Modulators of Alpha-2 Macroglobulin Upregulation by High Glucose in Glomerular Mesangial Cells
Bibliographic record
Abstract
Up to 40% of patients with diabetes mellitus will develop diabetic kidney disease (DKD), characterized pathologically by the accumulation of extracellular matrix proteins, which leads to the loss of kidney function over time. Our previous studies showed that the pan-protease inhibitor alpha 2-macroglobulin (A2M) is increased in DKD and is a critical regulator of the fibrotic response in glomerular mesangial cells (MC), an initial site of injury during DKD development. How A2M is regulated by high glucose (HG) has not yet been elucidated and is the focus of this investigation. Using serial deletions of the full A2M promoter, we identified the -405 bp region as HG-responsive in MC. Site-directed mutagenesis, siRNA, and ChIP studies showed that the transcription factor, nuclear factor of activated T cells 5 (NFAT5), regulated A2M promoter activity and protein expression in response to HG. Forkhead box P1 (FOXP1) served as a cooperative binding partner for NFAT5, required for A2M upregulation. Lastly, we showed that Smad3, known for its role in kidney fibrosis, regulated A2M promoter activity and protein production independently of HG. The importance of NFAT5, FOXP1, and Smad3 in A2M regulation was confirmed in ex vivo studies using isolated glomeruli. In conclusion, Smad3 is required for basal and HG-induced A2M expression, while NFAT5 and FOXP1 cooperatively regulate increased A2M transcription in response to HG. Inhibition of NFAT5/FOXP1 will be further evaluated as a potential therapeutic strategy to inhibit A2M production and attenuate profibrotic signaling in DKD.
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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".