Decontamination Efficacy and Skin Toxicity of Two Decontaminants against Bacillus anthracis
Bibliographic record
Abstract
Decontamination of bacterial endospores such as Bacillus anthracis has traditionally required the use of harsh or caustic chemicals. The aim of this study was to evaluate the efficacy of a chlorine dioxide decontaminant in killing Bacillus anthracis spores in solution and on a human skin simulant (porcine cadaver skin), compared to that of commonly used sodium hypochlorite or soapy water decontamination procedures. In addition, the relative toxicities of these decontaminants were compared in human skin keratinocyte primary cultures. The chlorine dioxide decontaminant was similarly effective to sodium hypochlorite in reducing spore numbers of Bacillus anthracis Ames in liquid suspension after a 10 minute exposure. After five minutes, the chlorine dioxide product was significantly more efficacious. Decontamination of isolated swine skin contaminated with Bacillus anthracis Sterne with the chlorine dioxide product resulted in no viable spores sampled. The toxicity of the chlorine dioxide decontaminant was up to two orders of magnitude less than that of sodium hypochlorite in human skin keratinocyte cultures. In summary, the chlorine dioxide based decontaminant efficiently killed Bacillus anthracis spores in liquid suspension, as well as on isolated swine skin, and was less toxic than sodium hypochlorite in cultures of human skin keratinocytes.
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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) | 0.001 | 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".