Cross-sectional analysis of Piroplasma species-infecting camel (Camelus dromedaries) in Egypt using a multipronged molecular diagnostic approach
Bibliographic record
Abstract
Camel piroplasmosis is a tick-borne disease (TBD) caused by hemoprotozoan parasites. Hereby, we describe a cross-sectional study aiming at identifying Piroplasma spp.-infecting camels in Egypt using a multipronged molecular diagnostic approach. A total of 531 blood samples from camels ( Camelus dromedarius ) were collected from slaughterhouses at different governorates in Egypt for analysis during the period from June 2018 to May 2019. Piroplasma spp. was identified using microscopical examination and several different and sequential polymerase chain reaction (PCR) assays targeting the 18S rRNA genes. The overall prevalence of Piroplasma spp. in microscopical and molecular analyses in the samples was 11% (58/531) and 38% (203/531), respectively. Further discriminative multiplex PCR analysis targeting the 18S rRNA gene applied on all Piroplasma spp.-positive samples allowed the detection of Theileria equi (41%) , Babesia caballi (5.4%) , Babesia bigemina (0.5%), and Babesia bovis (4%). Additionally, the blast analysis of nested (n) PCR, targeting the V4 region, amplicon sequences resulted in the identification of B. vulpes (22%), Babesia sp. (9%), and Theileria sp. (3%). Overall, the results of this study confirmed the high prevalence of TBDs caused by several types of piroplasm hemoparasites in camel and suggests the need for future interventions aimed at improving the control of these potentially debilitating diseases that may be t-hreatening important economic resources and food security in Egypt.
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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) | 0.001 | 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".