Preventive effects of benfotiamine in chronic diabetic complications
Bibliographic record
Abstract
UNLABELLED: Aims/Introduction: In diabetes, increased oxidative stress as a result of damage to the electron transport chain can lead to tissue injury through upregulation of multiple vasoactive factors and extracellular matrix proteins. Benfotiamine, a lipid soluble thiamine derivative, through reducing mitochondrial superoxide production, blocks multiple pathways leading to tissue damage in hyperglycemia. We investigated if treatment with benfotiamine can prevent diabetes-induced production of vasoactive factors and extracellular matrix proteins, and whether such effects are tissue-specific. We also examined whether effects of benfotiamine are mediated through a nuclear mechanism. MATERIALS AND METHODS: Retinal, renal and cardiac tissues from the streptozotocin-induced diabetic rats were examined after 4 months of follow up. mRNA levels were quantified using real-time RT-PCR. Protein levels were quantified using western blot and ELISA. Cellular expressions of 8-Hydroxy-2'-deoxyguanosine, a marker of nuclear DNA damage and Phospho-H2AX were also examined. RESULTS: Diabetic animals showed hyperglycemia, glucosuria, increased urinary albumin/creatine ratio and loss of bodyweight. In the kidneys, heart and retina, diabetes caused increased production of endothelin-1, transforming growth factor-β1, vascular endothelial growth factor and augmented extracellular matrix proteins (collagen, fibronectin [FN] and its splice variant extradomain B containing FN), along with evidence of structural alterations, characteristic of diabetes-induced tissue damage. Such changes were prevented by benfotiamine. Furthermore, benfotiamine prevented diabetes-induced oxidative DNA damage and upregulation of p300, a histone acetylator and a transcription coactivator. CONCLUSIONS: Data from the present study suggest that benfotiamine is effective in preventing tissue damage in diabetes and at the transcriptional level such effects are mediated through prevention of p300 upregulation. (J Diabetes Invest, doi: 10.1111/j.2040-1124.2010.00077.x, 2010).
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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 | 0.001 |
| 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) | 0.000 | 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".