Solute Size Effects on the Diffusion in Biofilms of <i>Streptococcus mutans</i>
Bibliographic record
Abstract
The diffusion of poly(ethylene glycol) (PEG) (MW varying between 200 and 10,000), and of three different types of micelles was examined in Streptococcus mutans biofilms using infrared spectroscopy. PEGs were used because they show limited interactions with biological materials and their weight can be selected in order to cover a wide range of size. The study showed that a considerable fraction at the base of the biofilm was not accessible to the diffusing solute molecules and this inaccessible fraction was very dependent on the size of the diffusing molecules. In parallel, it was found that the diffusion coefficients of these solutes in the biofilms were less than those in water and this reduction was less pronounced for large macromolecules, an effect proposed to be related to their limited penetration. Triton X-100, a neutral detergent, forms micelles that behave like PEG, suggesting that the behaviour observed for neutral macromolecules can be extrapolated to neutral macroassemblies. However, the diffusion, as well as the penetration of sodium dodecylsulphate micelles (a negatively charged surfactant) and cetylpyridinium chloride micelles (positively charged), in the biofilms appeared to be significantly influenced by electrostatic interactions with biofilm components. The present findings provide useful insights associated with the molecular parameters required to efficiently penetrate bacterial biofilms. The study suggests a rationale for the limited bactericidal power of some antibiotics (the large ones). The restricted accessibility of macromolecules and macroassemblies to biofilms must be examined carefully in order to offer guidelines in the development of novel antibacterial treatments.
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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 | 0.001 |
| 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 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".