Evidence map›Paper›PMID 40119834›Full record

ReviewAdvanced healthcare materials2025

Nano-Topography Enhanced Topological-Cell-Analysis in Radiation-Therapy.

Francesca Pagliari, Maria-Francesca Spadea, Pierre Montay-Gruel, Anggraeini Puspitasari-Kokko, Joao Seco, Luca Tirinato, Angelo Accardo, Francesco De Angelis, Francesco Gentile

Abstract readReview
In one paragraph

Review in Advanced healthcare materials, 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. 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

9 authors.

Francesca PagliariDivision of BioMedical Physics in Radiation Oncology, German Cancer Research Center, 69120, Heidelberg, Germany.
Maria-Francesca SpadeaInstitute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), 76131, Karlsruhe, Germany.
Pierre Montay-GruelRadiation Oncology Department, Iridium Netwerk, Antwerp, 2610, Belgium.ORCID 0000-0003-0623-1355
Anggraeini Puspitasari-KokkoResearch and Development - HollandPTC, Delft University of Technology, Delft, The Netherlands.
Joao SecoDivision of BioMedical Physics in Radiation Oncology, German Cancer Research Center, 69120, Heidelberg, Germany.
Luca TirinatoDepartment of Medical and Surgical Sciences, University Magna Graecia of Catanzaro, Catanzaro, 88100, Italy.
Angelo AccardoDepartment of Precision and Microsystems Engineering, Faculty of Mechanical Engineering, Delft University of Technology, Mekelweg 2, Delft, 2628 CD, The Netherlands.
Francesco De AngelisPlasmon nano-technologies, Italian Institute of Technology, Genova, 16163, Italy.
Francesco GentileNanotechnology Research Center, Department of Experimental and Clinical Medicine, University of Magna Graecia of Catanzaro, Catanzaro, 88100, Italy.ORCID 0000-0002-1724-6301

Funding

Associazione Italiana per la Ricerca sul Cancro IG 25656
6 · The paper itself

Abstract

Radiotherapy (RT) is a cancer treatment technique that involves exposing cells to ionizing radiation, including X-rays, electrons, or protons. RT offers promise to treat cancer, however, some inherent limitations can hamper its performance. Radio-resistance, whether innate or acquired, refers to the ability of tumor cells to withstand treatment, making it a key factor in RT failure. This perspective hypothesizes that nanoscale surface topography can impact on the topology of cancer cells network under radiation, and that this understanding can possibly advance the assessment of cell radio-resistance in RT applications. An experimental plan is proposed to test this hypothesis, using cancer cells exposed to various RT forms. By examining the influence of 2D surface and 3D scaffold nanoscale architecture on cancer cells, this approach diverges from traditional methodologies, such as clonogenic assays, offering a novel viewpoint that integrates fields such as tissue engineering, artificial intelligence, and nanotechnology. The hypotheses at the base of this perspective not only may advance cancer treatment but also offers insights into the broader field of structural biology. Nanotechnology and label-free Raman phenotyping of biological samples are lenses through which scientists can possibly better elucidate the structure-function relationship in biological systems.

Indexed as

NanotechnologyNeoplasmsRadiotherapyCell Line, TumorHumansAIbiomaterialsnano‐topographynetworks scienceradiation‐therapyRaman phenotypingscaffoldstopology

Identifiers

PMID40119834
PMCPMC12057610

What OpenQuestion holds

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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.