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Record W2047356004 · doi:10.3109/08977194.2013.830611

GDFs promote tenogenic characteristics on human periodontal ligament-derived cells in culture at late passages

2013· article· en· W2047356004 on OpenAlexaff
Dengsheng Xia, Yoshinori Sumita, Younan Liu, Yunlin Tai, Jinsong Wang, Masataka Uehara, Hideki Agata, Hideaki Kagami, Zhipeng Fan, Izumi Asahina, Songlin Wang, Simon D. Tran

Bibliographic record

VenueGrowth Factors · 2013
Typearticle
Languageen
FieldMedicine
TopicTendon Structure and Treatment
Canadian institutionsMcGill University
Fundersnot available
KeywordsPeriodontal fiberCell biologyMesenchymal stem cellGrowth differentiation factorLigamentTendonCementogenesisAnatomyChemistryBone morphogenetic proteinBiologyDentistryMedicineGeneDentin

Abstract

fetched live from OpenAlex

Tendon/ligament injures are leading disabilities worldwide. The periodontal ligament (PDL) connects teeth to bone, and is comparable to a tendon/ligament-to-bone insertion. PDL-derived cells (PDLCs) express both osteo/cementogenesis and teno/ligamentogenesis genes. However, an efficient method to induce a tenogenic differentiation of PDLCs has not been thoroughly examined. Therefore, this study tested if growth/differentiation factors (GDFs) enhanced tenogenic characteristics of human PDLCs, as a potential cell source for tendon/ligament engineering. Results demonstrated recombinant GDF-5/GDF-7 inhibited alkaline phosphatase (ALP) activity of PDLCs from passage 3 to 6, while GDF-5 enhanced ALP in dental pulp-derived cells and mesenchymal stem cells. GDF-5 (particularly at 10 ng/ml concentration) induced high expression of both early (scleraxis) and mature (tenomodulin, aggrecan, collagen3) tenogenic genes in P4-6 PDLCs, while inhibiting expression of specific transcription-factors for osteogenic, chondrogenic and adipogenic differentiation. Exogenous GDFs might lead PDLCs being expanded in culture during several passages to highly useful cell source for tendon/ligament engineering.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.446
Threshold uncertainty score0.903

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)0.0010.000

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 head0.017
GPT teacher head0.251
Teacher spread0.234 · 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 designObservational
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

Citations13
Published2013
Admission routes1
Has abstractyes

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