Multispecies Biofilms Transform Selenium Oxyanions into Elemental Selenium Particles: Studies Using Combined Synchrotron X-ray Fluorescence Imaging and Scanning Transmission X-ray Microscopy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Selenium (Se) is an element of growing environmental concern, because low aqueous concentrations can lead to biomagnification through the aquatic food web. Biofilms, naturally occurring microbial consortia, play numerous important roles in the environment, especially in biogeochemical cycling of toxic elements in aquatic systems. The complexity of naturally forming multispecies biofilms presents challenges for characterization because conventional microscopic techniques require chemical and physical modifications of the sample. Here, multispecies biofilms biotransforming selenium oxyanions were characterized using X-ray fluorescence imaging (XFI) and scanning transmission X-ray microscopy (STXM). These complementary synchrotron techniques required minimal sample preparation and were applied correlatively to the same biofilm areas. Sub-micrometer XFI showed distributions of Se and endogenous metals, while Se K-edge X-ray absorption spectroscopy indicated the presence of elemental Se (Se 0 ). Nanoscale carbon K-edge STXM revealed the distributions of microbial cells, extracellular polymeric substances (EPS), and lipids using the protein, saccharide, and lipid signatures, respectively, together with highly localized Se 0 using the Se L III edge. Transmission electron microscopy showed the electron-dense particle diameter to be 50–700 nm, suggesting Se 0 nanoparticles. The intimate association of Se 0 particles with protein and polysaccharide biofilm components has implications for the bioavailability of selenium in the environment.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.007 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 it