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REVIEW 2 major objections 2 minor 52 references

Effect of Antral Motility on Food Hydrolysis and Gastric Emptying from the Stomach: Insights from Computational Models

T0 review · 2 major / 2 minor · reviewed 2026-05-24 · grok-4.3

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Pith's one-line read Antral contraction waves enhance mixing that accelerates protein hydrolysis and gastric emptying in a computational stomach model.

desk verdict The paper runs four forward simulations of a stomach model with varying antral contraction amplitudes and reports that lower motility slows both emptying and protein hydrolysis while changing mixing patterns. read the letter →

arxiv 2208.06668 v1 submitted 2022-08-13 physics.flu-dyn

Sharun Kuhar , Jae Ho Lee , Jung-Hee Seo , Pankaj J Pasricha , Rajat Mittal This is my paper · ORCID
classification physics.flu-dyn
keywords gastricmotilityantralcontractionwavesproteinhydrolysisemptyingcomputationalmodelingpepsinstomachfluiddynamics
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

This paper simulates the digestion of a liquid protein meal in an imaging-based model of the human stomach where pepsin is secreted from the proximal walls. It compares a control motility case to three cases with reduced peristaltic amplitudes to measure changes in hydrolysis extent, emptying rate, and jet velocities. The results link stronger antral contractions to better mixing that speeds both breakdown and emptying. A sympathetic reader would care because these mechanics could help explain digestive issues tied to impaired stomach motion.

What carries the argument

Antral contraction waves that drive fluid mixing and transport in the stomach.

What would settle it

Experimental measurements in human subjects or animal models showing no difference in hydrolysis rates between normal and reduced antral motility conditions.

Watch

Extended reading notes

Core claim

Reducing the amplitude of antral contraction waves in the model decreases the mixing in the stomach, which in turn reduces the rate of pepsin-catalyzed protein hydrolysis and slows the rate of gastric emptying.

Load-bearing premise

The computational model based on imaging data accurately represents the physiological processes of enzyme secretion, reaction kinetics, and fluid flow in the human stomach.

Editorial extensions

If this is right

  • Weaker peristaltic amplitudes lead to lower jet velocities from the antrum.
  • The extent of hydrolysis decreases with reduced motility.
  • Gastric emptying rate correlates positively with motility strength.
  • Observations tie directly to the mixing induced by the waves.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • Disorders that reduce antral motility could impair the timing of nutrient breakdown.
  • The model framework could be tested against solid meals or additional enzymes.
  • Interventions that alter motility might be assessed by predicted changes in hydrolysis.
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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit.

Referee Report

2 major / 2 minor

Summary. The paper presents computational simulations of protein hydrolysis and gastric emptying in an imaging-derived human stomach model. Pepsin is secreted from the proximal wall and reacts via first-order kinetics with stomach contents under Navier-Stokes flow driven by prescribed antral peristaltic waves. Results are reported for a control motility case and three reduced-amplitude cases, showing that lower peristaltic amplitude reduces emptying rate and hydrolysis extent while altering mixing patterns induced by antral contraction waves.

Significance. If the model geometry, wall motion, secretion, and kinetics are physiologically representative, the comparative results quantify the mechanical role of antral motility in digestion and link emptying/hydrolysis changes to mixing, providing data that are difficult to obtain experimentally. The forward-simulation approach with no free parameters fitted from the reported data is a methodological strength.

major comments (2)
  1. [Methods] Methods (numerical setup): The manuscript supplies no information on spatial discretization (mesh type, resolution, or convergence), temporal scheme, boundary-condition implementation for wall motion and secretion, or any validation against analytic or experimental benchmarks for the flow solver or reaction model. Without these, the quantitative claims on emptying rates, jet velocities, and hydrolysis extents cannot be assessed for numerical reliability.
  2. [Results] Results (mixing-hydrolysis link): The correlation between antral-wave mixing and hydrolysis is asserted but not supported by a quantitative mixing metric (e.g., scalar variance, residence-time distribution, or local strain-rate statistics). The reported changes in hydrolysis could arise from other factors (residence time, local concentration) rather than mixing per se; a direct quantitative link is required to substantiate the central mechanistic claim.
minor comments (2)
  1. [Abstract] Abstract: The three reduced-motility cases are described only as 'varying peristaltic amplitudes' without stating the specific amplitude ratios or frequencies used; these values should be given explicitly.
  2. [Figures] Figure captions and text: Several figures showing concentration or velocity fields lack scale bars, color-bar ranges, or quantitative legends, making it difficult to interpret the magnitude of reported differences.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for the constructive comments. We respond point-by-point to the major comments below.

read point-by-point responses

  1. Referee: [Methods] Methods (numerical setup): The manuscript supplies no information on spatial discretization (mesh type, resolution, or convergence), temporal scheme, boundary-condition implementation for wall motion and secretion, or any validation against analytic or experimental benchmarks for the flow solver or reaction model. Without these, the quantitative claims on emptying rates, jet velocities, and hydrolysis extents cannot be assessed for numerical reliability.

    Authors: We agree that the numerical methods description is incomplete. The revised manuscript will add details on the mesh type and resolution, mesh convergence studies, the temporal discretization scheme, implementation of the prescribed wall motion and secretion boundary conditions, and any validation performed for the Navier-Stokes solver and first-order reaction model. revision: yes

  2. Referee: [Results] Results (mixing-hydrolysis link): The correlation between antral-wave mixing and hydrolysis is asserted but not supported by a quantitative mixing metric (e.g., scalar variance, residence-time distribution, or local strain-rate statistics). The reported changes in hydrolysis could arise from other factors (residence time, local concentration) rather than mixing per se; a direct quantitative link is required to substantiate the central mechanistic claim.

    Authors: We acknowledge that the manuscript correlates hydrolysis extent with antral-wave mixing patterns but does not include a quantitative mixing metric. In the revision we will add such a metric (scalar variance of a passive tracer or local strain-rate statistics) and demonstrate its correlation with the observed hydrolysis changes to strengthen the mechanistic link. revision: yes

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity; forward simulation from independent inputs

full rationale

The paper performs forward CFD simulations of gastric flow and hydrolysis using imaging-derived geometry, prescribed antral wall motion as input, proximal-wall pepsin secretion, and first-order reaction kinetics solved via Navier-Stokes. Outputs (jet velocities, emptying rates, hydrolysis extent) are computed across motility amplitudes without any parameter fitting to those outputs, without self-citation load-bearing on uniqueness theorems, and without renaming or self-defining the reported quantities. All load-bearing steps remain external to the target results.

Assumptions & free parameters 0 free parameters · 2 assumptions · 0 invented entities

Only the abstract is available, so the ledger is necessarily incomplete; the model relies on standard CFD assumptions plus domain-specific physiological parameters whose exact values and sources are not stated.

assumptions (2)
  • domain assumption Stomach geometry and motility patterns derived from imaging data are representative of human physiology
    Model construction described as 'based on imaging data' in the abstract.
  • standard math Navier-Stokes equations with appropriate boundary conditions govern gastric flow
    Implicit in any computational fluid dynamics model of peristaltic flow.

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Cite this review

Pith. "Pith review of Effect of Antral Motility on Food Hydrolysis and Gastric Emptying from the Stomach: Insights from Computational Models." pith.science (2026). https://pith.science/paper/2208.06668

@misc{pith2026220806668,
  author       = {Pith},
  title        = {Pith review of: Effect of Antral Motility on Food Hydrolysis and Gastric Emptying from the Stomach: Insights from Computational Models},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/2208.06668}},
  note         = {Machine review of arXiv:2208.06668}
}
read the original abstract

The peristaltic motion of the stomach walls combines with the secretion of enzymes to initiate the process that breaks down food. Computational modelling of this phenomenon can help reveal the details that would be hard to capture via in-vivo or in-vitro means. In this study, the digestion of a liquid meal containing protein is simulated in a human-stomach model based on imaging data. Pepsin, the gastric enzyme for protein hydrolysis, is secreted from the proximal region of the stomach walls and allowed to react with the contents of the stomach. The jet velocities, the emptying rate, and the extent of hydrolysis are quantified for a control case, and also for three other cases of reduced motility with varying peristaltic amplitudes. The findings quantify the effect of motility on the rate of food breakdown and emptying, and correlate the observations with the mixing in the stomach induced by the antral contraction waves.

Figures

Figures reproduced from arXiv: 2208.06668 by the authors.

Figure 1
Figure 1. FIG. 1. Description of the stomach geometry and the motility model. The amplitude modulation function, [PITH_FULL_IMAGE:figures/full_fig_p005_1.png] view at source ↗
Figure 2
Figure 2. FIG. 2. The triangulated surface mesh is immersed in an outer Cartesian mesh with an open fundus at the [PITH_FULL_IMAGE:figures/full_fig_p006_2.png] view at source ↗
Figure 3
Figure 3. FIG. 3. Comparison of velocity magnitude contours shown on a cross-section through the antro-duodenal [PITH_FULL_IMAGE:figures/full_fig_p011_3.png] view at source ↗
Figures from the paper (8 more)
Figure 5
Figure 5. Figure 5: FIG. 5. Amount of (a) unhydrolyzed protein and (b) pepsin emptied per cycle for different cases. [PITH_FULL_IMAGE:figures/full_fig_p015_5.png]
Figure 6
Figure 6. Figure 6: FIG. 6. Amount of digesta (hydrolyzed protein) emptied per cycle for different antral contraction wave [PITH_FULL_IMAGE:figures/full_fig_p016_6.png]
Figure 7
Figure 7. Figure 7: FIG. 7. The amount of digesta emptied per cycle at steady state for different motility cases. This corresponds [PITH_FULL_IMAGE:figures/full_fig_p018_7.png]
Figure 8
Figure 8. Figure 8: FIG. 8. Calculating the interface at a cross-section through the antrum for [PITH_FULL_IMAGE:figures/full_fig_p018_8.png]
Figure 9
Figure 9. Figure 9: FIG. 9. Reaction interfaces for different motility amplitudes ( [PITH_FULL_IMAGE:figures/full_fig_p019_9.png]
Figure 10
Figure 10. Figure 10: FIG. 10. The normalized area integral of [PITH_FULL_IMAGE:figures/full_fig_p020_10.png]
Figure 11
Figure 11. Figure 11: FIG. 11. (a) Interface area of pepsin is shown as a function of time. After initial transience, the interface [PITH_FULL_IMAGE:figures/full_fig_p021_11.png]
Figure 12
Figure 12. Figure 12: FIG. 12. The procedure for calculating interface, [PITH_FULL_IMAGE:figures/full_fig_p023_12.png]

Discussion (0). Continue with ORCID to comment.

Reference graph

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Pith tools

Reviewed May 24, 2026 · model on record in the stance chip above.