Competition and the Evolution of Reproductive Restraint in Malaria Parasites
Bibliographic record
Abstract
All organisms must trade off resource allocation between different life processes that determine their survival and reproduction. Malaria parasites replicate asexually in the host but must produce sexual stages to transmit between hosts. Because different specialized stages are required for these functions, the division of resources between these life-history components is a key problem for natural selection to solve. Despite the medical and economic importance of these parasites, their reproductive strategies remain poorly understood and often seem counterintuitive. Here, we tested recent theory predicting that in-host competition shapes how parasites trade off investment in in-host replication relative to between-host transmission. We demonstrate, across several genotypes, that Plasmodium chabaudi parasites detect the presence of competing genotypes and facultatively respond by reducing their investment in sexual stages in the manner predicted to maximize their competitive ability. Furthermore, we show that genotypes adjust their allocation to sexual stages in line with the availability of exploitable red blood cell resources. Our findings are predicted by evolutionary theory developed to explain life-history trade-offs in more traditionally studied multicellular taxa and suggest that the answer to the long-standing question of why so few transmission stages are produced is that in most natural infections heavy investment in reproduction may compromise in-host survival.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".