Role of Fetuin-A in Systemic Sclerosis-associated Calcinosis
Bibliographic record
Abstract
To the Editor: Calcinosis, a soft-tissue calcification occurring in the setting of normal serum calcium and phosphate levels, has been observed in connective tissue diseases, including systemic sclerosis (SSc)1, more frequently in the limited form (lcSSc) and in patients who are anticentromere antibody (ACA)-positive1. Calcinosis may be exceedingly painful and cause major clinical problems, including ulceration, infection, and joint contractures1. Hypovascularity, hypoxia, and tissue damage seem to favor its development, with genetic factors also playing a role. No treatment exists so far, and even surgical removal is unsatisfactory, since recurrences are common1. Fetuin-A (α-2-Heremans-Schmid glycoprotein, AHSG) is a major inhibitor of systemic calcification, and low serum levels have been associated with vascular and soft-tissue calcifications2. Any situation that lowers serum fetuin-A, including inflammatory conditions, could increase the risk of calcification, because fetuin-A is a negative acute-phase protein. AHSG gene variations seem to influence fetuin-A serum concentration3. Forty-one consecutive Italian patients with SSc [40 women, age 63 ± 13 years, 16 diffuse SSc (dcSSc), 25 lcSSc] were … Address correspondence to Dr. L. Belloli, Via Manzoni 56, Rozzano 20089, Italy. E-mail: laurabelloli{at}tiscali.it
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".