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Record W2056084314 · doi:10.1080/08977190903137819

Comparison of platelet-rich plasma, bovine BMP, and rhBMP-4 on bone matrix protein expression<i>in vitro</i>

2009· article· en· W2056084314 on OpenAlexaff
Zhenming Hu, Sean Peel, Stephen Ho, George K.B. Sándor, Cameron M. L. Clokie

Bibliographic record

VenueGrowth Factors · 2009
Typearticle
Languageen
FieldMedicine
TopicPeriodontal Regeneration and Treatments
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsBone sialoproteinOsteopontinBone morphogenetic protein 2Bone morphogenetic proteinChemistryBone morphogenetic protein 7Stromal cellPlatelet-rich plasmaMesenchymal stem cellBone morphogenetic protein 6In vitroGrowth factorType I collagenMolecular biologyAlkaline phosphataseBiologyCell biologyEndocrinologyImmunologyOsteocalcinPlateletBiochemistryCancer researchGene

Abstract

fetched live from OpenAlex

This study investigated the potential use of platelet-rich plasma (PRP) in conjunction with mRNA expression of bone matrix proteins using bioassay and RT-PCR comparing bovine bone morphogenetic proteins (BMP), recombinant human BMP-4 (rhBMP-4) during rat bone marrow stromal cell (Mesenchymal Stem Cell) differentiation at 14 days. The results showed that all three growth factors were associated with significantly elevated alkaline phosphatase activity. PRP and bovine BMP resulted in increased protein content. The mRNA of type I collagen was expressed with all three growth factors and remained consistently elevated. Osteopontin was observed with PRP from days 1 to 7; bone sialoprotein expression was detected on days 1 and 3. PRP, bovine BMP and rhBMP-4 enhanced the steady-state expression of PDGF-A as time-dependent to day 14 and in PRP was the strongest. PTHr was expressed at days 1 and 5. Vascular endothelial growth factor expression was the most highly expressed after day 3. These findings suggest that PRP increases mRNA expression of bone matrix protein, enchances osteogenesis and angiogenesis in vitro.

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)0.000
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 score0.062
Threshold uncertainty score0.551

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.022
GPT teacher head0.305
Teacher spread0.284 · 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

Citations31
Published2009
Admission routes1
Has abstractyes

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