Identification of extracellular vesicle proteins in circulating exosomes from human lung transplant recipients
Bibliographic record
Abstract
Abstract Molecular mechanisms involved in rejection following human lung transplantation (LTx) are not well understood. We identified proteomic signatures of clinical outcomes in circulating extracellular vesicles (EVs) isolated from human lung transplant recipients (LTxRs) who was diagnosed with chronic rejection (Bronchiolitis Obliterans Syndrome (BOS)), acute rejection (AR), respiratory viral infection requiring intervention (RVI) or stable following transplantation. Differential analysis revealed one protein unique to AR (Skin-specific protein 32), four unique to RVI (Guanine nucleotide-binding protein G(I)/G(S)/G(T) subunit beta-2, Transmembrane 9 superfamily member 2, Ras-related C3 botulinum toxin substrate 2, and EH domain-containing protein) and two unique to stable (Coagulation factor X, and N-acetylmuramoyl-L-alanine amidase). Comparison of each rejection group to stable identified 128, 180, and 216 significantly differentially expressed proteins (p-value<0.05, fold-change>2) in BOS, AR, and RVI respectively. Although no unique signatures were found in BOS, an increased enrichment of immune processes such as antigen processing and presentation of exogenous peptide antigen via MHC class I and Fc receptor signaling pathway were observed. Functional enrichment analysis (Gene Ontology) associated differentially expressed EV proteins in AR and RVI conditions with wound repair processes. These diverse signatures detected in each condition highlight complex immune mechanisms underlying the pathophysiology of rejection following LTx. Future studies are needed to validate these signatures in larger LTxR cohorts in order to promote early clinical diagnosis and predict outcome.
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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 | 0.000 |
| 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".