Cooperation between Monocyte-Derived Cells and Lymphoid Cells in the Acute Response to a Bacterial Lung Pathogen
Bibliographic record
Abstract
Legionella pneumophila is the causative agent of Legionnaires' disease, a potentially fatal lung infection. Alveolar macrophages support intracellular replication of L. pneumophila, however the contributions of other immune cell types to bacterial killing during infection are unclear. Here, we used recently described methods to characterise the major inflammatory cells in lung after acute respiratory infection of mice with L. pneumophila. We observed that the numbers of alveolar macrophages rapidly decreased after infection coincident with a rapid infiltration of the lung by monocyte-derived cells (MC), which, together with neutrophils, became the dominant inflammatory cells associated with the bacteria. Using mice in which the ability of MC to infiltrate tissues is impaired it was found that MC were required for bacterial clearance and were the major source of IL12. IL12 was needed to induce IFNγ production by lymphoid cells including NK cells, memory T cells, NKT cells and γδ T cells. Memory T cells that produced IFNγ appeared to be circulating effector/memory T cells that infiltrated the lung after infection. IFNγ production by memory T cells was stimulated in an antigen-independent fashion and could effectively clear bacteria from the lung indicating that memory T cells are an important contributor to innate bacterial defence. We also determined that a major function of IFNγ was to stimulate bactericidal activity of MC. On the other hand, neutrophils did not require IFNγ to kill bacteria and alveolar macrophages remained poorly bactericidal even in the presence of IFNγ. This work has revealed a cooperative innate immune circuit between lymphoid cells and MC that combats acute L. pneumophila infection and defines a specific role for IFNγ in anti-bacterial immunity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".