Granzyme B Disrupts Epithelial Barrier Function
Bibliographic record
Abstract
The epithelium functions as a barrier to the external environment, which is maintained in large part by cell junctions. Age‐related and chronic inflammatory conditions of the skin result in a loss of epithelial barrier integrity through the degradation of cell adhesion proteins. Granzyme B (GzmB) is a serine protease that accumulates in the extracellular milieu in a number of autoimmune skin conditions. As such, GzmB may contribute to the progressive loss of epithelial barrier function. We hypothesized that GzmB disrupts epithelial barrier function through the proteolytic cleavage of cell junction proteins. Human keratinocytes were treated with exogenous GzmB, in the presence or absence of a GzmB inhibitor. Subsequently, epithelial barrier function was assessed by Electric Cell‐substrate Impedance Sensing (ECIS) and immunofluorescence (confocal) microscopy was used to visualize E‐cadherin. GzmB treatment resulted in a loss of E‐cadherin staining on the cell membrane which was further supported by western blot analysis of cell supernatants and biochemical cleavage assays, where we observed a dose‐dependent increase in E‐cadherin fragmentation. E‐cadherin cleavage was markedly decreased when treated with a GzmB inhibitor. Moreover, ECIS analysis showed a noticeable decline in barrier function after GzmB treatment. In summary, GzmB contributes to a decline in epithelial barrier function in part through the proteolytic cleavage of E‐cadherin. Support or Funding Information BC Lung Association
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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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".