Evidence map›Paper›PMID 37642807›Full record

ArticleBiomechanics and modeling in mechanobiology2024

Computational modeling based on confocal imaging predicts changes in osteocyte and dendrite shear stress due to canalicular loss with aging.

Mohammad Niroobakhsh, Loretta E Laughrey, Sarah L Dallas, Mark L Johnson, Thiagarajan Ganesh

Open access · greenAbstract read
In one paragraph

Article in Biomechanics and modeling in mechanobiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
3.2field-weighted citation impact, top 8% 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

6 citing papers in PubMed, 13 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
  4. Review
  5. Article
  6. Analysis and Imaging of Osteocytes.Journal of visualized experiments : JoVE · 2024
    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

5 authors at 1 institution in 1 country.

Mohammad NiroobakhshDivision of Natural and Built Environment, School of Science and Engineering, University of Missouri-Kansas City, 350 L Flarsheim Hall, 5100 Rockhill Road, Kansas City, MO, 64110, USA.
Loretta E LaughreyDivision of Natural and Built Environment, School of Science and Engineering, University of Missouri-Kansas City, 350 L Flarsheim Hall, 5100 Rockhill Road, Kansas City, MO, 64110, USA.
Sarah L DallasDepartment of Oral and Craniofacial Sciences, School of Dentistry, University of Missouri-Kansas City, 620 E 25th Street, Kansas City, MO, 64108, USA.
Mark L JohnsonDepartment of Oral and Craniofacial Sciences, School of Dentistry, University of Missouri-Kansas City, 620 E 25th Street, Kansas City, MO, 64108, USA.
Thiagarajan GaneshDivision of Natural and Built Environment, School of Science and Engineering, University of Missouri-Kansas City, 350 L Flarsheim Hall, 5100 Rockhill Road, Kansas City, MO, 64110, USA. ganesht@umkc.edu.
University of Missouri–Kansas City · US

Funding

Transgenic and Mechanical Loading CoreP01AG039355 · NIA · UNIVERSITY OF MISSOURI KANSAS CITY · PI BONEWALD, LYNDA F · 2012 to 2024
$19.3M
Dynamics of Bone ECM Assembly and ResorptionR01AR083438 · NIAMS · UNIVERSITY OF MISSOURI KANSAS CITY · PI SARAH L DALLAS · 2024 to 2026
$1.4M
Leica TCS Sp8 MP Multiphoton MicroscopeS10OD021665 · OD · UNIVERSITY OF MISSOURI KANSAS CITY · PI DALLAS, SARAH L · 2016 to 2016
$600k
Leica Stellaris 8 Confocal Microscope SystemS10OD032373 · OD · UNIVERSITY OF MISSOURI KANSAS CITY · PI DALLAS, SARAH L · 2022 to 2022
$599k
Aging Effects on Mechanoregulation of Osteocytes using Multiscale MultiphysicsR15AG080524 · NIA · UNIVERSITY OF MISSOURI KANSAS CITY · PI GANESH, THIAGARAJAN · 2024 to 2024
$456k
Zeiss LSM 710 Confocal Microscopy System for Imaging of Mineralized TissuesS10RR027668 · NCRR · UNIVERSITY OF MISSOURI KANSAS CITY · PI DALLAS, SARAH L · 2011 to 2011
$446k
Osteocytes as Dynamic CellsR21AR054449 · NIAMS · UNIVERSITY OF MISSOURI KANSAS CITY · PI DALLAS, SARAH L · 2007 to 2008
$340k
NCRR NIH HHS S10 RR027668NIAMS NIH HHS R01 AR083438NIAMS NIH HHS R21 AR054449NIA NIH HHS P01 AG039355NIA NIH HHS R15 AG080524NIH HHS NIH - NIA P01 AG039355NIH HHS S10 OD021665NIH HHS S10 OD032373
6 · The paper itself

Abstract

Exercise and physical activity exert mechanical loading on the bones which induces bone formation. However, the relationship between the osteocyte lacunar-canalicular morphology and mechanical stress experienced locally by osteocytes transducing signals for bone formation is not fully understood. In this study, we used computational modeling to predict the effect of canalicular density, the number of fluid inlets, and load direction on fluid flow shear stress (FFSS) and bone strains and how these might change following the microstructural deterioration of the lacunar-canalicular network that occurs with aging. Four distinct computational models were initially generated of osteocytes with either ten or eighteen dendrites using a fluid-structure interaction method with idealized geometries. Next, a young and a simulated aged osteocyte were developed from confocal images after FITC staining of the femur of a 4-month-old C57BL/6 mouse to estimate FFSS using a computational fluid dynamics approach. The models predicted higher fluid velocities in the canaliculi versus the lacunae. Comparison of idealized models with five versus one fluid inlet indicated that with four more inlets, one-half of the dendrites experienced FFSS greater than 0.8 Pa, which has been associated with osteogenic responses. Confocal image-based models of real osteocytes indicated a six times higher ratio of canalicular to lacunar surface area in the young osteocyte model than the simulated aged model and the average FFSS in the young model (FFSS = 0.46 Pa) was three times greater than the aged model (FFSS = 0.15 Pa). Interestingly, the surface area with FFSS values above 0.8 Pa was 23 times greater in the young versus the simulated aged model. These findings may explain the impaired mechano-responsiveness of osteocytes with aging.

Indexed as

AgingOsteocytesAnimalsComputer SimulationDendritesMiceMice, Inbred C57BLStress, MechanicalAgingComputational fluid dynamics (CFD)Confocal imagingFluid–structure interaction (FSI)MechanotransductionOsteocyte

Identifiers

PMID37642807
PMCPMC12183637
OpenAlexW4386245446

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Registered trials

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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.