Sporosarcina pasteurii can form nanoscale calcium carbonate crystals on cell surface
Bibliographic record
Abstract
The bacterium Sporosarcina pasteurii (SP) is known for its ability to cause the phenomenon of microbially induced calcium carbonate precipitation (MICP). We explored bacterial participation in the initial stages of the MICP process at the cellular length scale under two different growth environments (a) liquid culture (b) MICP in a soft agar (0.5%) column. In the liquid culture, ex-situ imaging of the cellular environment indicated that S. pasteurii was facilitating nucleation of nanoscale crystals of calcium carbonate on bacterial cell surface and its growth via ureolysis. During the same period, the meso-scale environment (bulk medium) was found to have overgrown calcium carbonate crystals. The effect of media components (urea, CaCl2), presence of live and dead in the growth medium were explored. The agar column method allows for in-situ visualization of the phenomena, and using this platform, we found conclusive evidence of the bacterial cell surface facilitating formation of nanoscale crystals in the microenvironment. Here also the bulk environment or the meso-scale environment was found to possess overgrown calcium carbonate crystals. Extensive elemental analysis using Energy dispersive X-ray spectroscopy (EDS) and X-ray powder diffraction (XRD), confirmed that the crystals to be calcium carbonate, and two different polymorphs (calcite and vaterite) were identified. Active participation of S. pasteurii cell surface as the site of calcium carbonate precipitation has been shown using EDS elemental mapping with Scanning transmission electron microscopy (STEM) and scanning electron microscopy (SEM).
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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) | 0.000 | 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".