Honeybee glands as possible infection reservoirs of Nosema ceranae and Nosema apis in naturally infected forager bees
Bibliographic record
Abstract
AIMS: To determine whether Nosema ceranae and Nosema apis are present in different gland tissues of honeybee, Apis mellifera L. and to monitor spore presence and quantity in these glands in naturally infected hives from July 2009 to July 2010 in Quebec, Canada. METHODS AND RESULTS: Nosema spp. were quantified using duplex quantitative real-time PCR in the thoracic salivary, hypopharyngeal, mandibular glands, and venom sac and glands of A. mellifera over a period of 8 months. Both Nosema species were present in all the glands as single or mixed species; however, N. apis was not present as single-species detections in the salivary glands (see Table 2). Nosema ceranae was more prevalent throughout the 8 months. Significant correlative relationships were established for N. ceranae and N. apis levels in the honeybee glands and those found within the intestines of forager honeybees. Overall, the seasonality of N. ceranae and N. apis in the different glands tightly followed the seasonal patterns in the honeybee guts. CONCLUSIONS: Nosema ceranae and N. apis are not tissue specific, and honeybee glands have potential to become a useful indicator of the extent of disease in the colony and may represent a potential infection reservoir. SIGNIFICANCE AND IMPACT OF THE STUDY: First report of spore load quantification of Nosema spp. in different honeybee glands.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".