Influence of Slc11a1 on the Outcome of<i>Salmonella enterica</i>Serovar Enteritidis Infection in Mice Is Associated with Th Polarization
Bibliographic record
Abstract
Genetic analyses identified Ses1 as a significant quantitative trait locus influencing the carrier state of 129S6 mice following a sublethal challenge with Salmonella enterica serovar Enteritidis. Previous studies have determined that Slc11a1 was an excellent candidate gene for Ses1. Kinetics of infection in 129S6 mice and Slc11a1-deficient (129S6-Slc11a1(tm1Mcg)) mice demonstrated that the wild-type allele of Slc11a1 contributed to the S. enterica serovar Enteritidis carrier state as early as 7 days postinfection. Gene expression profiling demonstrated that 129S6 mice had a significant up-regulation of proinflammatory genes associated with macrophage activation at day 10 postinfection, followed by a gradual increase in immunoglobulin transcripts, whereas 129S6-Slc11a1(tm1Mcg) mice had higher levels of immunoglobulins earlier in the infection. Quantitative reverse transcription-PCR revealed an increase in Th1 cytokine (Ifng and Il12) and Th1-specific transcription factor Tbx21 expression during infection in both the 129S6 and 129S6-Slc11a1(tm1Mcg) strains. However, the expression of Gata3, a transcription factor involved in Th2 polarization, Cd28, and Il4 was markedly increased in Slc11a1-deficient mice during infection, suggesting a predominant Th2 phenotype in 129S6-Slc11a1(tm1Mcg) animals following S. enterica serovar Enteritidis infection. A strong immunoglobulin G2a response, reflecting Th1 activity, was observed only in 129S6 mice. All together, these results are consistent with an impact of Slc11a1 on Th cell differentiation during chronic S. enterica serovar Enteritidis infection. The presence of a Th2 bias in Slc11a1-deficient mice is associated with improved bacterial clearance.
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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 | 0.000 |
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".