Validation of cold plasma treatment for protein inactivation: a surface plasmon resonance-based biosensor study
Why this work is in the frame
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Bibliographic record
Abstract
Gas plasma is being proposed as an interesting and promising tool to achieve sterilization. The efficacy of gas plasma to destroy bacterial spores (the most resistant living microorganisms) has been demonstrated and documented over the last ten years. In addition to causing damage to deoxyribonucleic acid by UV radiation emitted by excited species originating from the plasma, gas plasma has been shown to promote erosion of the microorganism in addition to possible oxidation reactions within the microorganism. In this work, we used lysozyme as a protein model to assess the effect of gas plasma on protein inactivation. Lysozyme samples have been subjected to the flowing afterglow of a gas discharge achieved in a nitrogen–oxygen mixture. The efficiency of this plasma treatment on lysozyme has been tested by two different assays. These are an enzyme-linked immunosorbent assay (ELISA) and a surface plasmon resonance (SPR)-based biosensor assay. The two methods showed that exposure to gas plasma can abrogate lysozyme interactions with lysozyme-specific antibodies, more likely by destroying the epitopes responsible for the interaction. More specifically, two SPR-based assays were developed since our ELISA approach did not allow us to discriminate between background and low, but still intact, quantities of lysozyme epitope after plasma treatment. Our SPR results clearly demonstrated that significant protein destruction or desorption was achieved when amounts of lysozyme less than 12.5 ng had been deposited in polystyrene 96-well ELISA plates. At higher lysozyme amounts, traces of available lysozyme epitopes were detected by SPR through indirect measurements. Finally, we demonstrated that a direct SPR approach in which biosensor-immobilized lysozyme activity is directly measured prior and after plasma treatment is more sensitive, and thus, more appropriate to define plasma treatment efficacy with more certainty.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 it