Evidence map›Paper›PMID 40942919›Full record

ArticleSensors (Basel, Switzerland)2025

Modeling and Validation of Oocyte Mechanical Behavior Using AFM Measurement and Multiphysics Simulation.

Yue Du, Yu Cai, Zhanli Yang, Ke Gao, Mingzhu Sun, Xin Zhao

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. From Cytoskeletal Remodeling to Oocyte Quality: The Emerging Role of Mechanics.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Review
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

6 authors.

Yue DuSchool of Computer and Information Science, Qinghai Institute of Technology, Xining 810016, China.
Yu CaiNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, The Engineering Research Center of Trusted Behavior Intelligence, Ministry of Education, The Tianjin Key Laboratory of intelligent Robotics (tiKLIR), Institute of Robotics and Automatic Information System (IRAIS), College of Artificial Intelligence, Nankai University, Tianjin 300350, China.
Zhanli YangNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, The Engineering Research Center of Trusted Behavior Intelligence, Ministry of Education, The Tianjin Key Laboratory of intelligent Robotics (tiKLIR), Institute of Robotics and Automatic Information System (IRAIS), College of Artificial Intelligence, Nankai University, Tianjin 300350, China.
Ke GaoNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, The Engineering Research Center of Trusted Behavior Intelligence, Ministry of Education, The Tianjin Key Laboratory of intelligent Robotics (tiKLIR), Institute of Robotics and Automatic Information System (IRAIS), College of Artificial Intelligence, Nankai University, Tianjin 300350, China.
Mingzhu SunNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, The Engineering Research Center of Trusted Behavior Intelligence, Ministry of Education, The Tianjin Key Laboratory of intelligent Robotics (tiKLIR), Institute of Robotics and Automatic Information System (IRAIS), College of Artificial Intelligence, Nankai University, Tianjin 300350, China.ORCID 0000-0002-9179-9668
Xin ZhaoNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, The Engineering Research Center of Trusted Behavior Intelligence, Ministry of Education, The Tianjin Key Laboratory of intelligent Robotics (tiKLIR), Institute of Robotics and Automatic Information System (IRAIS), College of Artificial Intelligence, Nankai University, Tianjin 300350, China.

Funding

the National Natural Science Foundation of China 62463028,62333012, 62027812 and 62173240the Science and Technology Foundation of Qinghai Province 2025-ZJ-978Q
6 · The paper itself

Abstract

Mechanical models are capable of simulating the deformation and stress distribution of oocytes under external forces, thereby providing insights into the underlying mechanisms of intracellular mechanical responses. Interactions with micromanipulation tools involve forces like compression and punction, which are effectively analyzed using principles of solid mechanics. Alternatively, fluid-structure interactions, such as shear stress at fluid junctions or pressure gradients within microchannels, are best described by a multiphase flow model. Developing the two models instead of a single comprehensive model is necessary due to the distinct nature of cell-tool interactions and cell-fluid interactions. In this study, we developed a finite element (FE) model of porcine oocytes that accounts for the viscoelastic properties of the zona pellucida (ZP) and cytoplasm for the case when the oocytes interacted with a micromanipulation tool. Atomic force microscopy (AFM) was employed to measure the Young's modulus and creep behavior of these subcellular components that were incorporated into the FE model. When the oocyte was solely interacting with the fluids, we simulated oocyte deformation in microfluidic channels by modeling the oocyte-culture-medium system as a three-phase flow, considering the non-Newtonian behavior of the oocyte's components. Our results show that the Young's modulus of the ZP and cytoplasm were determined to be 7 kPa and 1.55 kPa, respectively, highlighting the differences in the mechanical properties between these subcomponents. Using the developed layered FE model, we accurately simulated oocyte deformation during their passage through a narrow-necked micropipette, with a deformation error of approximately 5.2% compared to experimental results. Using the three-phase flow model, we effectively simulated oocyte deformation in microfluidic channels under various pressures, validating the model's efficacy through close agreement with experimental observations. This work significantly contributes to assessing oocyte quality and serves as a valuable tool for advancing cell mechanics studies.

Indexed as

Microscopy, Atomic ForceModels, BiologicalOocytesAnimalsBiomechanical PhenomenaCytoplasmElastic ModulusFemaleFinite Element AnalysisSwineZona PellucidaAFMcell mechanical modelcreep behaviorlayered structurethree-phase flow modelviscoelastic properties

Identifiers

PMID40942919
PMCPMC12431014

What OpenQuestion holds

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LicenceCC BY
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 OpenQuestion graph.