Transcriptomic profiling of CD4 lymphocytes in a murine model of AdTGFß-1 induced lung fibrosis
Bibliographic record
Abstract
Idiopathic pulmonary fibrosis (IPF) is a severe diffuse parenchymal lung disease (DPLD) associated with high mortality. Patients with IPF frequently demonstrate lymphoplasmacellular infiltrates within the lung peribronchovascular compartment but its pathogenetic significance is currently unclear. Therefore, we aimed at deciphering the role of CD4pos T cells in a mouse model of pulmonary fibrosis induced by adenoviral delivery of biologically active transforming growth factor β1 (AdTGF-β1). Exposure of mice to AdTGF-β1 triggered significant recruitment of T cells into the bronchoalveolar space and lung parenchymal tissue, with peak values observed on days 14 and 21 post-exposure, relative to control vector exposed mice. Transcriptomic profiling of flow-sorted CD4pos T cells collected from mice with established lung fibrosis revealed a total of 3,143 differentially expressed genes (DEGs) on day 14, and a total of 1,840 DEGs on day 21. Assigning DEGs to Gene Ontology terms revealed significant enrichment of DEGs in T helper cell immune response/ T cell differentiation. B cell homeostasis genes were found to be expressed on day 14 post-treatment, while on day 21 post-treatment, strongest enrichment of DEGs was observed in B cell apoptosis-related processes. Together, the current data show that lymphocyte subset mobilization coincides with developing fibrosis in mice and suggest complex lymphocyte subset regulatory networks underlie pulmonary fibrogenesis.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".