Metabolic manipulation by Pseudomonas fluorescens: a powerful stratagem against oxidative and metal stress
Bibliographic record
Abstract
Metabolism is the foundation of all living organisms and is at the core of numerous if not all biological processes. The ability of an organism to modulate its metabolism is a central characteristic needed to proliferate, to be dormant and to survive any assault. Pseudomonas fluorescens is bestowed with a uniquely versatile metabolic framework that enables the microbe to adapt to a wide range of conditions including disparate nutrients and toxins. In this mini-review we elaborate on the various metabolic reconfigurations evoked by this microbial system to combat reactive oxygen/nitrogen species and metal stress. The fine-tuning of the NADH/NADPH homeostasis coupled with the production of α-keto-acids and ATP allows for the maintenance of a reductive intracellular milieu. The metabolic networks propelling the synthesis of metabolites like oxalate and aspartate are critical to keep toxic metals at bay. The biochemical processes resulting from these defensive mechanisms provide molecular clues to thwart infectious microbes and reveal elegant pathways to generate value-added products.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".