Evidence map›Paper›PMID 37248215›Full record

ArticleNature communications2023

Quantitative structured illumination microscopy via a physical model-based background filtering algorithm reveals actin dynamics.

Yanquan Mo, Kunhao Wang, Liuju Li, Shijia Xing, Shouhua Ye, Jiayuan Wen, Xinxin Duan, Ziying Luo, Wen Gou, Tongsheng Chen and 4 more

Abstract read
In one paragraph

Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

  1. Review
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  5. Review
  6. Time-deterministic cryo-optical microscopy.Light, science & applications · 2025
    Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Review
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  16. Live-cell imaging in the deep learning era.Current opinion in cell biology · 2023
    Review
  17. Article
  18. 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

14 authors.

Yanquan MoState Key Laboratory of Membrane Biology, Center for Life Sciences, College of Future Technology, Peking University, Beijing, 100871, China.ORCID 0000-0003-1399-2427
Kunhao WangKey Laboratory of Laser Life Science, Ministry of Education, College of Biophotonics, South China Normal University, Guangzhou, 510631, China.
Liuju LiState Key Laboratory of Membrane Biology, Center for Life Sciences, College of Future Technology, Peking University, Beijing, 100871, China.
Shijia XingState Key Laboratory of Membrane Biology, Center for Life Sciences, College of Future Technology, Peking University, Beijing, 100871, China.
Shouhua YeGuangzhou Computational Super-resolution Biotech Co., Ltd, Guangzhou, 510535, China.
Jiayuan WenGuangzhou Computational Super-resolution Biotech Co., Ltd, Guangzhou, 510535, China.
Xinxin DuanBritton Chance Center and MOE Key Laboratory for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, 430074, China.
Ziying LuoGuangzhou Computational Super-resolution Biotech Co., Ltd, Guangzhou, 510535, China.
Wen GouChongqing Key Laboratory of Image Cognition, College of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China.
Tongsheng ChenKey Laboratory of Laser Life Science, Ministry of Education, College of Biophotonics, South China Normal University, Guangzhou, 510631, China.ORCID 0000-0002-9036-6676
Yu-Hui ZhangBritton Chance Center and MOE Key Laboratory for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, 430074, China.ORCID 0000-0002-5158-0645
Changliang GuoState Key Laboratory of Membrane Biology, Center for Life Sciences, College of Future Technology, Peking University, Beijing, 100871, China.ORCID 0000-0001-6724-9060
Junchao FanChongqing Key Laboratory of Image Cognition, College of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China. fanjc@cqupt.edu.cn.ORCID 0000-0003-2586-7973
Liangyi ChenState Key Laboratory of Membrane Biology, Center for Life Sciences, College of Future Technology, Peking University, Beijing, 100871, China. lychen@pku.edu.cn.ORCID 0000-0003-1270-7321

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite the prevalence of superresolution (SR) microscopy, quantitative live-cell SR imaging that maintains the completeness of delicate structures and the linearity of fluorescence signals remains an uncharted territory. Structured illumination microscopy (SIM) is the ideal tool for live-cell SR imaging. However, it suffers from an out-of-focus background that leads to reconstruction artifacts. Previous post hoc background suppression methods are prone to human bias, fail at densely labeled structures, and are nonlinear. Here, we propose a physical model-based Background Filtering method for living cell SR imaging combined with the 2D-SIM reconstruction procedure (BF-SIM). BF-SIM helps preserve intricate and weak structures down to sub-70 nm resolution while maintaining signal linearity, which allows for the discovery of dynamic actin structures that, to the best of our knowledge, have not been previously monitored.

Indexed as

LightingMicroscopyActinsAlgorithmsHumansActins

Identifiers

PMID37248215
PMCPMC10227022

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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.