Spectrum of chronic lung allograft pathology in a mouse minor-mismatched orthotopic lung transplant model
Bibliographic record
Abstract
Chronic lung allograft dysfunction (CLAD) is a fatal condition that limits survival after lung transplantation (LTx). The pathological hallmark of CLAD is obliterative bronchiolitis (OB). A subset of patients present with a more aggressive CLAD phenotype, called restrictive allograft syndrome (RAS), characterized by lung parenchymal fibrosis (PF). The mouse orthotopic single LTx model has proven relevant to the mechanistic study of allograft injury. The minor-alloantigen-mismatched strain combination using C57BL/10(B10) donors and C57BL/6(B6) recipients reportedly leads to OB. Recognizing that OB severity is a spectrum that may coexist with other pathologies, including PF, we aimed to characterize and quantify pathologic features of CLAD in this model. Left LTx was performed in the following combinations: B10→B6, B6→B10, B6→B6. Four weeks posttransplant, blinded pathologic semi-quantitative assessment showed that OB was present in 66% of B10→B6 and 30% of B6→B10 grafts. Most mice with OB also had PF with a pattern of pleuroparenchymal fibroelastosis, reminiscent of human RAS-related pathology. Grading of pathologic changes demonstrated variable severity of airway fibrosis, PF, acute rejection, vascular fibrosis, and epithelial changes, similar to those seen in human CLAD. These assessments can make the murine LTx model a more useful tool for further mechanistic studies of CLAD pathogenesis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".