Salivarian Trypanosomes Have Adopted Intricate Host-Pathogen Interaction Mechanisms That Ensure Survival in Plain Sight of the Adaptive Immune System
Bibliographic record
Abstract
Salivarian trypanosomes are extracellular parasites affecting humans, livestock and game animals. Trypanosoma brucei rhodesiense and Trypanosoma brucei gambiense are human infective sub-species of T. brucei causing human African trypanosomiasis (HAT—sleeping sickness). The related T. b. brucei parasite lacks the resistance to survive in human serum, and only inflicts animal infections. Animal trypanosomiasis (AT) is not restricted to Africa, but is present on all continents. T. congolense and T. vivax are the most widespread pathogenic trypanosomes in sub-Saharan Africa. Through mechanical transmission, T. vivax has also been introduced into South America. T. evansi is a unique animal trypanosome that is found in vast territories around the world and can cause atypical human trypanosomiasis (aHT). All salivarian trypanosomes are well adapted to survival inside the host’s immune system. This is not a hostile environment for these parasites, but the place where they thrive. Here we provide an overview of the latest insights into the host-parasite interaction and the unique survival strategies that allow trypanosomes to outsmart the immune system. In addition, we review new developments in treatment and diagnosis as well as the issues that have hampered the development of field-applicable anti-trypanosome vaccines for the implementation of sustainable disease control.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".