Evaluation of medium-chain-length polyhydroxyalkanoate production by<i>Pseudomonas putida</i>LS46 using biodiesel by-product streams
Bibliographic record
Abstract
Medium-chain-length polyhydroxyalkanoate (mcl-PHA) production by Pseudomonas putida LS46 was analyzed in shake-flask-based batch reactions, using pure chemical-grade glycerol (PG), biodiesel-derived "waste" glycerol (WG), and biodiesel-derived "waste" free fatty acids (WFA). Cell growth, substrate consumption, mcl-PHA accumulation within the cells, and the monomer composition of the synthesized biopolymers were monitored. The patterns of mcl-PHA synthesis in P. putida LS46 cells grown on PG and WG were similar but differed from that of cells grown with WFA. Polymer accumulation in glycerol-based cultures was stimulated by nitrogen limitation and plateaued after 48 h in both PG and WG cultures, with a total accumulation of 17.9% cell dry mass and 16.3% cell dry mass, respectively. In contrast, mcl-PHA synthesis was independent of nitrogen concentration in P. putida LS46 cells cultured with WFA, which accumulated to 29% cell dry mass. In all cases, the mcl-PHAs synthesized consisted primarily of 3-hydroxyoctanoate (C(8)) and 3-hydroxydecanoate (C(10)). WG and WFA supported similar or greater cell growth and mcl-PHA accumulation than PG under the experimental conditions used. These results suggest that biodiesel by-product streams could be used as low-cost carbon sources for sustainable mcl-PHA production.
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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".