Metabolic Networks to Counter Al Toxicity<i>in Pseudomonas Fluorescens</i>: A Holistic View
Bibliographic record
Abstract
As our reliance on aluminum (Al) increases, so too does its presence in the environment and living systems. Although generally recognized as safe, its interactions with most living systems have been nefarious. This review presents an overview of how Pseudomonas fluorescens can reprogram its metabolic pathways to survive an Al-contaminated environment. In an effort to expulse the metal as an insoluble precipitate, P. fluorescens shuttles metabolites toward the production of organic acids and lipids that play key roles in chelating, immobilizing, and exuding Al. To counter the Fe conundrum induced by Al toxicity, P. fluorescens utilizes isocitrate lyase and NADP-dependent isocitrate dehydrogenase to metabolize citrate when confronted with an ineffective aconitase provoked by Al stress. The metabolic networks aimed at NADPH production and ATP generation in an O2-independent manner are described. This holistic view on Al–microbe interaction underscores the significance of metabolism in biological functions and brings to the forefront the three molecular participants (i.e., oxalate, ATP, and NADPH) that orchestrate the survival of P. fluorescens.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".