<I>In vitro</I> Peroxisome Proliferator-Activated Receptors α and γ Ativation Effects of Iridoids and Lignans Isolated from the Leaves of <I>Nephrolepis exaltata</I> L. (Nephrolepidaceae)
Bibliographic record
Abstract
Peroxisome proliferator-activated receptor-γ (PPARγ) is the drug target for certain antidiabetic agents. While peroxisome proliferator-activated receptor-α (PPARα) is targeted by lipid lowering agents. Compounds with double activation on PPARα/γ are major components in prevention of progression of renal damage. The aim of the study is to evaluate the in vitro PPARα/γ activation effects of iridoids and lignans isolated from the leaves of Nephrolepis exaltata L. (Nephrolepidaceae). Phytochemical investigation of the ethanol extract of Nephrolepis exaltata resulted in the isolation of megastigmens, lignans and iridoids and their structures elucidated. The effect of the isolated compounds on PPAR-α and PPAR-γ in human hepatoma (HepG2) cells were investigated via reporter gene assays using a 96-well tissue culture plate were transfected with cells at a density of 5 × 104 cells/well and grown for 24 h. Each cell were treated with plant extract (25, 50 and 100 μg/mL), the isolated compounds, ciprofibrate (10 µM) for PPARα or rosiglitazone (10 µM) for PPARγ assay. The luciferase activity was measured using a luciferase assay system. Compounds isolated from the leaves of N. exaltata dehydrovomifoliol (1), Dehydrololiolide (2), methoxygaertneroside (3), pinoresinol 4′-O-β-D-glucopyranoside (4) glochidiobioside (5), have double activities on PPARα/γ with a fold induction of more than 2.0 over the control. The compounds were non-cytotoxic to HepG2 cells as the cell viability for all the compound remained greater than 80%. Compounds isolated from the leaves of ethanol extract of N. exaltata has dual PPARα and γ indicating their potential to maintain the integrity of the kidney.
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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) | 0.002 | 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".