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This paper presents two metazoan zooplankton datasets obtained by imaging samples collected on the Bay of Biscay continental shelf in spring during the PELGAS (PELagique GAScogne) integrated surveys over the 2004–2019 period. The samples were collected at night with a 200 µm mesh-size WP2 net fitted with a Hydrobios (back-run stop) mechanical flowmeter and hauled vertically from the sea floor to the surface, with the maximum depth set at 100 m when the bathymetry was deeper than this. The first dataset originates from samples collected from 2004 to 2016 and imaged on land with the ZooScan and is composed of 1 153 507 imaged and measured objects. The second dataset originates from samples collected from 2016 to 2019 and imaged onboard the R/V Thalassa with the ZooCAM and is composed of 702 111 imaged and measured objects. The imaged objects are composed of zooplankton individuals, zooplankton pieces, non-living particles and imaging artefacts ranging from 300 µm to 3.39 mm in equivalent spherical diameter which were individually imaged, measured and identified. Each imaged object is geolocated and associated with a station, a survey, a year and other metadata. Each object is described by a set of morphological and grey-level-based features (8 bit encoding, 0 = black, 255 = white), including size, that were automatically extracted from each individual image. Each object was taxonomically identified using the web-based application Ecotaxa with built-in random-forest and CNN-based semi-automatic sorting tools, which was followed by expert validation or correction. The objects were sorted into 172 taxonomic and morphological groups. Each dataset features a table combining metadata and data at individual-object granularity from which one can easily derive quantitative population and community descriptors such as abundances, mean sizes, biovolumes, biomasses and size structure. Each object's individual image is provided along with the data. These two datasets can be used in combination for ecological studies, as the two instruments are interoperable, or they can be used as training sets for ZooScan and ZooCAM users. The data presented here are available at the SEANOE dataportal: https://doi.org/10.17882/94052 (ZooScan dataset, Grandremy et al., 2023c) and https://doi.org/10.17882/94040 (ZooCAM dataset, Grandremy et al., 2023d).

Introduction and objectiveThis study aimed to identify clinical features representing predictive factors of active treatment (AT) compared to active surveillance (AS) for renal angiomyolipoma (AML).Patients and methodsFrom 1990 to 2020, patients referred to two institutions for a renal mass and diagnosed with an AML based on typical features on CT were included in the analysis. The study population was divided into two groups based on the treatment received: active surveillance (AS) or active treatment (AT). Age, gender, tuberous sclerosis syndrome, tumor size, contralateral kidney disease, renal function, year of diagnosis, and symptoms at presentation were assessed as potential predictive factors of active treatment using a logistic regression model in univariate and multivariate analyses.ResultsIn total, 253 patients (mean age 52.3 ± 15.7 years; 70% women; 70.9% incidentally diagnosed) were included in the analysis. One hundred and nine (43%) received AS, whereas 144 (57%) were actively treated. For univariate analysis, age, tuberous sclerosis complex syndrome, tumor size, symptoms at presentation, and contralateral kidney disease were found to be predictors of AT. Only tumor size (p

Living benthic foraminifera, known as environmental bio-indicators of both natural and anthropogenic conditions in marine environments, were investigated in the coastal environment of Roscoff Aber Bay (Brittany, France). Eight sampling sites subject to natural variations (freshwater inputs, tides) and/or anthropogenic impacts (pollution, eutrophication) were studied over four seasons in 2021–2022 (November, February, May, August). We sought to understand the spatial distribution of foraminiferal populations within and between sampling sites over the different seasons and to identify sensitive species and those tolerant to anthropogenic impacts. To this end, sedimentary and biogeochemical characteristics of the sediments were examined by measuring grain size, temperature, oxygen, salinity, pH, environmental pigment concentration (chl a and phaeopigments), total organic carbon (TOC), isotopic ratios of carbon (δ13C), nitrogen (δ15N) and sulfide (δ34S), and chl a fluorescence. Considering these parameters as potential driving factors, four environments were distinguished among the sampling sites: open water, terrestrial, oligotrophic and eutrophic. These showed an increasing gradient of organic supply as well as very different microbial activities, highlighted by carbon and sulfide isotopic ratios. Foraminiferal population study revealed the dominant species characterising these main environments. The lowest abundance but highest diversity of foraminifera was found in the harbour site, associated with the dominance of Haynesina germanica, suggesting this species is tolerant to eutrophic environments and anthropogenic impacts. Open water was dominated by Ammonia beccarii and Elphidium crispum, while Quinqueloculina seminula was the most abundant species in the site with the greatest terrestrial influence. Interestingly, the observed organic enrichment of the harbour due to anthropogenic activities (fisheries, waste deposits, etc.) does not seem to significantly affect foraminiferal diversity. Overall, the benthic foraminiferal species in Roscoff Aber Bay appear to be an excellent proxy for marine environmental conditions under various natural and anthropogenic influences. [ABSTRACT FROM AUTHOR]

This paper presents two metazoan zooplankton datasets obtained by imaging samples collected on the Bay of Biscay continental shelf in spring during the PELGAS integrated surveys, over the 2004-2019 period. The samples were collected at night, with a WP2 200 µm mesh size fitted with a Hydrobios (back-run stop) mechanical flowmeter, hauled vertically from the sea floor to the surface with a maximum depth set at 100 m when the bathymetry is deeper. The first dataset originates from samples collected from 2004 to 2016, imaged on land with the ZooScan and is composed of 1,153,507 imaged and measured objects. The second dataset originates from samples collected from 2016 to 2019, imaged on board the R/V Thalassa with the ZooCAM and is composed of 702,111 imaged and measured objects. The imaged objects is composed of zooplankton individuals, zooplankton pieces, non-living particles and imaging artefacts, ranging from 300 µm to 3.39 mm Equivalent Spherical Diameter, individually imaged, measured and identified. Each imaged object is geolocated, associated to a station, a survey, a year and other metadata. Each object is described by a set of morphological and grey level based features (8 bits encoding, 0 = black, 255 = white), including size, automatically extracted on each individual image. Each object was taxonomically identified using the web based application Ecotaxa with built-in, random forest and CNN based, semi-automatic sorting tools followed by expert validation or correction. The objects were sorted in 172 taxonomic and morphological groups. Each dataset features a table combining metadata and data, at the individual object granularity, from which one can easily derive quantitative population and communities descriptors such as abundances, mean sizes, biovolumes, biomasses, and size structure. Each object's individual image is provided along with the data. These two datasets can be used combined together for ecological studies as the two instruments are interoperable, or as training sets for ZooScan and ZooCAM users. [ABSTRACT FROM AUTHOR]