Evidence map›Paper›PMID 42136395›Full record

ReviewACS applied materials & interfaces2026

Infrared Near-Field Microscopy as a Platform for Nanoscale Biomedical Spectroscopy and Imaging.

Hongcai Deng, Xin Zhao, Xinyue Na, Ankang Liu, Ruofan Cheng, Fantao Jiang, Qi Zhang, Fengwei Gao, Hong Wu, Ting Zhang and 2 more

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in ACS applied materials & interfaces, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

12 authors.

Hongcai DengNational Engineering Research Center of Electromagnetic Radiation Control Materials University of Electronic Science and Technology of China, Chengdu 611731, China.
Xin ZhaoLaboratory of Hepatic AI Translation, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu 611731, People's Republic of China.
Xinyue NaNational Engineering Research Center of Electromagnetic Radiation Control Materials University of Electronic Science and Technology of China, Chengdu 611731, China.
Ankang LiuNational Engineering Research Center of Electromagnetic Radiation Control Materials University of Electronic Science and Technology of China, Chengdu 611731, China.
Ruofan ChengNational Engineering Research Center of Electromagnetic Radiation Control Materials University of Electronic Science and Technology of China, Chengdu 611731, China.
Fantao JiangNational Engineering Research Center of Electromagnetic Radiation Control Materials University of Electronic Science and Technology of China, Chengdu 611731, China.
Qi ZhangCollege of Biological and Chemical Engineering, Qilu Institute of Technology, Jinan 250200, PR China.
Fengwei GaoLaboratory of Hepatic AI Translation, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu 611731, People's Republic of China.
Hong WuLaboratory of Hepatic AI Translation, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu 611731, People's Republic of China.
Ting ZhangLaboratory of Hepatic AI Translation, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu 611731, People's Republic of China.
Weiliang MaNational Engineering Research Center of Electromagnetic Radiation Control Materials University of Electronic Science and Technology of China, Chengdu 611731, China.ORCID 0009-0003-0933-5632
Longjiang DengNational Engineering Research Center of Electromagnetic Radiation Control Materials University of Electronic Science and Technology of China, Chengdu 611731, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Precision medicine requires tools that can resolve molecular information at the nanoscale, where many early biological and pathological changes arise. Scanning near-field optical microscopy (SNOM) combines molecular vibrational fingerprints with nanoscale spatial resolution, providing a unique platform for overcoming the diffraction limit of conventional optics and enabling in situ chemical characterization of biological samples. This paper systematically reviews the development of SNOM from near-field imaging to spectroscopic platforms such as nano-FTIR and AFM-IR, and summarizes the latest advances in ultrafast, liquid-phase, terahertz, and miniaturized systems. Focusing on representative studies involving proteins, nucleic acids, bacteria, viruses, extracellular vesicles, and cell-material interfaces, this paper discusses SNOM's ability to resolve molecular heterogeneity, structural transitions, and local biochemical interactions in near-natural environments. Additionally, the article analyzes the major challenges facing its clinical translation, including sample preparation, signal-to-noise ratio, measurement speed, quantitative analysis, and standardization, and explores its application potential in AI-assisted analysis, portability, and neuroscience. SNOM is expected to become a key technological platform bridging molecular diagnostics and nanobiological imaging.

Indexed as

MicroscopyNanotechnologyAnimalsHumansSpectroscopy, Fourier Transform Infraredbiomedical spectroscopyclinical translationinfrared SNOMlabel-free molecular fingerprintingnanoscale vibrational spectroscopy

Identifiers

PMID42136395
PMCPMC13220876

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.