A Novel <i>Francisella</i> -Like Endosymbiont in <i>Haemaphysalis longicornis</i> and <i>Hyalomma asiaticum</i> , China
Bibliographic record
Abstract
Francisella tularensis causes a highly infectious zoonotic disease tularemia. Both Haemaphysalis longicornis and Hyalomma asiaticum are widely distributed in China, but the presence of Francisella and Francisella-like endosymbionts (FLEs) in the two tick species is poorly understood. Therefore, a total of 627 H. longicornis (471 adults and 156 nymphs) and 88 Hy. asiaticum ticks (adults) were collected, of which 88 were from Bole of Xinjiang, 236 from Liaoyang, and 176 from Shenyang of Liaoning, and 215 from Wuhan of Hubei. Notably, five H. longicornis pools from Liaoyang of Liaoning province might have harbored F. tularensis, showing a minimum prevalence of 2.12% (5/236). This study should alert the health department and veterinarians working within the region to prevent and control the emergence of tularemia. After the screening of 16S rRNA and tul4 genes, the results revealed that FLEs were detected in Hy. asiaticum ticks in Bole and in H. longicornis ticks in Liaoyang and Shenyang. Their infection rate was 100% (88/88), 3.39% (8/236 is a minimum), and 8.52% (15/176), respectively. Phylogenetic analyses indicated that the sequence named bole in Hy. Asiaticum from Bole, the sequence named liaoyang1 in H. longicornis from Liaoyang, and the sequence named shanyang1 in H. longicornis from Shenyang shared consistent 16S rRNA sequence, and the difference between Chinese FLEs and the known FLEs was obvious. These findings suggest that this FLE species might be a potentially novel FLE circulating in H. longicornis and Hy. asiaticum from China.
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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 | 0.001 | 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 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".