Infection with Borrelia afzelii reduces moulting time of Ixodes ricinus ticks
Bibliographic record
Abstract
Abstract Arthropod vectors carry vector-borne pathogens that cause infectious disease in vertebrate hosts, and arthropod-associated non-pathogenic microorganisms. Both types of micro-organisms can influence the fitness of their arthropod vectors, and hence the epidemiology of vector-borne diseases. The bacterium Borrelia afzelii, which causes Lyme disease in Europe, is transmitted among vertebrate reservoir hosts by Ixodes ricinus ticks, which also harbour a large diversity of non-pathogenic bacteria. The purpose of this study was to test experimentally whether B. afzelii and tick-associated non-pathogenic bacteria influence the fitness of I. ricinus. Eggs obtained from field-collected adult female ticks were washed with bleach, which reduced the abundance of non-pathogenic bacteria in the hatched I. ricinus larvae by 28-fold compared to larvae that hatched from eggs washed with water. The dysbiosed and control larvae were subsequently fed on B. afzelii-infected or uninfected control mice, and the engorged larvae were allowed to moult into nymphs under laboratory conditions. I. ricinus larvae that fed on B. afzelii-infected mice had a significantly faster larva-to-nymph moulting time compared to larvae that fed on uninfected control mice. In contrast, we found no evidence that B. afzelii infection or larval dysbiosis influenced the four other life history traits of the immature I. ricinus ticks, which included engorged larval weight, unfed nymphal weight, larva-to-nymph moulting success, and immature tick survival. A power analysis found that our sampling effort had sufficient power (>80%) to detect small effects (difference of 5% – 10%) of either B. afzelii infection or larval dysbiosis. Under the laboratory conditions of our study, B. afzelii appears to be a mostly passive passenger in I. Ricinus ticks.
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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 | 0.000 | 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".