Pathogenesis and therapeutic approaches for improved topical treatment in localized scleroderma and systemic sclerosis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
SSc is a chronic progressive disorder of unknown aetiology characterized by excess synthesis and deposition of collagen and other extracellular matrix components in a variety of tissues and organs. Localized scleroderma (LS) differs from SSc in that with LS only skin and occasionally subcutaneous tissues are involved. Although rarely life threatening, LS can be disfiguring and disabling and, consequently, can adversely affect quality of life. There is no known effective treatment for LS, and various options, including, as examples, corticosteroids and other immunomodulatory agents, ultraviolet radiation and vitamin D analogues, are of unproven efficacy. Clinical trials evaluating combination therapy such as corticosteroids with MTX or UVA1 exposure with psoralens have not been established as consistently effective. New immunomodulators such as tacrolimus and thalidomide are also being evaluated. A better understanding of the molecular and cellular mechanisms of LS has led to evaluation of new treatments that modulate profibrotic cytokines such as TGF-beta and IL-4, regulate assembly and deposition of extracellular matrix components, and restore Th1/Th2 immune balance by administering IL-12 or IFN-gamma. IFN-gamma acts by directly inhibiting collagen synthesis and by restoring immune balance. In this review, we evaluate current and future treatment options for LS and cutaneous involvement in SSc. Recent advances in therapy focus mainly on anti-fibrotic agents. Delivery of these drugs into the skin as the target tissue might be a key factor in developing more effective and safer therapy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it