Evidence map›Paper›PMID 42339005›Full record

ArticleCommunications physics2026

Role of cell density and proximity in electroporation for tissue ablation.

Lujia Ding, Mike A J Moser, Bing Zhang, Chris Zhang, Ningning Hu

Abstract read
In one paragraph

Article in Communications physics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Lujia DingThe Division of Biomedical Engineering, University of Saskatchewan, Saskatoon, SK Canada.
Mike A J MoserDepartment of Surgery, University of Saskatchewan, Saskatoon, SK Canada.
Bing ZhangThe School of Mechatronic Engineering and Automation, Shanghai University, Shanghai, China.ORCID 0000-0001-5650-2518
Chris ZhangThe Division of Biomedical Engineering, University of Saskatchewan, Saskatoon, SK Canada.ORCID 0000-0001-7973-8769
Ningning HuThe Division of Biomedical Engineering, University of Saskatchewan, Saskatoon, SK Canada.ORCID 0000-0003-1134-2500

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Electroporation has advanced significantly in biomedical applications, particularly in tissue ablation. While the influence of individual cellular features, such as cell size and nucleus-to-cytoplasm ratio, on ablation is recognized, this study highlights the key role of the cell grouping factor, namely cell density. Experiments using 2D cell monolayers demonstrated a density-dependent ablation effect: higher cell density significantly elevates resistance to electroporation, evident from reduced ablation areas and ~30% higher lethal electric thresholds (LETs). To explain this, a cell-cell proximity electroporation model was established representing cell density by intercellular distance and degree of containment. It indicated significant inhibition when cells were closely spaced (0-2 µm), with lower pore density and reduced pore area ratios (PARs). This inhibitory effect decays logarithmically as spacing increases, persisting over several cell diameters. Furthermore, fully surrounded cells exhibit a 33% lower PAR than isolated cells, consistent with the observed LET gap between high- and low-density populations. As such, the shielding effect from neighboring cells leads to the density-dependent electroporation at cellular scale and may therefore account for the density-dependent ablation observed at tissue scale. In light of this, considering tissue-specific cell density are critical for better mimicking in vivo conditions, and improving precision in electroporation-based tissue therapies.

Indexed as

Computational biophysicsNanoscale biophysics

Identifiers

PMID42339005
PMCPMC13283845

What OpenQuestion holds

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Registered trials

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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.