Mapping the Speciation of Iron in <i>Pseudomonas aeruginosa</i> Biofilms Using Scanning Transmission X-ray Microscopy
Bibliographic record
Abstract
An important feature of microbial communities is the spatial heterogeneity of extracellular chemistry. Scanning transmission X-ray microscopy (STXM) was used to map the spatial distribution of iron speciesthroughout Pseudomonas aeruginosa biofilms to assess the influence of chemical heterogeneity on biomineralization. P. aeruginosa biofilms were treated with Fe(III)-amended media. Speciation and quantitative mapping using STXM image sequences in the Fe 2p(3/2) (L3) absorption edge region revealed both Fe(II) and Fe(III) in localized microenvironments. Fe(III) was mainly associated with cell surfaces, while small amounts of Fe(II) was found in the extracellular space. Biofilms were also characterized using C 1s edge STXM image sequences. Anaerobic growth assays and confocal microscopy revealed the inability of P. aeruginosa to directly reduce Fe(III), implicating indirect iron reduction mechanisms in the formation of fine-grained, multivalent minerals. These studies suggest that geochemical microenvironments found throughout microbial communities are even more complex than previously believed.
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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".