Evidence map›Paper›PMID 32403589›Full record

ArticleOptics express2020

Background-free imaging of chemical bonds by a simple and robust frequency-modulated stimulated Raman scattering microscopy.

Hanqing Xiong, Naixin Qian, Zhilun Zhao, Lingyan Shi, Yupeng Miao, Wei Min

Abstract read
In one paragraph

Article in Optics express, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Multimodal Optical Imaging Platform for Studying Cellular Metabolism.Journal of visualized experiments : JoVE · 2025
    Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Advances in stimulated Raman scattering imaging for tissues and animals.Quantitative imaging in medicine and surgery · 2021
    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

6 authors.

Hanqing Xiong
Naixin Qian
Zhilun Zhao
Lingyan Shi
Yupeng Miao
Wei Min

Funding

Ultrahigh-resolution and single-molecule stimulated Raman scattering (SRS) microscopyR01GM132860 · NIGMS · COLUMBIA UNIV NEW YORK MORNINGSIDE · PI MIN, WEI · 2019 to 2022
$1.3M
NIGMS NIH HHS R01 GM132860
6 · The paper itself

Abstract

Being able to image chemical bonds with high sensitivity and speed, stimulated Raman scattering (SRS) microscopy has made a major impact in biomedical optics. However, it is well known that the standard SRS microscopy suffers from various backgrounds, limiting the achievable contrast, quantification and sensitivity. While many frequency-modulation (FM) SRS schemes have been demonstrated to retrieve the sharp vibrational contrast, they often require customized laser systems and/or complicated laser pulse shaping or introduce additional noise, thereby hindering wide adoption. Herein we report a simple but robust strategy for FM-SRS microscopy based on a popular commercial laser system and regular optics. Harnessing self-phase modulation induced self-balanced spectral splitting of picosecond Stokes beam propagating in standard single-mode silica fibers, a high-performance FM-SRS system is constructed without introducing any additional signal noise. Our strategy enables adaptive spectral resolution for background-free SRS imaging of Raman modes with different linewidths. The generality of our method is demonstrated on a variety of Raman modes with effective suppressing of backgrounds including non-resonant cross phase modulation and electronic background from two-photon absorption or pump-probe process. As such, our method is promising to be adopted by the SRS microscopy community for background-free chemical imaging.

Identifiers

PMID32403589
PMCPMC7340375

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.