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Record W1991906978 · doi:10.1073/pnas.1036475100

Mesenchymal progenitor self-renewal deficiency leads to age-dependent osteoporosis in Sca-1/Ly-6A null mice

2003· article· en· W1991906978 on OpenAlexaff
Mortaza Bonyadi, Stephen D. Waldman, Danmei Liu, Jane E. Aubin, Marc D. Grynpas, William L. Stanford

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2003
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBone Metabolism and Diseases
Canadian institutionsLunenfeld-Tanenbaum Research InstituteUniversity of TorontoMount Sinai Hospital
Fundersnot available
KeywordsMesenchymal stem cellProgenitor cellStem cellBiologyBone marrowOsteoporosisCell biologyProgenitorOsteoclastHaematopoiesisCancer researchImmunologyIn vitroEndocrinologyGenetics

Abstract

fetched live from OpenAlex

The cellular and molecular mechanisms that underlie age-dependent osteoporosis, the most common disease in the Western Hemisphere, are poorly understood in part due to the lack of appropriate animal models in which to study disease progression. Here, we present a model that shows many similarities to the human disease. Sca-1, well known for its expression on hematopoietic stem cells, is present on a subset of bone marrow stromal cells, which potentially include mesenchymal stem cells. Longitudinal studies showed that Sca-1(-/-) mice undergo normal bone development but with age exhibit dramatically decreased bone mass resulting in brittle bones. In vivo and in vitro analyses demonstrated that Sca-1 is required directly for the self-renewal of mesenchymal progenitors and indirectly for the regulation of osteoclast differentiation. Thus, defective mesenchymal stem or progenitor cell self-renewal may represent a previously uncharacterized mechanism of age-dependent osteoporosis in humans.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.018
GPT teacher head0.280
Teacher spread0.262 · 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 designBench or experimental
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

Citations247
Published2003
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the National Academy of SciencesSame topicBone Metabolism and DiseasesFrench-language works237,207