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Record W4388665643 · doi:10.1016/j.bone.2023.116960

Understanding basic multicellular unit activity in cortical bone through 3D morphological analysis: New methods to define zones of the remodeling space

2023· article· en· W4388665643 on OpenAlexafffund
Lindsay L. Loundagin, Kim D. Harrison, Xuan Wei, David M. L. Cooper

Bibliographic record

VenueBone · 2023
Typearticle
Languageen
FieldMedicine
TopicBone health and osteoporosis research
Canadian institutionsUniversity of Saskatchewan
FundersGovernment of SaskatchewanNatural Sciences and Engineering Research Council of CanadaNational Research CouncilCanadian Institutes of Health ResearchCanada Foundation for InnovationUniversity of Saskatchewan
KeywordsBone remodelingContext (archaeology)Cortical boneAppositionMulticellular organismBiologyAnatomyPaleontology

Abstract

fetched live from OpenAlex

The activity of basic multicellular units (BMU) in cortical bone is classically described as a sequential order of events- resorption, reversal and formation. This simplified portrayal of the remodeling process is pervasive despite the reported variability in remodeling space morphology. These variations may reflect meaningful nuances in BMU activity but methods to quantify 3D remodeling space morphology within the context of the cellular activity are currently lacking. This study developed new techniques to define zones of BMU activity based on the 3D morphology of remodeling spaces in rabbit cortical bone and integrated morphological data with the BMU longitudinal erosion rate (LER) to elucidate the spatial-temporal coordination of BMUs and estimate mineral apposition rate (MAR). The tibiae of New Zealand white rabbits (n = 5) were imaged in vivo using synchrotron radiation and two weeks later ex vivo with desktop microCT. The in vivo and ex vivo datasets were co-registered, and 27 remodeling spaces were identified at both timepoints. A radial profile representing the 3D morphology was the platform for partitioning the remodeling spaces into resorption, reversal and formation zones. Manual, automated and semi-automated partitioning approaches were compared, and the zone-segmentations were used to calculate the length, change in radius and slope of each zone. The manual approach most accurately defined the zones of idealized remodeling spaces with known dimensions (relative error = 0.9-9.2 %) while the semi-automated method reliably defined the zones in rabbit remodeling spaces (ICC = 0.85-1.00). Combining LER and the manually derived zone dimensions indicated that a BMU passes through a cross-section in approximately 18.8 days with resorption, reversal and formation taking 4.1, 2.2, and 12.5 days, respectively. MAR estimated by the 3D analysis was not significantly different than that determined with classic histomorphometry (p = 0.48). These techniques have the potential to assess dynamic parameters of bone resorption and formation, eliminate the need for fluorochrome labeling and provide a more comprehensive perspective of the remodeling process.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.315
GPT teacher head0.446
Teacher spread0.131 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations12
Published2023
Admission routes2
Has abstractno

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