Mannose-6-Phosphate/IGF-II Receptors Mediate the Effects of IGF-1-Induced Latent Transforming Growth Factor β1 on Expression of Type I Collagen and Collagenase in Dermal Fibroblasts
Bibliographic record
Abstract
We have previously shown that insulin-like growth factor-1 (IGF-1) induces the expression of latent transforming growth factor beta 1 (LTGF-beta 1) through activation of c-fos and c-jun oncogenes. In this study we investigated whether IGF-1 induced latent TGF-beta 1 has autocrine effects on dermal fibroblasts and described a possible mechanism. Human dermal fibroblasts were treated with either vehicle, IGF-1 alone, or IGF-1 with either anti-TGF-beta 1 neutralizing antibody or mannose-6-phosphate (M6P) and levels of mRNAs for TGF-beta 1, collagenase and the pro alpha 1(I) chain of type I collagen were then evaluated by Northern analysis. Conditioned medium was also collected from treated and untreated cells and assayed for TGF-beta 1 protein by enzyme-linked immunosorbent assay. The results of the Northern analysis revealed a differential effect on the expression of the pro alpha 1(I) chain of type I collagen and collagenase in dermal fibroblasts: mRNA for the former being significantly increased in response to IGF-1 treatment while that for collagenase was markedly suppressed. These effects of IGF-1 were blocked to a significant extent by TGF-beta 1 neutralizing antibody at a concentration of 0.5-2.0 micrograms/ml. As the TGF-beta 1 induced by IGF-1 is inactive in the traditionally used mink lung epithelial cell growth inhibition assay, we explored the possible role of IGF-II/M6P receptors in facilitating these autocrine effects. The results showed that the greater than two-fold increase (201.9 +/- 38 vs 81.8 +/- 13, p < 0.05) in mRNA for the pro alpha 1(I) chain of type I collagen induced by IGF-1 was at least 60% inhibited by M6P in a time-dependent fashion. A direct correlation between the expression of TGF-beta 1 and the pro alpha 1(I) chain of type I collagen was found in response to either IGF-1 alone or IGF-1 with M6P. Treatment of cell cultures with TGF-beta 1 neutralizing antibody mimicked the effect of M6P. In contrast to the effects on expression of type I collagen, the level of collagenase mRNA was markedly reduced by IGF-1 alone and was restored by the administration of M6P. The levels of TGF-beta 1 in conditioned medium from treated and untreated cells showed a similar pattern to that of the mRNA detected by Northern analysis. These findings suggest that IGF-1 induces latent TGF-beta 1 and that the matrix-modulating autocrine effects of LTGF-beta 1 on dermal fibroblasts are facilitated by M6P/IGF-II receptors on these cells.
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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 | 0.000 | 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".