Glucosamine activates the plasminogen activator inhibitor 1 gene promoter through Sp1 DNA binding sites in glomerular mesangial cells.
Bibliographic record
Abstract
Increased flux through the hexosamine biosynthetic pathway is associated with altered gene expression. To investigate the underlying mechanisms, we treated glomerular mesangial cells with glucosamine and studied the regulation of the plasminogen activator inhibitor (PAI)-1 gene. Incubating mesangial cells with 2 mmol/l glucosamine for 4 days resulted in a 3.1+/-0.4-fold increase in PAI-1 mRNA levels (P < 0.01) and a 33+/-9-fold increase in the activity of a transiently transfected PAI-1 promoter-luciferase reporter gene (P < 0.01). Cotransfection of an expression vector for a dominant-negative type II TGF-beta receptor with the PAI-1 promoter-reporter gene did not interfere with this effect of glucosamine. However, mutation of 2 putative Sp1 sites in the PAI-1 promoter, at -76 to -71 and -44 to -39, markedly reduced induction of PAI-1 luciferase activity by glucosamine, from 8.9+/-1.9-fold to 1.7+/-0.5-fold (P < 0.01). An electrophoretic mobility shift assay demonstrated that glucosamine increased Sp1 DNA binding by 31+/-11% (P < 0.05), implying that the effects of glucosamine were explained, in part, by changes in Sp1 DNA binding. High glucose (20 mmol/l) also activated the transiently transfected PAI-1 promoter (2.5+/-0.4-fold). This effect was diminished by mutation of both the PAI-1 promoter Sp1 sites (1.2+/-0.3-fold, P < 0.05). In addition, 6-diazo-5-oxo-L-norleucine, a glutamine:fructose-6-phosphate-amidotransferase inhibitor, blocked the induction by high glucose (4.7+/-0.8- to 0.9+/-0.1-fold, P < 0.01). These results indicate that stimulation of the PAI-1 promoter by both high glucose and glucosamine involves Sp1 and that the hexosamine pathway may be involved in the regulation of gene expression by high glucose in glomerular mesangial cells.
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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 | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".