Phytochemical Analysis and Evaluation of Biological Activity of Lawsonia inermis Seeds Related to Alzheimer’s Disease
Bibliographic record
Abstract
Using Lawsonia inermis L. (henna) seeds has been frequently recommended for the improvement of memory in Iranian Traditional Medicine (ITM). In this respect, different fractions of the plant were prepared and evaluated for their in vitro biological assays related to Alzheimer’s disease (AD), including acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) inhibitory activity as well as metal chelating ability and DPPH antioxidant activity. The dichloromethane and ethyl acetate fractions were able to inhibit the BChE selectively with IC50 values of 113.47 and 124.90 μg/mL, respectively, compared with donepezil as the reference drug (IC50 = 1.52 μg/mL). However, all fractions were inactive toward AChE. Phytochemical analysis of the dichloromethane fraction indicated the presence of β-sitosterol (1), 3-O-β-acetyloleanolic acid (2), 3-O-(Z)-coumaroyl oleanolic acid (3), betulinic acid (4), and oleanolic acid (5). The inhibitory activity of isolated compounds was also evaluated toward AChE and BChE. Among them, compounds 2 and 5 showed potent inhibitory activity toward BChE with IC50 values of 77.13 and 72.20 μM, respectively. However, all compounds were inactive toward AChE. Moreover, molecular docking study confirmed desired interactions between those compounds and the BChE active site. The ability of fractions and compounds to chelate biometals (Cu2+, Fe2+, and Zn2+) was also investigated. Finally, DPPH antioxidant assay revealed that the ethyl acetate (IC50 = 3.08 μg/mL) and methanol (IC50 = 3.64 μg/mL) fractions possessed excellent antioxidant activity in comparison to BHA as the positive control (IC50 = 3.79 μg/mL).
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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".