Gene Therapy, A Targeted Treatment for Diabetic Nephropathy
Bibliographic record
Abstract
Diabetic nephropathy (DN) is a major complication of diabetes and the leading cause of end-stage renal disease (ESRD). Approximately, one third of diabetic patients develop diabetic nephropathy. As diabetes and its associated metabolic diseases are becoming epidemic, DN is emerging as a major health threat to humans. Currently, there are no effective therapeutic treatments for the disease. As a result, most DN cases progress to ESRD; patients with ESRD will need to undergo renal replacement through either dialysis or kidney transplantation. Therefore, developing new and effective means to control DN has been a major focus in the diabetes research. DN is a complex disease with pathological changes occurred in the glomerulus and renal tubules. It is, nonetheless, widely believed that the primary defects lie in the glomeruli, which lead to disrupting the integrity of the glomerular filtration barrier. While a variety of factors contribute to the impairment of glomerular filtration function, a large body of evidence demonstrates that damage in podocytes is the leading cause. Renal fibrosis plays critical roles in promoting DN progression. The primary mechanism responsible for renal fibrosis is abnormal activation of the transforming growth factor (TGF)-β pathway. Based on this understanding of DN pathogenesis, one strategy to control DN is to specifically protect podocytes from diabetes-induced injuries and to inhibit TGF-β signaling using gene therapy methodology. In this review, we will discuss the current research effort in developing gene therapy for DN.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| 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 | 0.000 |
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".