Extracellular Vesicles: Translational Agenda Questions for Three Protozoan Parasites
Bibliographic record
Abstract
The protozoan parasites Plasmodium falciparum, Leishmania spp. and Trypanosoma cruzi continue to exert a significant toll on the disease landscape of the human population in sub-Saharan Africa and Latin America. Control measures have helped reduce the burden of their respective diseases-malaria, leishmaniasis and Chagas disease-in endemic regions. However, the need for new drugs, innovative vaccination strategies and molecular markers of disease severity and outcomes has emerged because of developing antimicrobial drug resistance, comparatively inadequate or absent vaccines, and a lack of trustworthy markers of morbid outcomes. Extracellular vesicles (EVs) have been widely reported to play a role in the biology and pathogenicity of P. falciparum, Leishmania spp. and T. cruzi ever since they were discovered. EVs are secreted by a yet to be fully understood mechanism in protozoans into the extracellular milieu and carry a cargo of diverse molecules that reflect the originator cell's metabolic state. Although our understanding of the biogenesis and function of EVs continues to deepen, the question of how EVs in P. falciparum, Leishmania spp. and T. cruzi can serve as targets for a translational agenda into clinical and public health interventions is yet to be fully explored. Here, as a consortium of protozoan researchers, we outline a plan for future researchers and pose three questions to direct an EV's translational agenda in P. falciparum, Leishmania spp. and T. cruzi. We opine that in the long term, executing this blueprint will help bridge the current unmet needs of these medically important protozoan diseases in sub-Saharan Africa and Latin America.
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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 | 0.011 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.010 |
| Scholarly communication | 0.009 | 0.014 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.010 | 0.015 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".