Vesicle self-assembly of amphiphilic siderophores produced by bacterial isolates from Soap Lake, Washington
Bibliographic record
Abstract
Soap Lake, located in Washington State, is a meromictic soda lake that was the subject of a prior National Science Foundation funded Microbial Observatory. Several organisms inhabiting this lake have been identified as producers of siderophores that are unique in structure. Two isolates found to be of the species Halomonas, SL01 and SL28, were found to produce suites of amphiphilic siderophores consisting of a peptidic head-group, which binds iron appended to fatty acid moieties of various lengths. The ability for siderophores to self-assemble into vesicles was determined for three suites of amphiphilic siderophores of unique structure (two from SL01 and one from SL28). These siderophores resemble the amphiphilic aquachelin siderophores produced by Halomonas aquamarina strain DS40M3, a marine bacterium. Vesicle self-assembly studies were performed by dynamic light scattering and epifluorescence microscopy. The addition of ferric iron (Fe3+) at different equivalents, where an equivalence of iron is defined as equal to the molarity of the siderophore, demonstrated vesicle formation. This was suggested by both dynamic light scattering and epifluorescence microscopy. Bacteria thriving under saline and alkaline conditions are capable of producing unique siderophores that self-assemble in micelles and vesicles due to ferric iron chelation.
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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) | 0.000 | 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".