Nanoscale aerovirology: An efficient yet simple method to analyze the viral distribution of single bioaerosols
Bibliographic record
Abstract
The aerosolization mechanisms of viruses are poorly known, because of the challenges related to their sampling and observation. For example, single particle studies are needed to improve our understanding of bioaerosol enrichment processes. Such studies would help to develop models of airborne disease propagation. We propose a novel approach to study viral aerosols in single particles using a combination of fluorescence and transmission electron microscopy (TEM). This method allows for rapid analysis of labeled bacteriophages aerosolized and captured on a black membrane filter. It also requires performing image analyses on fluorescent spots. TEM is necessary to determine a single bacteriophage dimensions. Thus, the clustering of bacteriophage PP01 in a single aerosol particle was investigated and found to give a comparable number of virions to what was observed with TEM. The impact of the GFP (green fluorescent protein) in the head of PP01 virion compared to wild type (WT) PP01 was also tested by comparing the clustering of similar bioaerosol sizes generated by the aerosolization of PP01 WT, PP01-GFP, and PP01-GFP labeled with syto-red dye. Surprisingly, the PP01 WT bioaerosols were enriched compared to the PP01-GFP ones (64.9 ± 17.5% more). PP01-GFPs were also found to be more numerous compared to those produced by PP01-GFP labeled with syto-red dye (28.9 ± 16.9% more). The aerosolization process might be dependent on the electrochemical properties of the viruses and the environment. Changes of this nature could affect the mechanism of the aerosol formation in natural forming aerosols as demonstrated in this study for artificially generated aerosols.© 2016 American Association for Aerosol Research
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| 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".