Upregulation of α<sub>8</sub>β<sub>1</sub>-integrin in cardiac fibroblast by angiotensin II and transforming growth factor-β1
Bibliographic record
Abstract
Using a novel pharmacological tool with (125)I-echistatin to detect integrins on the cell, we have observed that cardiac fibroblasts harbor five different RGD-binding integrins: alpha(8)beta(1), alpha(3)beta(1), alpha(5)beta(1), alpha(v)beta(1), and alpha(v)beta(3). Stimulation of cardiac fibroblasts by angiotensin II (ANG II) or transforming growth factor-beta1 (TGF-beta1) resulted in an increase of protein and heightening by 50% of the receptor density of alpha(8)beta(1)-integrin. The effect of ANG II was blocked by an AT(1), but not an AT(2), receptor antagonist, or by an anti-TGF-beta1 antibody. ANG II and TGF-beta1 increased fibronectin secretion, smooth muscle alpha-actin synthesis, and formation of actin stress fibers and enhanced attachment of fibroblasts to a fibronectin matrix. The alpha(8)- and beta(1)-subunits were colocalized by immunocytochemistry with vinculin or beta(3)-integrin at focal adhesion sites. These results indicate that alpha(8)beta(1)-integrin is an abundant integrin on rat cardiac fibroblasts. Its positive modulation by ANG II and TGF-beta1 in a myofibroblast-like phenotype suggests the involvement of alpha(8)beta(1)-integrin in extracellular matrix protein deposition and cardiac fibroblast adhesion.
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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 | 0.000 | 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) | 0.001 | 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 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".