web indicators for the UK's Marine Strategy, the EU's Marine Strategy Framework Directive, and for the Convention for the Protection of the Marine Environment of the North-East Atlantic (OSPAR) biodiversity assessments. The Plankton Lifeform Extraction Tool currently integrates 155 000 samples, containing over 44 million plankton records, from nine different plankton datasets within UK and European seas, collected between 1924 and 2017. Additional datasets can be added, and time series can be updated. The Plankton Lifeform Extraction Tool is hosted by The Archive for Marine Species and Habitats Data (DASSH) at https://www.dassh.ac.uk/lifeforms/ (last access: 22 November 2021, Ostle et al., 2021). The lifeform outputs are linked to specific, DOI-ed, versions of the Plankton Lifeform Traits Master List and each underlying dataset.Funding that supports this work and the data collected has come from the European Commission, European Union (EU) grant no. 11.0661/2015/712630/SUB/ENVC.2 OSPAR; UK Natural Environment Research Council (grant nos. NE/R002738/1 and NE/M007855/1); EMFF, Climate Linked Atlantic Sector Science (grant no. NE/R015953/1), Department for Environment, Food and Rural Affairs, UK Government (grant nos. ME-5308 and ME-414135), NSF USA OCE-1657887, DFO CA F5955150026/001/HAL, Natural Environment Research Council UK (grant no. NC-R8/H12/100); Horizon 2020 (MISSION ATLANTIC (grant no. 862428)); iCPR (grant no. SBFF-2019-36526), IMR Norway; DTU Aqua Denmark; and the French Ministry of Environment, Energy, and the Sea (MEEM). Recent funding for the development of PLET and the Pelagic Habitats Indicator has been provided by HBDSEG/Defra and MMO/EMFF. The MSS Scottish Coastal Observatory data and analyses are funded and maintained by the Scottish Government Schedules of Service (grant nos. ST05a and ST02H), MSS Stonehaven Samplers, North Atlantic Fisheries College, Shetland, Orkney Islands Harbour Council, and Isle Ewe Shellfish

Clustering COVID-19 ARDS patients through the first days of ICU admission. An analysis of the CIBERESUCICOVID Cohort

Background Acute respiratory distress syndrome (ARDS) can be classified into sub-phenotypes according to different inflammatory/clinical status. Prognostic enrichment was achieved by grouping patients into hypoinflammatory or hyperinflammatory sub-phenotypes, even though the time of analysis may change the classification according to treatment response or disease evolution. We aimed to evaluate when patients can be clustered in more than 1 group, and how they may change the clustering of patients using data of baseline or day 3, and the prognosis of patients according to their evolution by changing or not the cluster.Methods Multicenter, observational prospective, and retrospective study of patients admitted due to ARDS related to COVID-19 infection in Spain. Patients were grouped according to a clustering mixed-type data algorithm (k-prototypes) using continuous and categorical readily available variables at baseline and day 3.Results Of 6205 patients, 3743 (60%) were included in the study. According to silhouette analysis, patients were grouped in two clusters. At baseline, 1402 (37%) patients were included in cluster 1 and 2341(63%) in cluster 2. On day 3, 1557(42%) patients were included in cluster 1 and 2086 (57%) in cluster 2. The patients included in cluster 2 were older and more frequently hypertensive and had a higher prevalence of shock, organ dysfunction, inflammatory biomarkers, and worst respiratory indexes at both time points. The 90-day mortality was higher in cluster 2 at both clustering processes (43.8% [n = 1025] versus 27.3% [n = 383] at baseline, and 49% [n = 1023] versus 20.6% [n = 321] on day 3). Four hundred and fifty-eight (33%) patients clustered in the first group were clustered in the second group on day 3. In contrast, 638 (27%) patients clustered in the second group were clustered in the first group on day 3.Conclusions During the first days, patients can be clustered into two groups and the process of clustering patients may change as they continue to evolve. This means that despite a vast majority of patients remaining in the same cluster, a minority reaching 33% of patients analyzed may be re-categorized into different clusters based on their progress. Such changes can significantly impact their prognosis

Globally consistent quantitative observations of planktonic ecosystems

In this paper we review the technologies available to make globally quantitative observations of particles in general—and plankton in particular—in the world oceans, and for sizes varying from sub-microns to centimeters. Some of these technologies have been available for years while others have only recently emerged. Use of these technologies is critical to improve understanding of the processes that control abundances, distributions and composition of plankton, provide data necessary to constrain and improve ecosystem and biogeochemical models, and forecast changes in marine ecosystems in light of climate change. In this paper we begin by providing the motivation for plankton observations, quantification and diversity qualification on a global scale. We then expand on the state-of-the-art, detailing a variety of relevant and (mostly) mature technologies and measurements, including bulk measurements of plankton, pigment composition, uses of genomic, optical and acoustical methods as well as analysis using particle counters, flow cytometers and quantitative imaging devices. We follow by highlighting the requirements necessary for a plankton observing system, the approach to achieve it and associated challenges. We conclude with ranked action-item recommendations for the next 10 years to move toward our vision of a holistic ocean-wide plankton observing system. Particularly, we suggest to begin with a demonstration project on a GO-SHIP line and/or a long-term observation site and expand from there, ensuring that issues associated with methods, observation tools, data analysis, quality assessment and curation are addressed early in the implementation. Global coordination is key for the success of this vision and will bring new insights on processes associated with nutrient regeneration, ocean production, fisheries and carbon sequestration

Hyperoxemia and excess oxygen use in early acute respiratory distress syndrome : Insights from the LUNG SAFE study

Publisher Copyright: © 2020 The Author(s). Copyright: Copyright 2020 Elsevier B.V., All rights reserved.Background: Concerns exist regarding the prevalence and impact of unnecessary oxygen use in patients with acute respiratory distress syndrome (ARDS). We examined this issue in patients with ARDS enrolled in the Large observational study to UNderstand the Global impact of Severe Acute respiratory FailurE (LUNG SAFE) study. Methods: In this secondary analysis of the LUNG SAFE study, we wished to determine the prevalence and the outcomes associated with hyperoxemia on day 1, sustained hyperoxemia, and excessive oxygen use in patients with early ARDS. Patients who fulfilled criteria of ARDS on day 1 and day 2 of acute hypoxemic respiratory failure were categorized based on the presence of hyperoxemia (PaO2 > 100 mmHg) on day 1, sustained (i.e., present on day 1 and day 2) hyperoxemia, or excessive oxygen use (FIO2 ≥ 0.60 during hyperoxemia). Results: Of 2005 patients that met the inclusion criteria, 131 (6.5%) were hypoxemic (PaO2 < 55 mmHg), 607 (30%) had hyperoxemia on day 1, and 250 (12%) had sustained hyperoxemia. Excess FIO2 use occurred in 400 (66%) out of 607 patients with hyperoxemia. Excess FIO2 use decreased from day 1 to day 2 of ARDS, with most hyperoxemic patients on day 2 receiving relatively low FIO2. Multivariate analyses found no independent relationship between day 1 hyperoxemia, sustained hyperoxemia, or excess FIO2 use and adverse clinical outcomes. Mortality was 42% in patients with excess FIO2 use, compared to 39% in a propensity-matched sample of normoxemic (PaO2 55-100 mmHg) patients (P = 0.47). Conclusions: Hyperoxemia and excess oxygen use are both prevalent in early ARDS but are most often non-sustained. No relationship was found between hyperoxemia or excessive oxygen use and patient outcome in this cohort. Trial registration: LUNG-SAFE is registered with ClinicalTrials.gov, NCT02010073publishersversionPeer reviewe

Outcomes of elective liver surgery worldwide: a global, prospective, multicenter, cross-sectional study

Background: The outcomes of liver surgery worldwide remain unknown. The true population-based outcomes are likely different to those vastly reported that reflect the activity of highly specialized academic centers. The aim of this study was to measure the true worldwide practice of liver surgery and associated outcomes by recruiting from centers across the globe. The geographic distribution of liver surgery activity and complexity was also evaluated to further understand variations in outcomes. Methods: LiverGroup.org was an international, prospective, multicenter, cross-sectional study following the Global Surgery Collaborative Snapshot Research approach with a 3-month prospective, consecutive patient enrollment within January–December 2019. Each patient was followed up for 90 days postoperatively. All patients undergoing liver surgery at their respective centers were eligible for study inclusion. Basic demographics, patient and operation characteristics were collected. Morbidity was recorded according to the Clavien–Dindo Classification of Surgical Complications. Country-based and hospital-based data were collected, including the Human Development Index (HDI). (NCT03768141). Results: A total of 2159 patients were included from six continents. Surgery was performed for cancer in 1785 (83%) patients. Of all patients, 912 (42%) experienced a postoperative complication of any severity, while the major complication rate was 16% (341/2159). The overall 90-day mortality rate after liver surgery was 3.8% (82/2,159). The overall failure to rescue rate was 11% (82/ 722) ranging from 5 to 35% among the higher and lower HDI groups, respectively. Conclusions: This is the first to our knowledge global surgery study specifically designed and conducted for specialized liver surgery. The authors identified failure to rescue as a significant potentially modifiable factor for mortality after liver surgery, mostly related to lower Human Development Index countries. Members of the LiverGroup.org network could now work together to develop quality improvement collaboratives