BIOLOGICAL AVAILABILITY OF IRON TO THE FRESHWATER CYANOBACTERIUM <i>ANABAENA FLOS‐AQUAE</i><sup>1</sup>
Bibliographic record
Abstract
Iron acquisition from various ferric chelates and colloids was studied using iron‐limited cells of Anabaena flos‐aquae (Lyng.) Brèb UTEX 1444, a cyanobacterial strain that produces high levels of siderophores under iron limitation. Various chelators of greatly varying affinity for Fe3+ (HEDTA, EDDHA, desferrioxamine mesylate, HBED, 8‐hydroxyquinoline) were assayed for the degree of iron acquisition by iron‐limited cyanobacterial cells. Iron uptake rates (measured by graphite furnace atomic absorption spectrometry) varied approximately inversely with calculated [Fe3+] (calculated as pFe) and decreased with increasing chelator‐to‐iron ratio. No iron uptake was observed when Fe3+ was chelated with HBED, the strongest of the tested chelators. Iron‐limited Anabaena cells were able to take up iron from 8‐hydroxyquinoline (oxine or 8HQ), a compound sometimes used to quantify aquatic iron bioavailability. Iron bound to purified humic acid was poorly available but did support some growth at high humic acid concentrations. These results suggest that for cyanobacteria, even tightly bound iron is biologically available, including to a limited extent iron bound to humic acids. However, iron bound to some extremely strong chelators (e.g. HBED) is likely to be biologically unavailable.
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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) | 0.001 | 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".