Kalpaamruthaa modulates oxidative stress in cardiovascular complication associated with type 2 diabetes mellitus through PKC-β/Akt signaling
Bibliographic record
Abstract
This study aimed at investigating the efficacy of Kalpaamruthaa (KA) on cardiovascular damage (CVD) associated with type 2 diabetes mellitus in experimental rats by reducing oxidative stress and the modulation of the protein kinase C-β (PKC-β)/Akt signaling pathway. CVD-induced rats were treated with KA (200 mg·(kg body mass)(-1)·(day)(-1)) orally for 4 weeks. KA effectively reduced insulin resistance with alterations in blood glucose, hemoglobin, and glycosylated hemoglobin in CVD-induced rats. Elevated levels of lipids in CVD-induced rats were decreased upon KA administration. In CVD-induced rats the levels of lipoproteins were returned to normal by KA treatment. KA effectively reduced the lipid peroxidative product and protein carbonyl content in liver of CVD-induced rats. KA increased the activities and (or) levels of enzymatic and nonenzymatic antioxidants in liver of CVD-induced rats. KA treatment reduced the fatty inclusion and mast cell infiltration in liver of CVD-induced rats. Further, treatment with KA reduced the chromatin condensation and marginization in myocardium of CVD-induced rats. KA alters insulin signaling by decreasing PKC-β and increasing p-Akt and GLUT4 expressions in heart of CVD-induced rats. The above findings suggest that KA renders protection against CVD induced by type 2 diabetes mellitus by augmenting the cellular antioxidant defense capacity and modulating PKC-β and the p-Akt signaling pathway.
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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".