Propolis Counteracts Some Threats to Honey Bee Health
Bibliographic record
Abstract
Honey bees (Apis mellifera) are constantly dealing with threats from pathogens, pests, pesticides and poor nutrition. It is critically important to understand how honey bees’ natural immune responses (individual immunity) and collective behavioral defenses (social immunity) can improve bee health and productivity. One form of social immunity in honey bee colonies is the collection of antimicrobial plant resins and their use in the nest architecture as propolis. We review research on the constitutive benefits of propolis on the honey bee immune system, and its known therapeutic, colony-level effects against the pathogens Paenibacillus larvae and Ascosphaera apis. We also review the limited research on the effects of propolis against other pathogens, parasites and pests (Nosema, viruses, Varroa destructor, and hive beetles) and how propolis may enhance bee products such as royal jelly and honey. Although propolis may be a source of pesticide contamination, it also has the potential to be a detoxifying agent or primer of detoxification pathways, as well as increasing bee longevity via antioxidant-related pathways. Throughout this paper, we discuss opportunities for future research goals and present ways in which the beekeeping community can promote propolis use in standard colonies, as one way to improve and maintain colony health and resiliency.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".