M(IL-4) Tissue Macrophages Support Efficient Interferon-Gamma Production in Antigen-Specific CD8+ T Cells with Reduced Proliferative Capacity
Bibliographic record
Abstract
CD8+ cytotoxic T cell (CTL) responses are necessary for the lysis of virally infected cells and control of infection. CTLs are activated when their TCRs bind a major histocompatibility complex (MHC)-I/peptide complex on the surface of antigen presenting cells such as macrophages (MΦ). It is now apparent that MΦ display remarkable plasticity in response to environmental signals to polarize into classically activated M(LPS + IFN-γ) or alternatively activated M(IL-4). However, little is known about how MΦ activation status influences their antigen presentation function to CD8+ T cell in models of virus infection. Consequently, we tested how polarization of spleen-derived (Sp)-MΦ impacts direct presentation of viral antigens to influence effector and proliferative CD8+ T-cell responses. We show that M(IL-4) Sp-MΦ retain MHC-I surface expression and the ability to stimulate IFN-γ production by CTL following peptide stimulation and lymphocytic choriomeningitis virus infection to levels similar to M0 and M(LPS + IFN-γ) MΦ. However, memory CD8+ T cells cultured in the presence of M(IL-4) MΦ underwent significantly reduced proliferation and produced similar IFN-γ levels as coculturing with M0 or M(LPS + IFN-γ) cells. Thus, these results show a novel ability of polarized MΦ to regulate CD8+ T-cell proliferation and effector functions during virus infection.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".