Evidence map›Paper›PMID 40681818›Full record

ReviewScience China. Life sciences2025

Cellular optical imaging techniques: a dynamic advancing frontier.

Yaning Li, Chuankang Li, Caiwei Zhou, Jie Wang, Weixing Li, Tianying Pan, Chenying He, Xiaodong Guan, Yichen Wang, Yingda Huang and 8 more

Abstract readReview
PubMed Publisher
In one paragraph

Review in Science China. Life sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

18 authors.

Yaning Li *College of Future Technology, Peking University, Beijing, 100871, China.
Chuankang Li *State Key Laboratory of Extreme Photonics and Instrumentation, College of Optical Science and Engineering, Zhejiang University, Hangzhou, 310027, China.
Caiwei Zhou *State Key Laboratory of Membrane Biology, Biomedical Pioneer Innovation Center (BIOPIC), Beijing, 100871, China.
Jie Wang *School of Optical and Electronic Information-Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, 430074, China.
Weixing Li *Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China.
Tianying Pan *Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China.
Chenying HeState Key Laboratory of Extreme Photonics and Instrumentation, College of Optical Science and Engineering, Zhejiang University, Hangzhou, 310027, China.
Xiaodong GuanState Key Laboratory of Membrane Biology, Biomedical Pioneer Innovation Center (BIOPIC), Beijing, 100871, China.
Yichen WangState Key Laboratory of Membrane Biology, Biomedical Pioneer Innovation Center (BIOPIC), Beijing, 100871, China.
Yingda HuangCollege of Future Technology, Peking University, Beijing, 100871, China.
Xianao ZhaoInstitute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China.
Lusheng GuInstitute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China.
Peng XiCollege of Future Technology, Peking University, Beijing, 100871, China. xipeng@pku.edu.cn.
Cuifang KuangState Key Laboratory of Extreme Photonics and Instrumentation, College of Optical Science and Engineering, Zhejiang University, Hangzhou, 310027, China. cfkuang@zju.edu.cn.
Yujie SunCollege of Future Technology, Peking University, Beijing, 100871, China. sun_yujie@pku.edu.cn.
Peng FeiSchool of Optical and Electronic Information-Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, 430074, China. feipeng@hust.edu.cn.
Wei JiInstitute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China. jiwei@ibp.ac.cn.
Liangyi ChenCollege of Future Technology, Peking University, Beijing, 100871, China. lychen@pku.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This article reviews recent super-resolution (SR) optical imaging techniques for cellular study, encompassing structured illumination microscopy (SIM), point-scanning super-resolution (PS-SR) microscopy, single-molecule localization microscopy (SMLM), mathematical and deep learning (DL) SR algorithms. Historically, the resolution of traditional far-field optical imaging was constrained by the diffraction limit. The emergence of SR imaging techniques and image processing algorithms has propelled biological research into nanoscale realm. SIM enhances resolution by manipulating spatial frequency content, effectively doubling the resolution capacity of traditional microscopy. PS-SR imaging, on the other hand, offers superior optical sectioning and a high signal-to-noise ratio. SMLM has achieved a remarkable spatial resolution of approximately 20 nm and supports multi-color, wide-field-of-view (FOV), automated 3D high-throughput imaging, thus broadening the horizons for advanced biomedical investigations. Additionally, both mathematical and DL-based SR algorithms have significantly advanced the conversion of low-resolution images to high-resolution counterparts, extending the capabilities of conventional microscopes. This review underscores the principles, recent developments, and diverse applications of these cutting-edge SR imaging methodologies in biological research.

Indexed as

Optical ImagingAlgorithmsAnimalsDeep LearningHumansImage Processing, Computer-AssistedImaging, Three-DimensionalMicroscopyMicroscopy, FluorescenceSignal-To-Noise RatioSingle Molecule Imagingdeep learningMINFLUXpoint-scanning super-resolution microscopysingle-molecule localization microscopystructured illumination microscopysuper-resolution microscopy

Identifiers

PMID40681818

What OpenQuestion holds

Textmetadata
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 OpenQuestion graph.