Analysis of Force Interactions between AFM Tips and Hydrophobic Bacteria Using DLVO Theory
Bibliographic record
Abstract
Microbial adhesion to surfaces and interfaces is strongly influenced by their structure and physicochemical properties. We used atomic force microscopy (AFM) to measure the forces between chemically functionalized AFM tips and two bacterial species exhibiting different cell surface hydrophobicities, measured as the oil/water contact angle (theta): Acinetobacter venetianus RAG-1 (theta = 56.4 degrees ) and Rhodococcus erythropolis 20S-E1-c (theta = 152.9 degrees ). The forces were measured as the AFM tips, coated with either hydrophobic (octadecane) or hydrophilic (undecanol) groups, approached the bacterial cells in aqueous buffer. The experimental force curves between the two microbial cells and functionalized AFM probes were not successfully described by the classical Derjaguin-Landau-Verwey-Overbeek (DLVO) theory of colloid stability. To reconcile the discrepancy between theory and experiments, two types of extended DLVO models were proposed. The first modification considers an additional acid-base component that accounts for attractive hydrophobic interactions and repulsive hydration effects. The second model considers an additional exponentially decaying steric interaction between polymeric brushes in addition to the acid-base interactions. These extended DLVO predictions agreed well with AFM experimental data for both A. venetianus RAG-1, whose surface consists of an exopolymeric capsule and pili, and R. erythropolis 20S-E1-c, whose surface is covered by an exopolymeric capsule. The extended models for the bacteria-AFM tip force-distance curves were consistent with the effects of steric interactions.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".