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Modeling energy depletion in rat livers using Nash equilibrium metabolic pathway analysis
Get PDFThe current gold standard of Static Cold Storage (SCS), which is static cold storage on ice (about + 4 °C) in a specialized media such as the University of Wisconsin solution (UW), limits storage to few hours for vascular and metabolically active tissues such as the liver and the heart. The liver is arguably the pinnacle of metabolism in human body and therefore metabolic pathway analysis immediately becomes very relevant. In this article, a Nash Equilibrium (NE) approach, which is a first principles approach, is used to model and simulate the static cold storage and warm ischemia of a proposed model of liver cells. Simulations of energy depletion in the liver in static cold storage measured by ATP content and energy charge are presented along with comparisons to experimental data. In addition, conversion of Nash Equilibrium iterations to time are described along with an uncertainty analysis for the parameters in the model. Results in this work show that the Nash Equilibrium approach provides a good match to experimental data for energy depletion and that the uncertainty in model parameters is very small with percent variances less than 0.1%
Inequality, Economic and Cultural Polarization, and Entrepreneurship Challenges in Emerging Contexts
Get PDFRelevance of digital measures to people with early Parkinson’s for monitoring meaningful symptoms in the WATCH-PD study
Get PDFGlobal patterns in marine organic matter stoichiometry driven by phytoplankton ecophysiology
Get PDFThe proportion of major elements in marine organic matter links cellular processes to global nutrient, oxygen and carbon cycles. Differences in the C:N:P ratios of organic matter have been observed between ocean biomes, but these patterns have yet to be quantified from the underlying small-scale physiological and ecological processes. Here we use an ecosystem model that includes adaptive resource allocation within and between ecologically distinct plankton size classes to attribute the causes of global patterns in the C:N:P ratios. We find that patterns of N:C variation are largely driven by common physiological adjustment strategies across all phytoplankton, while patterns of N:P are driven by ecological selection for taxonomic groups with different phosphorus storage capacities. Although N:C varies widely due to cellular adjustment to light and nutrients, its latitudinal gradient is modest because of depth-dependent trade-offs between nutrient and light availability. Strong latitudinal variation in N:P reflects an ecological balance favouring small plankton with lower P storage capacity in the subtropics, and larger eukaryotes with a higher cellular P storage capacity in nutrient-rich high latitudes. A weaker N:P difference between southern and northern hemispheres, and between the Atlantic and Pacific oceans, reflects differences in phosphate available for cellular storage. Despite simulating only two phytoplankton size classes, the emergent global variability of elemental ratios resembles that of all measured species, suggesting that the range of growth conditions and ecological selection sustain the observed diversity of stoichiometry among phytoplankton
Low-Ammonium Environment Increases the Nutrient Exchange between Diatom–Diazotroph Association Cells and Facilitates Photosynthesis and N2 Fixation—a Mechanistic Modeling Analysis
Get PDFDiatom–diazotroph associations (DDAs) are one of the most important symbiotic dinitrogen (N2) fixing groups in the oligotrophic ocean. Despite their capability to fix N2, ammonium (NH4+) remains a key nitrogen (N) source for DDAs, and the effect of NH4+ on their metabolism remains elusive. Here, we developed a coarse-grained, cellular model of the DDA with NH4+ uptake and quantified how the level of extracellular NH4+ influences metabolism and nutrient exchange within the symbiosis. The model shows that, under a fixed growth rate, an increased NH4+ concentration may lower the required level of N2 fixation and photosynthesis, and decrease carbon (C) and N exchange. A low-NH4+ environment leads to more C and N in nutrient exchange and more fixed N2 to support a higher growth rate. With higher growth rates, nutrient exchange and metabolism increased. Our study shows a strong effect of NH4+ on metabolic processes within DDAs, and thus highlights the importance of in situ measurement of NH4+ concentrations
Modeling the elemental stoichiometry and silicon accumulation in diatoms
Get PDFDiatoms are important microorganisms involved in global primary production, nutrient cycling, and carbon sequestration. A unique feature of diatoms is their silica frustules, which impact sinking speed, defense against predators and viruses, and growth cycling. Thus, frustules are inherently linked to their role in ecosystems and biogeochemical cycles. However, constraints on cellular silicon levels remain unclear and few existing models resolve diatom elemental stoichiometry to specifically include variable silicon levels. Here, we use a coarse-grained model of the diatom, Thalassiosira pseudonana, compared with laboratory results to illustrate the relationship of silicon uptake with elemental stoichiometry of other nutrients. The model-data comparison suggests the balance between growth rate and silicon uptake constrains the amount of cellular silicon. Additionally, it expresses relationships between silicon, nitrogen, phosphorus, and carbon to changing growth rates in nitrogen-limited and phosphorus-limited regimes. First, our model-data comparison suggests Si uptake hits a maximum cellular quota at low growth rates and below this maximum there is independent Si uptake. In each nutrient regime, Si:N, Si:P, and Si:C decrease exponentially with growth rate when Si is below the maximum limit. This is explained by independent Si uptake and increased loss of Si to new cells. These results provide predictions of diatom stoichiometry and allocation, which can be used in ecosystem models to differentiate phytoplankton types to better represent diatoms’ contribution to global biogeochemical cycles and ecosystems
Overview of the MOSAiC expedition- Atmosphere
No full textWith the Arctic rapidly changing, the needs to observe, understand, and model the changes are essential. To support these needs, an annual cycle of observations of atmospheric properties, processes, and interactions were made while drifting with the sea ice across the central Arctic during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition from October 2019 to September 2020. An international team designed and implemented the comprehensive program to document and characterize all aspects of the Arctic atmospheric system in unprecedented detail, using a variety of approaches, and across multiple scales. These measurements were coordinated with other observational teams to explore crosscutting and coupled interactions with the Arctic Ocean, sea ice, and ecosystem through a variety of physical and biogeochemical processes. This overview outlines the breadth and complexity of the atmospheric research program, which was organized into 4 subgroups: atmospheric state, clouds and precipitation, gases and aerosols, and energy budgets. Atmospheric variability over the annual cycle revealed important influences from a persistent large-scale winter circulation pattern, leading to some storms with pressure and winds that were outside the interquartile range of past conditions suggested by long-term reanalysis. Similarly, the MOSAiC location was warmer and wetter in summer than the reanalysis climatology, in part due to its close proximity to the sea ice edge. The comprehensiveness of the observational program for characterizing and analyzing atmospheric phenomena is demonstrated via a winter case study examining air mass transitions and a summer case study examining vertical atmospheric evolution. Overall, the MOSAiC atmospheric program successfully met its objectives and was the most comprehensive atmospheric measurement program to date conducted over the Arctic sea ice. The obtained data will support a broad range of coupled-system scientific research and provide an important foundation for advancing multiscale modeling capabilities in the Arctic
An automated framework for long-range acoustic positioning of autonomous underwater vehicles
No full textAn automated method was developed to align underwater acoustic receptions at various depths and ranges to a single reference prediction of long range acoustic arrival structure as it evolves with range in order to determine source-receiver range. Acoustic receptions collected by four autonomous underwater vehicles deployed in the Philippine Sea as part of an ocean acoustic propagation experiment were used to demonstrate the method. The arrivals were measured in the upper 1000 m of the ocean at ranges up to 700 km from five moored, low frequency broadband acoustic tomography sources. Acoustic arrival time structure for pulse compressed signals at long ranges is relatively stable, yet real ocean variability presents challenges in acoustic arrival matching. The automated method takes advantage of simple projections of the measured structure onto the model space that represents all possible pairings of measured peaks to predicted eigenrays and minimizes the average travel-time offset across selected pairings. Compared to ranging results obtained by manual acoustic arrival matching, 93% of the automatically-obtained range estimates were within 75 m of the manually-obtained range estimates. Least squares residuals from positioning estimates using the automatically-obtained ranges with a fault detection scheme were 55 m root-mean-square
Barcoding and its application for visualizing ecological dynamics
Get PDFTime is perceived to be unidirectional and continuous in the philosophy of science. This continuity can play a crucial role in time series analysis as events are generally seen as an outcome of the past, or subject to events that occurred previously in time. In this study, we describe an ordinal approach to perceiving ecological time series – one that relies on pattern formation with both antecedent and future events. Our approach defines a limited set of structural shapes that can occur for past, present, and future time points. Such a library of all possible shapes can then be used for novel approaches to data visualization and time series analysis. We applied this method to simple ecological models and then to natural time series data for measles cases in London and the phytoplankter Pseudo-nitzschia spp. in Narragansett Bay, Rhode Island. Alternative perspectives on time series representation can strengthen our ability to identify important patterns in dynamics and effectively discriminate between similar time series. When used in conjunction with conventional line-plots, barcodes can be tailored to demonstrate the presence or absence of specific structural patterns or features. Our results show that data exploration without the assumption of time series continuity can yield important and novel insight into the behavior of ecological systems
