Airway epithelial wound repair: role of carbohydrate sialyl Lewis<sup>x</sup>
Bibliographic record
Abstract
Epithelial repair is a complex cellular and molecular process, the details of which are still not clearly understood. Plasma membrane glycoconjugates can modulate cell function by altering the function of protein and lipids. Sialyl Lewisx (sLex), a fucose-containing tetrasaccharide, decorates membrane-bound and secreted proteins and mediates cell-cell interaction. In the present study we investigated the role of sLex in airway epithelial repair. Using immunohistochemistry, we showed an increased expression of sLex in areas of damaged bronchial epithelium compared with intact regions. Confluent monolayers of airway epithelial cells were mechanically wounded and allowed to close. Wounded monolayers were photographed for wound closure kinetics, fixed for immunocytochemical studies, or subjected to RNA extraction. Examining the expression of different alpha1,3-fucosyltransferases (FucT), enzymes that mediate the final step in the synthesis of sLex, we found that FucT-IV was the common gene expressed in all cell lines and primary airway epithelial cells. We demonstrated an increased expression of sLex over time after mechanical injury. Blocking of sLex with an inhibitory antibody completely prevented epithelial repair. Our data suggest an essential functional role for sLex in epithelial repair. Further studies are necessary to explore the exact mechanism for sLex in mediating cell-cell interaction in bronchial epithelial cells to facilitate epithelial migration and repair.
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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".