Loss of claudin‐1 in lipopolysaccharide‐treated periodontal epithelium
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: The epithelial barrier is a critical component of innate immunity and provides protection against microbial invasion. Claudin-1, a tight junction protein, is known to contribute to the epithelial cell barrier. An experimentally induced rat periodontal disease model was used to study the effects of lipopolysaccharide (LPS) on the expression of tight junction-associated molecule genes in the junctional epithelium. MATERIAL AND METHODS: LPS was applied for 8 wk in the gingival sulcus, and junctional epithelium was collected by laser-capture microdissection and subjected to microarray analysis. RESULTS: Microarray analysis identified that expression of the claudin-1 gene was decreased in the epithelium by chronic LPS challenge. Immunohistochemical analysis confirmed the expression of claudin-1 protein in junctional epithelium and that 8 wk of chronic LPS topical application significantly reduced claudin-1 expression. The effect of LPS on claudin-1 protein expression was validated using a porcine junctional epithelial cell culture Transwell model. The epithelial barrier, as measured using transmembrane resistance, was significantly reduced after 3 wk of LPS challenge and this was associated with a decreased level of expression of claudin-1 protein. CONCLUSION: These results confirm that the initiation of experimental periodontal disease is associated with reduction in the expression of claudin-1 gene and protein. This decreased level of a critical tight junction protein may result in the disruption of barrier function and may play an important role in the initiation of periodontal disease.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".