Algerian Propolis from Distinct Geographical Locations: Chemical Profiles, Antioxidant Capacity, Cytotoxicity and Inhibition of 5‐Lipoxygenase Product Biosynthesis
Bibliographic record
Abstract
Abstract Propolis was collected from honeybee hives in three geographically distinct Algerian climates and extracts were characterized for composition and bioactivity. Bees were identified as native subspecies using an in‐silico DraI mtDNA COI‐COII test. Over 20 compounds were identified in extracts by LC‐MS. Extracts from the Medea region were more enriched in phenolic content (302±28 mg GAE/g of dry extract) than those from Annaba and Ghardaia regions. Annaba extracts had the highest flavonoid content (1870±385 mg QCE/g of dry extract). Medea extracts presented the highest free‐radical scavenging activity (IC 50 =13.5 μg/mL) using the DPPH radical assay while Ghardaia extracts from the desert region were weak (IC 50 >100 μg/mL). Antioxidant activities measured using AAPH oxidation of linoleic acid were similar in all extracts with IC 50 values ranging from 2.9 to 4.9 μg/mL. All extracts were cytotoxic (MTT assay) and proapoptotic (Annexin‐V) against human leukemia cell lines in the low μg/mL range, although the Annaba extract was less active against the Reh cell line. Extracts inhibited cellular 5‐lipoxygenase product biosynthesis with IC 50 values ranging from 0.6 to 3.2 μg/mL. Overall, examined propolis extracts exhibited significant biological activity that warrant further characterization in cellular and in vivo models.
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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 | 0.000 |
| 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".