Protein Profiling of Wild-Caught Phlebotomus papatasi in Morocco: First Observation of Nematodes in Moroccan Population of Sandflies
Bibliographic record
Abstract
Phlebotomine-borne diseases, transmitted by sand flies, cause significant public health burdens worldwide. In Morocco, Phlebotomus papatasi is a primary vector for Leishmania major and phleboviruses. Despite extensive research in other countries, entomopathogenic parasite investigations in P. papatasi have not been conducted in Morocco until now. This study performed proteomic analysis of female P. papatasi collected from four Moroccan localities using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Our analysis revealed that Phlebotomus papatasi peptides were the most abundant, with 884 peptides identified. Additionally, we detected 732 peptides from nematodes, 86 from Leishmania major, 79 from L. infantum, eight from L. tropica, and two peptides associated with phleboviruses. Microscopic examination of 1752 sand flies confirmed P. sergenti female infected with Tetranematidae, Didilia spp. in Imintanout (Z2). This study provides the first report of nematodes in sand flies in Africa and represents the first application of proteomics to identify pathogens carried by P. papatasi. These findings highlight remarkable proteomic differences among localities and generate critical data for understanding parasite-vector interactions.
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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".