An improved medium for the anaerobic growth of Paracoccus denitrificans Pd1222
Bibliographic record
Abstract
Paracoccus denitrificans is a well studied model organism with respect to its aerobic and anaerobic respiratory enzymes. However, until now, the growth medium for this organism has not been optimized for anaerobic growth. In particular, the requirements of P. denitrificans for trace elements (TEs) are not well known. In the present study we aimed to improve growth rates of P. denitrificans Pd1222 on a defined medium under anoxic conditions. We designed media containing different combinations of TEs at various concentrations, and tested their performance against previously reported media. Our results suggest that growth rate and yield depend on the availability and concentration of TEs in the medium. A chelated TE solution was more suitable than an acidified TE solution. Highest growth rates were achieved with medium comprising the TEs iron, manganese, molybdenum, copper and zinc ranging from 0.1 to 9 μM. On this medium, P. denitrificans Pd1222 grew with a generation time of 4.4 h under anoxic conditions and 2.8 h under oxic conditions. Diauxic growth was clearly shown with respect to nitrate and nitrite reduction under anoxic conditions.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".