Manganese orchestrates a metabolic shift leading to the increased bioconversion of glycerol into α-ketoglutarate.
Bibliographic record
Abstract
Glycerol is a major by-product of the biodiesel industry and its transformation into value-added products is an ongoing technological challenge. Here we report on the ability of the nutritionally-versatile Pseudomonas fluorescens to synthesize copious amount of α-ketoglutarate (KG) in a glycerol medium supplemented with manganese (Mn). The enhanced production of this keto-acid was mediated by the increased activities of isocitrate dehydrogenase (ICDH)-(NAD)P dependent and aminotransaminases. At stationary phase of growth when the optimal quantity of KG was recorded, these enzymes exhibited maximal activities. Two isoforms of pyruvate carboxylase (PC) that were identified in the Mn-treated cells provided an effective route for the synthesis of oxaloacetate, a metabolite critical in the production of KG. Furthermore, the increased activities of phosphoenol pyruvate carboxylase (PEPC) and pyruvate orthophosphate dikinase (PPDK) ensured the efficacy of this KG-generating metabolic system by supplying pyruvate and ATP from the oxaloacetate synthesized by PC. Mn-exposed whole cells converted 90% of industrial glycerol into KG. This Mn-evoked metabolic network can be optimized into the economic transformation of glycerol into KG.
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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".