The fibrotic phenotype of systemic sclerosis fibroblasts varies with disease duration and severity of skin involvement: reconstitution of skin fibrosis development using a tissue engineering approach
Bibliographic record
Abstract
We set out to examine the pathophysiological mechanisms of fibrosis in diffuse systemic sclerosis (SSc) using a tissue engineering approach. Skin fibroblasts were isolated from lesional skin of SSc patients with a disease duration of less than 1 year (early-stage SSc) or more than 10 years (late-stage SSc). Fibroblasts were also isolated from non-lesional skin and compared with normal fibroblasts isolated from healthy adults. Cells were cultured using a tissue engineering method to reconstruct a human dermis, and histologically observed. Dermal thickness was measured, as it reflects the global and intrinsic capacity of cells to reconstitute matrix. Collagen I, MMP-1, and MMP activity were evaluated. Cells were treated with TGFbeta1 or CTGF during dermis formation to study their fibrogenic role. Clinical severity of skin involvement was measured by a modified Rodnan score. Thickness of the dermis generated with non-lesional early-stage SSc fibroblasts was similar to normal cells. In contrast, reconstructed dermis from lesional early-stage SSc fibroblasts and non-lesional late-stage SSc cells was thinner, while lesional late-stage SSc fibroblasts made a thicker dermis. Dermis was always thicker when produced with TGFbeta1-treated cells, except when lesional late-stage SSc fibroblasts from patients with high Rodnan skin scores were used. CTGF did not affect dermal thickness. Measurements of collagen I and collagenases in the culture medium of the various reconstructed dermis could explain some of the changes observed. We conclude that the fibrotic phenotype of SSc fibroblasts varies with disease duration and with severity of skin involvement, and this is clearly visualized during in vitro dermis reconstruction.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".