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In Vitro Osteogenic Response of Rat Bone Marrow Cells to bFGF and BMP-2 Treatments

2006· article· en· W2070384418 on OpenAlexaff
Mathew Varkey, Cezary Kucharski, Takrima Haque, Walter Sebald, Hasan Uludağ

Bibliographic record

VenueClinical Orthopaedics and Related Research · 2006
Typearticle
Languageen
FieldMedicine
TopicMesenchymal stem cell research
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineBone morphogenetic protein 2In vitroBone marrowBone morphogenetic proteinBone morphogenetic protein 7PathologyBiochemistry

Abstract

fetched live from OpenAlex

Basic fibroblast growth factor (bFGF) and bone morphogenetic protein-2 (BMP-2) are actively pursued for stimulation of bone formation. To assess their promise for systemic therapy of osteoporosis, we ascertained the effects of bFGF and BMP-2 on bone marrow cells in vitro. Bone marrow cells were obtained from young (8 weeks) and adult (32 weeks) rats by femoral aspiration and were exposed to osteogenic medium (ie, basal medium with 10 mM beta-glycerolphosphate and 100 nM dexamethasone) containing the growth factors. The cell viability in osteogenic medium was reduced after 3 weeks but not if the concentration of beta-glycerolphosphate/dexamethasone was reduced to 3 mM/30 nM. Unlike BMP-2, bFGF at 2-50 ng/mL was capable of enhancing long-term cell viability. Continuous treatment of bone marrow cells for 3 weeks resulted in dose-dependent stimulation of mineralization by BMP-2, but not by bFGF, whose activity was optimal at 2-10 ng/mL. To explore the effect of short-term exposure, bone marrow cells were treated with growth factors for 1 week and subsequent mineralization was investigated. BMP-2 exposure increased the extent of mineralization, but bFGF was not effective after the short exposure. We concluded bFGF was more potent (ie, required lower concentration) for stimulating osteogenic parameters, but BMP-2 effects were lasting on the bone marrow cells.

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)0.011
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.593
Threshold uncertainty score0.653

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
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 head0.063
GPT teacher head0.420
Teacher spread0.357 · 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

Citations63
Published2006
Admission routes1
Has abstractyes

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