Packaging materials for plasma sterilization with the flowing afterglow of an N<sub>2</sub>–O<sub>2</sub> discharge: damage assessment and inactivation efficiency of enclosed bacterial spores
Bibliographic record
Abstract
In conventional sterilization methods (steam, ozone, gaseous chemicals), after their proper cleaning, medical devices are wrapped/enclosed in adequate packaging materials, then closed/sealed before initiating the sterilization process: these packaging materials thus need to be porous. Gaseous plasma sterilization being still under development, evaluation and comparison of packaging materials have not yet been reported in the literature. To this end, we have subjected various porous packagings used with conventional sterilization systems to the N2–O2 flowing afterglow and also a non-porous one to evaluate and compare their characteristics towards the inactivation of B. atrophaeus endospores deposited on a Petri dish and enclosed in such packagings. Because the sterilization process with the N2–O2 discharge afterglow is conducted under reduced-pressure conditions, non-porous pouches can be sealed only after returning to atmospheric pressure. All the tests were therefore conducted with one end of the packaging freely opened, post-sealing being required. The features of these packaging materials, namely mass loss, resistance, toxicity to human cells as well as some characteristics specific to the plasma method used such as ultraviolet transparency, were examined before and after exposure to the flowing afterglow. All of our results show that the non-porous packaging considered is much more suitable than the conventionally used porous ones as far as ensuring an efficient and low-damage sterilization process with an N2–O2 plasma-afterglow is concerned.
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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".