Cutting Edge: STAT1 and T-bet Play Distinct Roles in Determining Outcome of Visceral Leishmaniasis Caused by <i>Leishmania donovani</i>
Bibliographic record
Abstract
T-bet and STAT1 regulate IFN-gamma gene transcription in CD4+ T cells, which mediate protection against Leishmania. Here we show that T-bet and STAT1 are required for the induction of an efficient Th1 response during Leishmania donovani infection, but they play distinct roles in determining disease outcome. Both STAT1(-/-) and T-bet(-/-) mice failed to mount a Th1 response, but STAT1(-/-) mice were highly resistant to L. donovani and developed less immunopathology, whereas T-bet(-/-) mice were highly susceptible and eventually developed liver inflammation. Adoptive cell transfer studies showed that RAG2(-/-) recipients receiving STAT1(+/+) or STAT1(-/-) T cells developed comparable liver pathology, but those receiving STAT1(-/-) T cells were significantly more susceptible to infection. These unexpected findings reveal distinct roles for T-bet and STAT1 in mediating host immunity and liver pathology during visceral leishmaniasis.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".