Evidence map›Paper›PMID 32415135›Full record

ArticleScientific reports2020

Multi-photon attenuation-compensated light-sheet fluorescence microscopy.

Madhu Veettikazhy, Jonathan Nylk, Federico Gasparoli, Adrià Escobet-Montalbán, Anders Kragh Hansen, Dominik Marti, Peter Eskil Andersen, Kishan Dholakia

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. FastBiomedical optics express · 2020
    Article
  5. 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

8 authors.

Madhu VeettikazhyDTU Health Tech, Technical University of Denmark, Frederiksborgvej 399, 4000, Roskilde, Denmark. madve@dtu.dk.
Jonathan NylkSUPA, School of Physics and Astronomy, University of St Andrews, North Haugh, St Andrews, KY16 9SS, UK.
Federico GasparoliSUPA, School of Physics and Astronomy, University of St Andrews, North Haugh, St Andrews, KY16 9SS, UK.
Adrià Escobet-MontalbánSUPA, School of Physics and Astronomy, University of St Andrews, North Haugh, St Andrews, KY16 9SS, UK.
Anders Kragh HansenDTU Fotonik, Technical University of Denmark, Frederiksborgvej 399, 4000, Roskilde, Denmark.
Dominik MartiDTU Health Tech, Technical University of Denmark, Frederiksborgvej 399, 4000, Roskilde, Denmark.
Peter Eskil AndersenDTU Health Tech, Technical University of Denmark, Frederiksborgvej 399, 4000, Roskilde, Denmark.
Kishan DholakiaSUPA, School of Physics and Astronomy, University of St Andrews, North Haugh, St Andrews, KY16 9SS, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Attenuation of optical fields owing to scattering and absorption limits the penetration depth for imaging. Whilst aberration correction may be used, this is difficult to implement over a large field-of-view in heterogeneous tissue. Attenuation-compensation allows tailoring of the maximum lobe of a propagation-invariant light field and promises an increase in depth penetration for imaging. Here we show this promising approach may be implemented in multi-photon (two-photon) light-sheet fluorescence microscopy and, furthermore, can be achieved in a facile manner utilizing a graded neutral density filter, circumventing the need for complex beam shaping apparatus. A "gold standard" system utilizing a spatial light modulator for beam shaping is used to benchmark our implementation. The approach will open up enhanced depth penetration in light-sheet imaging to a wide range of end users.

Identifiers

PMID32415135
PMCPMC7229186

What OpenQuestion holds

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LicenceCC BY
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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.