Getting Out of a Sticky Situation: Targeting the Myofibroblast in Scleroderma
Bibliographic record
Abstract
There is no treatment for the fibrosis observed in scleroderma (systemic sclerosis, SSc). Although genome-wide expression profiling has suggested that differences in gene expression patters between non-lesional and lesional skin are minimal, phenotypically these areas of tissue are quite different. In fact, lesional areas of scleroderma patients can be distinguished by the presence of a differentiated form of fibroblast, termed the myofibroblast. This cell type expresses the highly contractile protein α-smooth muscle actin (α-SMA). Fibroblasts isolated from SSc lesions excessively synthesize, adhere to and contract extracellular matrix (ECM) and display activated adhesive signaling pathways. Strategies aimed at blocking myofibroblast differentiation, persistence and activity are therefore likely to be useful in alleviating the fibrosis in scleroderma.
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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 | 0.001 | 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".