Cellular dynamics and signalling mechanisms in dentine repair: A narrative review
Bibliographic record
Abstract
BACKGROUND: Bioactive molecules have gained significant attention in regenerative medicine due to their ability to boost the reparative properties of stem cells, including those in the dental pulp. This narrative review aims to deepen our understanding of the dynamics of bioactive molecules in the dental pulp and their role in enhancing hard tissue reparative processes. OBJECTIVES: (i) To discuss the role of different cells and the critical pathways involved in dentine formation through direct (reparative) or indirect (infection control and immunomodulatory) mechanisms. (ii) To highlight how innovative therapeutic strategies could be employed to target key molecules for successful dentine repair and regeneration. METHODS: The review encompassed all years up to the search period. Databases such as PubMed, Scopus and Medline were utilized to gather relevant studies. The search strategy involved specific signalling molecules such as Transforming growth factor-β1 (TGF-β), Bone Morphogenetic Proteins (BMP), Small Integrin Binding Ligand N-linked Glycoproteins (SIBLING) and growth factors. Cell types including odontoblasts, fibroblasts, immune cells and dental pulp stem cells (DPSCs) were of interest. Additionally, signalling pathways like Wnt, Notch, Shh, amongst others, were investigated for their roles in repair mechanisms. Key terms were combined using Boolean operators [Cell type] AND [signalling molecules] AND/OR [dentine], [Cell type] AND/OR [signalling pathways] AND/OR [dentine] to include studies addressing the interaction of these components in enhancing repair processes. DISCUSSION: Key molecules such as TGF-β1, BMP and SIBLING proteins effectively enhance the dentine reparative response, whilst other molecules such as complement proteins and antimicrobial peptides primarily activate immune cells and facilitate pathogen clearance to promote the regenerative capabilities of DPSCs. This well-orchestrated interaction emphasizes the need to investigate the effects of these molecules on all cells within the dental pulp. Morphogenic signalling molecules such as BMP-2, -4 and -7, and Wnt show temporal, yet significant regenerative properties, whilst Shh and Notch present inconsistent effects on dentine regeneration, and a consensus on their roles and properties in dentine repair has yet to be reached. CONCLUSIONS: This review highlights the critical role of bioactive molecules in dentine repair to guide the development of next-generation bioinspired therapeutics for vital pulp therapy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".