Preliminary studies of microencapsulation and anticancer activity of polyphenols extract from <scp> <i>Punica granatum</i> </scp> peels
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Bibliographic record
Abstract
Abstract The purpose of this study was to prepare functional formulations using two different types of Punica granatum (pomegranate) peels extracts (the native and the enriched extract), as an important source of polyphenolic compounds such as punicalagin and ellagic acid. These two extracts were microencapsulated by a spray‐drying technique. Polyphenol constituents of P. granatum play a significant role in the prevention of different diseases from cancer to cardiovascular and neurodegenerative diseases. In general, polyphenols are sensitive and present low bioavailability in the human body. Microencapsulation could be a perfect alternative to modify the reactivity, durability, sensitivity, and photosensitivity of these natural compounds. Arabic gum, pectin, and modified chitosan were used as biopolymers‐based carriers in this research. The mean size of the microparticles prepared is between 2.55–6.86 μm (volume distribution). Release studies were implemented. The fastest release was observed for Arabic gum‐based carriers. The pectin‐based microparticles showed the slowest release profile. The Korsmeyer‐Peppas model was adjusted to the experimental release profiles. In addition, some anticancer activity studies were performed. When incubated with the human gastric cancer cell line AGS and human lung cancer cell line A549, both extracts elicited some loss of cancer cell viability, which increased in the case of the enriched extract. The bioactive pomegranate extracts microencapsulated seem to be a valid strategy to enhance their biological activity. A final powder formulation was obtained, which can improve the bioavailability and stability of these active constituents and overcome their limitations of application.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it