Effect of chlorophyll content on the multifunctional properties of Telfairia occidentalis aqueous leaf polyphenolic concentrate
Bibliographic record
Abstract
• Chlorophyll-enriched Telfairia occidentalis leaf fraction had strong iron reducing capacity. • The Chlorophyll-enriched fraction exhibited strong total antioxidant capacity. • The Chlorophyll-enriched fraction inhibited amylase, renin, and lipase activities strongly. • The Chlorophyll-reduced fraction was a strong metal ion chelator. The aqueous extract from Telfairia occidentalis (TO) leaves was separated by column chromatography into chlorophyll-enriched (CH-E) and chlorophyll-reduced (CH-R) fractions, and their antioxidant and rate of enzyme inhibition activities compared . The total chlorophyll content of CH-E was 46.22 ± 0.16 mg g -1 when compared to 25.29 ± 0.21 and 37.84 ± 0.21 mg g -1 for CH-R and TO, respectively. The main polyphenols found in TO, CH-E, and CH-R were quercetin O-rutinoside and kaempferol O-rutinoside. In comparison to the CH-R fraction, the CH-E and TO had significantly ( p < 0.05) higher ferric-reducing antioxidant power, total antioxidant capacity, and enzyme inhibitory activities against lipase, DPP-IV, α-amylase, α-glucosidase, and renin. In contrast, the CH-R had significantly ( p < 0.05) stronger metal chelation activity but similar angiotensin-converting enzyme inhibition when compared to CH-E. We conclude that the presence of chlorophyll is a positive contributing factor to enhanced radical scavenging and enzyme inhibitory properties of the leaf extract.
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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".