ON STABILITY OF STATIONARY STATES OF REVERSIBLE REACTIONS OF THE FIRST ORDER

The article discusses reversible first-order reactions. A system of differential equations is written. First integral and stationary state found. Using Lyapunov's direct method, stationary stability was investigated

Glucose feeds the TCA cycle via environmental ethanol in fermenting yeast

Ethanol and lactate are typical waste products of glucose fermentation. In mammals, glucose is catabolized by glycolysis into circulating lactate, which is broadly used throughout the body as a carbohydrate fuel. Individual cells can both uptake and excrete lactate, uncoupling glycolysis from glucose oxidation. Here we show that similar uncoupling occurs in the yeast Saccharomyces cerevisiae. Even in fermenting yeast that are net releasing ethanol, media 13C-ethanol rapid enters and is oxidized to acetaldehyde and acetyl-CoA. This is evident in exogenous ethanol being a major source of both cytosolic and mitochondrial acetyl units. 2H-tracing reveals that ethanol is also a major source of both NADH and NADPH, and this role is augmented under oxidative stress conditions. Thus, uncoupling of glycolysis from the oxidation of glucose-derived carbon via rapid reversible reactions is an ancient and conserved feature of eukaryotic metabolism.

A general framework for straightforward model construction of multi-component thermodynamic equilibrium systems

Mathematical modelling of molecular systems helps elucidating complex phenomena in (bio)chemistry. However, equilibrium conditions in systems consisting of more than two components can typically not be analytically determined without assumptions and resulting (semi-)numerical models are not trivial to derive by the non-expert. Here we present a framework for equilibrium models that utilizes a general derivation method capable of generating custom models for complex molecular systems, based on the simple, reversible reactions describing these systems. Several molecular systems are revisited via the framework and demonstrate the simplicity, the generality and validity of the approach. The ease of use of the framework and the ability to both analyze systems and gain additional insights in the underlying parameters strongly aids the analysis and understanding of molecular equilibrium systems. This conceptual framework severely reduces the time and expertise requirements which currently impede the broad integration of these highly valuable models into chemical research.

Egalitarian Kinetic Models: Concepts and Results

In this paper, two main ideas of chemical kinetics are distinguished, i.e., a hierarchy and commensuration. A new class of chemical kinetic models is proposed and defined, i.e., egalitarian kinetic models (EKM). Contrary to hierarchical kinetic models (HKM), for the models of the EKM class, all kinetic coefficients are equal. Analysis of EKM models for some complex chemical reactions is performed for sequences of irreversible reactions. Analytic expressions for acyclic and cyclic mechanisms of egalitarian kinetics are obtained. Perspectives on the application of egalitarian models for reversible reactions are discussed. All analytical results are illustrated by examples.

Air separation via two-step solar thermochemical cycles based on SrFeO3−δ and (Ba,La)0.15Sr0.85FeO3−δ perovskite reduction/oxidation reactions to produce N2: rate limiting mechanism(s) determination

Two-step solar thermochemical cycles based on reversible reactions of SrFeO3−δ and (Ba,La)0.15Sr0.85FeO3−δ perovskites were considered for air separation.

Nucleophilic catalysis of p-substituted aniline derivatives in acylhydrazone formation and exchange

Hydrazone bond formation is a versatile reaction employed in several research fields. It is one of the most popular reversible reactions in dynamic combinatorial chemistry. Under physiological conditions, hydrazone exchange...

The State of the Nitric Oxide Cycle in Respiratory Tract Diseases

This review describes the unique links of the functioning of the nitric oxide cycle in the respiratory tract in normal and pathological conditions. The concept of a nitric oxide cycle has been expanded to include the NO-synthase and NO-synthase-independent component of its synthesis and the accompanying redox cascades in varying degrees of reversible reactions. The role of non-NO-synthase cycle components has been shown. Detailed characteristics of substrates for the synthesis of nitric oxide (NO) in the human body, which can be nitrogen oxides, nitrite and nitrate anions, and organic nitrates, as well as nitrates and nitrites of food products, are given. The importance of the human microbiota in the nitric oxide cycle has been shown. The role of significant components of nitrite and nitrate reductase systems in the nitric oxide cycle and the mechanisms of their activation and deactivation (participation of enzymes, cofactors, homeostatic indicators, etc.) under various conditions have been determined. Consideration of these factors allows for a detailed understanding of the mechanisms underlying pathological conditions of the respiratory system and the targeting of therapeutic agents. The complexity of the NO cycle with multidirectional cascades could be best understood using dynamic modeling.

Concentration Sensing in Crowded Environments

ABSTRACTSignal transduction within crowded cellular compartments is essential for the physiological function of cells and organisms. While the accuracy with which receptors can probe the concentration of ligands has been thoroughly investigated in dilute systems, the effect of macromolecular crowding on the inference of concentration remains unknown. In this work we develop a novel algorithm to simulate reversible reactions between reacting Brownian particles. This facilitates the calculation of reaction rates and correlation times for ligand-receptor systems in the presence of macromolecular crowding. Using this method, we show that it is possible for crowding to increase the accuracy of estimated ligand concentration based on receptor occupancy. In particular, we find that crowding can enhance the effective association rates between small ligands and receptors to a large enough degree to overcome the increased chance of rebinding due to caging by crowding molecules. For larger ligands, crowding decreases the accuracy of the receptor’s estimate primarily by decreasing the microscopic association and dissociation rates.SIGNIFICANCEDeveloping an understanding of how cells effectively transmit signals within or between compartments under physical constraints is an important challenge for biophysics. This work investigates the effect that macromolecular crowding can have on the accuracy of a simple ligand-receptor signaling system. We show that the accuracy of an inferred ligand concentration based on the occupancy of the receptor can be enhanced by crowding under certain circumstances. Additionally, we develop a simulation algorithm that speeds the calculation of reaction rates in crowded environments and can be readily applied to other, more complex systems.