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Explore a minimal mathematical model describing how bacteriostatic antibiotics inhibit bacterial growth through interference with essential autocatalytic metabolic cycles. Learn how this model recovers established growth laws and characterizes different antibiotic types while confirming two distinct regimes of growth-dependent susceptibility previously observed only in ribosome-targeting antibiotics. Discover the introduction of a cell risk proxy that enables comparative analysis of various antibiotic effects, and examine model extensions covering combination therapies targeting multiple autocatalytic cycles and scenarios where waste products inhibit cell growth. Gain insights into the mathematical framework connecting environmental factors like nutrient availability, toxic inhibitors, and product inhibition to bacterial population dynamics through this conference presentation from the Workshop on Extremal Statistics in Biology.
