INVESTIGATING THE QUALITATIVE AND QUANTITATIVE PHYTOCHEMICAL ANALYSIS OF ACANTHOCEREUS TETRAGONUS (CACTACEAE FAMILY) ALONG WITH THE ANTIOXIDANT ACTIVITY
Bibliographic record
Abstract
Acanthocereus tetragonus is a cactus plant belonging to family Cactaceae. Literature suggests that cactus plants are known for their anti-inflammatory, anti-ulcer, anti-diabetic, anti-obesity, and anti-cancer properties. Thus, cactus plants have a wide range of therapeutic properties and have been used for centuries by indigenous people for their medicinal benefits. While more research is needed to fully understand the mechanisms behind these therapeutic effects, the use of cactus plants in traditional medicine is a promising avenue for future research and development of new therapeutics. Therefore, the present study aims to evaluate the qualitative and quantitative phytochemicals and antioxidant property of Acanthocereus tetragonus plant. The study reports the total phenolic and flavonoid content of both hydro-methanolic and ethyl acetate extracts, using the Folin-Ciocalteau and aluminium chloride method respectively. The hydro-methanolic extract exhibited higher total phenolic content, while the ethyl acetate extract had a higher total flavonoid content. Antioxidant activity was also measured using DPPH and FRAP assays, and the hydro-methanolic extract showed comparatively better free radical scavenging activity than ethyl acetate extract. However, the study highlights the importance of quantitative phytochemical analysis for understanding the chemical composition and their potential benefits for human health. The results also suggest that A. tetragonus extracts have significant antioxidant activity and can be explored further for their potential medicinal and therapeutic uses.
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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 | 0.001 | 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 | 0.000 |
| 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".