Antioxidant and Free Radical Scavenging Capacity of Crude and Refined Oil Extracted From Azadirachta indica A. Juss.
Bibliographic record
Abstract
Naturally nutritive and non-nutritive occurring antioxidants have been proven potent and safe for management of variety of diseases. This study investigated the antioxidant and free radical scavenging capacity of crude and refined Azadirachta indica (Neem tree) oil. The neem crude oil (NCO) was extracted from the seeds by mechanical press and degummed. The neem oil was de-pigmented with activated charcoal, and fractionated with silica gel in a capillary column. The ability of the oils to act as hydrogen/electrons donor were determined in-vitro using 2, 2-dipphenyl-1-picrylhydrazyl (DPPH), 2, 2-azinobis - (3-ethylbenzothiazolin - 6-sulfonic acid) diammonium salt (ABTS), lipid peroxyl (LP) and nitric oxide (NO) radicals scavenging assays, at different extract concentrations (0.1, 0.2, 0.3 and 0.4 mg/mL). The IC50 of the NCO oil (1.50 ± 0.10 mg/mL) showed that antioxidant activity is comparable to vitamin C and beta-carotene (1.60 ± 0.10 and 1.27 ± 0.12 mg/mL respectively) in scavenging DPPH radical. The crude neem oil exhibited superior activity against NO radical, than the refined oil and vitamin C. Generally, in the four antioxidant assays, a significant correlation existed between concentrations of the oils and percentage inhibition of the four different radicals. GC/MS analyses identified monounsaturated and saturated fatty acids, aldehydes and pentanethiol as the major compounds in the oils, these may account for their antioxidant capacity.
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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) | 0.001 | 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".