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Record W2020651053 · doi:10.1002/jcb.22262

A novel purification method for multipotential skeletal stem cells

2009· article· en· W2020651053 on OpenAlexaff
Shousaku Itoh, Jane E. Aubin

Bibliographic record

VenueJournal of Cellular Biochemistry · 2009
Typearticle
Languageen
FieldMedicine
TopicMesenchymal stem cell research
Canadian institutionsCanada Research ChairsUniversity of Toronto
Fundersnot available
KeywordsStem cellStromal cellCell biologyMesenchymal stem cellBone marrowHaematopoiesisOsteoblastBiologyProgenitor cellStem cell transplantation for articular cartilage repairPopulationClinical uses of mesenchymal stem cellsAdult stem cellImmunologyIn vitroCancer researchEndothelial stem cellMedicineBiochemistry

Abstract

fetched live from OpenAlex

At least some cells within bone marrow stromal populations are multipotential (i.e., differentiate in vitro into osteoblasts, chondrocytes, and adipocytes) and thus designated skeletal stem cells (SSCs) or mesenchymal stem cells (MSCs) amongst other names. Recently, a subpopulation of stromal cells, notably osteoblasts or their progenitors, has been identified as a definitive regulatory component of the hematopoietic stem cell (HSC) niche. Thus, the development of methods for purifying not only SSCs but cells comprising the HSC niche is of interest. Here, we report a method for purifying a novel bone marrow-derived population with a high frequency of osteoprogenitors and high expression levels of osteoblast differentiation markers (highly purified osteoprogenitors (HipOPs)) as well as markers of the bone niche for HSCs. In vivo transplantation experiments demonstrated that donor HipOPs differentiated into not only osteoblasts, osteocytes and cells around sinusoids but also hematopoietic cells. Thus, HipOPs represent a novel population for simultaneous reconstruction of bone and bone marrow microenvironments.

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: none
Teacher disagreement score0.488
Threshold uncertainty score0.547

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 head0.029
GPT teacher head0.328
Teacher spread0.299 · 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

Citations27
Published2009
Admission routes1
Has abstractyes

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