Nanoscale imaging approaches to quantifying the electrical properties of pathogenic bacteria
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Biofilms are natural, resilient films formed when microorganisms adhere to a surface and form a complex three-dimensional structure that allows them to persist in a wide variety of environments. Readily forming in hospitals and on medical equipment, biofilms are frequent causes of infections and their subsequent complications. Due to the complexity of these structures, systematically studying individual bacterial cells and their interactions with their surrounding environment will provide a deeper understanding of the processes occurring within the biofilm as whole versus bulk population based methods that do not differentiate individual cells or species. Methods based on atomic force microscopy (AFM) are particularly suited to the study of individual cells, but are underutilized for the study of bacterial electrical properties. The ability of electrical currents to impair bacterial attachment is well documented, but to utilize electrical current as an effective antibacterial treatment, it is important to understand the electrical properties of bacteria. Therefore, we used AFM, Kelvin probe force microscopy, and ResiScope (module to perform conductive AFM) to measure the surface potential and conductance of Psuedomonas aeruginosa and methicillin resistance Staphylococcus aureus (MRSA) on gold and stainless steel. This is the first study to directly measure the electrical resistance of single bacterial cells using ResiScope. Our goal was to develop a framework for measuring biological molecules using conductive AFM. We found that the average resistance for P. aeruginosa was 135 ± 25 GΩ, while MRSA had an average of 173 ± 16 GΩ. Using KPFM, the surface potential of MRSA shifted from −0.304 V to 0.153 V and from −0.280 V to 0.172 V for P. aeruginosa on gold versus stainless steel substrates, respectively. In an attempt to identify a potential charge carrier, peptidoglycan was also measured with the ResiScope module and shown to have a resistance of 105 GΩ.
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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) | 0.000 | 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) | 0.000 | 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