Patient and public involvement in numerical aspects of trials : a mixed methods theory-informed survey of trialists’ current practices, barriers and facilitators

Funding: BG was supported to develop this research by the Wellcome Trust Institutional Strategic Support Fund at the University of Aberdeen.Peer reviewedPublisher PD

Vers une automédication responsable (rôle du pharmacien dans le contrôle de l'automédication concernant les médicaments conseil)

TOURS-BU Sciences Pharmacie (372612104) / SudocSudocFranceF

Potential directional asymmetry of the otolith shape tested on the red mullet (Mullus barbatus) in the Mediterranean Sea: comparative analysis of 2D and 3D otolith shape data

A wide number of techniques were developed and applied to identify and discriminate stocks. Among them, otolith’s shape, which is affected by environment and genetic factors, can be used as a tool to identify the populations within the species. Before to identify the boundaries of stocks, the potential drivers, which control the otolith shape, must be analysed. In this study, Directional Asymmetry (DA; the effect of otolith’s location side, i.e., left versus right inner ear) was tested combining the approaches to otolith shape in 2D and 3D on 560 adults of the red mullet Mullus barbatus (Linnaeus, 1758) which is one of the most abundant demersal fish species in the Mediterranean Sea. Studied individual were sampled from 7 subunits for 2D analysis (476 individuals) and 3 subunits for 3D analysis (84 individuals) of geographical subareas (GSAs). To analyse otolith shape, the normalized Elliptical Fourier Descriptors (EFDs) computed from the two-dimensional outlines (extracted from otolithes 2D pictures) and Spherical Harmonic shape descriptors computed from three-dimensional surfaces/meshes (extracted from otolithes 3D scans) were analysed with principal component analysis (PCA) method. PCA’s scores were used in the multivariate mixed-effects model with side and subunits effects. From 3D surfaces/meshes, the univariate variables (i.e. otolithe’s surface and volume) were analysed with Redundancy analysis (RDA) too. The EFDs from 2D images showed that the side effect was significant on the otolith shape (p-value<0.00001). The reconstructed outlines of the mean Fourier harmonics of the left and right side were plotted and the percentage of non-overlapping surface was 1.010%. However, the interaction between side and geographical subareawas  nosignificant from 2D images. The EFDs from 3D images showed that the side effect was signifant (p-value<0.00001). In additionnal, the interaction between side effect and geographical subarea was signifiant (p-value< 0.00001) from 3D images. The relationship between the fish length and the surface of 3D otolith shape was significant (p-value =0.001), this trend was not observed by the otolith volume (p-value=0.698). For these two univariate descriptors of 3D otolith shape, there were no significant difference between left and right otoliths. This comparative analysis of otolith shape in 2D and in 3D showed showed that the 3D approach, presents the data with more accuracy than those extracted from the regurlarly used 2D approach. This difference is very important because the directionnal asymmetry was significant on the relationship between the otolith 3D shape and the geographical area of sampling while this trend is not observable from the otolith 2D shape.  This first study showing the difference between 2D and 3D approaches should be confirmed in the future

Asymmetry of Sagittal Otolith Shape Based on Inner Ear Side Tested on Mediterranean Red Mullet (Mullus barbatus Linnaeus, 1758): Comparative Analysis of 2D and 3D Otolith Shape Data

Sagittal otolith shape analysis is one of the most widespread techniques worldwide to discriminate fish stock units, as this proxy integrates both environmental and genetic factors. All previous otolith shape studies have been carried out using two-dimensional (2D) images, a partial representation of the whole shape of the otolith. However, prior to the identification of stock unit boundaries, the influence of other potential drivers controlling the otolith shape must be analysed to limit their bias. In this study, the presence of asymmetry in otolith shape depending on the inner ear side (i.e., left versus right inner ears) was tested by comparing the approaches of 2D and three-dimensional (3D) sagittal otolith shape analyses. Eighty-two red mullet adults (Mullus barbatus) from three locations in the eastern part of the Mediterranean Sea were studied. Fourier harmonic descriptors computed from 2D outlines and spherical harmonic descriptors computed from 3D meshes were used to evaluate otolith shape variation. The results of a multivariate mixed-effects model from 2D images showed that there was no asymmetry effect of inner ear side on the otolith shape in any location. There was, however, a significant geographical effect for the 2D otolith shape between the Adriatic Sea and the Levantine Sea. In contrast, 3D information showed that both side effects and geographical differences were significant. This is the first study comparing 2D and 3D data showing different results on the same sample of red mullet. These results demonstrate the importance of 3D otolith shape analysis for stock discrimination

Asymmetry of Sagittal Otolith Shape Based on Inner Ear Side Tested on Mediterranean Red Mullet (Mullus barbatus Linnaeus, 1758): Comparative Analysis of 2D and 3D Otolith Shape Data

International audienceSagittal otolith shape analysis is one of the most widespread techniques worldwide to discriminate fish stock units, as this proxy integrates both environmental and genetic factors. All previous otolith shape studies have been carried out using two-dimensional (2D) images, a partial representation of the whole shape of the otolith. However, prior to the identification of stock unit boundaries, the influence of other potential drivers controlling the otolith shape must be analysed to limit their bias. In this study, the presence of asymmetry in otolith shape depending on the inner ear side (i.e., left versus right inner ears) was tested by comparing the approaches of 2D and three-dimensional (3D) sagittal otolith shape analyses. Eighty-two red mullet adults (Mullus barbatus) from three locations in the eastern part of the Mediterranean Sea were studied. Fourier harmonic descriptors computed from 2D outlines and spherical harmonic descriptors computed from 3D meshes were used to evaluate otolith shape variation. The results of a multivariate mixed-effects model from 2D images showed that there was no asymmetry effect of inner ear side on the otolith shape in any location. There was, however, a significant geographical effect for the 2D otolith shape between the Adriatic Sea and the Levantine Sea. In contrast, 3D information showed that both side effects and geographical differences were significant. This is the first study comparing 2D and 3D data showing different results on the same sample of red mullet. These results demonstrate the importance of 3D otolith shape analysis for stock discrimination

Analyse de forme en 3D des otolithes pour mieux délimiter les stocks du rouget barbet de vase en utilisant l'asymétrie des côtés de l'oreille interne

L’otolithe est une structure calcifiée présente dans l’oreille interne des poissons. L'analyse de la forme de l'otolithe est l'une des techniques les plus répandues dans le monde pour distinguer les unités de stock de poissons, car elle intègre à la fois des facteurs environnementaux et génétiques. Toutes les études précédentes sur la forme de l'otolithe ont été réalisées à l'aide d'images bidimensionnelles (2D), une représentation partielle de la forme totale de l'otolithe. Avant d'identifier les limites des unités de stock, l'influence d'autres facteurs potentiels contrôlant la forme de l'otolithe doit être analysée afin de limiter leur biais. Dans cette étude, la présence d'une asymétrie dans la forme de l'otolithe en fonction du côté de l'oreille interne (c'est-à-dire l'oreille interne gauche par rapport à l'oreille interne droite) a été testée sur le rouget barbet de vase (Mullus barbartus) provenant de la mer Méditerranée ; en comparant les approches des analyses de la forme de l'otolithe en 2D et en trois dimensions (3D). Les résultats montrent que les images 3D peuvent détecter des différences significatives là où les images 2D ne les détecte pas

Tick-borne zoonotic flaviviruses and Borrelia infections in wildlife hosts: what have field studies contributed?

International audienceTick-borne flaviviruses and Borrelia spp. are globally spread pathogens of zoonotic potential that are maintained by a transmission cycle at the interface between ticks and vertebrate hosts, mainly wild animals. Aside data on pathogen burden in ticks, information on the status of various hosts relative to infection is important to acquire. We reviewed how those infections have been studied in wildlife host species in the field to discuss how collected data provided relevant epidemiological information and to identify needs for further studies. The literature was screened for observational studies on pathogen or antibody detection for tick-borne Borrelia spp. and flaviviruses in wildlife host animals. Overall, Borrelia spp. were more studied (73% of case studies, representing 297 host species) than flaviviruses (27% of case studies, representing 114 host species). Studies on both Borrelia spp. and flaviviruses focused mainly on the same species, namely bank vole and yellow-necked mouse. Most studies were order-specific and cross-sectional, reporting prevalence at various locations, but with little insight into the underlying epidemiological dynamics. Host species with potential to act as reservoir hosts of these pathogens were neglected, notably birds. We highlight the necessity of collecting both demographics and infection data in wildlife studies, and to consider communities of species, to better estimate zoonotic risk potential in the One Health context

Combination of “machine learning” methodologies and automated data acquisition systems for phytoplankton detection and classification

International audienceIn recent years, improvements in automated data acquisition techniques have been carried out in order to sample, characterize and quantify phytoplankton communities during oceanographic campaigns or in the frame of monitoring networks (at low or high frequency). However, these acquisition and digitization techniques, including those concerning «imaging-in-flow» and «flow cytometry» systems, still generate an important quantity of data which cannot be processed manually. Indeed, a full manual quantification of the particles based on a simple visual inspection can be time-consuming, tedious and consequently lead to erroneous or missing identifications. For this purpose, different dedicated R-packages were and are still being developed to allow greater automation in data analysis and classification while permitting a limited user-interaction during the process. The common methodology consists in combining few expert knowledge and some “machine learning” algorithms at different levels: to classify particles into different groups based on the definition of a specific training set, but also to partially validate the “most suspect” predictions which can represent a consequent fraction of the global error. Moreover, in order to orientate the automated classification and consequently to reduce the global error rate, some interactive tools were developed to adapt the training set to the phytoplankton communities generally encountered in the studied area (“active learning”), or to constraint the algorithms to merge or separate some groups (“constrained clustering”).These different semi-automated analytical tools were applied on different in vivo image and signal datasetsacquired with the FlowCAM and CytoSense devices respectively, during several cruises in the English Channel, inorder to evaluate their operational ability to automatically monitor the diversity of samples. Spatial distributions of the target groups, based on their abundance, were computed and could allow to highlight different sub-regions in the English Channel during the studied periods

MAREL Carnot data and metadata from Coriolis Data Center

The French coast of the Eastern English Channel (ECC) is classified as potential eutrophication zone by the Paris and Oslo Convention (OSPAR), and as moderate to poor according to phytoplankton quality element of the Water Framework Directive (WFD). Indeed, the French part of the EEC is regularly affected by Phaeocystis globosa bloom events, which have detrimental effects on the marine ecosystem, economy as well as public health. Since phytoplankton is an important indicator of water quality, the MAREL Carnot oceanographic multi-sensor station was installed in the Eastern English Channel at the Carnot wall in Boulogne sur Mer in 2004 to monitor water quality and phytoplankton in order to complement results from existing more conventional low resolution monitoring programs, with high frequency data (sampling every 20 minutes). The purpose of this paper is to introduce the MAREL Carnot dataset and show how it can be used for several research objectives. MAREL Carnot collects high frequency, multi-parameter observations from surface water, as well as meteorological measurements, and send data almost immediately to an inshore data center. In this paper, we present several physiochemical and biological parameters measured by this station. In addition, we demonstrated, based on previous research activities, that the MAREL Carnot dataset is useful for evaluating environmental or ecological statuses, marine phytoplankton ecology, physical oceanography, turbulence, as well as public policy. Most importantly, we showed its contribution to Marine Strategy Framework Directive (MSFD) and other regional or universal conventions