Here we developed an advanced reaction-diffusion model to predict the evolution of the myoglobin state in beef meat using numerous reactions with rate constants of different orders of magnitude. The initial scheme included 44 reactions from the literature. Sensitivity analysis proved that this initial scheme was equivalent to a simple 22-reaction scheme. Results calculated with this scheme were compared against the spatial distributions of oxymyoglobin (MbO), metmyoglobin (MMb) and deoxymyoglobin (DMb) measured in meat cuts stored at 20°C under air-permeable packaging. We found global agreement between measured and calculated distributions when adequate rate constant values were used, particularly for the formation of MbO from DMb. The model was used to calculate evolutions in MbO and MMb distributions under different situations (modified-atmosphere packaging, Fenton chemistry with or without water-soluble antioxidants, increased mitochondrial oxygen consumption). Results were used to discuss the underlying kinetics reaction mechanisms and the performances and limits of the model.
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http://dx.doi.org/10.1016/j.meatsci.2022.108866 | DOI Listing |
Theor Popul Biol
December 2024
Cornell University, Department of Computational Biology, 102 Tower Rd, Ithaca, 14850, NY, USA.
Ordinary differential equation models such as the classical SIR model are widely used in epidemiology to study and predict infectious disease dynamics. However, these models typically assume that populations are homogeneously mixed, ignoring possible variations in disease prevalence due to spatial heterogeneity. To address this issue, reaction-diffusion models have been proposed as an alternative approach to modeling spatially continuous populations in which individuals move in a diffusive manner.
View Article and Find Full Text PDFbioRxiv
December 2024
TC Jenkins Department of Biophysics, Johns Hopkins University, Baltimore, MD, 21218, USA.
Particle-based reaction-diffusion models offer a high-resolution alternative to the continuum reaction-diffusion approach, capturing the discrete and volume-excluding nature of molecules undergoing stochastic dynamics. These methods are thus uniquely capable of simulating explicit self-assembly of particles into higher-order structures like filaments, spherical cages, or heterogeneous macromolecular complexes, which are ubiquitous across living systems and in materials design. The disadvantage of these high-resolution methods is their increased computational cost.
View Article and Find Full Text PDFSci Adv
December 2024
State Key Laboratory of Urban Water Resource and Environment, School of Chemistry and Chemical Engineering, Harbin Institute of Technology, Harbin 150001, PR China.
Although covalent organic frameworks (COFs) demonstrate notable potential for developing advanced separation membranes, contemporary COF membranes still lack controlled stacking and highly efficient sieving. Here, Turing-architecture COF membranes were constructed by engineering a reaction-diffusion assembly process via heterogeneous nucleation synthesis with tannic acid (TA). TA covalently binds with amine monomers to form a composite precursor with increased reactivity and decreased diffusivity.
View Article and Find Full Text PDFPhys Rev Lett
November 2024
Department of Mathematics, KU Leuven Campus Kortrijk (KULAK), Kortrijk 8500, Belgium.
An important development in nonlinear dynamics is the discovery of chimera states that represent the coexistence of synchronized and desynchronized activity in populations of identically coupled oscillators. Identification and characterization of chimera states is currently an active area of theoretical and applied research. Here, we unveil a novel chimera state called "self-organized target wave chimera" in reaction-diffusion media where synchronized target waves spontaneously emerge from a pacemaker composed of asynchronous oscillators.
View Article and Find Full Text PDFAngew Chem Int Ed Engl
January 2025
School of Physical Science and Technology, ShanghaiTech University, 201210, Shanghai, China.
Autocatalytic reaction present a significant opportunity for the precise spatial and temporal control of dynamic materials, mimicking the characteristics of living matter within autonomous chemical systems. Herein, we have crafted an autocatalytic chemical reaction network (CRN) designed to be incorporated into a dynamic system, allowing for efficient control of both sol(I)-gel and gel-sol(II) transitions through autocatalytic fronts. The CRN incorporates two autocatalytic reactions.
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