Enhancing sterilization efficacy: Evaluating bacterial resistance to supercritical CO2
Bibliographic record
Abstract
Sterilization using supercritical CO₂ (scCO₂) can be conducted at relatively low temperatures but additive-assisted treatments are often required for the complete inactivation of dried resistant strains. Such treatments have not been validated across a panel of relevant target microorganisms. This study aimed to investigate the bacterial reduction of 16 bacterial strains with known resistance to diverse environmental stressors. The selection included strains of Escherichia coli and Bacillus spp. that are highly resistant to wet heat, the heat resistant Geobacillus stearothermophilus , strains of Salmonella with exceptional resistance to dry heat, and Klebsiella pneumoniae isolates from chlorinated wastewater. Treatment of desiccated cells or endospores with scCO 2 at 11 MPa and 40 °C with 200 H 2 O 2 reduced cell counts of most strains by more than 6 log 10 (cfu / mL) but cell counts of G. stearothermophilus , Salmonella and K. pneumoniae were reduced by 1 to 4 log 10 (cfu / mL). Addition of 200 ppm and 400 ppm peracetic acid increased treatment lethality; treatment with scCO 2 at 11 MPa and 40 °C in the presence of 200 H 2 O 2 and 400 ppm peracetic acid reduced cell counts of all strains by more than 6 log 10 (cfu / mL). In conclusion, treatment with scCO 2 at 11 MPa and 40 °C in the presence of H 2 O 2 and peracetic acid reduces cell counts of resistant target microorganisms. This is particularly relevant for the sterilization of implantable and reusable medical devices and serves as a suitable alternative for sterilizing devices that contain heat-sensitive polymers. This graphical abstract was created using BioRender (Created in BioRender) • The resistance to scCO 2 of a panel of strains was investigated at 110 bar and 40 °C. • Vegetative cells or spores were treated after drying. • G. stearothermophilus , Salmonella and K. pneumoniae were the most resistant to scCO 2 . • ScCO 2 treatment with H 2 O 2 and peracetic acid reduced cell counts of resistant microorganisms.
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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 | 0.002 | 0.003 |
| 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 | 0.001 | 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 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".