Re-evaluation of Fibrogenic Cytokines in Lung Fibrosis
Bibliographic record
Abstract
Idiopathic Pulmonary Fibrosis (IPF) is a chronic interstitial lung disease which results in end-stage fibrosis. The pathogenesis is believed to be related to a dysregulation in cross-talk between inflammatory and structural cells, mediated by various cytokines, chemokines and growth factors, which are responsible for the maintenance of tissue homeostasis and which coordinate the response to injury. The large number of mediators involved and the complexity of their interaction makes it difficult to identify the factors responsible for initiation of fibrogenesis and progression to chronicity. Whether a mediator's presence in fibrotic lung is as a result of tissue injury or if it playsan active role in disease onset and progression has been partly answered by the use of transient and/or permanent transgenic and gene knock-out approaches to over-express single factors at a time. Chemokines such as interleukin-8 (IL-8), RANTES, IP-10, MIG or lymphotactin, do not appear to induce fibrosis when over-expressed in rodent lung. Amongst many tested, four cytokines and growth factors have been found to be pro-fibrotic; IL-1beta, which demonstrates marked inflammation, tissue damage and chronic fibrosis, TNF-alpha, which induces inflammation and mild fibrosis, and GM-CSF, which induces moderate inflammation and fibrosis. A common finding with these cytokines are increased lung TGF-beta levels, proportionate to the degree of fibrosis generated, while TGF-beta itself causes minor inflammation but marked progressive chronic fibrosis. A growth factor 'downstream' from the pro-fibrotic effects of TGF-beta, CTGF, is a likely critical mediator. However, over-expression of CTGF produces only mild and reversible fibrosis.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".