Quantifying in vitro B. anthracis growth and PA production and decay: a mathematical modelling approach
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SUBMITTER: Williams B
PROVIDER: S-EPMC10980772 | biostudies-literature | 2024 Jan
REPOSITORIES: biostudies-literature
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Project description:BackgroundAntibiotic-resistant bacteria (ARB) are selected by the use of antibiotics. The rational design of interventions to reduce levels of antibiotic resistance requires a greater understanding of how and where ARB are acquired. Our aim was to determine whether acquisition of ARB occurs more often in the community or hospital setting.MethodsWe used a mathematical model of the natural history of ARB to estimate how many ARB were acquired in each of these two environments, as well as to determine key parameters for further investigation. To do this, we explored a range of realistic parameter combinations and considered a case study of parameters for an important subset of resistant strains in England.ResultsIf we consider all people with ARB in the total population (community and hospital), the majority, under most clinically derived parameter combinations, acquired their resistance in the community, despite higher levels of antibiotic use and transmission of ARB in the hospital. However, if we focus on just the hospital population, under most parameter combinations a greater proportion of this population acquired ARB in the hospital.ConclusionsIt is likely that the majority of ARB are being acquired in the community, suggesting that efforts to reduce overall ARB carriage should focus on reducing antibiotic usage and transmission in the community setting. However, our framework highlights the need for better pathogen-specific data on antibiotic exposure, ARB clearance and transmission parameters, as well as the link between carriage of ARB and health impact. This is important to determine whether interventions should target total ARB carriage or hospital-acquired ARB carriage, as the latter often dominated in hospital populations.
| S-EPMC6106940 | biostudies-literature
Project description:Systems composed of high density cells incorporated with growth factor-releasing polymer microspheres have recently been shown to promote chondrogenic differentiation and cartilage formation. Within these systems, the effects of spatial and temporal patterning of growth factor release on hyaline cartilage-specific extracellular matrix production have been examined. However, at present, it is unclear which microsphere densities and growth factor delivery profiles are optimal for inducing human mesenchymal stem cell differentiation and glycosaminoglycan production. A mathematical model to describe glycosaminoglycan production as a function of initial microsphere loading and microsphere degradation rate over a period of 3 weeks is presented. Based on predictions generated by this model, it may be feasible to design a bioactive microsphere system with specific spatiotemporal growth factor presentation characteristics to promote glycosaminoglycan production at controllable rates. Copyright © 2014 John Wiley & Sons, Ltd.
| S-EPMC6927471 | biostudies-literature
Project description:The growth of microorganisms involves the conversion of nutrients in the environment into biomass, mostly proteins and other macromolecules. This conversion is accomplished by networks of biochemical reactions cutting across cellular functions, such as metabolism, gene expression, transport and signalling. Mathematical modelling is a powerful tool for gaining an understanding of the functioning of this large and complex system and the role played by individual constituents and mechanisms. This requires models of microbial growth that provide an integrated view of the reaction networks and bridge the scale from individual reactions to the growth of a population. In this review, we derive a general framework for the kinetic modelling of microbial growth from basic hypotheses about the underlying reaction systems. Moreover, we show that several families of approximate models presented in the literature, notably flux balance models and coarse-grained whole-cell models, can be derived with the help of additional simplifying hypotheses. This perspective clearly brings out how apparently quite different modelling approaches are related on a deeper level, and suggests directions for further research.
| S-EPMC5721159 | biostudies-literature
Project description:In vertical farms, the supplementation of far-red light has been widely applied to regulate plant growth and development. However, the relative contribution of far-red to photosynthesis and plant growth in indoor production systems is not sufficiently quantified. This study quantify the photosynthesis and growth responses under different levels of supplemental far-red in lettuce using a 3D modelling approach. Lettuce were cultivated under either white light or red to far-red (R:FR) ratio of 1.6 or 0.8. Measurements of plant morphological traits, leaf photosynthesis, and organ fresh and dry mass were taken and the 3D modelling approach was used to simulate plant photosynthesis and biomass accumulation. Results showed that leaf elevation angle, leaf expansion rate, and plant height significantly increased at each growth stage as the R:FR ratio decreased. Far-red light also promoted plant growth, leading to an increase in the dry and fresh weight of lettuce throughout the entire growth period. However, plants cultivated at low R:FR showed reduced maximum Rubisco carboxylation rate and maximum electron transport rate, which indicated that far-red light reduced the photosynthetic capacity in lettuce. Nevertheless, 3D model simulations demonstrated that plants exposed to enhanced far-red light exhibited increased light interception and whole-plant photosynthesis. The integrated analysis of photosynthetic parameters and plant morphological changes on the photosynthetic rate of the whole plant indicated that the positive effects of plant morphological changes outweighed the negative impacts of photosynthetic parameters. These results implied that far-red light-induced morphological changes enhanced light interception and whole-plant photosynthesis, thereby increased lettuce yield.
| S-EPMC11638671 | biostudies-literature
Project description:The mechanism by which flat hexagonal lattices of clathrin trimers transform into pentagonal/hexagonal spheres remains a mystery. In light of the geometrical nature of this process we have pursued a mathematical approach to the question. Through the geometrical analysis of flat hexagonal lattices we have discovered three possible forms of transformation to introduce curvature into the centre of the lattice: hub-centre transformation; hub-edge transformation; fringe transformation. Hub-edge and fringe transformations are used first to close the lattice while introducing localized curvature at the edges of the lattice. Hub-centre transformation is used after closure to relax the severely localized curvature generated during closure. This scheme not only maximizes the size of the coated vesicle generated, but also minimizes the number of transformations, thus minimizing the energy expended.
| S-EPMC1152632 | biostudies-other
Project description:BackgroundSimultaneous inhibition of multiple components of the BRAF-MEK-ERK cascade (vertical inhibition) has become a standard of care for treating BRAF-mutant melanoma. However, the molecular mechanism of how vertical inhibition synergistically suppresses intracellular ERK activity, and consequently cell proliferation, are yet to be fully elucidated.MethodsWe develop a mechanistic mathematical model that describes how the mutant BRAF inhibitor, dabrafenib, and the MEK inhibitor, trametinib, affect BRAFV600E-MEK-ERK signalling. The model is based on a system of chemical reactions that describes cascade signalling dynamics. Using mass action kinetics, the chemical reactions are re-expressed as ordinary differential equations that are parameterised by in vitro data and solved numerically to obtain the temporal evolution of cascade component concentrations.ResultsThe model provides a quantitative method to compute how dabrafenib and trametinib can be used in combination to synergistically inhibit ERK activity in BRAFV600E-mutant melanoma cells. The model elucidates molecular mechanisms of vertical inhibition of the BRAFV600E-MEK-ERK cascade and delineates how elevated BRAF concentrations generate drug resistance to dabrafenib and trametinib. The computational simulations further suggest that elevated ATP levels could be a factor in drug resistance to dabrafenib.ConclusionsThe model can be used to systematically motivate which dabrafenib-trametinib dose combinations, for treating BRAFV600E-mutated melanoma, warrant experimental investigation.
| S-EPMC8608797 | biostudies-literature
Project description:BackgroundThe UK was the first country to start national COVID-19 vaccination programmes, initially administering doses 3 weeks apart. However, early evidence of high vaccine effectiveness after the first dose and the emergence of the SARS-CoV-2 alpha variant prompted the UK to extend the interval between doses to 12 weeks. In this study, we aimed to quantify the effect of delaying the second vaccine dose in England.MethodsWe used a previously described model of SARS-CoV-2 transmission, calibrated to COVID-19 surveillance data from England, including hospital admissions, hospital occupancy, seroprevalence data, and population-level PCR testing data, using a Bayesian evidence-synthesis framework. We modelled and compared the epidemic trajectory in the counterfactual scenario in which vaccine doses were administered 3 weeks apart against the real reported vaccine roll-out schedule of 12 weeks. We estimated and compared the resulting numbers of daily infections, hospital admissions, and deaths. In sensitivity analyses, we investigated scenarios spanning a range of vaccine effectiveness and waning assumptions.FindingsIn the period from Dec 8, 2020, to Sept 13, 2021, the number of individuals who received a first vaccine dose was higher under the 12-week strategy than the 3-week strategy. For this period, we estimated that delaying the interval between the first and second COVID-19 vaccine doses from 3 to 12 weeks averted a median (calculated as the median of the posterior sample) of 58 000 COVID-19 hospital admissions (291 000 cumulative hospitalisations [95% credible interval 275 000-319 000] under the 3-week strategy vs 233 000 [229 000-238 000] under the 12-week strategy) and 10 100 deaths (64 800 deaths [60 200-68 900] vs 54 700 [52 800-55 600]). Similarly, we estimated that the 3-week strategy would have resulted in more infections compared with the 12-week strategy. Across all sensitivity analyses the 3-week strategy resulted in a greater number of hospital admissions. In results by age group, the 12-week strategy led to more hospitalisations and deaths in older people in spring 2021, but fewer following the emergence of the delta variant during summer 2021.InterpretationEngland's delayed-second-dose vaccination strategy was informed by early real-world data on vaccine effectiveness in the context of limited vaccine supplies in a growing epidemic. Our study shows that rapidly providing partial (single-dose) vaccine-induced protection to a larger proportion of the population was successful in reducing the burden of COVID-19 hospitalisations and deaths overall.FundingUK National Institute for Health Research; UK Medical Research Council; Community Jameel; Wellcome Trust; UK Foreign, Commonwealth and Development Office; Australian National Health and Medical Research Council; and EU.
| S-EPMC9910835 | biostudies-literature
Project description:Stable isotopes are currently used to measure glucose fluxes responsible for observed glucose concentrations, providing information on hepatic and peripheral insulin sensitivity. The determination of glucose turnover, along with fasting and postprandial glucose concentrations, is relevant for inferring insulin sensitivity levels. At equilibrium (e.g. during the fasting state) the rate of glucose entering the circulation equals its rate of disappearance from the circulation. If under these conditions tracer is infused at a constant rate and Specific Activity (SA) or Tracer to Tracee (TTR) ratio is computed, the Rate of Appearance (RA) equals the Rate of Disappearance (RD) and equals the ratio between infusion rate and TTR or SA. In the post-prandial situation or during perturbation studies, however, estimation of RA and RD becomes more complex because they are not necessarily equal and, furthermore, may vary over time due to gastric emptying, glucose absorption, appearance of ingested or infused glucose, variations of EGP and glucose disappearance. Up to now, the most commonly used approach to compute RA, RD and EGP has been the single-pool model by Steele. Several authors, however, report pitfalls in the use of this method, such as "paradoxical" increase in EGP immediately after meal ingestion and "negative" rates of EGP. Different attempts have been made to reduce the impact of these errors, but the same problems are still encountered. In the present work a completely different approach is proposed, where cold and labeled [6, 6-2H2] glucose observations are simultaneously fitted and where both RD and EGP are represented by simple but reasonable functions. As an example, this approach is applied to an intra-venous experiment, where cold glucose is infused at variable rates to reproduce a desired glycaemic time-course. The goal of the present work is to show that appropriate, if simple, modelling of the whole infusion procedure together with the underlying physiological system allows robust estimation of EGP with single-tracer administration, without the artefacts produced by the Steele method.
| S-EPMC9770442 | biostudies-literature
Project description:BackgroundMpumalanga in South Africa is committed to eliminating malaria by 2018 and efforts are increasing beyond that necessary for malaria control. Differential Equation models may be used to study the incidence and spread of disease with an important benefit being the ability to enact exogenous change on the system to predict impact without committing any real resources. The model is a deterministic non-linear ordinary differential equation representation of the dynamics of the human population. The model is fitted to weekly data of treated cases from 2002 to 2008, and then validated with data from 2009 to 2012. Elimination-focused interventions such as the scale-up of vector control, mass drug administration, a focused mass screen and treat campaign and foreign source reduction are applied to the model to assess their potential impact on transmission.ResultsScaling up vector control by 10% and 20% resulted in substantial predicted decreases in local infections with little impact on imported infections. Mass drug administration is a high impact but short-lived intervention with predicted decreases in local infections of less that one infection per year. However, transmission reverted to pre-intervention levels within three years. Focused mass screen and treat campaigns at border-entry points are predicted to result in a knock-on decrease in local infections through a reduction in the infectious reservoir. This knock-on decrease in local infections was also predicted to be achieved through foreign source reduction. Elimination was only predicted to be possible under the scenario of zero imported infections in Mpumalanga.ConclusionsA constant influx of imported infections show that vector control alone will not be able to eliminate local malaria as it is insufficient to interrupt transmission. Both mass interventions have a large and immediate impact. Yet in countries with a large migrant population, these interventions may fail due to the reintroduction of parasites and their impact may be short-lived. While all strategies (in isolation or combined) contributed to decreasing local infections, none was predicted to decrease local infections to zero. The number of imported infections highlights the importance of reducing imported infections at source, and a regional approach to malaria elimination.
| S-EPMC4127654 | biostudies-literature
Project description:BackgroundThe emergence and spread of antibiotic-resistant pathogens have led to the exploration of antibiotic combinations to enhance clinical effectiveness and counter resistance development. Synergistic and antagonistic interactions between antibiotics can intensify or diminish the combined therapy's impact. Moreover, these interactions can evolve as bacteria transition from wildtype to mutant (resistant) strains. Experimental studies have shown that the antagonistically interacting antibiotics against wildtype bacteria slow down the evolution of resistance. Interestingly, other studies have shown that antibiotics that interact antagonistically against mutants accelerate resistance. However, it is unclear if the beneficial effect of antagonism in the wildtype bacteria is more critical than the detrimental effect of antagonism in the mutants. This study aims to illuminate the importance of antibiotic interactions against wildtype bacteria and mutants on the deacceleration of antimicrobial resistance.MethodsTo address this, we developed and analyzed a mathematical model that explores the population dynamics of wildtype and mutant bacteria under the influence of interacting antibiotics. The model investigates the relationship between synergistic and antagonistic antibiotic interactions with respect to the growth rate of mutant bacteria acquiring resistance. Stability analysis was conducted for equilibrium points representing bacteria-free conditions, all-mutant scenarios, and coexistence of both types. Numerical simulations corroborated the analytical findings, illustrating the temporal dynamics of wildtype and mutant bacteria under different combination therapies.ResultsOur analysis provides analytical clarification and numerical validation that antibiotic interactions against wildtype bacteria exert a more significant effect on reducing the rate of resistance development than interactions against mutants. Specifically, our findings highlight the crucial role of antagonistic antibiotic interactions against wildtype bacteria in slowing the growth rate of resistant mutants. In contrast, antagonistic interactions against mutants only marginally affect resistance evolution and may even accelerate it.ConclusionOur results emphasize the importance of considering the nature of antibiotic interactions against wildtype bacteria rather than mutants when aiming to slow down the acquisition of antibiotic resistance.
| S-EPMC10903357 | biostudies-literature