SPARC/SFN interaction, suppresses type I collagen in dermal fibroblasts
Bibliographic record
Abstract
We previously suggested that keratinocyte releasable factors might modulate the wound healing process by regulating the expression of key extracellular matrix components such as collagenase (matrix metalloproteinase-1) and type I collagen in fibroblasts. The first one, we called it keratinocyte-derived anti-fibrogenic factor (KDAF), identified as stratifin (SFN) also named 14-3-3σ, revealing a strong collagenase activity. However, the second factor, which we named keratinocyte-derived collagen-inhibiting factor(s) (KD-CIF) that has shown to control the synthesis of type I collagen, was not known. Upon conducting a series of systematic protein purification methods followed by mass spectroscopy, two proteins: secreted protein acidic rich in cystein (SPARC) and SFN were identified in keratinocyte-conditioned media. Using co-immunoprecipitation and 3D modeling, we determined that SFN and SPARC form a complex thereby controlling the type I collagen synthesis and expression in fibroblasts. The levels of these proteins in fibrotic tissues (animal and human) were also evaluated and a differential expression of these proteins between normal and fibrotic tissue confirmed their potential role in development of fibrotic condition. In conclusion, this study describes for the first time an interaction between SPARC and SFN that may have implications for the regulation of matrix deposition and prevention of dermal fibrotic conditions such as hypertrophic scars and keloid.
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.
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 | 0.000 | 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".