Noninvasive Measurement of Skin Autofluorescence Is Increased in Patients with Systemic Sclerosis: An Indicator of Increased Advanced Glycation Endproducts?
Bibliographic record
Abstract
OBJECTIVE: Skin autofluorescence noninvasively assesses expression of advanced glycation endproducts and therefore potentially the presence of oxidative stress that is implicated in the pathogenesis of systemic sclerosis (SSc). We investigated whether autofluorescence was increased in patients with SSc, primary Raynaud's phenomenon (RP), and morphea as compared to healthy controls. METHODS: Measurements of autofluorescence were made at 5 upper limb sites in 16 healthy controls, 16 patients with diffuse cutaneous SSc (dcSSc), 15 with limited cutaneous SSc (lcSSc), 15 with primary RP, and 13 with morphea. For patients with morphea, additional measurements were made at the affected and an adjacent unaffected site. RESULTS: Autofluorescence was significantly increased in patients with dcSSc but not lcSSc as compared to controls at the proximal phalanx [dcSSc median 0.15, interquartile range (IQR) 0.10-0.24, vs control 0.10, IQR 0.07-0.13; p = 0.014], dorsum of the hand (dcSSc 0.17, IQR 0.11-0.36, vs control 0.12, IQR 0.09-0.17; p = 0.031), the wrist (dcSSc 0.22, IQR 0.13-0.33, vs control 0.13, IQR 0.09-0.18; p = 0.005), and forearm (dcSSc 0.19, IQR 0.12-0.47, vs control 0.14, IQR 0.10-0.16; p = 0.022). There was a trend for autofluorescence to be increased in patients with lcSSc and at morphea sites, compared to noninvolved skin. CONCLUSION: Autofluorescence is increased in patients with dcSSc compared to primary RP and to healthy controls. This suggests increased oxidative stress and the potential for autofluorescence as a biomarker.
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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 | 0.001 | 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".