Evidence map›Paper›PMID 36551083›Full record

ReviewBiosensors2022

Review: Advanced Atomic Force Microscopy Modes for Biomedical Research.

Fangzhou Xia, Kamal Youcef-Toumi

Abstract readReview
In one paragraph

Review in Biosensors, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing 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

24 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Article
  6. Article
  7. Review
  8. Guidance on biomaterials for periodontal tissue regeneration: Fabrication methods, materials and biological considerations.Dental materials : official publication of the Academy of Dental Materials · 2025
    Review
  9. Article
  10. Review
  11. Review
  12. Review
  13. Review
  14. Review
  15. Magnetic-Dielectric Cantilevers for Atomic Force Microscopy.Nanomaterials (Basel, Switzerland) · 2024
    Article
  16. Review
  17. Article
  18. Article
  19. Article
  20. 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.

Fangzhou XiaMechatronics Research Lab, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.ORCID 0000-0002-6314-3717
Kamal Youcef-ToumiMechatronics Research Lab, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Visualization of biomedical samples in their native environments at the microscopic scale is crucial for studying fundamental principles and discovering biomedical systems with complex interaction. The study of dynamic biological processes requires a microscope system with multiple modalities, high spatial/temporal resolution, large imaging ranges, versatile imaging environments and ideally in-situ manipulation capabilities. Recent development of new Atomic Force Microscopy (AFM) capabilities has made it such a powerful tool for biological and biomedical research. This review introduces novel AFM functionalities including high-speed imaging for dynamic process visualization, mechanobiology with force spectroscopy, molecular species characterization, and AFM nano-manipulation. These capabilities enable many new possibilities for novel scientific research and allow scientists to observe and explore processes at the nanoscale like never before. Selected application examples from recent studies are provided to demonstrate the effectiveness of these AFM techniques.

Indexed as

Biomedical ResearchNanotechnologyMicroscopy, Atomic Forceatomic force microscopybiomedical researchhigh-speed imagingmaterial property mappingmechanobiologynano-manipulationnanotechnology

Identifiers

PMID36551083
PMCPMC9775674

What Socratic holds

Textmetadata
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 Socratic graph.