Two Mosquito Salivary Antigens Demonstrate Promise as Biomarkers of Recent Exposure to <i>Plasmodium falciparum–</i>Infected Mosquito Bites
Bibliographic record
Abstract
BACKGROUND: Measuring malaria transmission intensity using the traditional entomological inoculation rate is difficult. Antibody responses to mosquito salivary proteins like SG6 have been used as biomarkers of exposure to Anopheles mosquito bites. Here, we investigate 4 mosquito salivary proteins as potential biomarkers of human exposure to mosquitoes infected with Plasmodium falciparum: mosGILT, SAMSP1, AgSAP, and AgTRIO. METHODS: We tested population-level human immune responses in longitudinal and cross-sectional plasma from individuals with known P falciparum infection from low- and moderate-transmission areas in Senegal using a multiplexed magnetic bead-based assay. RESULTS: AgSAP and AgTRIO were the best indicators of recent exposure to infected mosquitoes. Antibody responses to AgSAP, in a moderate-endemicity area, and to AgTRIO in both low- and moderate-endemicity areas, were significantly higher than nonendemic controls. No antibody responses significantly differed between low- and moderate-transmission areas, or between equivalent groups during and outside the malaria transmission seasons. AgSAP and AgTRIO reactivity peaked 2-4 weeks after clinical P falciparum infection and declined 3 months after infection. CONCLUSIONS: Reactivity to AgSAP and AgTRIO reflects exposure to infectious mosquitoes or recent bites rather than general mosquito exposure, highlighting their promise for incorporation into multiplexed assays for serosurveillance of population-level changes in P falciparum-infected mosquito exposure.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".