Evidence map›Paper›PMID 39335524›Full record

ReviewBiomedicines2024

Applying the Atomic Force Microscopy Technique in Medical Sciences-A Narrative Review.

Karolina Krawczyk-Wołoszyn, Damian Roczkowski, Adam Reich, Magdalena Żychowska

Abstract readReview
In one paragraph

Review in Biomedicines, 2024. 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. Article
  4. Review
  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

4 authors.

Karolina Krawczyk-WołoszynDoctoral School, University of Rzeszow, 35-959 Rzeszów, Poland.
Damian RoczkowskiDepartment of Dermatology, Institute of Medical Sciences, Medical College of Rzeszow University, 35-959 Rzeszów, Poland.
Adam ReichDepartment of Dermatology, Institute of Medical Sciences, Medical College of Rzeszow University, 35-959 Rzeszów, Poland.ORCID 0000-0002-5573-1754
Magdalena ŻychowskaDepartment of Dermatology, Institute of Medical Sciences, Medical College of Rzeszow University, 35-959 Rzeszów, Poland.ORCID 0000-0001-8268-0529

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Penetrating deep into the cells of the human body in real time has become increasingly possible with the implementation of modern technologies in medicine. Atomic force microscopy (AFM) enables the effective live imaging of cellular and molecular structures of biological samples (such as cells surfaces, components of biological membranes, cell nuclei, actin networks, proteins, and DNA) and provides three-dimensional surface visualization (in X-, Y-, and Z-planes). Furthermore, the AFM technique enables the study of the mechanical, electrical, and magnetic properties of cells and cell organelles and the measurements of interaction forces between biomolecules. The technique has found wide application in cancer research. With the use of AFM, it is not only possible to differentiate between healthy and cancerous cells, but also to distinguish between the stages of cancerous conditions. For many years, AFM has been an important tool for the study of neurodegenerative diseases associated with the deposition of peptide amyloid plaques. In recent years, a significant amount of research has been conducted on the application of AFM in the evaluation of connective tissue cell mechanics. This review aims to provide the spectrum of the most important applications of the AFM technique in medicine to date.

Indexed as

atomic force microscopy (AFM)biomedical researchmelanomaoncologyskin cells

Identifiers

PMID39335524
PMCPMC11429229

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.