The use of image fusion in prenatal medicine

Fusion imaging (FI), the simultaneous display of the same anatomical region using two imaging modalities, has been used in other areas of medicine for both diagnosis and guiding interventions. Examples include positron emission tomography-computed tomography (PET-CT) imaging in oncology and ultrasound-magnetic resonance imaging (US-MRI) fusion in biopsies of the prostate gland. The underlying principle is to take advantage of the complementary information in each modality to improve accuracy, be it diagnostic accuracy or targeting accuracy in biopsies. For example, PET-CT overlays the metabolic activity of lesions on the superb spatial and anatomical detail of CT. While the historical mainstay of fetal imaging has been ultrasound, advances in ultrafast MR imaging together with advances in fetal MRI over the past two decades, have resulted in the opportunity to explore fusion imaging in fetal medicine. We present an overview of the principles of US-MRI fusion imaging in prenatal medicine, report our local experience, and review the literature in this emerging area. We share our perspective on how FI can improve diagnostic confidence, be used as an educational tool, and potentially enhance guidance in certain fetal procedures.     

Sources and historical record of tin and butyl-tin species in a Mediterranean bay (Toulon Bay,France)

Concentrations of inorganic tin (Sn_inorg), tributyltin (TBT) and its degradation products dibutyltin (DBT) and monobutyltin (MBT) were measured in surface sediments and in two cores from the Toulon Bay, hosting the major French military harbour. Anticipating planned dredging, the aim of the present work is to map and evaluate for the first time the recent and historic contamination of these sediments by inorganic and organic Sn species derived from antifouling paints used for various naval domains including military, trade, tourism and leisure. Tin and butyl-Sn concentrations in the bay varied strongly (4 orders of magnitude), depending on the site, showing maximum values near the shipyards. The concentrations of total Sn (1.3–112 μg g^?1), TBT (<0.5–2,700 ng g^?1), DBT (<0.5–1,800 ng g^?1) and MBT (0.5–1,000 ng g^?1) generally decreased towards the open sea, i.e. as a function of both distance from the presumed main source and bottom currents. Progressive degradation state of the butyl-Sn species according to the same spatial scheme and the enrichment factors support the scenario of a strongly polluted bay with exportation of polluted sediment to the open Mediterranean. Low degradation and the historical records of butyl-Sn species in two ²¹⁰Pb-dated sediment cores, representative of the Northern Bay, are consistent with the relatively recent use of TBT by military shipyards and confirm maximum pollution during the 1970s, which will persist in the anoxic sediments for several centuries. The results show that (a) degradation kinetics of butyl-Sn species depend on environmental conditions, (b) the final degradation product Sn_inorgBT is by far the dominant species after 10–12 half-life periods and (c) using recent data to reliably assess former TBT contamination requires the use of a modified butyl-Sn degradation index BDI_mod. Resuspension of extremely contaminated subsurface sediments by the scheduled dredging will probably result in mobilization of important amounts of butyl-Sn species.     

An integrated environmental approach to investigate biomarker fluctuations in the blue mussel Mytilus edulis L. in the Vilaine estuary, France

Estuarine areas represent complex and highly changing environments at the interface between freshwater and marine aquatic ecosystems. Therefore, the aquatic organisms living in estuaries have to face highly variable environmental conditions. The aim of this work was to study the influence of environmental changes from either natural or anthropogenic origins on the physiological responses of Mytilus edulis. Mussels were collected in the Vilaine estuary during early summer because this season represents a critical period of active reproduction in mussels and of increased anthropogenic inputs from agricultural and boating activities into the estuary. The physiological status of the mussel M. edulis was evaluated through measurements of a suite of biomarkers related to: oxidative stress (catalase, malondialdehyde), detoxication (benzopyrene hydroxylase, carboxylesterase), neurotoxicity (acetylcholinesterase), reproductive cycle (vitelline, condition index, maturation stages), immunotoxicity (hemocyte concentration, granulocyte percentage, phagocytosis, reactive oxygen species production, oxidative burst), and general physiological stress (lysosomal stability). A selection of relevant organic contaminant (pesticides, (polycyclic aromatic hydrocarbons, polychlorobiphenyls) was measured as well as environmental parameters (water temperature, salinity, total suspended solids, turbidity, chlorophyll a, pheopigments) and mussel phycotoxin contamination. Two locations differently exposed to the plume of the Vilaine River were compared. Both temporal and inter-site variations of these biomarkers were studied. Our results show that reproduction cycle and environmental parameters such as temperature, organic ontaminants, and algal blooms could strongly influence the biomarker responses. These observations highlight the necessity to conduct integrated environmental approaches in order to better understand the causes of biomarker variations.     

Leveraging social media and deep learning to detect rare megafauna in video surveys

Deep learning has become a key tool for the automated monitoring of animal populations with video surveys. However, obtaining large numbers of images to train such models is a major challenge for rare and elusive species because field video surveys provide few sightings. We designed a method that takes advantage of videos accumulated on social media for training deep-learning models to detect rare megafauna species in the field. We trained convolutional neural networks (CNNs) with social media images and tested them on images collected from field surveys. We applied our method to aerial video surveys of dugongs (Dugong dugon) in New Caledonia (southwestern Pacific). CNNs trained with 1303 social media images yielded 25% false positives and 38% false negatives when tested on independent field video surveys. Incorporating a small number of images from New Caledonia (equivalent to 12% of social media images) in the training data set resulted in a nearly 50% decrease in false negatives. Our results highlight how and the extent to which images collected on social media can offer a solid basis for training deep-learning models for rare megafauna detection and that the incorporation of a few images from the study site further boosts detection accuracy. Our method provides a new generation of deep-learning models that can be used to rapidly and accurately process field video surveys for the monitoring of rare megafauna.     

Stratospheric temperature monitoring using a vibrational Raman lidar. Part 1: aerosols and ozone interferences

Lidar measurements of temperature for the upper troposphere and lower stratosphere are commonly derived by the Raman technique. Lidar signals derived from vibrational Raman processes have been subjected to numerous simulation tests to examine their sensitivity to the presence of aerosols and ozone in the atmosphere. The influence of aerosols characteristics (wavelength dependence of aerosol extinction and particle phase function) and of ozone concentration on Raman temperature profiles is estimated. Simulations indicate large temperature deviations for post-volcanic conditions. For a Raman backscatter at 607 nm, bias is below 1 K for a total optical depth less than 9 x 10(-3) in the case of a stratospheric contamination and less than 6 x 10(-3) for a tropospheric contamination. The effect of aerosols depends on phase function and a few parameters such as altitude, optical depth and the shape of the high-altitude cloud. The wavelength dependence of aerosol extinction has some influence only for severe post-volcanic conditions (Scattering Ratio, SR >2). For a Raman backscatter at 387 nm, bias is larger and can be significant even in background aerosol conditions. Changes in the ozone density profile lead to significant Raman temperature deviations only for some specific conditions. Results suggest that both aerosol and ozone corrections are necessary to obtain an accuracy better than the 1 K requested for most atmospheric applications.     

Evolution of self-organized division of labor in a response threshold model

Division of labor in social insects is determinant to their ecological success. Recent models emphasize that division of labor is an emergent property of the interactions among nestmates obeying to simple behavioral rules. However, the role of evolution in shaping these rules has been largely neglected. Here, we investigate a model that integrates the perspectives of self-organization and evolution. Our point of departure is the response threshold model, where we allow thresholds to evolve. We ask whether the thresholds will evolve to a state where division of labor emerges in a form that fits the needs of the colony. We find that division of labor can indeed evolve through the evolutionary branching of thresholds, leading to workers that differ in their tendency to take on a given task. However, the conditions under which division of labor evolves depend on the strength of selection on the two fitness components considered: amount of work performed and on worker distribution over tasks. When selection is strongest on the amount of work performed, division of labor evolves if switching tasks is costly. When selection is strongest on worker distribution, division of labor is less likely to evolve. Furthermore, we show that a biased distribution (like 3:1) of workers over tasks is not easily achievable by a threshold mechanism, even under strong selection. Contrary to expectation, multiple matings of colony foundresses impede the evolution of specialization. Overall, our model sheds light on the importance of considering the interaction between specific mechanisms and ecological requirements to better understand the evolutionary scenarios that lead to division of labor in complex systems. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00265-012-1343-2) contains supplementary material, which is available to authorized users.     

The use of fetal MRI for renal and urogenital tract anomalies

Fetal anomalies are detected in approximately 2% of all fetuses and, among these, genitourinary tract abnormalities account for 30% to 50% of all structural anomalies present at birth. Although ultrasound remains the first line diagnostic modality, fetal MRI provides important additional structural and functional information, especially with the development of faster sequences and the use of functional sequences. The added value of MRI-based imaging is three-fold: (a) improvement of diagnostic accuracy by adequate morphological examination, (b) detection of additional anomalies, and (c) in addition, MRI has the potential to provide information regarding renal function. In this review, we describe the role of fetal MRI in the anatomical evaluation of renal and urogenital tract anomalies, and we also touch upon the contribution of functional MRI to the diagnostic workup of these conditions.