X-Ray Absorption Near-Edge Structure (XANES) Spectroscopy Study of the Interaction of Silver Ions with Staphylococcus aureus, Listeria monocytogenes, and Escherichia coli
Bibliographic record
Abstract
Silver ions are widely used as antibacterial agents, but the basic molecular mechanism of this effect is still poorly understood. X-ray absorption near-edge structure (XANES) spectroscopy at the Ag LIII, S K, and P K edges reveals the chemical forms of silver in Staphylococcus aureus and Escherichia coli (Ag(+) treated). The Ag LIII-edge XANES spectra of the bacteria are all slightly different and very different from the spectra of silver ions (silver nitrate and silver acetate), which confirms that a reaction occurs. Death or inactivation of bacteria was observed by plate counting and light microscopy. Silver bonding to sulfhydryl groups (Ag-S) in cysteine and Ag-N or Ag-O bonding in histidine, alanine, and DL-aspartic acid was detected by using synthesized silver-amino acids. Significantly lower silver-cysteine content, coupled with higher silver-histidine content, in Gram-positive S. aureus and Listeria monocytogenes cells indicates that the peptidoglycan multilayer could be buffering the biocidal effect of silver on Gram-positive bacteria, at least in part. Bonding of silver to phosphate groups was not detected. Interaction with DNA or proteins can occur through Ag-N bonding. The formation of silver-cysteine can be confirmed for both bacterial cell types, which supports the hypothesis that enzyme-catalyzed reactions and the electron transport chain within the cell are disrupted.
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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 | 0.000 | 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 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".