Evidence map›Paper›PMID 40680685›Full record

ArticleJournal of biomechanics2025

Modeling and prediction of body segment inertial properties of sheep from tomographic imaging.

Aaron Henry, Carson Benner, Bailee CoVan, Annabelle Helin, Dana Gaddy, Larry J Suva, Andrew B Robbins

Abstract read
In one paragraph

Article in Journal of biomechanics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Aaron HenryDepartment of Multidisciplinary Engineering, College of Engineering, Texas A&M University, United States of America. Electronic address: ahenry@tamu.edu.
Carson BennerDepartment of Multidisciplinary Engineering, College of Engineering, Texas A&M University, United States of America; School of Engineering Medicine, Texas A&M University, United States of America. Electronic address: carsonmbenner@tamu.edu.
Bailee CoVanDepartment of Multidisciplinary Engineering, College of Engineering, Texas A&M University, United States of America; School of Engineering Medicine, Texas A&M University, United States of America. Electronic address: covan@tamu.edu.
Annabelle HelinDepartment of Biomedical Engineering, College of Engineering, Texas A&M University, United States of America. Electronic address: annabelle.helin@tamu.edu.
Dana GaddyDepartment of Veterinary Integrative Biosciences, College of Veterinary Medicine & Biomedical Sciences, Texas A&M University, United States of America. Electronic address: dgaddy@tamu.edu.
Larry J SuvaDepartment of Veterinary Physiology & Pharmacology, College of Veterinary Medicine & Biomedical Sciences, Texas A&M University, United States of America. Electronic address: lsuva@cvm.tamu.edu.
Andrew B RobbinsDepartment of Mechanical Engineering, University of Texas at Tyler, United States of America. Electronic address: arobbins@uttyler.edu.

Funding

Modeling Odontohypophosphatasia in the SheepR21DE028076 · NIDCR · TEXAS A&M AGRILIFE RESEARCH · PI GADDY, DANA · 2018 to 2019
$422k
Respiratory Distress in Sheep with Hypophosphatasia: Etiology, Functional Consequences and RescueR21HD114076 · NICHD · TEXAS A&M AGRILIFE RESEARCH · PI GADDY, DANA · 2024 to 2025
$409k
NICHD NIH HHS R21 HD114076NIDCR NIH HHS R21 DE028076
6 · The paper itself

Abstract

Sheep are frequently used animal models of musculoskeletal diseases and orthopedic procedures due to their docility, size and body weight, and similar joint biomechanics to humans. Estimation of body segment inertial properties (BSIPs) is a crucial step in development of biomechanical models, but few resources exist for BSIPs in sheep. The goal of this study was to develop predictive models to estimate the mass, center of mass, and inertia tensor of the hindlimbs of sheep from easily obtainable morphometric data. In addition, this study presents a more comprehensive and repeatable method for defining each hindlimb body segment when directly calculating BSIPs from tomographic imaging. Briefly, CT scans from 16 sheep of varying age, weight, sex, and phenotype were used to calculate BSIPs for the pelvis, thigh, crus, metatarsus, and pastern segments. Those measurements were then used to develop predictive models to estimate the BSIPs for those segments. The predictive models developed showed similar prediction errors to models developed in human populations.

Indexed as

HindlimbModels, BiologicalAnimalsBiomechanical PhenomenaFemaleMaleSheepTomography, X-Ray ComputedHindlimbInertiaOvine

Identifiers

PMID40680685
PMCPMC12360281

What OpenQuestion holds

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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.