Bottom mixed layer oxygen dynamics in the Celtic Sea

The seasonally stratified continental shelf seas are highly productive, economically important environments which are under considerable pressure from human activity. Global dissolved oxygen concentrations have shown rapid reductions in response to anthropogenic forcing since at least the middle of the twentieth century. Oxygen consumption is at the same time linked to the cycling of atmospheric carbon, with oxygen being a proxy for carbon remineralisation and the release of CO2. In the seasonally stratified seas the bottom mixed layer (BML) is partially isolated from the atmosphere and is thus controlled by interplay between oxygen consumption processes, vertical and horizontal advection. Oxygen consumption rates can be both spatially and temporally dynamic, but these dynamics are often missed with incubation based techniques. Here we adopt a Bayesian approach to determining total BML oxygen consumption rates from a high resolution oxygen time-series. This incorporates both our knowledge and our uncertainty of the various processes which control the oxygen inventory. Total BML rates integrate both processes in the water column and at the sediment interface. These observations span the stratified period of the Celtic Sea and across both sandy and muddy sediment types. We show how horizontal advection, tidal forcing and vertical mixing together control the bottom mixed layer oxygen concentrations at various times over the stratified period. Our muddy-sand site shows cyclic spring-neap mediated changes in oxygen consumption driven by the frequent resuspension or ventilation of the seabed. We see evidence for prolonged periods of increased vertical mixing which provide the ventilation necessary to support the high rates of consumption observed

Oxygen dynamics in shelf seas sediments incorporating seasonal variability

Shelf sediments play a vital role in global biogeochemical cycling and are particularly important areas of oxygen consumption and carbon mineralisation. Total benthic oxygen uptake, the sum of diffusive and faunal mediated uptake, is a robust proxy to quantify carbon mineralisation. However, oxygen uptake rates are dynamic, due to the diagenetic processes within the sediment, and can be spatially and temporally variable. Four benthic sites in the Celtic Sea, encompassing gradients of cohesive to permeable sediments, were sampled over four cruises to capture seasonal and spatial changes in oxygen dynamics. Total oxygen uptake (TOU) rates were measured through a suite of incubation experiments and oxygen microelectrode profiles were taken across all four benthic sites to provide the oxygen penetration depth and diffusive oxygen uptake (DOU) rates. The difference between TOU and DOU allowed for quantification of the fauna mediated oxygen uptake and diffusive uptake. High resolution measurements showed clear seasonal and spatial trends, with higher oxygen uptake rates measured in cohesive sediments compared to the permeable sediment. The significant differences in oxygen dynamics between the sediment types were consistent between seasons, with increasing oxygen consumption during and after the phytoplankton bloom. Carbon mineralisation in shelf sediments is strongly influenced by sediment type and seasonality

DAG-informed regression modelling, agent-based modelling, and microsimulation modelling: A critical comparison of methods for causal inference

The current paradigm for causal inference in epidemiology relies primarily on the evaluation of counterfactual contrasts via statistical regression models informed by graphical causal models (often in the form of directed acyclic graphs, or DAGs) and their underlying mathematical theory. However, there have been growing calls for supplementary methods, and one such method that has been proposed is agent-based modelling due to its potential for simulating counterfactuals. However, within the epidemiological literature there currently exists a general lack of clarity regarding what exactly agent-based modelling is (and is not) and, importantly, how it differs from microsimulation modelling – perhaps its closest methodological comparator. We clarify this distinction by briefly reviewing the history of each method, which provides context for their similarities and differences, and casts light on the types of research questions that they have evolved (and thus are well-suited) to answering; we do the same for DAG-informed regression methods. The distinct historical evolutions of DAG-informed regression modelling, microsimulation modelling, and agent-based modelling have given rise to distinct features of the methods themselves, and provide a foundation for critical comparison. Not only are the three methods well-suited to addressing different types of causal questions, but in doing so they place differing levels of emphasis on fixed and random effects, and also tend to operate on different timescales and in different timeframes

Development and Applications of Fluorogen/Light-Up RNA Aptamer Pairs for RNA Detection and More.

The central role of RNA in living systems made it highly desirable to have noninvasive and sensitive technologies allowing for imaging the synthesis and the location of these molecules in living cells. This need motivated the development of small pro-fluorescent molecules called "fluorogens" that become fluorescent upon binding to genetically encodable RNAs called "light-up aptamers." Yet, the development of these fluorogen/light-up RNA pairs is a long and thorough process starting with the careful design of the fluorogen and pursued by the selection of a specific and efficient synthetic aptamer. This chapter summarizes the main design and the selection strategies used up to now prior to introducing the main pairs. Then, the vast application potential of these molecules for live-cell RNA imaging and other applications is presented and discussed.journal article2020importe

Combined tipranavir and enfuvirtide use associated with higher plasma tipranavir concentrations but not with increased hepatotoxicity: sub-analysis from RESIST

In RESIST, enfuvirtide co-administered with ritonavir-boosted tipranavir was associated with higher plasma tipranavir concentrations, which seldom rose above those associated with an increased risk of grade 3/4 transaminase elevations. Transaminase elevation rates (6.5%) and clinical hepatic event rates (5.9 events/100 person exposure years) were lower in the tipranavir/ritonavir with enfuvirtide group than in the tipranavir/ritonavir without enfuvirtide group. Observed increases in plasma tipranavir concentrations thus had no apparent effect on the risk of hepatotoxicity