MétaCan
Menu
Back to cohort
Record W4406062784 · doi:10.1016/j.matbio.2024.12.011

FGF and TGF-β growth factor isoform modulation of human gingival and periodontal ligament fibroblast wound healing phenotype

2025· article· en· W4406062784 on OpenAlexafffund
Chengyu Guo, Amin S. Rizkalla, Douglas W. Hamilton

Bibliographic record

VenueMatrix Biology · 2025
Typearticle
Languageen
FieldMedicine
TopicPeriodontal Regeneration and Treatments
Canadian institutionsWestern University
FundersCanadian Institutes of Health Research
KeywordsPeriodontal fiberFibroblast growth factorWound healingTransforming growth factorPhenotypeGene isoformFibroblastMedicineGrowth factorDentistryInternal medicineChemistryImmunologyGeneIn vitroReceptorBiochemistry

Abstract

fetched live from OpenAlex

• Local growth factor delivery is a viable option to change the microenvironment of the periodontium to facilitate repair. • FGF family members increased migration, while TGF-β isoforms increased α-SMA expression and matrix production. • Based on Effects, we investigated the combined effect of TGF-β3 and FGF-2 on gingival and periodontal ligament fibroblasts. • Combinatory treatment with TGF-β3+FGF-2 enhanced migration and fibronectin levels in both gingival and periodontal ligament fibroblasts. • TGF-β3+FGF-2 regulate cell phenotype simultaneously through distinct p-SMAD2/3 and p-ERK pathways. • Soft tissue healing could be enhanced with local delivery of TGF-β3+FGF-2 Release of growth factors in the tissue microenvironment is a critical process in the repair and regeneration of periodontal tissues, regulating fibroblast behavior and phenotype. As a result of the complex architecture of the periodontium, distinct fibroblast populations in the periodontal ligament and gingival connective tissue exist in close proximity. Growth factor therapies for periodontal regeneration have gained traction, but quantification of their effects on multiple different fibroblast populations that are required for repair has been poorly investigated. In this study, we examined the effects of TGF-β1, TGF-β3, FGF-2, and FGF-9 on human gingival fibroblasts (hGF) and human periodontal ligament cells (hPDL), as well as the combined effects of TGF-β3 and FGF-2. We show that FGF-2 enhances cell migration while TGF-β1 and TGF-β3 promotes matrix production, and TGF-β1 promotes fibroblast to myofibroblast transition. Interestingly, the combination of TGF-β3 and FGF-2, acting through both p-SMAD3 and p-ERK pathways, mitigates the inhibitory effects of TGF-β3 on migration in hPDL cells, suggesting synegystic and complimentary effects of FGF-2 and TGF-β3. Additionally, fibronectin production in hGF increased when treated with the combined TGF-β3+FGF-2 compared to FGF-2 alone, indicating that the effects of TGF-β3 in promoting extracellular matrix production are still active in the combined treatment condition. Finally, our study highlights that FGF-9 did not influence migration, α-SMA expression, or extracellular matrix production in either cell type, emphasizing the unique roles of specific growth factors in cellular responses. The synergistic effects observed with combined TGF-β3 and FGF-2 treatments present promising avenues for further research and clinical advancements in regenerative medicine.

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 score0.591
Threshold uncertainty score0.331

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 head0.016
GPT teacher head0.316
Teacher spread0.301 · 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

Citations15
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueMatrix BiologySame topicPeriodontal Regeneration and TreatmentsFrench-language works237,207