Evidence map›Paper›PMID 40957564›Full record

ArticleJournal of the Royal Society, Interface2025

Nanoparticle deposition to a cell transiting through a soft tissue: three-dimensional simulation and Lagrangian coherent structure dynamics.

Mazyar Dawoodian, Amalendu Sau

Abstract read
In one paragraph

Article in Journal of the Royal Society, Interface, 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. 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

2 authors.

Mazyar DawoodianDepartment of Aerospace Engineering, Gyeongsang National University, Jinju-si, Republic of Korea.
Amalendu SauDepartment of Aerospace Engineering, Gyeongsang National University, Jinju-si, Republic of Korea.ORCID 0009-0005-5911-8278

Funding

The NRF
6 · The paper itself

Abstract

We elucidate the role of time-invariant spatial attractors-repellers in segregating nano-suspensions around a tumour cell. A major challenge for targeted therapeutic drug delivery is the inadequate understanding of active nano-bio-separatrices at the delivery site. Using the lattice-Boltzmann-immersed-boundary method, first, we simulate the kinematics of a compound cell in a micro-vessel partly blocked by an invasive tissue and examine the stretching of its plasma membrane (PM) and nuclear envelope (NE) for varied nucleus size, capillary number and blockage hole. Second, we compute the trajectories of the suspended large number of inertial nanoparticles (NPs) in the vessel using a dynamical system approach. Third, we compute the particle Lagrangian coherent structures (pLCS) for the advecting NPs and identify the time-invariant geometric separatrices. The dominant attractive-repulsive pLCS effectually demarcates fluid regions from where NPs move closer/attach to the cell and from where NPs move away. Our study explains that delivering nanomedicine to a cell is feasible only through its stretched PM's high-tension rear side. The created repulsive pLCS barricades NPs from moving closer to a cell's PM's low-tension lateral/front sides. We thus unfold a universal separation behaviour of NPs around a cell. NP delivery rate increased for a larger capillary number and cell nucleus size. It decreased for heavier NPs and a cell stiffer nucleus/NE.

Indexed as

Cell MembraneDrug Delivery SystemsModels, BiologicalNanoparticlesNeoplasmsComputer SimulationHumansNuclear Envelopecell deformationdynamical systemLagrangian coherent structureslattice Boltzmann methodnanoparticle delivery

Identifiers

PMID40957564
PMCPMC12440631

What OpenQuestion holds

Textmetadata
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.