Evidence map›Paper›PMID 28855543›Full record

ArticleScientific reports2017

Improved vessel painting with carbocyanine dye-liposome solution for visualisation of vasculature.

Alu Konno, Naoya Matsumoto, Shigetoshi Okazaki

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.4field-weighted citation impact, top 19% 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

11 citing papers in PubMed, 17 citations in OpenAlex.

  1. Review
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  5. TISSUE CLEARING.Nature reviews. Methods primers · 2021
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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

3 authors at 2 institutions in 1 country.

Alu KonnoDepartment of Medical Spectroscopy, Preeminent Medical Photonics Education & Research Center, Institute for Medical Photonics Research, Hamamatsu University School of Medicine, Shizuoka, Japan.
Naoya MatsumotoCentral Research Laboratory, Hamamatsu Photonics K.K., Shizuoka, Japan.
Shigetoshi OkazakiDepartment of Medical Spectroscopy, Preeminent Medical Photonics Education & Research Center, Institute for Medical Photonics Research, Hamamatsu University School of Medicine, Shizuoka, Japan. okazaki@hama-med.ac.jp.
Hamamatsu University School of Medicine · JPHamamatsu Photonics (Japan) · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Vessel painting is one of the most accessible and cost-effective techniques for visualising vasculature by fluorescence microscopy. In this method, the hydrophobic carbocyanine dye DiIC18 labels the plasma membrane via insertion of its alkyl chains into the lipid bilayer. A major disadvantage of this procedure is that it does not stain veins and some microvessels in mouse brain. Furthermore, DiIC18 molecules can aggregate during perfusion, thereby occluding arteries and reducing the success rate and reproducibility of the experiment. To overcome these problems, we developed an improved vessel painting procedure that employs neutral liposomes (NLs) and DiIC12. NLs prevented DiI aggregation under physiological conditions whereas DiIC12 showed enhanced dye incorporation into liposomes and consequently increased staining intensity. Using this method, we successfully labelled all major blood vessel types in the mouse brain, including both veins and microvessels. Thus, liposome-mediated vessel painting is a simple and efficient method for visualising vasculature.

Indexed as

AnimalsBlood VesselsBrainCarbocyaninesColoring AgentsLiposomesMice, Inbred C57BLMicroscopy, FluorescenceStaining and LabelingCarbocyaninesColoring AgentsLiposomes

Identifiers

PMID28855543
PMCPMC5577039
OpenAlexW2747245170

What OpenQuestion holds

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LicenceCC BY
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.