Chemopreventative Potential of Plant-Based Extracts Coffee (Coffea) and Mauby (Colubrina Arborescens) using the Global Antioxidant Response (GAR) Method via in vitro Simulated Digestion
Bibliographic record
Abstract
Plant-based extracts such as coffee (coffea) and Mauby (Colubrina Arborescens) were tested for chemopreventative potential by measuring their antioxidant activity (i.e., reducing power and free radical scavenging capacity) conventionally using chemical assays 1, 1-Diphenyl-2-picryl-hydrazyl (DPPH) and Ferric Reducing Antioxidant Power (FRAP). Alternately, extracts were also analyzed for their chemopreventative potential via a novel method (Global Antioxidant Response [GAR]), where they were subjected to simulated digestion before their antioxidant activity was determined via conventional methods previously mentioned. Next, the antioxidant capacities of the extracts, conventional versus the novel (GAR) method were compared. Overall, the analysis indicated that the reducing power (FRAP) and free radical scavenging capacity (DPPH) of coffee and Mauby were reduced (~16%) after undergoing simulated digestion. It was also observed that while the antioxidants in Mauby scavenged radicals at a significantly higher capacity than those in coffee (95.7% ± 0.67 and 90% ± 2.1 before digestion, and 77.7% ± 2.2 and 74.6% ± 2.3 after digestion, respectively), antioxidants in coffee exhibited higher reducing power compared to those in Mauby. Specifically, after undergoing simulated digestion, 1.12 mM FeSO4/mL ± 0.05 to 0.68 mM FeSO4/mL ± 0.07 ions were reduced before digestion, and 0.73 mM FeSO4/mL ± 0.09 to 0.48 mM FeSO4/mL ± 0.04 ions were reduced after digestion for coffee and Mauby, respectively. These findings suggest that while the antioxidants in coffee may have been more powerful in their ability to reduce ions, the antioxidants in Mauby may have been more effective in scavenging and neutralizing radicals.
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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) | 0.000 | 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".