Bibliographic record
Abstract
Human schistosomes combat the unique immune systems of two vastly different hosts during their indirect life cycles. In gastropod molluscs, they face a potent innate immune response composed of variable immune recognition molecules and highly phagocytic hemocytes. In humans, a wide variety of innate and adaptive immune processes exist in proximity to these parasites throughout their lifespan. To survive and thrive as the second most common parasitic disease in humans, schistosomes have evolved many techniques to avoid and combat these targeted host responses. Among these techniques are molecular mimicry of host antigens, the utilization of an immune resistant outer tegument, the secretion of several potent proteases, and targeted release of specific immunomodulatory factors affecting immune cell functions. This review seeks to describe these key immune evasion mechanisms, among others, which schistosomes use to survive in both of their hosts. After diving into foundational observational studies of the processes mediating the establishment of schistosome infections, more recent transcriptomic and proteomic studies revealing crucial components of the host/parasite molecular interface are discussed. In order to combat this debilitating and lethal disease, a comprehensive understanding of schistosome immune evasion strategies is necessary for the development of novel therapeutics and treatment plans, necessitating the discussion of the numerous ways in which these parasitic flatworms overcome the immune responses of both hosts.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".