Oxidative Stress Evokes a Metabolic Adaptation That Favors Increased NADPH Synthesis and Decreased NADH Production in <i>Pseudomonas fluorescens</i>
Bibliographic record
Abstract
The fate of all aerobic organisms is dependent on the varying intracellular concentrations of NADH and NADPH. The former is the primary ingredient that fuels ATP production via oxidative phosphorylation, while the latter helps maintain the reductive environment necessary for this process and other cellular activities. In this study we demonstrate a metabolic network promoting NADPH production and limiting NADH synthesis as a consequence of an oxidative insult. The activity and expression of glucose-6-phosphate dehydrogenase, malic enzyme, and NADP(+)-isocitrate dehydrogenase, the main generators of NADPH, were markedly increased during oxidative challenge. On the other hand, numerous tricarboxylic acid cycle enzymes that supply the bulk of intracellular NADH were significantly downregulated. These metabolic pathways were further modulated by NAD(+) kinase (NADK) and NADP(+) phosphatase (NADPase), enzymes known to regulate the levels of NAD(+) and NADP(+). While in menadione-challenged cells, the former enzyme was upregulated, the phosphatase activity was markedly increased in control cells. Thus, NADK and NADPase play a pivotal role in controlling the cross talk between metabolic networks that produce NADH and NADPH and are integral components of the mechanism involved in fending off oxidative stress.
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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 | 0.000 |
| 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".