Bacterial involvement in determining domoic acid levels in Pseudo-nitzschia multiseries cultures
Bibliographic record
Abstract
This study examining factors contributing to the production or elimination of domoic acid (DA) in cultures of Pseudo-nitzschia multiseries showed that in axenic cultures doubling the silicate concentrations increased growth, but not DA levels. DA concentration for axenic cultures was increased by the addition of gluconolactone (GlcA), especially in cultures with increased silicon. In non-axenic cultures, there were similar increases in growth with increased silicon, but a reduction of DA production in the presence of GlcA. Detailed examinations confirmed these findings and also showed that in non-axenic cultures, glucose alone resulted in a reduction of DA while a combination of glucose with gluconolactone resulted in a complete elimination of DA. Subsequent trials with axenic P. multiseries cultures showed that additions of DA or DA plus glucose introduced at the early stationary growth phase and incubated for 5 d had no impact on DA concentrations. In contrast, a 6 d incubation of the associated bacteria separated from the non-axenic diatom cultures showed reductions of added DA concentrations ranging from 46 to 72%, depending upon co-additives. The diatom does not use extracellular DA present in surrounding culture medium whereas bacteria associated with the diatom can utilize DA readily. Reductions in the production of DA by aging P. multiseries cultures appear to be the result of changing balances over time among bacteria associated with the diatom. These data coupled with results from other studies indicate that the amount of DA measured in P. multiseries cultures is a result of competitive interaction, i.e. a function of the diatom's production rate versus the extra-cellular utilization of DA by associated bacteria.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".