Evidence map›Paper›PMID 25356198›Full record

ArticleGigaScience2014

A dataset comprising 141 magnetic resonance imaging scans of 98 extant sea urchin species.

Alexander Ziegler, Cornelius Faber, Susanne Mueller, Nina Nagelmann, Leif Schröder

Abstract read
In one paragraph

Article in GigaScience, 2014. 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

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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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.

Alexander ZieglerZiegler Biosolutions, Fahrgasse 5, 79761 Waldshut-Tiengen, Germany.
Cornelius FaberInstitut für Klinische Radiologie, Universitätsklinikum Münster, Albert-Schweitzer-Campus 1, 48149 Münster, Germany.
Susanne MuellerCentrum für Schlaganfallforschung, Charité-Universitätsmedizin Berlin, Charitéplatz 1, 10117 Berlin, Germany.
Nina NagelmannInstitut für Klinische Radiologie, Universitätsklinikum Münster, Albert-Schweitzer-Campus 1, 48149 Münster, Germany.
Leif SchröderMolecular Imaging Group, Leibniz-Institut für Molekulare Pharmakologie, Robert-Rössle-Straße 10, 13125 Berlin, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundApart from its application in human diagnostics, magnetic resonance imaging (MRI) can also be used to study the internal anatomy of zoological specimens. As a non-invasive imaging technique, MRI has several advantages, such as rapid data acquisition, output of true three-dimensional imagery, and provision of digital data right from the onset of a study. Of particular importance for comparative zoological studies is the capacity of MRI to conduct high-throughput analyses of multiple specimens. In this study, MRI was applied to systematically document the internal anatomy of 98 representative species of sea urchins (Echinodermata: Echinoidea).

findingsThe dataset includes raw and derived image data from 141 MRI scans. Most of the whole sea urchin specimens analyzed were obtained from museum collections. The attained scan resolutions permit differentiation of various internal organs, including the digestive tract, reproductive system, coelomic compartments, and lantern musculature. All data deposited in the GigaDB repository can be accessed using open source software. Potential uses of the dataset include interactive exploration of sea urchin anatomy, morphometric and volumetric analyses of internal organs observed in their natural context, as well as correlation of hard and soft tissue structures.

conclusionsThe dataset covers a broad taxonomical and morphological spectrum of the Echinoidea, focusing on 'regular' sea urchin taxa. The deposited files significantly expand the amount of morphological data on echinoids that are electronically available. The approach chosen here can be extended to various other vertebrate and invertebrate taxa. We argue that publicly available digital anatomical and morphological data gathered during experiments involving non-invasive imaging techniques constitute one of the prerequisites for future large-scale genotype-phenotype correlations.

Indexed as

AnatomyEchinodermataEchinoideaEvolutionMorphologyMorphomicsMRIRepositorySoft tissueSystematics

Identifiers

PMID25356198
PMCPMC4212584

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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.