Extracellular electron supply from titanium( <scp>III</scp> )nitrilotriacetic acid promotes production of reduced fermentation end products in <i>Clostridium ljungdahlii</i>
Bibliographic record
Abstract
Abstract Interest in the microbial production of bioethanol from renewable sources has prompted efforts to improve its production in homoacetogenic bacteria. It has been suggested that a strongly reducing environment might support the formation of more reduced products. This study investigated the effects of titanium(III)nitrilotriacetic acid (Ti(III)NTA), a highly electronegative redox mediator, on Clostridium ljungdahlii cultures grown in fructose‐based media with either an N 2 or a 20% CO 2 /80% H 2 atmosphere, and in autotrophic cultures with 20% CO 2 /80% H 2 . An atmosphere containing a 4:1 H 2 :CO 2 ratio, rather than the usual 3:1 ratio required for autotrophic acetate production in C. ljungdahlii , was used to determine the effect of excess H 2 electrons on autotrophic versus mixotrophic fermentation. Excess H 2 did not affect the metabolic end‐product profiles observed but the use of Ti(III)NTA resulted in increased production of reduced metabolites such as ethanol, 2,3‐butanediol and lactic acid beyond those reported when CO was used as the sole carbon and energy source. These results reveal a possible correlation between the redox potential of supplied electrons and their metabolic effect. The electronegativity of supplied electrons is crucial, as electrons with sufficient redox potential to reduce ferredoxin gave the observed result.
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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".