Estimation of vector competence of Moroccan Sand fly Populations Using a Proteomic Approach
Bibliographic record
Abstract
Abstract Background Phlebotomine vector born disease are distributed throughout the world, and different pathogens are associated with varying degrees of disease severity. In Morocco, sand fly populations are incriminated in the transmission of several pathogens, such Leishmania spp. and phlebovirus, in particular the most relevant sand fly species as the case of Phlebotomus papatasi. This species is the main vector of Leishmania major in Morocco, and incriminated in phlebovirus transmission. Not to pass over without investigating its possible role on the transmission of entomopathogenic parasite already reported in literature. Methodology and finding The present study focused on proteomic analysis in Phlebotomus papatasi from four localities in Morocco. Proteomic analysis in female P. papatasi was performed with Liquid chromatography-tandem mass spectrometry (LC-MS/MS). A total of 239 identified proteins for Leishmania spp., 26 identified proteins for phlebovirus and 1132 identified proteins for nematode were detected in the 20 pools of P. papatasi from investigated localities. The microscopic examination of 1752 sandflies collected showed, the infection of two specimens of female’s P. sergenti with Tetranematid Didilia spp. and potential Microfilariae in Imintanout locality (Z2).Conclusion This study presents the first report of nematodes in sand flies of Africa. Also, the first use of proteomic tools for estimation of vector competence of P. papatasi which could be a specific tool to a better understanding of the vectorial capacity of Moroccan sandflies population.
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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".