Identification of iron-responsive genes in <i>Proteus vulgaris</i>
Bibliographic record
Abstract
Iron is essential for almost all bacteria, and iron homeostasis is precisely controlled by the ferric uptake regulator (Fur). The Fur regulons have been well characterized in some model bacteria, yet little is known in the common opportunistic pathogen Proteus vulgaris. In this study, Fur regulon and iron-responsive genes in P. vulgaris were mainly defined by in silico and proteomic analyses. The results showed that about 250 potential Fur-regulated operons including 14 transcriptional factors were predicted, while 559 proteins exhibited differential expression in response to iron deficiency, not all being directly regulated by Fur, such as transcriptional factors lexA, recA, narL, and arcA. Collectively, these results demonstrated that Fur functioned as a global regulatory protein to repress or activate expression of a large repertoire of genes in P. vulgaris; besides, not all the iron-responsive genes were directly regulated by Fur, whereas indirectly regulated through other mechanisms such as additional transcriptional regulatory proteins.
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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 | 0.001 | 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) | 0.000 | 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".