Biogenic hydroxyapatite synthesis by <i>Bacillus subtilis</i> : An efficient passivator for the reduction of cadmium contamination in agricultural soil
Bibliographic record
Abstract
Abstract Cadmium (Cd) can cause various diseases and threaten human health through its accumulation in crops. In this study, Bacillus subtilis was used to prepare biogenic hydroxyapatite (B‐HAP), and chemical hydroxyapatite (C‐HAP) without microorganisms was produced as the control. The abilities of B‐HAP and C‐HAP to adsorb Cd in aqueous solutions and passivate the migration of Cd in actual soil were analyzed. In the adsorption experiments, the Cd concentration in the solutions decreased by 94.8% and 95.8% when 0.20 mmol of B‐HAP and C‐HAP were added. In the incubation experiment, the soil pH increased from 7.08 to 7.30 and from 7.08 to 7.43 when 0.021% of B‐HAP and C‐HAP were added. B‐HAP had little disturbance to the soil pH value. The results showed that Cd in the mobilizable state, at 0.021% B‐HAP and C‐HAP, respectively, decreased by 38.6% and 36.8% in the actual soil samples. The structure and morphology of B‐HAP were characterized using various techniques, which indicated that the adsorption mode of B‐HAP would change with time from ion exchange to specific adsorption. Therefore, B‐HAP can be used as an effective passivator for Cd removal from agricultural soil. The concentrations of Olsen‐P decreased by 35% when 0.021% B‐HAP was added after 104 days. This study provides insights into the development of novel passivators that benefit soil health and green development and has reference significance for the eco‐friendly regulation of low‐concentration‐Cd–contaminated agricultural soil.
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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".