A Dual Zinc plus Arginine formulation protects against tumor necrosis factor-alpha-induced barrier dysfunction and enhances cell proliferation and migration in an in vitro gingival keratinocyte model
Bibliographic record
Abstract
OBJECTIVE: To investigate the effects of Dual Zinc plus Arginine formulations (aqueous solution and dentifrice) on tumor necrosis factor-alpha (TNF-α)-induced barrier dysfunction as well as on cell proliferation and migration in an in vitro gingival keratinocyte model. DESIGN: Gingival keratinocytes were seeded onto the membrane of a double-chamber system in the absence and presence of recombinant TNF-α and the formulations under investigation. The barrier function was assessed by determination of transepithelial electrical resistance (TER) and paracellular transport of fluorescein isothiocyanate (FITC)-dextran. The distribution of zonula occludens-1 (ZO-1) and occludin was visualized by immunofluorescence microscopy. The effects of the formulations on keratinocyte cell proliferation were determined using a fluorescent cell tracker dye, while a migration assay kit was used to investigate their effects on cell migration. RESULTS: Under conditions where TNF-α induces loss of keratinocyte barrier integrity, the Dual Zinc plus Arginine formulations (aqueous solution and dentifrice) protected the keratinocyte tight junction against the damages since they prevented the TNF-α-induced drop in TER and increase in FITC-dextran paracellular flux in the in vitro model. The treatment of keratinocytes with the formulations markedly mitigated the altered distribution of ZO-1 and occludin. Both formulations increased the proliferation of keratinocytes and alleviated the negative impact caused by TNF-α. Lastly, the formulations increased the migration capacity of keratinocytes. CONCLUSIONS: The ability of the Dual Zinc plus Arginine formulations to protect the barrier integrity of gingival keratinocytes from TNF-α-induced damage and to promote their proliferation and migration suggests that they may offer benefits for oral health.
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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 | 0.000 | 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".