Evidence map›Paper›PMID 33133331›Full record

ArticleScanning2020

A New Approach for the AFM-Based Mechanical Characterization of Biological Samples.

S V Kontomaris, A Malamou, A Stylianou

Abstract read
In one paragraph

Article in Scanning, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. 3D AFM Nanomechanical Characterization of Biological Materials.Nanomaterials (Basel, Switzerland) · 2023
    Article
  5. 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

3 authors.

S V KontomarisAthens Metropolitan College, Faculty of Architecture, Engineering and Built Environment, Athens, Greece.ORCID https://orcid.org/0000-0003-4843-1208
A MalamouRadar Systems and Remote Sensing Lab of School of Electrical & Computer Engineering of National Technical University of Athens, Greece.
A StylianouCancer Biophysics Laboratory, Department of Mechanical and Manufacturing Engineering, Faculty of Engineering, University of Cyprus, Cyprus.ORCID https://orcid.org/0000-0002-1641-1854

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The AFM nanoindentation technique is a powerful tool for the mechanical characterization of biological samples at the nanoscale. The data analysis of the experimentally obtained results is usually performed using the Hertzian contact mechanics. However, the aforementioned theory can be applied only in cases that the sample is homogeneous and isotropic and presents a linear elastic response. However, biological samples often present depth-dependent mechanical properties, and the Hertzian analysis cannot be used. Thus, in this paper, a different approach is presented, based on a new physical quantity used for the determination of the mechanical properties at the nanoscale. The aforementioned physical quantity is the work done by the indenter per unit volume. The advantages of the presented analysis are significant since the abovementioned magnitude can be used to examine if a sample can be approximated to an elastic half-space. If this approximation is valid, then the new proposed method enables the accurate calculation of Young's modulus. Additionally, it can be used to explore the mechanical properties of samples that are characterized by a depth-dependent mechanical behavior. In conclusion, the proposed analysis presents an accurate yet simple technique for the determination of the mechanical properties of biological samples at the nanoscale that can be also used beyond the Hertzian limit.

Indexed as

Elastic ModulusHumansMicroscopy, Atomic ForceStress, Mechanical

Identifiers

PMID33133331
PMCPMC7591964

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.