Managing Microbiota Activity of Apis mellifera with Probiotic (Bactocell®) and Antimicrobial (Fumidil B®) Treatments: Effects on Spring Colony Strength
Bibliographic record
Abstract
Against a backdrop of declining bee colony health, this study aims to gain a better understanding of the impact of an antimicrobial (Fumidil B®, Can-Vet Animal Health Supplies Ltd., Guelph, ON, Canada) and a probiotic (Bactocell®, Lallemand Inc., Montreal, QC, Canada) on bees’ microbiota and the health of their colonies after wintering. Therefore, colonies were orally exposed to these products and their combination before wintering in an environmental room. The results show that the probiotic significantly improved the strength of the colonies in spring by increasing the total number of bees and the number of capped brood cells. This improvement translated into a more resilient structure of the gut microbiota, highlighted by a more connected network of interactions between bacteria. Contrastingly, the antimicrobial treatment led to a breakdown in this network and a significant increase in negative interactions, both being hallmarks of microbiota dysbiosis. Although this treatment did not translate into a measurable colony strength reduction, it may impact the health of individual bees. The combination of these products restored the microbiota close to control, but with mixed results for colony performance. More tests will be needed to validate these results, but the probiotic Bactocell® could be administrated as a food supplement before wintering to improve colony recovery in spring.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".