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Record W1968353004 · doi:10.1002/ar.20645

Histomorphometric and Densitometric Changes in the Femora of Spinal Cord Transected Mice

2008· article· en· W1968353004 on OpenAlexaff
Sylvain Picard, Nicolas Lapointe, Jacques P. Brown, Pierre A. Guertin

Bibliographic record

VenueThe Anatomical Record · 2008
Typearticle
Languageen
FieldMedicine
TopicSpinal Cord Injury Research
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsSpinal cordSpinal cord injuryAnatomyTrabecular boneBone tissueBone mineralMedicinePathologyOsteoporosis

Abstract

fetched live from OpenAlex

Spinal cord injury (SCI) leads generally to significant bone tissue loss within a few months to a few years post-trauma. Although, increasing data from rat models are available to study the underlying mechanisms of SCI-associated bone loss, little is known about the extent and rapidity of bone tissue changes in mouse models of SCI. The objectives are to characterize and describe quantitatively femoral bone tissue changes during 1 month in adult paraplegic mice. Histomorphometric and densitometric measurements were performed in 3- to 4-month-old CD1 mice spinal cord transected at the low-thoracic level (Th9/10). We found a general decrease in bone volume (-22%), trabecular thickness (-10%), and trabecular number (-14%) within 30 days post-transection. Dual-energy X-ray absorptiometric measurements revealed no change in bone mineral density but a significant reduction (-14%) in bone mineral content. These results show large structural changes occurring within only a few weeks post-spinal cord transection in the femora of adult mice. Given the increasing availability of genetic and molecular research tools for research in mice, this murine model may be useful to study further the cellular and molecular mechanisms of demineralization associated with SCI.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.669
Threshold uncertainty score0.331

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.005
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.089
GPT teacher head0.362
Teacher spread0.272 · 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 teacher head, not a consensus.

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

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

Citations25
Published2008
Admission routes1
Has abstractyes

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