XB130 Deficiency Affects Tracheal Epithelial Differentiation during Airway Repair
Bibliographic record
Abstract
The repair and regeneration of airway epithelium is important for maintaining homeostasis of the respiratory system. XB130 is an adaptor protein involved in the regulation of cell proliferation, survival and migration. In the human trachea, XB130 is expressed on the apical site of ciliated epithelial cells. We hypothesize that XB130 may play a role in epithelial repair and regeneration after injury. Xb130 knockout (KO) mice were generated, and a mouse isogenic tracheal transplantation model was used. Adult Xb130 KO mice did not show any significant anatomical and physiological phenotypes in comparison with their wild type (WT) littermates. The tracheal epithelium in Xb130 KO mice, however, was significantly thicker than that in WT mice. Severe ischemic epithelial injury was observed immediately after the tracheal transplantation, which was followed by epithelial cell flattening, proliferation and differentiation. No significant differences were observed in terms of initial airway injury and apoptosis. However, at Day 10 after transplantation, the epithelial layer was significantly thicker in Xb130 KO mice, and associated with greater proliferative (Ki67+) and basal (CK5+) cells, as well as thickening of the connective tissue and fibroblast layer between the epithelium and tracheal cartilages. These results suggest that XB130 is involved in the regulation of airway epithelial differentiation, especially during airway repair after injury.
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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 | 0.001 |
| 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 | 0.000 |
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".