Symmetry in cancer networks identified: Proposal for multicancer biomarkers

One of the most challenging problems in biomedicine and genomics is the identification of disease biomarkers. In this study, proteomics data from seven major cancers were used to construct two weighted protein–protein interaction networks, i.e., one for the normal and another for the cancer conditions. We developed rigorous, yet mathematically simple, methodology based on the degeneracy at –1 eigenvalues to identify structural symmetry or motif structures in network. Utilizing eigenvectors corresponding to degenerate eigenvalues in the weighted adjacency matrix, we identified structural symmetry in underlying weighted protein–protein interaction networks constructed using seven cancer data. Functional assessment of proteins forming these structural symmetry exhibited the property of cancer hallmarks. Survival analysis refined further this protein list proposing BMI, MAPK11, DDIT4, CDKN2A, and FYN as putative multicancer biomarkers. The combined framework of networks and spectral graph theory developed here can be applied to identify symmetrical patterns in other disease networks to predict proteins as potential disease biomarkers

Dynamics of air–sea CO2 fluxes in the northwestern European shelf based on voluntary observing ship and satellite observations

From January 2011 to December 2013, we constructed a comprehensive pCO2 data set based on voluntary observing ship (VOS) measurements in the western English Channel (WEC). We subsequently estimated surface pCO2 and air–sea CO2 fluxes in northwestern European continental shelf waters using multiple linear regressions (MLRs) from remotely sensed sea surface temperature (SST), chlorophyll a concentration (Chl a), wind speed (WND), photosynthetically active radiation (PAR) and modeled mixed layer depth (MLD). We developed specific MLRs for the seasonally stratified northern WEC (nWEC) and the permanently well-mixed southern WEC (sWEC) and calculated surface pCO2 with uncertainties of 17 and 16 μatm, respectively. We extrapolated the relationships obtained for the WEC based on the 2011–2013 data set (1) temporally over a decade and (2) spatially in the adjacent Celtic and Irish seas (CS and IS), two regions which exhibit hydrographical and biogeochemical characteristics similar to those of WEC waters. We validated these extrapolations with pCO2 data from the SOCAT and LDEO databases and obtained good agreement between modeled and observed data. On an annual scale, seasonally stratified systems acted as a sink of CO2 from the atmosphere of −0.6 ± 0.3, −0.9 ± 0.3 and −0.5 ± 0.3 mol C m−2 yr−1 in the northern Celtic Sea, southern Celtic sea and nWEC, respectively, whereas permanently well-mixed systems acted as source of CO2 to the atmosphere of 0.2 ± 0.2 and 0.3 ± 0.2 mol C m−2 yr−1 in the sWEC and IS, respectively. Air–sea CO2 fluxes showed important inter-annual variability resulting in significant differences in the intensity and/or direction of annual fluxes. We scaled the mean annual fluxes over these provinces for the last decade and obtained the first annual average uptake of −1.11 ± 0.32 Tg C yr−1 for this part of the northwestern European continental shelf. Our study showed that combining VOS data with satellite observations can be a powerful tool to estimate and extrapolate air–sea CO2 fluxes in sparsely sampled area

Carrier-mediated magnetoelectricity in complex oxide heterostructures

While tremendous success has been achieved to date in creating both single phase and composite magnetoelectric materials, the quintessential electric-field control of magnetism remains elusive. In this work, we demonstrate a linear magnetoelectric effect which arises from a novel carrier-mediated mechanism, and is a universal feature of the interface between a dielectric and a spin-polarized metal. Using first-principles density functional calculations, we illustrate this effect at the SrRuO$_3$/SrTiO$_3$ interface and describe its origin. To formally quantify the magnetic response of such an interface to an applied electric field, we introduce and define the concept of spin capacitance. In addition to its magnetoelectric and spin capacitive behavior, the interface displays a spatial coexistence of magnetism and dielectric polarization suggesting a route to a new type of interfacial multiferroic

Spectral Theory of Sparse Non-Hermitian Random Matrices

Sparse non-Hermitian random matrices arise in the study of disordered physical systems with asymmetric local interactions, and have applications ranging from neural networks to ecosystem dynamics. The spectral characteristics of these matrices provide crucial information on system stability and susceptibility, however, their study is greatly complicated by the twin challenges of a lack of symmetry and a sparse interaction structure. In this review we provide a concise and systematic introduction to the main tools and results in this field. We show how the spectra of sparse non-Hermitian matrices can be computed via an analogy with infinite dimensional operators obeying certain recursion relations. With reference to three illustrative examples --- adjacency matrices of regular oriented graphs, adjacency matrices of oriented Erd\H{o}s-R\'{e}nyi graphs, and adjacency matrices of weighted oriented Erd\H{o}s-R\'{e}nyi graphs --- we demonstrate the use of these methods to obtain both analytic and numerical results for the spectrum, the spectral distribution, the location of outlier eigenvalues, and the statistical properties of eigenvectors.Comment: 60 pages, 10 figure

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

Seasonality and spatial heterogeneity of the surface ocean carbonate system in the northwest European continental shelf

In 2014–5 the UK NERC sponsored an 18 month long Shelf Sea Biogeochemistry research programme which collected over 1500 nutrient and carbonate system samples across the NW European Continental shelf, one of the largest continental shelves on the planet. This involved the cooperation of 10 different Institutes and Universities, using 6 different vessels. Additional carbon dioxide (CO2) data were obtained from the underway systems on three of the research vessels. Here, we present and discuss these data across 9 ecohydrodynamic regions, adapted from those used by the EU Marine Strategy Framework Directive (MSFD). We observed strong seasonal and regional variability in carbonate chemistry around the shelf in relation to nutrient biogeochemistry. Whilst salinity increased (and alkalinity decreased) out from the near-shore coastal waters offshore throughout the year nutrient concentrations varied with season. Spatial and seasonal variations in the ratio of DIC to nitrate concentration were seen that could impact carbon cycling. A decrease in nutrient concentrations and a pronounced under-saturation of surface pCO2 was evident in the spring in most regions, especially in the Celtic Sea. This decrease was less pronounced in Liverpool Bay and to the North of Scotland, where nutrient concentrations remained measurable throughout the year. The near-shore and relatively shallow ecosystems such as the eastern English Channel and southern North Sea were associated with a thermally driven increase in pCO2 to above atmospheric levels in summer and an associated decrease in pH. Non-thermal processes (such as mixing and the remineralisation of organic material) dominated in winter in most regions but especially in the northwest of Scotland and in Liverpool Bay. The large database collected will improve understanding of carbonate chemistry over the North-Western European Shelf in relation to nutrient biogeochemistry, particularly in the context of climate change and ocean acidification

Mechanisms for a nutrient-conserving carbon pump in a seasonally stratified, temperate continental shelf sea

Continental shelf seas may have a significant role in oceanic uptake and storage of carbon dioxide (CO2) from the atmosphere, through a ‘continental shelf pump’ mechanism. The northwest European continental shelf, in particular the Celtic Sea (50°N 8°W), was the target of extensive biogeochemical sampling from March 2014 to September 2015, as part of the UK Shelf Sea Biogeochemistry research programme (UK-SSB). Here, we use the UK-SSB carbonate chemistry and macronutrient measurements to investigate the biogeochemical seasonality in this temperate, seasonally stratified system. Following the onset of stratification, near-surface biological primary production during spring and summer removed dissolved inorganic carbon and nutrients, and a fraction of the sinking particulate organic matter was subsequently remineralised beneath the thermocline. Water column inventories of these variables throughout 1.5 seasonal cycles, corrected for air-sea CO2 exchange and sedimentary denitrification and anammox, isolated the combined effect of net community production (NCP) and remineralisation on the inorganic macronutrient inventories. Overall inorganic inventory changes suggested that a significant fraction (>50%) of the annual NCP of around 3 mol-C m–2 yr–1 appeared to be stored within a long-lived organic matter (OM) pool with a lifetime of several months or more. Moreover, transfers into and out of this pool appeared not to be in steady state over the one full seasonal cycle sampled. Accumulation of such a long-lived and potentially C-rich OM pool is suggested to be at least partially responsible for the estimated net air-to-sea CO2 flux of ∼1.3 mol-C m–2 yr–1 at our study site, while providing a mechanism through which a nutrient-conserving continental shelf pump for CO2 could potentially operate in this and other similar regions

Unusual <i>Hemiaulus</i> bloom influences ocean productivity in Northeastern US Shelf waters

Because of its temperate location, high dynamic range of environmental conditions, and extensive human activity, the long-term ecological research site in the coastal Northeastern US Shelf (NES) of the northwestern Atlantic Ocean offers an ideal opportunity to understand how productivity shifts in response to changes in planktonic community composition. Ocean production and trophic transfer rates, including net community production (NCP), net primary production (NPP), gross oxygen production (GOP), and microzooplankton grazing rates, are key metrics for understanding marine ecosystem dynamics and associated impacts on biogeochemical cycles. Although small phytoplankton usually dominate phytoplankton community composition and Chl a concentration in the NES waters during the summer, in August 2019, a bloom of the large diatom genus Hemiaulus, with N2-fixing symbionts, was observed in the mid-shelf region. NCP was 2.5 to 9 times higher when Hemiaulus dominated phytoplankton carbon compared to NCP throughout the same geographic area during the summers of 2020–2022. The Hemiaulus bloom in summer 2019 also coincided with higher trophic transfer efficiency from phytoplankton to microzooplankton and higher GOP and NPP than in the summers 2020–2022. This study suggests that the dominance of an atypical phytoplankton community that alters the typical size distribution of primary producers can significantly influence productivity and trophic transfer, highlighting the dynamic nature of the coastal ocean. Notably, summer 2018 NCP levels were also high, although the size distribution of Chl a was typical and an atypical phytoplankton community was not observed. A better understanding of the dynamics of the NES in terms of biological productivity is of primary importance, especially in the context of changing environmental conditions due to climate processes.</p

Trait‐based analysis of subpolar North Atlantic phytoplankton and plastidic ciliate communities using automated flow cytometer

Plankton are an extremely diverse and polyphyletic group, exhibiting a large range in morphological and physiological traits. Here, we apply automated optical techniques, provided by the pulse‐shape recording automated flow cytometer—CytoSense—to investigate trait variability of phytoplankton and plastidic ciliates in Arctic and Atlantic waters of the subpolar North Atlantic. We used the bio‐optical descriptors derived from the CytoSense (light scattering [forward and sideward] and fluorescence [red, yellow/green and orange from chlorophyll a, degraded pigments, and phycobiliproteins, respectively]) and translated them into functional traits to demonstrate ecological trait variability along an environmental gradient. Cell size was the master trait varying in this study, with large photosynthetic microplankton (> 20 μm in cell diameter), including diatoms as single cells and chains, as well as plastidic ciliates found in Arctic waters, while small‐sized phytoplankton groups, such as the picoeukaryotes (< 4 μm) and the cyanobacteria Synechococcus were dominant in Atlantic waters. Morphological traits, such as chain/colony formation and structural complexity (i.e., cellular processes, setae, and internal vacuoles), appear to favor buoyancy in highly illuminated and stratified Arctic waters. In Atlantic waters, small cell size and spherical cell shape, in addition to photo‐physiological traits, such as high internal pigmentation, offer chromatic adaptation for survival in the low nutrient and dynamic mixing waters of the Atlantic Ocean. The use of automated techniques that quantify ecological traits holds exciting new opportunities to unravel linkages between the structure and function of plankton communities and marine ecosystems

Multi-frequency quantitative imaging of high contrat objects : canonical approximation

We consider the inverse scattering problem for three dimensional cylindrical objects which are infinite in the axial direction. Our aim being to achieve quantitative ultrasound imaging of bones, we focus at first on the simplified problem of reconstructing one section of the cylinder perpendicular to its axis. Several difficulties inherent to the bone structure and its environment (flesh) have to be dealt with, in order to solve the problem in vivo. Moreover, as in many imaging applications the problem is non-linear and the solution is not unique [l]. We focus in this paper on the quantitative reconstruction of the mechanical parameters (velocity, density) of a cylindrical object by approximating its geometry by a canonical circular cylinder according to the ICBA method (Intercepting Canonical Body Approximation) [2].We show that using the whole frequency range of the diffracted signal increases the accuracy and the robustness of the object's mechanical parameters reconstruction