An SCPPPQ1/LAM332 protein complex enhances the adhesion and migration of oral epithelial cells: Implications for dentogingival regeneration
Bibliographic record
Abstract
Common periodontal disease treatment procedures often fail to restore the structural integrity of the junctional epithelium (JE), the epithelial attachment of the gum to the tooth, leaving the tooth-gum interface prone to bacterial colonization. To address this issue, we introduced a novel bio-inspired protein complex comprised of a proline-rich enamel protein, SCPPPQ1, and laminin 332 (LAM332) to enhance the JE attachment. Using quartz crystal microbalance with dissipation monitoring (QCM-D), we showed that SCPPPQ1 and LAM332 interacted and assembled into a protein complex with high-affinity adsorption of 5.9e−8 [M] for hydroxyapatite (HA), the main component of the mineralized tooth surfaces. We then designed a unique shear device to study the adhesion strength of the oral epithelial cells to HA. The SCPPPQ1/LAM332 complex resulted in a twofold enhancement in adhesion strength of the cells to HA compared to LAM332 (from 31 dyn/cm2 to 63 dyn/cm2). In addition, using a modified wound-healing assay, we showed that gingival epithelial cells demonstrated a significantly high migration rate of 2.7 ± 0.24 µm/min over SCPPPQ1/LAM332-coated surfaces. Our collective data show that this protein complex has the potential to be further developed in designing a bioadhesive to enhance the JE attachment and protect the underlying connective tissue from bacterial invasion. However, its efficacy for wound healing requires further testing in vivo. This work is the first functional study towards understanding the combined role of the enamel protein SCPPPQ1 and laminin 332 (LAM332) in the epithelial attachment of the gum, the junctional epithelium (JE), to the tooth hydroxyapatite surfaces. Such studies are essential for developing therapeutic approaches to restore the integrity of the JE in the destructive form of gum infection. We have developed a model system that provided the first evidence of the strong interaction between SCPPPQ1 and LAM332 on hydroxyapatite surfaces that favored protein adsorption and subsequently oral epithelial cell attachment and migration. Our collective data strongly suggested using the SCPPPQ1/LAM332 complex to accelerate the reestablishment of the JE after surgical gum removal to facilitate gum regeneration.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".