Morphological, Microstructural, and In Situ Chemical Characteristics of Siderite Produced by Iron-Reducing Bacteria
Bibliographic record
Abstract
Dissimilatory iron-reducing bacteria (DIRB) oxidize organic matter or hydrogen and reduce ferric iron to form Fe(II)-bearing minerals, such as magnetite and siderite. However, compared with magnetite, which was extensively studied, the mineralization process and mechanisms of siderite remain unclear. Here, with the combination of advanced electron microscopy and synchrotron-based scanning transmission X-ray microscopy (STXM) approaches, we studied in detail the morphological, structural, and chemical features of biogenic siderite via a growth experiment with Shewanella oneidensis MR-4. Results showed that along with the growth of cells, Fe(II) ions were increasingly released into solution and reacted with CO 3 2– to form micrometer-sized siderite minerals with spindle, rod, peanut, dumbbell, and sphere shapes. They are composed of many single-crystal siderite plates that are fanned out from the center of the particles. Additionally, STXM revealed Fh and organic molecules inside siderite. This suggests that the siderite crystals might assemble around a Fh-organic molecule core and then continue to grow radially. This study illustrates the biomineralization and assembly of siderite by a successive multistep growth process induced by DIRB, also provides evidences that the distinctive shapes and the presence of organic molecules inside might be morphological and chemical features for biogenic siderite.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".