Current understanding of macrophage type 1 cytokine responses during intracellular infections.
Bibliographic record
Abstract
Macrophages are important effector cells in cell-mediated immunity against intracellular infection. Among cytokines that macrophages are able to release are IL-12 and TNF alpha. IL-12 is a critical linker between the innate and adaptive cell-mediated immunity, capable of Th1 differentiation and IFN gamma release by T and NK cells. IFN gamma is critically required for the activation of macrophage bactericidal activities. Recently emerging evidence suggests that macrophages are able to release not only IL-12 and TNF alpha but also IFN gamma. However, the mechanisms that control the release of each of these type 1 cytokines in macrophages appear different. While macrophages release TNF alpha in an indiscriminate and IL-12-independent way, the release of IL-12, particularly bioactive IL-12 p70, and IFN gamma is under tight control. We are just beginning to understand what controls the release of IL-12 p70, a question of fundamental importance to understanding the mechanisms underlying the initiation of cell-mediated immunity. Our recent findings have shed more insights into the regulatory mechanisms of macrophage IFN gamma responses. It has become evident that IL-12 is required not only for Th1 differentiation but also for IFN gamma responses by both T cells and macrophages during intracellular infection. In this overview, we have discussed about the current understanding of the regulation of macrophage type 1 cytokine responses during intracellular infection, based upon the recent findings from us and others.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.008 |
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".