Characterization of the Diffusion of Polyethylene Glycol in <i>Streptococcus Mutans</i> Biofilms by Raman Microspectroscopy
Bibliographic record
Abstract
We used Raman microspectroscopy to investigate in situ the spatial distribution of the biomass in Streptococcus mutans biofilms. We used the CH stretching band to probe the organic matter and the area of the OH stretching band as an internal intensity standard, the biofilms being highly hydrated. The size of the biofilm regions that were mapped was 300 x 300 microm. We also recorded, in the confocal mode, the z profiles describing the biomass distribution as a function of depth in the biofilms. In our growth conditions, the biofilm is described as an approximately 75 microm thick mat completely covering the surface and includes columnar clusters with a diameter of approximately 100 microm surrounded by voids filled with water. Raman mapping was also used to examine the diffusion of HOD and polyethylene glycol with a molar mass of 10,000 (PEG-10k) in the biofilms. This study establishes that HOD can diffuse practically everywhere in the biofilms but that the penetration of PEG-10k is limited. There is a correlation between the restricted penetration of the macromolecule and the biomass content in the different regions of the biofilms. The method presented here provides a convenient approach to determine the diffusion of molecules, including antibacterials, in bacterial biofilms.
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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 | 0.000 |
| 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 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".