Synergy effect of heat and UV photons on bacterial-spore inactivation in an N<sub>2</sub>–O<sub>2</sub> plasma-afterglow sterilizer
Bibliographic record
Abstract
As a rule, medical devices (MDs) made entirely from metals and ceramics can withstand, for sterilization purposes, elevated temperatures such as those encountered in autoclaves (moist heat ⩾120 °C) or Poupinel (Pasteur) ovens (dry heat ⩾160 °C). This not the case with MDs containing polymers: 70 °C seems to be a limit beyond which their structural and functional integrity will be compromised. Nonetheless, all the so-called low-temperature sterilization techniques, relying essentially on some biocidal chemistry (e.g. ethylene oxide, H2O2, O3), are operated at temperatures close to 65 °C, essentially to enhance the chemical reactivity of the biocidal agent. Based on this fact, we have examined the influence of increasing the temperature of the polystyrene Petri dish containing B. atrophaeus bacterial spores when exposing them to UV radiation coming from an N2–O2 flowing plasma afterglow. We have observed that, for a given UV radiation intensity, the inactivation rate increases with the temperature of the Petri dish, provided heat and UV photons are applied simultaneously, a clear case of synergistic effect. More specifically, it means that (i) simply heating the spores at temperatures below 65 °C without irradiating them with UV photons does not induce mortality; (ii) there is no additional increase in the inactivation rate when the Petri has been pre-heated and then brought back to ambient temperature before the spores are UV irradiated; (iii) no additional inactivation results from post-heating spores previously inactivated with UV radiation. Undoubtedly, the synergistic effect shows up only when the physico-chemical agents (UV photons and temperature) are simultaneously in action.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".