Current Knowledge on Honey and Its Derivatives with Genomic Stability: A Mini Review
Bibliographic record
Abstract
Genome health is an important factor that plays a role in various degenerative diseases. Instability of genome is the prevalence of mutation within the genome such as changed in nucleic acid and chromosomal arrangement and also the presence of abnormal number of chromosome in cell. Therefore, several method were used to overcome this problem and one of them is by using natural product such as honey, propolis, bee pollen and royal jelly that is high in antioxidant. Those are products that derive from honey bee and had been used as food supplement to increase the quality of life. Therefore, this systematic review provides the updates on the potential of honey bee products to decrease DNA damage both in in vivo and in vitro approaches. Search term of “honey”, “propolis”, “bee pollen”, royal jelly”, “DNA damage”, “genome integrity”, and “telomere” were used for searching purpose in three databases (Scopus, Pubmed and Medline) and also Google Scholar. All the published articles were assessed using PRISMA guidelines and finally after the eligibility process, only 34 published articles were selected for this review. Based on the reports, the product from the honey bee decrease the genome related diseases by reducing the accumulation of free radical, increase the DNA repair protein expression and decrease the telomerase activity in the cell. This provides a large gap in the research field focusing on the effect of those derivatives from bees on genomic stability.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".