Growth and Virulence of <i>Salmonella</i> Typhimurium Mutants Deficient in Iron Uptake
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide The present study investigated the effects of iron, iron chelators, and mutations of tonB or iroN fepA genes on the growth and virulence of Salmonella Typhimurium . Results indicated that organic iron (ferric citrate and ferrous- l -ascorbate) supported better growth of Salmonella compared to inorganic iron. Among tested chelators, 2,2′-bipyridyl at 500 μM showed the highest inhibition of Salmonella growth with 5 μM ferrous sulfate. Deletion of genes ( tonB – and iroN – fepA – ) in the iron uptake system attenuated Salmonella invasion of Caco-2 cells and its ability to damage the epithelial monolayer. The expression of all tested host genes in Caco-2 was not affected under the iron-poor condition. However, claudin 3, tight junction protein 1, tumor necrosis factor α (TNF-α), and interleukin-8 (IL-8) were altered under the iron-rich condition depending on individual mutations. In Caenorhabditis elegans, a significant down-regulation of ferritin 1 expression was observed when the nematode was infected by the wild-type (WT) strain.
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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 | 0.000 |
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".