Quantifying Diffusion in a Biofilm of <i>Streptococcus mutans</i>
Bibliographic record
Abstract
In biofilms, diffusion may limit the chemical activity of nutrients, toxic compounds, and medicines. This study provides direct, noninvasive insight into the factors that will most effectively limit the transport of antibiotics and biocides in biofilms. Self-diffusion coefficients have been determined for a number of fluorescent probes in biofilms of Streptococcus mutans using fluorescence correlation spectroscopy. The effects of probe size and charge and the roles of biofilm pH, ionic strength, and heterogeneity were studied systematically. The relative diffusion coefficients (D in the biofilm divided by that in water) decreased with increasing probe size (3,000-molecular-weight [3K], 10K, 40K, 70K, and 2,000K dextrans). Studies using variably charged substrates (tetramethylrhodamine, Oregon Green, rhodamine B, and rhodamine 6G) showed that the self-diffusion coefficients decreased with an increasing negative charge of the fluorescent probes. No significant effect was observed for changes to the ionic strength (10⁻⁴ to 10⁻¹ M) or pH (4 to 9) of the biofilm. Biofilm heterogeneity was responsible for variations of ca. one order of magnitude in the diffusion coefficients.
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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 | 0.000 | 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 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".