HLA-G Expression in the Skin of Patients with Systemic Sclerosis
Bibliographic record
Abstract
OBJECTIVE: To determine HLA-G expression in skin biopsies from patients with systemic sclerosis (SSc), and its association with epidemiological, clinical, and laboratory variables and survival. METHODS: Paraffin-embedded skin biopsies obtained from 21 SSc patients (14 limited SSc, 7 diffuse SSc) and from 28 healthy controls were studied. HLA-G expression was evaluated by immunohistochemistry. RESULTS: HLA-G molecules were detected in 57% of skin biopsies from patients with SSc (9 from limited SSc, 3 from diffuse SSc), whereas no control sample expressed HLA-G (p=0.000004). In patients, HLA-G molecules were consistently observed within epidermal and some dermal cells. HLA-G expression was associated with a lower frequency of vascular cutaneous ulcers (p=0.0004), telangiectasias (p=0.008), and inflammatory polyarthralgia (p=0.02). After a 15-year followup, SSc patients who exhibited HLA-G survived longer than patients who did not. CONCLUSION: HLA-G is expressed in skin biopsies from patients with SSc, and this is associated with a better disease prognosis. This suggests a modulatory role of HLA-G in SSc, as observed in other skin disorders.
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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 | 0.001 |
| 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".