Influence of Substrate Materials on Inactivation of <i>B. atrophaeus</i> Endospores in a Reduced‐pressure Argon Plasma
Bibliographic record
Abstract
Abstract High disinfection level/sterilization of medical devices (MDs) can be achieved through plasma immersion in an argon discharge operated at reduced pressure (100 Pa). The plasma source is a high‐frequency (HF) discharge from our laboratories. The power density absorbed in this system is low enough to allow the continuous processing of thermally‐sensitive materials. Bacterial B. atrophaeus endospores are deposited either on glass or polystyrene (PS) Petri dishes and thereafter subjected to the argon discharge. The role of these substrates in the spore inactivation process is analysed by means of spore survival curves and through examination by a scanning electron microscope of possible structural damage to the spore morphology. In addition, optical emission spectroscopy (OES) is performed in the presence of the glass and PS Petri dishes in the discharge, and modifications to the surface characteristics of the exposed substrates are evaluated by contact angle measurements and X‐ray photoelectron spectroscopy (XPS). It is found that: (i) inactivation of spores is less effective when they are deposited on PS substrates; (ii) spores deposited on glass are eroded while those on polystyrene are left almost morphologically intact; (iii) the OES spectrum from the discharge is not affected when glass substrates are introduced into it, whereas the presence of PS substrates strongly modifies it; (iv) exposed PS substrates show surface modifications, as revealed by contact‐angle measurements and XPS analysis; (v) the presence of air impurities in the discharge, even at very low levels, seems to play a key role in the inactivation process, in particular by leading to the generation of UV photons. The results obtained underline the need for a thorough evaluation and control of the materials from which the MDs are made. magnified image
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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".