Hyperhexosemia Induced Functional and Structural Changes in the Kidneys: Role of Endothelins
Bibliographic record
Abstract
BACKGROUND/AIMS: Glomerular basement membrane (GBM) thickening and mesangial matrix expansion are characteristic features of diabetic nephropathy. The present study investigates the role of endothelins (ETs) in the pathogenesis of such changes in diabetic nephropathy. METHODS: Diabetic (streptozotocin-induced, 65 mg/kg), galactose-fed (30%) and control animals were followed up for 1 and 6 months. Animal groups also included diabetic and galactose fed animals on dual ET(A)/ET(B) receptor antagonist bosentan (100 mg/kg). A semi-quantitative reverse transcription polymerase chain reaction method was used to quantify mRNA expression of ET-1, ET-3, ET(A), ET(B), fibronectin and collagen alpha2(IV). Histological analyses of the kidneys and ET-1, ET-3 and fibronectin immunohistochemistry were performed. Morphometric assessment of the GBM after 6 months was performed. RESULTS: Diabetes increased mRNA expression of ET-1, ET-3, ET(A), ET(B), fibronectin and collagen alpha2(IV) after one and six months. In contrast, although increased ET(A) and ET(B) mRNAs were present following galactose feeding both at 1 and 6 months, ET-1, ET-3, fibronectin and collagen alpha2(IV)mRNAs were increased after 6 months. Both diabetes and galactose feeding caused increased GBM thickening. Furthermore, diabetes caused an increase in mesangial matrix production. Bosentan prevented increased fibronectin and collagen alpha2(IV) mRNA expression, increased mesangial matrix deposition and GBM thickening. CONCLUSION: This study has demonstrated that diabetes and galactose feeding induced functional and structural changes in the kidney are mediated via ETs.
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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 | 0.001 |
| 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".