Production of 2,3‐butanediol from diverse saccharides via fermentation
Bibliographic record
Abstract
The present study aimed to evaluate the potential use of whey to produce 2,3‐BD via the fermentation of lactose and its monosaccharides, glucose and galactose, in a synthetic culture medium (medium 9, M9) using a modified strain of Escherichia coli K12 MG1655 (E. coli JFR12) at a 0.1 L/L (10 vol%) inoculum ratio, 37 °C, atmospheric pressure, an initial pH 7.4, and 100 rpm for 72 h varying the saccharide concentration from 12.5, 25, and 50 g/L. The 2,3‐BD yield was ∼80 % of the theoretical yield using 25 g/L of glucose and lactose, corresponding to 0.38 g/g saccharides at a fermentation time of 48 h (glucose) and 72 h (lactose). However, the 2,3‐BD yield was halved (0.19 g/g galactose), fermenting 25 g/L of galactose at 48 h. Taking into account these results, two important conclusions were determined: i) E. coli JFR12 could transform galactose into 2,3‐BD although its yield was half of the yield observed with glucose at 48 h; and ii) E. coli JFR12 was as efficient as other natural 2,3‐BD producers such as Klebsiella species fermenting lactose. However, the E. coli strain has the advantage of being an innocuous strain. To the best of our knowledge, there is no other study presenting the production of 2,3‐BD from galactose and lactose with a genetically modified E. coli strain.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".