Evidence map›Paper›PMID 29046689›Full record

ArticleFrontiers in plant science2017

An Updated Protocol for High Throughput Plant Tissue Sectioning.

Jonathan A Atkinson, Darren M Wells

Open access · goldAbstract read
In one paragraph

Article in Frontiers in plant science, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
7.1field-weighted citation impact, top 4% 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

25 citing papers in PubMed, 56 citations in OpenAlex.

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  8. Frontiers in plant science · 2024
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  20. A 3D Print Repository for Plant Phenomics.Plant phenomics (Washington, D.C.) · 2020
    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

2 authors at 2 institutions in 1 country.

Jonathan A AtkinsonThe Centre for Plant Integrative Biology, School of Biosciences, University of Nottingham, Nottingham, United Kingdom.
Darren M WellsThe Centre for Plant Integrative Biology, School of Biosciences, University of Nottingham, Nottingham, United Kingdom.
Biotechnology and Biological Sciences Research Council · GBUniversity of Nottingham · GB

Funding

Biotechnology and Biological Sciences Research Council BB/D019613/1Biotechnology and Biological Sciences Research Council BB/G023972/1European Research Council 294729
6 · The paper itself

Abstract

Quantification of the tissue and cellular structure of plant material is essential for the study of a variety of plant sciences applications. Currently, many methods for sectioning plant material are either low throughput or involve free-hand sectioning which requires a significant amount of practice. Here, we present an updated method to provide rapid and high-quality cross sections, primarily of root tissue but which can also be readily applied to other tissues such as leaves or stems. To increase the throughput of traditional agarose embedding and sectioning, custom designed 3D printed molds were utilized to embed 5-15 roots in a block for sectioning in a single cut. A single fluorescent stain in combination with laser scanning confocal microscopy was used to obtain high quality images of thick sections. The provided CAD files allow production of the embedding molds described here from a number of online 3D printing services. Although originally developed for roots, this method provides rapid, high quality cross sections of many plant tissue types, making it suitable for use in forward genetic screens for differences in specific cell structures or developmental changes. To demonstrate the utility of the technique, the two parent lines of the wheat (

Indexed as

3D printingconfocal microscopycross sectionroot anatomytissue sectioning

Identifiers

PMID29046689
PMCPMC5632646
OpenAlexW2761242333

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.