SaaS sRNA promotes the interfering effect of Salmonella on hepatic iron metabolism via modulating ferroportin 1
Bibliographic record
Abstract
Iron limitation plays a fundamental role in host immunity against Salmonella infection. The mechanisms by which Salmonella antagonizes nutritional immunity, particularly those regulated by small non-coding RNAs (sRNAs), remain incompletely understood. In this study, we investigated the role of a previously identified sRNA, Salmonella adhesive-associated sRNA (SaaS), in host iron metabolism. Utilizing a combined BALB/c mouse model and HepG2 cell model, we demonstrated that SaaS enhances hepcidin synthesis via the bone morphogenetic protein (BMP)-SMAD pathway, leading to decreased ferroportin 1 level. This suppression of ferroportin 1 results in reduced serum iron and increased hepatic iron accumulation, ultimately causing iron-deficiency anemia. The accumulation of iron triggers hepatic oxidative stress, exacerbating liver damage. Concurrently, SaaS activates the signal transducer and activator of transcription 3 (STAT3) pathway in a triggering receptor expressed on myeloid cells-1 (TREM1)-interleukin (IL)-6-dependent manner, intensifying the inflammatory response. Collectively, these results provide evidence that sRNAs serve as crucial regulators of Salmonella pathogenesis and underscore the potential of targeting sRNAs for the prevention of salmonellosis.
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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".