Evidence mapPaperPMID 41369430Full record

ReviewNanomaterials (Basel, Switzerland)2025

Nanoscale Imaging of Biological Tissues: Techniques, Challenges and Emerging Frontiers.

Rohit Kajla, Rebecca Leija-Cardenas, Meghraj Magadi Shivalingaiah, Muhammad Waqas Shabbir, Zihao Ou

Abstract readReview
In one paragraph

Review in Nanomaterials (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

5 authors.

Rohit KajlaDepartment of Physics, The University of Texas at Dallas, Richardson, TX 75080, USA.
Rebecca Leija-CardenasDepartment of Physics, The University of Texas at Dallas, Richardson, TX 75080, USA.
Meghraj Magadi ShivalingaiahDepartment of Physics, The University of Texas at Dallas, Richardson, TX 75080, USA.
Muhammad Waqas ShabbirDepartment of Physics, The University of Texas at Dallas, Richardson, TX 75080, USA.ORCID 0000-0002-4340-8896
Zihao OuDepartment of Physics, The University of Texas at Dallas, Richardson, TX 75080, USA.ORCID 0000-0003-2987-7423

Funding

The Kavli Foundation NAThe University of Texas at Dallas NA
6 · The paper itself

Abstract

Nanoscale characterization of biological tissues bridges molecular identity with structural, mechanical, and chemical organization, enabling high-resolution insights into intact specimens. This review provides a comprehensive overview of the principal imaging modalities that resolve cellular and subcellular features in biological tissues. Electron microscopy techniques offer ultrastructural details and volumetric reconstructions with sectioning and tomography techniques. Optical nanoscopy approaches such as single-molecule localization microscopy, stimulated emission depletion microscopy, structural illumination microscopy, and expansion microscopy achieve fluorescence-based mapping with tens-of-nanometer precision. Complementary platforms like atomic force microscopy and nanoscale secondary ion mass spectrometry extend nanoscale characterization into mechanical and chemical domains. Artificial intelligence has emerged as a transformative tool for segmentation, image restoration, and volumetric reconstruction, addressing bottlenecks in throughput and interpretability. From practical applications on biological tissues, we evaluate each technique's strengths, limitations, and potential for clinical applications. The review concludes with a discussion on emerging directions, including live-tissue nanoscopy, correlative light and electron microscopy, and machine-driven high-throughput imaging for further investigation of nanoscale biological structures and functions.

Indexed as

artificial intelligenceatomic force microscopybiomedical imagingelectron microscopyexpansion microscopymass spectroscopynanosciencesuper-resolution microscopy

Identifiers

PMID41369430
PMCPMC12692936

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.