Molecular Trade-Offs between Lattice Oxygen and Oxygen Vacancy Drive Organic Pollutant Degradation in Fungal Biomineralized Exoskeletons
Bibliographic record
Abstract
Fungal-mineral interactions can effectively alleviate cellular stress from organic pollutants, the production of which are expected to rapidly increase owing to the Earth moving into an unprecedented geological epoch, the Anthropocene. The underlying mechanisms that may enable fungi to combat organic pollution during fungal-mineral interactions remain unclear. Inspired by the natural fungal sporulation process, we demonstrate for the first time that fungal biomineralization triggers the formation of an ultrathin (hundreds of nanometers thick) exoskeleton, enriched in nanosized iron (oxyhydr)oxides and biomolecules, on the hyphae. Mapped biochemical composition of this coating at a subcellular scale via high spatial resolution (down to 50 nm) synchrotron radiation-based techniques confirmed aromatic C, C-N bonds, amide carbonyl, and iron (oxyhydr)oxides as the major components of the coatings. This nanobiohybrid system appeared to impart a strong (×2) biofunctionality for fungal degradation of bisphenol A through altering molecular-level trade-offs between lattice oxygen and oxygen vacancy. Together, fungal coatings could act as "artificial spores", which enable fungi to combat physical and chemical stresses in natural environments, providing crucial insights into fungal biomineralization and coevolution of the Earth's lithosphere and biosphere.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".