Deficiency of Leishmania Phosphoglycans Influences the Magnitude but Does Not Affect the Quality of Secondary (Memory) Anti-Leishmania Immunity
Bibliographic record
Abstract
Despite inducing very low IFN-γ response and highly attenuated in vivo, infection of mice with phosphoglycan (PG) deficient Leishmania major (lpg2-) induces protection against virulent L. major challenge. Here, we show that mice infected with lpg2- L. major generate Leishmania-specific memory T cells. However, in vitro and in vivo proliferation, IL-10 and IFN-γ production by lpg2- induced memory cells were impaired in comparison to those induced by wild type (WT) parasites. Interestingly, TNF recall response was comparable to WT infected mice. Despite the impaired proliferation and IFN-γ response, lpg2- infected mice were protected against virulent L. major challenge and their T cells mediated efficient infection-induced immunity. In vivo depletion and neutralization studies with mAbs demonstrated that lpg2- L. major-induced resistance was strongly dependent on IFN-γ, but independent of TNF and CD8(+) T cells. Collectively, these data show that the effectiveness of secondary anti-Leishmania immunity depends on the quality (and not the magnitude) of IFN-γ response. These observations provide further support for consideration of lpg2- L. major as a live-attenuated candidate for leishmanization in humans since it protects strongly against virulent challenge, without inducing pathology in infected animals.
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) | 0.000 | 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) | 0.001 | 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".