Evidence map›Paper›PMID 36157269›Full record

ArticleBiophysical reports2022

Mem3DG: Modeling membrane mechanochemical dynamics in 3D using discrete differential geometry.

Cuncheng Zhu, Christopher T Lee, Padmini Rangamani

Abstract read
In one paragraph

Article in Biophysical reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed.

  1. Article
  2. Red Blood Cell Membrane Mechanics Using Discrete Exterior Calculus (DEC) and Optimization.International journal for numerical methods in biomedical engineering · 2026
    Article
  3. Review
  4. Article
  5. Membrane bending energy selects for compact growth of protein assemblies.bioRxiv : the preprint server for biology · 2025
    Article
  6. Biophysical modeling of membrane curvature generation and curvature sensing by the glycocalyx.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Review
  15. Modeling membrane reshaping driven by dynamic protein assemblies.Current opinion in structural biology · 2023
    Review
  16. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Cuncheng ZhuDepartment of Mechanical and Aerospace Engineering, University of California San Diego, La Jolla CA 92093.
Christopher T LeeDepartment of Mechanical and Aerospace Engineering, University of California San Diego, La Jolla CA 92093.
Padmini RangamaniDepartment of Mechanical and Aerospace Engineering, University of California San Diego, La Jolla CA 92093.

Funding

Modeling and analysis of the mechanochemical processes that govern clathrin-mediated endocytosisR01GM132106 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI RANGAMANI, PADMINI · 2020 to 2024
$1.5M
NIGMS NIH HHS R01 GM132106
6 · The paper itself

Abstract

Biomembranes adopt varying morphologies that are vital to cellular functions. Many studies use computational modeling to understand how various mechanochemical factors contribute to membrane shape transformations. Compared with approximation-based methods (e.g., finite element method [FEM]), the class of discrete mesh models offers greater flexibility to simulate complex physics and shapes in three dimensions; its formulation produces an efficient algorithm while maintaining coordinate-free geometric descriptions. However, ambiguities in geometric definitions in the discrete context have led to a lack of consensus on which discrete mesh model is theoretically and numerically optimal; a bijective relationship between the terms contributing to both the energy and forces from the discrete and smooth geometric theories remains to be established. We address this and present an extensible framework, Mem3DG, for modeling 3D mechanochemical dynamics of membranes based on discrete differential geometry (DDG) on triangulated meshes. The formalism of DDG resolves the inconsistency and provides a unifying perspective on how to relate the smooth and discrete energy and forces. To demonstrate, Mem3DG is used to model a sequence of examples with increasing mechanochemical complexity: recovering classical shape transformations such as 1) biconcave disk, dumbbell, and unduloid; and 2) spherical bud on spherical, flat-patch membrane; investigating how the coupling of membrane mechanics with protein mobility jointly affects phase and shape transformation. As high-resolution 3D imaging of membrane ultrastructure becomes more readily available, we envision Mem3DG to be applied as an end-to-end tool to simulate realistic cell geometry under user-specified mechanochemical conditions.

Identifiers

PMID36157269
PMCPMC9495267

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.