We demonstrate that the Michaelis-Menten reaction mechanism can be accurately approximated by a linear system when the initial substrate concentration is low. This leads to pseudo-first-order kinetics, simplifying mathematical calculations and experimental analysis. Our proof utilizes a monotonicity property of the system and Kamke's comparison theorem. This linear approximation yields a closed-form solution, enabling accurate modeling and estimation of reaction rate constants even without timescale separation. Building on prior work, we establish that the sufficient condition for the validity of this approximation is , where is the Van Slyke-Cullen constant. This condition is independent of the initial enzyme concentration. Further, we investigate timescale separation within the linear system, identifying necessary and sufficient conditions and deriving the corresponding reduced one-dimensional equations.
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http://dx.doi.org/10.1007/s11538-024-01295-z | DOI Listing |
Sci Adv
January 2025
Université Paris Cité, Institut Pasteur, AP-HP, Inserm, Fondation Pour l'Audition, Institut de l'Audition, IHU reConnect, F-75012 Paris, France.
The temporal structure of sensory inputs contains essential information for their interpretation. Sensory cortex represents these temporal cues through two codes: the temporal sequences of neuronal activity and the spatial patterns of neuronal firing rate. However, it is unknown which of these coexisting codes causally drives sensory decisions.
View Article and Find Full Text PDFCapillary zone electrophoresis (CZE) is gaining attention in the field of single-cell proteomics for its ultra-low-flow and high-resolution separation abilities. Even more sample-limited yet rich in biological information are phosphoproteomics experiments, as the phosphoproteome composes only a fraction of the whole cellular proteome. Rapid analysis, high sensitivity, and maximization of sample utilization are paramount for single-cell analysis.
View Article and Find Full Text PDFCogn Neurodyn
December 2024
MathNeuro Team, Inria at Université Côte d'Azur, 2004 route des Lucioles-BP93, Sophia Antipolis, 06902 France.
Mixed affective states in bipolar disorder (BD) is a common psychiatric condition that occurs when symptoms of the two opposite poles coexist during an episode of mania or depression. A four-dimensional model by Goldbeter (Progr Biophys Mol Biol 105:119-127, 2011; Pharmacopsychiatry 46:S44-S52, 2013) rests upon the notion that manic and depressive symptoms are produced by two competing and auto-inhibited neural networks. Some of the rich dynamics that this model can produce, include complex rhythms formed by both small-amplitude (subthreshold) and large-amplitude (suprathreshold) oscillations and could correspond to mixed bipolar states.
View Article and Find Full Text PDFCurr Biol
December 2024
Department of Biology and the Howard Hughes Medical Institute, University of Massachusetts, 611 N Pleasant St, Amherst, MA 01003, USA. Electronic address:
Diverse eukaryotic cells assemble microtubule networks that vary in structure and composition. While we understand how cells build microtubule networks with specialized functions, we do not know how microtubule networks diversify across deep evolutionary timescales. This problem has remained unresolved because most organisms use shared pools of tubulins for multiple networks, making it difficult to trace the evolution of any single network.
View Article and Find Full Text PDFbioRxiv
December 2024
Department of Biological Sciences, University of South Carolina, 715 Sumter St. Columbia, SC 29208 USA.
Premise: Adaptive radiation in ecologically and morphologically diverse plant lineages presents an opportunity to investigate the rapid evolution of novel floral traits. While some types of floral traits, such as flower color, are well-characterized, other types of complex morphologies remain understudied. One example is occluded personate flowers, dorso-ventrally compressed flowers with obstructed floral passageways, which have evolved in multiple genera, but have only been characterized from snapdragon.
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