REDUCTION AND TRANSPORT OF ORGANICALLY BOUND IRON BY <i>THALASSIOSIRA OCEANICA</i> (BACILLARIOPHYCEAE)
Bibliographic record
Abstract
Thalassiosira oceanica (Hustedt) Hasle et Heimdal (clone 1003) attained rapid rates of growth in low Fe seawater containing the siderophore ferrioxamine B (FeDFB) as the sole Fe source. Short‐term rates of Fe uptake were 109 times faster than those predicted from the equilibrium concentration of inorganic Fe, suggesting that FeDFB was the substrate for the Fe transport system. An extracellular reduction step, mediated by a cell surface reductase, preceded Fe transport from FeDFB and was induced under Fe limitation. The half‐saturation constant for the reduction was 0.68 μM. Iron reduction rates were two times faster than uptake rates, so that the activities of the reductase and the transporter were tightly coupled. The rates of Fe reduction of a number of Fe chelators, including synthetic organic ligands (nitrilotriacetate, diethylenetriaminepentaacetate, and EDTA) and fungal siderophores (desferrioxamine B and desferrioxamine E), were inversely proportional to the ratio of the stability constants of their Fe(III) and Fe(II) complexes and varied by a factor of two times, like the redox potentials of the Fe complexes. Platinum (II), a known inhibitor of Fe reductase activity, appeared to reduce the rates of Fe uptake from FeDFB but not from inorganic complexes. The results suggested that reoxidation of Fe(II) produced by reduction may be a necessary part of the Fe internalization reaction. Ferric reductase could be relevant to phytoplankton nutrition in the open sea where organic Fe complexes dominate the dissolved speciation and where the concentration of inorganic Fe is limiting.
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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) | 0.000 | 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 | 0.000 |
| 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".