The molybdenum isotopic composition in river water: Constraints from small catchments

We report molybdenum isotope compositions and concentrations in water samples from a variety of river catchment profiles in order to investigate the influence of anthropogenic contamination, catchment geology, within-river precipitation, and seasonal river flow variations on riverine molybdenum. Our results show that the observed variations in δ98/95Mo from 0‰ to 1.9‰ are primarily controlled by catchment lithology, particularly by weathering of sulfates and sulfides. Erosion in catchments dominated by wet-based glaciers leads to very high dissolved molybdenum concentrations. In contrast, anthropogenic inputs affect neither the concentration nor the isotopic composition of dissolved molybdenum in the rivers studied here. Seasonal variations are also quite muted. The finding that catchment geology exerts the primary control on the delivery of molybdenum to seawater indicates that the flux and isotope composition of molybdenum to seawater has likely varied in the geologic past.

Graph-Based Multi-Surface Segmentation of OCT Data Using Trained Hard and Soft Constraints

Optical coherence tomography (OCT) is a well-established image modality in ophthalmology and used daily in the clinic. Automatic evaluation of such datasets requires an accurate segmentation of the retinal cell layers. However, due to the naturally low signal to noise ratio and the resulting bad image quality, this task remains challenging. We propose an automatic graph-based multi-surface segmentation algorithm that internally uses soft constraints to add prior information from a learned model. This improves the accuracy of the segmentation and increase the robustness to noise. Furthermore, we show that the graph size can be greatly reduced by applying a smart segmentation scheme. This allows the segmentation to be computed in seconds instead of minutes, without deteriorating the segmentation accuracy, making it ideal for a clinical setup. An extensive evaluation on 20 OCT datasets of healthy eyes was performed and showed a mean unsigned segmentation error of 3.05 ±0.54 μm over all datasets when compared to the average observer, which is lower than the inter-observer variability. Similar performance was measured for the task of drusen segmentation, demonstrating the usefulness of using soft constraints as a tool to deal with pathologies.

Cardiac sodium channel NaV1.5 distribution in myocytes via interacting proteins: the multiple pool model

The cardiac sodium current (INa) is responsible for the rapid depolarization of cardiac cells, thus allowing for their contraction. It is also involved in regulating the duration of the cardiac action potential (AP) and propagation of the impulse throughout the myocardium. Cardiac INa is generated by the voltage-gated Na(+) channel, NaV1.5, a 2016-residue protein which forms the pore of the channel. Over the past years, hundreds of mutations in SCN5A, the human gene coding for NaV1.5, have been linked to many cardiac electrical disorders, including the congenital and acquired long QT syndrome, Brugada syndrome, conduction slowing, sick sinus syndrome, atrial fibrillation, and dilated cardiomyopathy. Similar to many membrane proteins, NaV1.5 has been found to be regulated by several interacting proteins. In some cases, these different proteins, which reside in distinct membrane compartments (i.e. lateral membrane vs. intercalated disks), have been shown to interact with the same regulatory domain of NaV1.5, thus suggesting that several pools of NaV1.5 channels may co-exist in cardiac cells. The aim of this review article is to summarize the recent works that demonstrate its interaction with regulatory proteins and illustrate the model that the sodium channel NaV1.5 resides in distinct and different pools in cardiac cells. This article is part of a Special Issue entitled: Cardiomyocyte Biology: Cardiac Pathways of Differentiation, Metabolism and Contraction.