Deletion of fibrinogen-like protein 2, a novel CD4+CD25+ Treg effector molecule, leads to improved control of <i>Echinococcus mutilocularis</i>infection (MPF7P.718)
Bibliographic record
Abstract
Abstract The proliferation of Echinococcus multilocularis (E. multilocularis) metacestode is dependent on the nature/function of the periparasitic immune-mediated processes. Fibrinogen-like protein 2 (FGL2) was found to be up-regulated after E. multilocularis infection, however little is known about the contribution of this novel CD4+CD25+ Treg effector molecule to the control of a helminth infection. We showed that, as compared to AE-WT mice, AE-fgl2-deficient mice exhibited a significantly decreased parasite load and proliferation activity, associated with increased T cell proliferation in response to ConA, reduced Treg numbers and function, relative Th1 polarization, and increased B cell number and DC maturation. We showed for the first time that FGL2 is involved in negative immune regulation towards a helminth parasite and that IL-17A contributes to FGL2 regulation. By promoting Treg cell activity, FGL2 appears as a key-player in the immune orchestration of the outcome of E. multilocularis infection and measurement of plasma FGL2 levels might be useful to assess disease progression. Furthermore, targeting FGL2 could also be used for the development of novel treatment approaches in alveolar echinococcosis and other diseases caused by parasite pathogens.
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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 | 0.000 |
| 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 | 0.001 |
| 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".