Enhanced Protection Against Fatal Mycobacterial Infection in SCID Beige Mice by Reshaping Innate Immunity with IFN-γ Transgene
Bibliographic record
Abstract
Humans with immune-compromised conditions such as SCID are unable to control infection caused by normally nonpathogenic intracellular pathogens such as Mycobacterium bovis bacillus Calmette-Guérin. We found that SCID beige mice lacking both lymphocytes and NK cells had functionally normal lung macrophages and yet a selectively impaired response of type 1 cytokines IFN-gamma and IL-12, but not TNF-alpha, during M. bovis bacillus Calmette-Guérin infection. These mice succumbed to such infection. A repeated lung gene transfer strategy was designed to reconstitute IFN-gamma in the lung, which allowed investigation of whether adequate activation of innate macrophages could enhance host defense in the complete absence of lymphocytes. IFN-gamma transgene-based treatment was initiated 10 days after the establishment of mycobacterial infection and led to increased levels of both IFN-gamma and IL-12, but not TNF-alpha, in the lung. Lung macrophages were activated to express increased MHC molecules, type 1 cytokines and NO, and increased phagocytic and mycobactericidal activities. Activation of innate immunity markedly inhibited otherwise uncontrollable growth of mycobacteria and prolonged the survival of infected SCID hosts. Thus, our study proposes a cytokine transgene-based therapeutic modality to enhance host defense in immune-compromised hosts against intracellular bacterial infection, and suggests a central effector activity played by IFN-gamma-activated macrophages in antimycobacterial cell-mediated immunity.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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".