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Impact of Slow Wave Abnormalities and Impaired Coordination of Pyloric Closure and Antral Contraction on Gastric Emptying: A Compartmental Modeling Study

Fernandes, S. Q.; Kothare, M. V.; Sclocco, R.; Mahmoudi, B.

2025-11-11 biophysics
10.1101/2025.11.09.687391 bioRxiv
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PurposeTo develop a computationally efficient gastric compartmental model that simulates diseased stomach function by altering antral-pyloric coordination and "slow wave" properties. The model evaluates motility, gastric emptying and mixing. The computational efficiency of the model enables broad parameter sweeps to simulate various pathological conditions, offering an alternative to computationally expensive finite element or finite volume approaches. MethodsWe developed an extended compartmental model to simulate gastric function under dysrhythmic conditions. Building on prior work, this framework incorporates enhanced fluid flow equations and improved inter-compartment connectivity. These modifications enable simulation of impaired antro-pyloric coordination, regional variations in "slow wave" frequency (bradygastria, tachygastria), and reduced amplitude to mimic quiescent activity. Model outputs included gastric emptying rates, mixing efficiency, and transpyloric flow events across healthy and impaired conditions. ResultsSimulations demonstrated that abnormal "slow wave" frequency or amplitude delays gastric emptying and diminishes mixing efficiency. Bradygastria induced retrograde transpyloric flow, reflecting backflow from intestine to stomach, a pathological marker. These disruptions were most pronounced when antro-pyloric coordination was impaired. Predictions aligned with prior experimental and computational findings, while model execution was ~ 50-fold faster than real-time gastric dynamics, highlighting computational efficiency. ConclusionThis physiologically inspired compartmental model captures the impact of "slow wave" abnormalities on gastric motility. By reproducing impaired flow and mixing patterns characteristic of diseased states, it provides a valuable tool for probing mechanisms of gastric dysfunction. Importantly, its computational efficiency positions the model for use in developing and rapid testing of model-based, closed-loop neurostimulation therapies for gastrointestinal disorders.

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