L-selectin and Skin Damage in Systemic Sclerosis
Bibliographic record
Abstract
BACKGROUND: L-selectin ligands are induced on the endothelium of inflammatory sites. L-selectin expression on neutrophils and monocytes may mediate the primary adhesion of these cells at sites of inflammation by mediating the leukocyte-leukocyte interactions that facilitate their recruitment. L-selectin retains functional activity in its soluble form. Levels of soluble L-selectin have been reported as both elevated and lowered in patients with systemic sclerosis (SSc). This preliminary study seeks to discern amongst these disparate results and to discover whether there is an association between L-selectin concentrations in plasma and skin damage in SSc patients. METHODOLOGY AND PRINCIPAL FINDINGS: Nineteen cases with limited systemic sclerosis (lSSc) and 11 cases with diffuse systemic sclerosis (dSSc) were compared on a pairwise basis to age- and sex-matched controls. Criteria of the American College of Rheumatology were used to diagnose SSc. Skin involvement was assessed using the modified Rodnan skin score (mRSS). We find no association between mRSS and plasma L-selectin concentration in lSSc cases (p = 0.9944) but a statistically significant negative correlation in dSSc cases (R(2) = 73.11 per cent, p = 0.0008). The interpretation of the slope for dSSc cases is that for each increase of 100 ng/ml in soluble L-selectin concentration, the mRSS drops 4.22 (95 per cent CI: 2.29, 6.16). There was also a highly statistically significant negative correlation between sL-selectin and disease activity (p = 0.0007) and severity (p = 0.0007) in dSSc cases but not in lSSc cases (p = 0.2596, p = 0.7575, respectively). CONCLUSIONS AND SIGNIFICANCE: No effective treatments exist for skin damage in SSc patients. Nor is there a laboratory alternative to the modified Rodnan skin score as is the case for other organs within the body. Modulation of circulating L-selectin is a promising target for reducing skin damage in dSSc patients. Plasma levels of soluble L-selectin could serve as an outcome measure for dSSc patients in clinical trials.
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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 | 0.001 |
| 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) | 0.002 | 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".