Evidence map›Paper›PMID 29644998›Full record

ArticleNature biotechnology2018

Fast, long-term, super-resolution imaging with Hessian structured illumination microscopy.

Xiaoshuai Huang, Junchao Fan, Liuju Li, Haosen Liu, Runlong Wu, Yi Wu, Lisi Wei, Heng Mao, Amit Lal, Peng Xi and 5 more

Abstract read
PubMed Publisher
In one paragraph

Article in Nature biotechnology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 233 papers.

0numbers the graph read from it
0cells of the map it votes in
233citing 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

233 citing papers in PubMed.

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  13. Targeting Supramolecular Active Complexes of NaAdvanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Article
  14. Article
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  19. Review
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173 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

15 authors.

Xiaoshuai HuangState Key Laboratory of Membrane Biology, Beijing Key Laboratory of Cardiometabolic Molecular Medicine, Institute of Molecular Medicine, Peking University, Beijing, China.
Junchao FanKey Laboratory of Image Processing and Intelligent Control of Ministry of Education of China, School of Automation, Huazhong University of Science and Technology, Wuhan, China.
Liuju LiState Key Laboratory of Membrane Biology, Beijing Key Laboratory of Cardiometabolic Molecular Medicine, Institute of Molecular Medicine, Peking University, Beijing, China.
Haosen LiuKey Laboratory of Image Processing and Intelligent Control of Ministry of Education of China, School of Automation, Huazhong University of Science and Technology, Wuhan, China.
Runlong WuSchool of Electronics Engineering and Computer Science, Peking University, Beijing, China.
Yi WuSchool of Software and Microelectronics, Peking University, Beijing, China.
Lisi WeiState Key Laboratory of Membrane Biology, Beijing Key Laboratory of Cardiometabolic Molecular Medicine, Institute of Molecular Medicine, Peking University, Beijing, China.
Heng MaoSchool of Mathematical Sciences, Peking University, Beijing, China.
Amit LalCollege of Engineering, Department of Biomedical Engineering, Peking University, Beijing, China.
Peng XiCollege of Engineering, Department of Biomedical Engineering, Peking University, Beijing, China.
Liqiang TangColdSpring Science Corporation, Beijing, China.
Yunfeng ZhangSchool of Electronics Engineering and Computer Science, Peking University, Beijing, China.ORCID 0000-0003-2418-2120
Yanmei LiuState Key Laboratory of Membrane Biology, Beijing Key Laboratory of Cardiometabolic Molecular Medicine, Institute of Molecular Medicine, Peking University, Beijing, China.
Shan TanKey Laboratory of Image Processing and Intelligent Control of Ministry of Education of China, School of Automation, Huazhong University of Science and Technology, Wuhan, China.
Liangyi ChenState Key Laboratory of Membrane Biology, Beijing Key Laboratory of Cardiometabolic Molecular Medicine, Institute of Molecular Medicine, Peking University, Beijing, China.ORCID 0000-0003-1270-7321

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To increase the temporal resolution and maximal imaging time of super-resolution (SR) microscopy, we have developed a deconvolution algorithm for structured illumination microscopy based on Hessian matrixes (Hessian-SIM). It uses the continuity of biological structures in multiple dimensions as a priori knowledge to guide image reconstruction and attains artifact-minimized SR images with less than 10% of the photon dose used by conventional SIM while substantially outperforming current algorithms at low signal intensities. Hessian-SIM enables rapid imaging of moving vesicles or loops in the endoplasmic reticulum without motion artifacts and with a spatiotemporal resolution of 88 nm and 188 Hz. Its high sensitivity allows the use of sub-millisecond excitation pulses followed by dark recovery times to reduce photobleaching of fluorescent proteins, enabling hour-long time-lapse SR imaging of actin filaments in live cells. Finally, we observed the structural dynamics of mitochondrial cristae and structures that, to our knowledge, have not been observed previously, such as enlarged fusion pores during vesicle exocytosis.

Indexed as

Actin CytoskeletonAlgorithmsEndoplasmic ReticulumImage Processing, Computer-AssistedLightMicroscopy

Identifiers

PMID29644998

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.