A Computational Model for Estimating the Progression of COVID-19 Cases in the US West and East Coast Population Regions

AbstractThe ongoing coronavirus disease 2019 (COVID-19) pandemic is of global concern and has recently emerged in the US. In this paper, we construct a stochastic variant of the SEIR model to make a quasi-worst-case scenario prediction of the COVID-19 outbreak in the US West and East Coasts. The model is then fitted to current data and implemented using Runge-Kutta methods. Our computation results predict that the number of new cases would peak around mid-April 2000 and begin to abate by July, and that the number of cases of COVID-19 might be significantly mitigated by having greater numbers of functional testing kits available for screening. The model also showed how small changes in variables can make large differences in outcomes and highlights the importance of healthcare preparedness during pandemics.Author SummaryCoronavirus disease 2019 (COVID-19) has escalated into a global pandemic and has recently emerged in the US. While some countries have managed to contain COVID-19 efficiently, other countries previously thought to have been well-prepared for outbreaks due to higher living standards and healthcare quality have witnessed an unexpected number of cases. It is currently unclear how the US can cope with the COVID-19 pandemic, especially after mishaps during the initial stages. Our study combines conditions unique to the US and transmission dynamics in regions affected most by COVID-19 to produce a quasi-worse-case scenario of COVID-19 in the US and shows the importance of healthcare preparedness during pandemics.

Download Full-text

Review 3: A Computational Model for Estimating the Progression of COVID-19 Cases in the US West and East Coast Population Regions

10.1017/exp.2020.45.pr3 ◽

2020 ◽

Author(s):

Ivan Allaman

Keyword(s):

Computational Model ◽

East Coast ◽

The Us ◽

Us West

Download Full-text

Fluorine Mass Balance and Suspect Screening in Marine Mammals from the Northern Hemisphere

10.26434/chemrxiv.10128653.v1 ◽

2019 ◽

Author(s):

Kyra Spaan ◽

Carmen van Noordenburg ◽

Merle Plassmann ◽

Lara Schultes ◽

Susan D. Shaw ◽

...

Keyword(s):

Mass Balance ◽

Northern Hemisphere ◽

Marine Mammals ◽

East Coast ◽

Suspect Screening ◽

Targeted Analysis ◽

The Us ◽

Polyfluoroalkyl Substances ◽

Fluorine Determination ◽

Us West

There is increasing evidence that the ~20 routinely monitored per- and polyfluoroalkyl substances (PFASs) account for only a fraction of extractable organofluorine (EOF) occurring in the environment. To assess whether PFAS exposure is being underestimated in marine mammals from the Northern Hemisphere, we performed a fluorine mass balance on liver tissues from 11 different species using a combination of targeted PFAS analysis, EOF and total fluorine determination, and suspect screening. Samples were obtained from the east coast United States (US), west and east coast of Greenland, Iceland, and Sweden from 2000-2017. Of the 36 target PFASs, perfluorooctane sulfonate (PFOS) dominated in all but one Icelandic and three US samples, where the 7:3 fluorotelomer carboxylic acid (7:3 FTCA) was prevalent. This is the first report of 7:3 FTCA in polar bears (~1000 ng/g, ww) and cetaceans (<6-190 ng/g, ww). In 18 out of 25 samples, EOF was not significantly greater than fluorine concentrations derived from sum target PFASs. For the remaining 7 samples (mostly from the US east coast), 30-75% of the EOF was unidentified. Suspect screening revealed an additional 33 PFASs (not included in the targeted analysis) bringing the total to 59 detected PFASs from 12 different classes. Overall, these results highlight the importance of a multi-platform approach for accurately characterizing PFAS exposure in marine mammals.

Download Full-text

Fluorine Mass Balance and Suspect Screening in Marine Mammals from the Northern Hemisphere

10.26434/chemrxiv.10128653 ◽

2019 ◽

Author(s):

Kyra Spaan ◽

Carmen van Noordenburg ◽

Merle Plassmann ◽

Lara Schultes ◽

Susan D. Shaw ◽

...

Keyword(s):

Mass Balance ◽

Northern Hemisphere ◽

Marine Mammals ◽

East Coast ◽

Suspect Screening ◽

Targeted Analysis ◽

The Us ◽

Polyfluoroalkyl Substances ◽

Fluorine Determination ◽

Us West

There is increasing evidence that the ~20 routinely monitored per- and polyfluoroalkyl substances (PFASs) account for only a fraction of extractable organofluorine (EOF) occurring in the environment. To assess whether PFAS exposure is being underestimated in marine mammals from the Northern Hemisphere, we performed a fluorine mass balance on liver tissues from 11 different species using a combination of targeted PFAS analysis, EOF and total fluorine determination, and suspect screening. Samples were obtained from the east coast United States (US), west and east coast of Greenland, Iceland, and Sweden from 2000-2017. Of the 36 target PFASs, perfluorooctane sulfonate (PFOS) dominated in all but one Icelandic and three US samples, where the 7:3 fluorotelomer carboxylic acid (7:3 FTCA) was prevalent. This is the first report of 7:3 FTCA in polar bears (~1000 ng/g, ww) and cetaceans (<6-190 ng/g, ww). In 18 out of 25 samples, EOF was not significantly greater than fluorine concentrations derived from sum target PFASs. For the remaining 7 samples (mostly from the US east coast), 30-75% of the EOF was unidentified. Suspect screening revealed an additional 33 PFASs (not included in the targeted analysis) bringing the total to 59 detected PFASs from 12 different classes. Overall, these results highlight the importance of a multi-platform approach for accurately characterizing PFAS exposure in marine mammals.

Download Full-text

Robust Blood-Glucose Control of Type I Diabetes Patients Under Intensive Care Using Mathematica

Encyclopedia of Healthcare Information Systems ◽

10.4018/978-1-59904-889-5.ch151 ◽

2008 ◽

pp. 1210-1219 ◽

Cited By ~ 1

Author(s):

Béla Paláncz ◽

Levente Kovács ◽

Balázs Benyó ◽

Zoltán Benyó

Keyword(s):

Intensive Care ◽

Type I Diabetes ◽

Design Method ◽

Blood Glucose Control ◽

Model Parameters ◽

Type I ◽

Case Scenario ◽

Worst Case ◽

Robust Control Design ◽

Parameter Values

This article presents a robust control design method on frequency domain using Mathematica for regularization of glucose level in Type I diabetes persons under intensive care. The method originally proposed under Mathematica by Helton and Merino (1998) is now improved with a disturbance rejection constraint inequality, and is tested on the three-state minimal model. Nonlinear closed loop simulation in state-space, in case of standard meal disturbances, demonstrates the robustness of the resulted high-order linear controller. The obtained results are compared with H8 design implemented with Matlab, proving that the controller (for the considered model parameters) can operate properly, even in case of parameter values of the worst-case scenario.

Download Full-text

Effect of climate change on the potential distribution of Heloderma alvarezi (Squamata, Helodermatidae)

ZooKeys ◽

10.3897/zookeys.1070.69186 ◽

2021 ◽

Vol 1070 ◽

pp. 1-12

Author(s):

Aarón Gómez-Cruz ◽

Nancy G. Santos-Hernández ◽

José Alberto Cruz ◽

Daniel Ariano-Sánchez ◽

Christian Ruiz-Castillejos ◽

...

Keyword(s):

Climate Change ◽

Potential Distribution ◽

Current Data ◽

Conservation Strategies ◽

Suitable Habitat ◽

Case Scenario ◽

Worst Case ◽

Human Footprint ◽

Bioclimatic Variables ◽

The Impact

Climate change represents a real threat to biodiversity conservation worldwide. Although the effects on several species of conservation priority are known, comprehensive information about the impact of climate change on reptile populations is lacking. In the present study, we analyze outcomes on the potential distribution of the black beaded lizard (Heloderma alvarezi Bogert & Martin del Campo, 1956) under global warming scenarios. Its potential distribution, at present and in projections for the years 2050 and 2070, under both optimistic and pessimistic climate change forecasts, were computed using current data records and seven bioclimatic variables. General results predict a shift in the future potential distribution of H. alvarezi due to temperature increase. The optimistic scenario (4.5 W/m2) for 2070 suggests an enlargement in the species’ distribution as a response to the availability of new areas of suitable habitat. On the contrary, the worst-case scenario (7 W/m2) shows a distribution decrease by 65%. Moreover, the range distribution of H. alvarezi is directly related to the human footprint, which consequently could magnify negative outcomes for this species. Our research elucidates the importance of conservation strategies to prevent the extinction of the black beaded lizard, especially considering that this species is highly threatened by aversive hunting.

Download Full-text

Efficient reaction deletion algorithms for redesign of constraint-based metabolic networks for metabolite production with weak coupling

10.1101/563437 ◽

2019 ◽

Author(s):

Takeyuki Tamura

Keyword(s):

Strong Coupling ◽

Metabolic Networks ◽

Search Space ◽

Anaerobic Conditions ◽

Case Scenario ◽

Worst Case ◽

Metabolic Network Analysis ◽

Network Topologies ◽

Genome Scale ◽

Parameter Values

AbstractBackgroundMetabolic network analysis through flux balance is an established method for the computational redesign of production strains in metabolic engineering. The computational redesign is often based on reaction deletions from the original wild type networks. A key principle often used in this method is the production of target metabolites as by-products of cell growth. From a viewpoint of bioinformatics, it is very important to prepare a set of algorithms that can determine reaction deletions that achieve growth coupling whatever network topologies, target metabolites and parameter values will be considered in the future. Recently, the strong coupling-based method was used to demonstrate that the coupling of growth and production is possible for nearly all metabolites through reaction deletions in genome-scale metabolic models of Escherichia coli and Saccharomyces cerevisiae under aerobic conditions. However, when growing S. cerevisiae under anaerobic conditions, deletion strategies using the strong coupling-based method were possible for only 3.9% of all metabolites. Therefore, it is necessary to develop algorithms that can achieve growth coupling by reaction deletions for the conditions that the strong coupling-based method was not efficient.ResultsWe developed an algorithm that could calculate the reaction deletions that achieve the coupling of growth and production for 91.3% metabolites in genome-scale models of S. cerevisiae under anaerobic conditions. This analysis was conducted for the worst-case-scenario using flux variability analysis. To demonstrate the feasibility of the coupling, we derived appropriate reaction deletions using the new algorithm for target production in which the search space was divided into small cubes (CubeProd).ConclusionsWe developed a novel algorithm, CubeProd, to demonstrate that growth coupling is possible for most metabolites in S.cerevisiae under anaerobic conditions. This may imply that growth coupling is possible by reaction deletions for most target metabolites in any genome-scale constraint-based metabolic networks. The developed software, CubeProd, implemented in MATLAB, and the obtained reaction deletion strategies are freely available.

Download Full-text

Efficient reaction deletion algorithms for redesign of constraint-based metabolic networks for metabolite production with weak coupling

10.21203/rs.2.24108/v1 ◽

2020 ◽

Author(s):

Takeyuki Tamura

Keyword(s):

Strong Coupling ◽

Metabolic Networks ◽

Search Space ◽

Anaerobic Conditions ◽

Case Scenario ◽

Worst Case ◽

Metabolic Network Analysis ◽

Network Topologies ◽

Genome Scale ◽

Parameter Values

Abstract Background: Metabolic network analysis through flux balance is an established method for the computational redesign of production strains in metabolic engineering. The computational redesign is often based on reaction deletions from the original wild type networks. A key principle often used in this method is the production of target metabolites as by-products of cell growth. From a viewpoint of bioinformatics, it is very important to prepare a set of algorithms that can determine reaction deletions that achieve growth coupling whatever network topologies, target metabolites and parameter values will be considered in the future. Recently, the strong coupling-based method was used to demonstrate that the coupling of growth and production is possible for nearly all metabolites through reaction deletions in genome-scale metabolic models of Escherichia coli and Saccharomyces cerevisiae under aerobic conditions. However, when growing S. cerevisiae under anaerobic conditions, deletion strategies using the strong coupling-based method were possible for only 3.9% of all metabolites. Therefore, it is necessary to develop algorithms that can achieve growth coupling by reaction deletions for the conditions that the strong coupling-based method was not efficient. Results: We developed an algorithm that could calculate the reaction deletions that achieve the coupling of growth and production for 91.3% metabolites in genome-scale models of S. cerevisiae under anaerobic conditions. This analysis was conducted for the worst-case scenario using flux variability analysis. To demonstrate the feasibility of the coupling, we derived appropriate reaction deletions using the new algorithm for target production in which the search space was divided into small cubes (CubeProd). Conclusions: We developed a novel algorithm, CubeProd, to demonstrate that growth coupling is possible for most metabolites in S.cerevisiae under anaerobic conditions. This may imply that growth coupling is possible by reaction deletions for most target metabolites in any genome-scale constraint-based metabolic networks. The developed software, CubeProd, implemented in MATLAB, and the obtained reaction deletion strategies are freely available.

Download Full-text