Evidence map›Paper›PMID 41742410›Full record

ArticleSTAR protocols2026

Protocol for quantifying vertebral column morphology for the statistical analysis of scoliosis severity in zebrafish.

Brittney Voigt, Ece Atayeter, Ron Sistrunk, Ryan S Gray

Abstract read
In one paragraph

Article in STAR protocols, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Brittney VoigtDepartment of Nutritional Sciences, The University of Texas at Austin, Austin, TX 78705, USA; Department of Pediatrics, Dell Pediatric Research Institute, The University of Texas at Austin, Austin, TX 78723, USA. Electronic address: brittney.voigt@austin.utexas.edu.
Ece AtayeterDepartment of Nutritional Sciences, The University of Texas at Austin, Austin, TX 78705, USA; Department of Pediatrics, Dell Pediatric Research Institute, The University of Texas at Austin, Austin, TX 78723, USA.
Ron SistrunkDepartment of Nutritional Sciences, The University of Texas at Austin, Austin, TX 78705, USA; Department of Pediatrics, Dell Pediatric Research Institute, The University of Texas at Austin, Austin, TX 78723, USA.
Ryan S GrayDepartment of Nutritional Sciences, The University of Texas at Austin, Austin, TX 78705, USA; Department of Pediatrics, Dell Pediatric Research Institute, The University of Texas at Austin, Austin, TX 78723, USA. Electronic address: ryan.gray@austin.utexas.edu.

Funding

Non-coding/epigenetic regulationP01HD084387 · NICHD · UT SOUTHWESTERN MEDICAL CENTER · PI Nadav Ahituv, LILIANNA SOLNICAKREZEL · 2016 to 2026
$14.2M
NICHD NIH HHS P01 HD084387
6 · The paper itself

Abstract

Here, we present a protocol for quantifying zebrafish vertebral column morphology using micro-computed tomography (microCT) datasets for scoliosis researchers. We describe steps for orientation of skeletal and cranial microCT datasets in DataViewer, vertebral position measurements in ImageJ/Fiji, and analysis of vertebral position in R. The approach described here graphically depicts vertebral position while providing a means to quantify scoliosis severity and perform statistical analysis of differences in vertebral column morphology in zebrafish. For complete details on the use and execution of this protocol, please refer to Voigt et al.

Indexed as

ScoliosisSpineX-Ray MicrotomographyZebrafishAnimalsDisease Models, AnimalDevelopmental biologyMicroscopyModel Organisms

Identifiers

PMID41742410
PMCPMC13023086

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.