Induction and Coexpression of Latent Transforming Growth Factor β-Binding Protein-1 and Fibrillin-1 in Experimental Glomerulonephritis
Bibliographic record
Abstract
BACKGROUND: Latent transforming growth factor-beta-binding protein 1 (LTBP-1) and fibrillin-1 were shown to colocalize and interact in the extracellular matrix of the skin and vasculature. This interaction may regulate transforming growth factor-beta (TGF-beta) activity. TGF-beta is an important progression factor for glomerular diseases. We hypothesized that LTBP-1 and fibrillin-1 are coexpressed in the glomerulus and upregulated during glomerulonephritis. METHODS: Acute anti-Thy1.1 glomerulonephritis was induced with a single intravenous injection (1 mg/kg body weight) of a monoclonal anti-Thy1.1 antibody in rats. Real-time RT-PCR and immunohistochemical analyses for LTBP-1 and fibrillin-1 were performed. RESULTS: Induction of glomerular LTBP-1 mRNA was detected on day 2 of disease, while mRNA for fibrillin-1 was already upregulated 1 day after induction of disease. Both LTBP-1 and fibrillin-1 showed a mesangial distribution. An expansion of the LTBP-1 and fibrillin-1-positive mesangial area was seen on day 6 of disease, when transient matrix accumulation was most prominent. On day 12 of disease, glomerular LTBP-1 and fibrillin-1 immunoreactivities had returned to control levels. In serial sections, some colocalization of LTBP-1 and fibrillin-1 was detected in control as well as in nephritic glomeruli. CONCLUSION: Mesangial expression of LTBP-1 and fibrillin-1 is induced early in experimental nephritis and LTBP-1 and fibrillin-1 are partially colocalized in the nephritic glomerulus. An interaction of these molecules could stabilize latent TGF-beta complexes and thus attenuate the activation of TGF-beta during this self-limited glomerular disease.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".