Evidence map›Paper›PMID 26912448›Full record

ArticleScientific reports2016

Sparse deconvolution of high-density super-resolution images.

Siewert Hugelier, Johan J de Rooi, Romain Bernex, Sam Duwé, Olivier Devos, Michel Sliwa, Peter Dedecker, Paul H C Eilers, Cyril Ruckebusch

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
13.1field-weighted citation impact, top 2% of its field
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

17 citing papers in PubMed, 80 citations in OpenAlex.

  1. Review
  2. Article
  3. Review
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  5. Resolution enhancement with deblurring by pixel reassignment (DPR).bioRxiv : the preprint server for biology · 2023
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  7. Article
  8. Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. EXACT SPIKE TRAIN INFERENCE VIA ℓThe annals of applied statistics · 2018
    Article
  15. Computational multifocal microscopy.Biomedical optics express · 2018
    Article
  16. Article
  17. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors at 3 institutions in 3 countries.

Siewert HugelierUniversité de Lille, LASIR CNRS UMR 8516, F-59000 Lille, France.
Johan J de RooiErasmus MC, Department of Biostatistics, Rotterdam, the Netherlands.
Romain BernexUniversité de Lille, LASIR CNRS UMR 8516, F-59000 Lille, France.
Sam DuwéDepartment of Chemistry, KU Leuven, Belgium.
Olivier DevosUniversité de Lille, LASIR CNRS UMR 8516, F-59000 Lille, France.
Michel SliwaUniversité de Lille, LASIR CNRS UMR 8516, F-59000 Lille, France.
Peter DedeckerDepartment of Chemistry, KU Leuven, Belgium.
Paul H C EilersErasmus MC, Department of Biostatistics, Rotterdam, the Netherlands.
Cyril RuckebuschUniversité de Lille, LASIR CNRS UMR 8516, F-59000 Lille, France.
KU Leuven · BEErasmus MC · NLErasmus University Rotterdam · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In wide-field super-resolution microscopy, investigating the nanoscale structure of cellular processes, and resolving fast dynamics and morphological changes in cells requires algorithms capable of working with a high-density of emissive fluorophores. Current deconvolution algorithms estimate fluorophore density by using representations of the signal that promote sparsity of the super-resolution images via an L1-norm penalty. This penalty imposes a restriction on the sum of absolute values of the estimates of emitter brightness. By implementing an L0-norm penalty--on the number of fluorophores rather than on their overall brightness--we present a penalized regression approach that can work at high-density and allows fast super-resolution imaging. We validated our approach on simulated images with densities up to 15 emitters per μm(-2) and investigated total internal reflection fluorescence (TIRF) data of mitochondria in a HEK293-T cell labeled with DAKAP-Dronpa. We demonstrated super-resolution imaging of the dynamics with a resolution down to 55 nm and a 0.5 s time sampling.

Indexed as

AlgorithmsFluorescent DyesHEK293 CellsHumansImage Processing, Computer-AssistedMicroscopy, FluorescenceMitochondriaFluorescent Dyes

Identifiers

PMID26912448
PMCPMC4766479
OpenAlexW2296138801

What OpenQuestion holds

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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.