FcRγIIA response duality in leishmaniasis
Bibliographic record
Abstract
Leishmania is responsible for a neglected tropical disease affecting millions of people around the world and could potentially spread more due to climate change. This disease not only leads to significant morbidity but also imposes substantial social and economic burdens on affected populations, often exacerbating poverty and health disparities. Despite the complexity and effectiveness of the immune response, the parasite has developed various strategies to evade detection and manipulates host cells in favor of its replication. These evasion strategies start at early stages of the infection by hijacking immune receptors to silence critical cellular response that would otherwise limit the pathogen's propagation. Among these receptors, Fc receptors have emerged as a significant player in the immune evasion strategies employed by microorganisms, as they could promote inhibitory pathways. This review explores the potential role of one of these immune receptors, the FcγRIIA, in leishmaniasis and how this parasite may use it and the signaling pathways downstream to evade the host immune response. By understanding the potential interactions between Leishmania and immune receptors such as FcγRIIA, we may identify novel targets for therapeutic intervention aimed to enhance the host immune response and reduce the burden of this disease.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".