Distinct behavior of myelomonocytic cells and CD8 T cells underlies the hepatic response to Listeria monocytogenes
Bibliographic record
Abstract
Background : The immune response to Listeria monocytogenes (LM) is characterized by formation of leukocyte rich foci of infection in liver and spleen. Although much has been gained in our understanding of immune response through the study of LM, little is known about spatio-temporal regulation of immune response to Listeria in liver. Methods: We utilize a combination of molecular, genetic and intravital microscopic approaches to gain insight into the dynamics of foci and leukocyte behavior during hepatic Listeriosis. Results : LM foci efficiently exclude blood flow, indicating the presence of a barrier separating the foci and healthy tissue. Despite this barrier, sinusoidal myelomonocytic cells readily enter or transiently interact with cells at the edge of foci of infection. Next, utilizing L9.6 transgenic CD8 + T cells specific for an endogenously processed LM antigen, p60 217-225, along with LM deficient in this epitope, we define the role of TCR in T cell migratory behavior in infected liver. Surprisingly, T cell behavior varies with micro-anatomic locale. Near foci, non-specific adhesion mechanisms dominate lymphocyte behavior. Antigen specific effects on motility became detectable only distal to foci. Conclusions: These data suggest that LM antigens act in a paracrine manner to mediate protection from Listeriosis in the liver.
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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) | 0.002 | 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".