Noninvasive imaging of focal atherosclerotic lesions using fluorescence molecular tomography

Insights into the etiology of stroke and myocardial infarction suggest that rupture of unstable atherosclerotic plaque is the precipitating event. Clinicians lack tools to detect lesion instability early enough to intervene, and are often left to manage patients empirically, or worse, after plaque rupture. Noninvasive imaging of the molecular events signaling prerupture plaque progression has the potential to reduce the morbidity and mortality associated with myocardial infarction and stroke by allowing early intervention. Here, we demonstrate proof-of-principle in vivo molecular imaging of C-type natriuretic peptide receptor in focal atherosclerotic lesions in the femoral arteries of New Zealand white rabbits using a custom built fiber-based, fluorescence molecular tomography (FMT) system. Longitudinal imaging showed changes in the fluorescence signal intensity as the plaque progressed in the air-desiccated vessel compared to the uninjured vessel, which was validated by ex vivo tissue studies. In summary, we demonstrate the potential of FMT for noninvasive detection of molecular events leading to unstable lesions heralding plaque rupture

Gaugino and Scalar Masses in the Landscape

In this letter we demonstrate the genericity of suppressed gaugino masses M_a \sim m_{3/2}/ln(M_P/m_{3/2}) in the IIB string landscape, by showing that this relation holds for D7-brane gauginos whenever the associated modulus is stabilised by nonperturbative effects. Although m_{3/2} and M_a take many different values across the landscape, the above small mass hierarchy is maintained. We show that it is valid for models with an arbitrary number of moduli and applies to both the KKLT and exponentially large volume approaches to Kahler moduli stabilisation. In the latter case we explicitly calculate gaugino and moduli masses for compactifications on the two-modulus Calabi-Yau P^4_[1,1,1,6,9]. In the large-volume scenario we also show that soft scalar masses are approximately universal with m_i^2 \sim m_{3/2}^2 (1 + \epsilon_i), with the non-universality parametrised by \epsilon_i \sim 1/ln (M_P/m_{3/2})^2 \sim 1/1000. We briefly discuss possible phenomenological implications of our results.Comment: 15 pages, JHEP style; v2. reference adde

The Influences of Reproductive Status and Acute Stress on the Levels of Phosphorylated Mu Opioid Receptor Immunoreactivity in Rat Hippocampus

Opioids play a critical role in hippocampally dependent behavior and plasticity. In the hippocampal formation, mu opioid receptors (MOR) are prominent in parvalbumin (PARV) containing interneurons. Previously we found that gonadal hormones modulate the trafficking of MORs in PARV interneurons. Although sex differences in response to stress are well documented, the point at which opioids, sex, and stress interact to influence hippocampal function remains elusive. Thus, we used quantitative immunocytochemistry in combination with light and electron microscopy for the phosphorylated MOR (pMOR) at the SER375 carboxy-terminal residue in male and female rats to assess these interactions. In both sexes, pMOR-immunoreactivity (ir) was prominent in axons and terminals and in a few neuronal somata and dendrites, some of which contained PARV in the mossy fiber pathway region of the dentate gyrus (DG) hilus and CA3 stratum lucidum. In unstressed rats, the levels of pMOR-ir in the DG or CA3 were not affected by sex or estrous cycle stage. However, immediately following 30 min of acute immobilization stress (AIS), males had higher levels of pMOR-ir whereas females at proestrus and estrus (high estrogen stages) had lower levels of pMOR-ir within the DG. In contrast, the number and types of neuronal profiles with pMOR-ir were not altered by AIS in either males or proestrus females. These data demonstrate that although gonadal steroids do not affect pMOR levels at resting conditions, they are differentially activated both pre and postsynaptic MORs following stress. These interactions may contribute to the reported sex differences in hippocampally dependent behaviors in stressed animals

A framework for characterising and evaluating the effectiveness of environmental modelling

Environmental modelling is transitioning from the traditional paradigm that focuses on the model and its quantitative performance to a more holistic paradigm that recognises successful model-based outcomes are closely tied to undertaking modelling as a social process, not just as a technical procedure. This paper redefines evaluation as a multi-dimensional and multi-perspective concept, and proposes a more complete framework for identifying and measuring the effectiveness of modelling that serves the new paradigm. Under this framework, evaluation considers a broader set of success criteria, and emphasises the importance of contextual factors in determining the relevance and outcome of the criteria. These evaluation criteria are grouped into eight categories: project efficiency, model accessibility, credibility, saliency, legitimacy, satisfaction, application, and impact. Evaluation should be part of an iterative and adaptive process that attempts to improve model-based outcomes and foster pathways to better futures

Characterization of organic aerosol across the global remote troposphere: A comparison of ATom measurements and global chemistry models

The spatial distribution and properties of submicron organic aerosol (OA) are among the key sources of uncertainty in our understanding of aerosol effects on climate. Uncertainties are particularly large over remote regions of the free troposphere and Southern Ocean, where very few data have been available and where OA predictions from AeroCom Phase II global models span 2 to 3 orders of magnitude, greatly exceeding the model spread over source regions. The (nearly) pole-to-pole vertical distribution of nonrefractory aerosols was measured with an aerosol mass spectrometer onboard the NASA DC-8 aircraft as part of the Atmospheric Tomography (ATom) mission during the Northern Hemisphere summer (August 2016) and winter (February 2017). This study presents the first extensive characterization of OA mass concentrations and their level of oxidation in the remote atmosphere. OA and sulfate are the major contributors by mass to submicron aerosols in the remote troposphere, together with sea salt in the marine boundary layer. Sulfate was dominant in the lower stratosphere. OA concentrations have a strong seasonal and zonal variability, with the highest levels measured in the lower troposphere in the summer and over the regions influenced by biomass burning from Africa (up to 10 μgsm-3). Lower concentrations (~ 0:1 0.3 μgsm-3) are observed in the northern middle and high latitudes and very low concentrations (< 0:1 μgsm-3) in the southern middle and high latitudes. The ATom dataset is used to evaluate predictions of eight current global chemistry models that implement a variety of commonly used representations of OA sources and chemistry, as well as of the AeroCom-II ensemble. The current model ensemble captures the average vertical and spatial distribution of measured OA concentrations, and the spread of the individual models remains within a factor of 5. These results are significantly improved over the AeroCom-II model ensemble, which shows large overestimations over these regions. However, some of the improved agreement with observations occurs for the wrong reasons, as models have the tendency to greatly overestimate the primary OA fraction and underestimate the sec-ondary fraction. Measured OA in the remote free troposphere is highly oxygenated, with organic aerosol to organic carbon (OA= OC) ratios of ~ 2.2 2.8, and is 30 % 60% more oxygenated than in current models, which can lead to significant errors in OA concentrations. The model measurement comparisons presented here support the concept of a more dynamic OA system as proposed by Hodzic et al. (2016), with enhanced removal of primary OA and a stronger production of secondary OA in global models needed to provide better agreement with observations. © 2020 IEEE Computer Society. All rights reserved

Effective modeling for integrated water resource management: a guide to contextual practices by phases and steps and future opportunities

The effectiveness of Integrated Water Resource Management (IWRM) modeling hinges on the quality of practices employed through the process, starting from early problem definition all the way through to using the model in a way that serves its intended purpose. The adoption and implementation of effective modeling practices need to be guided by a practical understanding of the variety of decisions that modelers make, and the information considered in making these choices. There is still limited documented knowledge on the modeling workflow, and the role of contextual factors in determining this workflow and which practices to employ. This paper attempts to contribute to this knowledge gap by providing systematic guidance of the modeling practices through the phases (Planning, Development, Application, and Perpetuation) and steps that comprise the modeling process, positing questions that should be addressed. Practice-focused guidance helps explain the detailed process of conducting IWRM modeling, including the role of contextual factors in shaping practices. We draw on findings from literature and the authors’ collective experience to articulate what and how contextual factors play out in employing those practices. In order to accelerate our learning about how to improve IWRM modeling, the paper concludes with five key areas for future practice-related research: knowledge sharing, overcoming data limitations, informed stakeholder involvement, social equity and uncertainty management. © 2019 Elsevier Lt

Reduced basis approximation and a posteriori error estimation for the time-dependent viscous Burgers’ equation

In this paper we present rigorous a posteriori L 2 error bounds for reduced basis approximations of the unsteady viscous Burgers’ equation in one space dimension. The a posteriori error estimator, derived from standard analysis of the error-residual equation, comprises two key ingredients—both of which admit efficient Offline-Online treatment: the first is a sum over timesteps of the square of the dual norm of the residual; the second is an accurate upper bound (computed by the Successive Constraint Method) for the exponential-in-time stability factor. These error bounds serve both Offline for construction of the reduced basis space by a new POD-Greedy procedure and Online for verification of fidelity. The a posteriori error bounds are practicable for final times (measured in convective units) T≈O(1) and Reynolds numbers ν[superscript −1]≫1; we present numerical results for a (stationary) steepening front for T=2 and 1≤ν[superscript −1]≤200.United States. Air Force Office of Scientific Research (AFOSR Grant FA9550-05-1-0114)United States. Air Force Office of Scientific Research (AFOSR Grant FA-9550-07-1-0425)Singapore-MIT Alliance for Research and Technolog

Assessing the carcinogenic potential of low-dose exposures to chemical mixtures in the environment: the challenge ahead.

Lifestyle factors are responsible for a considerable portion of cancer incidence worldwide, but credible estimates from the World Health Organization and the International Agency for Research on Cancer (IARC) suggest that the fraction of cancers attributable to toxic environmental exposures is between 7% and 19%. To explore the hypothesis that low-dose exposures to mixtures of chemicals in the environment may be combining to contribute to environmental carcinogenesis, we reviewed 11 hallmark phenotypes of cancer, multiple priority target sites for disruption in each area and prototypical chemical disruptors for all targets, this included dose-response characterizations, evidence of low-dose effects and cross-hallmark effects for all targets and chemicals. In total, 85 examples of chemicals were reviewed for actions on key pathways/mechanisms related to carcinogenesis. Only 15% (13/85) were found to have evidence of a dose-response threshold, whereas 59% (50/85) exerted low-dose effects. No dose-response information was found for the remaining 26% (22/85). Our analysis suggests that the cumulative effects of individual (non-carcinogenic) chemicals acting on different pathways, and a variety of related systems, organs, tissues and cells could plausibly conspire to produce carcinogenic synergies. Additional basic research on carcinogenesis and research focused on low-dose effects of chemical mixtures needs to be rigorously pursued before the merits of this hypothesis can be further advanced. However, the structure of the World Health Organization International Programme on Chemical Safety 'Mode of Action' framework should be revisited as it has inherent weaknesses that are not fully aligned with our current understanding of cancer biology

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives