In Vitro Screening for Antioxidant and Anticholinesterase Effects of Uvaria littoralis Blume.: A Nootropic Phytotherapeutic Remedy
Bibliographic record
Abstract
Background: Oxidative stress is strongly linked in the development of numerous chronic and degenerative disorders. Medicinal plants with antioxidant and anticholinesterase activities exert a key role for the management of oxidative stress related disorders mainly Alzheimer's disease (AD). Therefore the purpose of this study was to assess antioxidant potentiality and anticholinesterase inhibitory activity of crude methanolic extract (CME), petroleum ether fraction (PEF), chloroform fraction (CLF), ethyl acetate fraction (EAF) and aqueous fraction (AQF) of Uvaria littoralis (U. littoralis) leaves. Methods: The antioxidant compounds namely total flavonoids contents (TFCs) and total proanthocyanidins contents (TPACCs) were determined for quantities constituent’s characterization. Antioxidant capacity of U. littoralis leaves were estimated by the iron reducing power (IRPA), 1, 1-diphenyl-2-picrylhydrazyl (DPPH) radical scavenging and nitric oxide (NO) radical scavenging capacity. Anticholinesterase effects were estimated for acetylcholinesterase (AChE) and butyrylcholinestrase (BChE) activity. Results: The EAF of U. littoralis leaves showed the highest TFCs as compared to CLF, CME, PEF and AQF. TPACCs were also found highest in EAF. The highest absorbance for IRPA was found in EAF (2.220 nm) with respect to CME and other fractions at the highest concentration. The EAF showed best DPPH and NO radical scavenging activity with IC50 values of 31.63 and 55.47 μg/mL, respectively with regard to CME and remaining fractions. The PEF represents highest AChE inhibitory activity with IC50 values of 35.19 μg/mL and CLF showed highest BChE inhibitory activity with IC50 values of 32.49 μg/mL. Conclusions: The findings of the current study demonstrate the presence of antioxidant phytochemicals, likewise, turns out antioxidant and anticholinesterase potentiality of U. littoralis leaves which could be a prestigious candidate for the treatment of neurodegenerative diseases especially AD.
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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 | 0.000 |
| 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".