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Record W2075425693 · doi:10.1002/jcb.24446

Osteogenesis and expression of the bone marrow niche in endothelial cell‐depleted HipOPs

2012· article· en· W2075425693 on OpenAlexafffund
Kristen P. McKenzie, Dana Mayer, Jane E. Aubin

Bibliographic record

VenueJournal of Cellular Biochemistry · 2012
Typearticle
Languageen
FieldMedicine
TopicMesenchymal stem cell research
Canadian institutionsCanada Research ChairsUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsMesenchymal stem cellCell biologyBone marrowHaematopoiesisPopulationStromal cellBiologyCD31Stem cellEndothelial stem cellOsteoblastImmunologyIn vitroCancer researchMedicineImmunohistochemistryBiochemistry

Abstract

fetched live from OpenAlex

The identification and purification of murine multipotent mesenchymal stem cells (MSCs) have been difficult due to their low frequency, the presence of contaminating cell types and lack of unambiguous markers. Using a magnetic micro-beads negative selection technique to remove hematopoietic cells from mouse bone marrow stromal cells (BMSCs), our lab recently isolated a highly purified osteoprogenitor (HipOP) population that was also enriched for other mesenchymal precursors, including MSCs [Itoh and Aubin, 2009]. We now report that HipOPs are also highly enriched in vascular endothelial cells (VECs), which we hypothesized were an accessory cell type regulating osteogenesis. However, when VECs were immunodepleted from HipOPs with anti-CD31 antibodies, the resulting CD31(-) HipOP population had equal osteogenic capacity to the HipOPs in vitro and in vivo. Analysis of gene expression of Ncad, Pth1r, Ang1, Cxcl12, Jag1, Pdgfr-β, α-sma, Desmin, and Ng2 suggested that both HipOPs and CD31(-) HipOPs are hemopoietic stem cell (HSC) niche populations. However, the data support the view that osteoblast differentiation and depletion of VECs modulate the HSC niche.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.039
Threshold uncertainty score0.341

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.014
GPT teacher head0.252
Teacher spread0.238 · 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 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

Citations3
Published2012
Admission routes2
Has abstractyes

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