Evidence map›Paper›PMID 30459565›Full record

ArticleFrontiers in neuroanatomy2018

Block Face Scanning Electron Microscopy of Fluorescently Labeled Axons Without Using Near Infra-Red Branding.

Catherine Maclachlan, Daniela A Sahlender, Shuichi Hayashi, Zoltán Molnár, Graham Knott

Open access · goldAbstract read
In one paragraph

Article in Frontiers in neuroanatomy, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
2.3field-weighted citation impact, top 10% 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

13 citing papers in PubMed, 23 citations in OpenAlex.

  1. Review
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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

5 authors at 2 institutions in 2 countries.

Catherine MaclachlanBioEM Facility, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
Daniela A SahlenderBioEM Facility, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
Shuichi HayashiDepartment of Physiology, Anatomy and Genetics, University of Oxford, Oxford, United Kingdom.
Zoltán MolnárDepartment of Physiology, Anatomy and Genetics, University of Oxford, Oxford, United Kingdom.
Graham KnottBioEM Facility, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
École Polytechnique Fédérale de Lausanne · CHUniversity of Oxford · GB

Funding

Medical Research Council MR/N026039/1
6 · The paper itself

Abstract

In this article, we describe the method that allows fluorescently tagged structures such as axons to be targeted for electron microscopy (EM) analysis without the need to convert their labels into electron dense stains, introduce any fiducial marks, or image large volumes at high resolution. We optimally preserve and stain the brain tissue for ultrastructural analysis and use natural landmarks, such as cell bodies and blood vessels, to locate neurites that had been imaged previously using confocal microscopy. The method relies on low and high magnification views taken with the light microscope, after fixation, to capture information of the tissue structure that can later be used to pinpoint the position of structures of interest in serial EM images. The examples shown here are td Tomato expressing cortico-thalamic axons in the posteromedial nucleus of the mouse thalamus, imaged in fixed tissue with confocal microscopy, and subsequently visualized with serial block-face EM (SBEM) and reconstructed into 3D models for analysis.

Indexed as

axonscorrelative light and electron microscopy (CLEM)neuron ultrastructurescanning electron microscopyserial block-face electron microscopy (SBEM)

Identifiers

PMID30459565
PMCPMC6232369
OpenAlexW2900188528

What OpenQuestion holds

Textmetadata
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.