<i>Salmonella typhimurium</i> Infection and Lipopolysaccharide Stimulation Induce Similar Changes in Macrophage Gene Expression
Bibliographic record
Abstract
Changes in macrophage phenotype induced during infection result from the recognition of bacterial products as well as the action of bacterial virulence factors. We used the unprecedented opportunity provided by gene arrays to simultaneously study the expression of hundreds of genes during Salmonella typhimurium infection of macrophages and to assess the contribution of the bacterial virulence factor, LPS, in initiating the host responses to Salmonella. We found that S. typhimurium infection caused significant changes in the expression of numerous genes encoding chemokines, cell surface receptors, signaling molecules, and transcriptional activators at 4 h postinfection of the RAW 264.7 murine macrophage cell line. Our results revealed changes in the expression of several genes that had not been previously implicated in the host responses to S. typhimurium infection, as well as changes in the expression of several genes previously shown to be regulated by S. typhimurium infection. An overlapping spectrum of genes was expressed in response to virulent S. typhimurium and purified S. typhimurium LPS, reinforcing the major role of this surface molecule in stimulating the early response of macrophages to bacterial infection. The macrophage gene expression profile was further altered by activation with IFN-gamma, indicating that host cell responses depend on the activation state of the cell.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".