Markers of Type 2 Inflammation and Immunosenescence Are Upregulated in Localized Scleroderma
Bibliographic record
Abstract
Localized scleroderma (LS) is an autoimmune, fibrotic skin disease that is thought to be triggered by environmental factors. Recent evidence from systemic autoimmune diseases proposed that the induction of immunosenescence may link environmental triggers with autoimmunity development. We aimed to explore the inflammatory signature in juvenile LS and investigate the presence of DNA instability and immunosenescence using publicly available transcriptomic data. High-throughput RNA sequencing data from 28 juvenile LS and 10 healthy controls were analyzed. Unsupervised clustering, pathway analyses, cell-type enrichment, fusion analyses, and immunosenescence gene set enrichment were performed. IFN and Type 1/2/3 pathways were upregulated in clinically active and histologically inflammatory LS. Type 2 inflammatory signature in both inflammatory and fibrotic LS was demonstrated by enriched genes, pathways, and deconvolution analyses (eosinophils). Features of genotoxic stress signals manifesting as DNA instability genes, pathways, and fusion events as well as mitochondrial dysfunction were demonstrated for the first time in LS. Features of immunosenescence (e.g., the upregulation of pathways involved in T cell exhaustion, inhibitory receptors, and cellular senescence and the enrichment of senescent genes) were also confirmed in (active and inflammatory) LS. Immunosenescence and inflammaging may underlie the complex and heterogeneous nature of immune responses seen in LS and should be further studied.
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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 | 0.001 |
| 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".