Towards identification and development of alternative vaccines against pregnancy-associated malaria based on naturally acquired immunity
Bibliographic record
Abstract
Pregnant women are particularly susceptible to Plasmodium falciparum malaria, leading to substantial maternal and infant morbidity and mortality. While highly effective malaria vaccines are considered an essential component towards malaria elimination, strides towards development of vaccines for pregnant women have been minimal. The leading malaria vaccine, RTS,S/AS01, has modest efficacy in children suggesting that it needs to be strengthened and optimized if it is to be beneficial for pregnant women. Clinical trials against pregnancy-associated malaria (PAM) focused on the classical VAR2CSA antigen are ongoing. However, additional antigens have not been identified to supplement these initiatives despite the new evidence that VAR2CSA is not the only molecule involved in pregnancy-associated naturally acquired immunity. This is mainly due to a lack of understanding of the immune complexities in pregnancy coupled with difficulties associated with expression of malaria recombinant proteins, low antigen immunogenicity in humans, and the anticipated complications in conducting and implementing a vaccine to protect pregnant women. With the accelerated evolution of molecular technologies catapulted by the global pandemic, identification of novel alternative vaccine antigens is timely and feasible. In this review, we discuss approaches towards novel antigen discovery to support PAM vaccine studies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".