Confocal Raman microspectroscopy as a tool for studying the chemical heterogeneities of biofilms in situ
Bibliographic record
Abstract
AIMS: To investigate the use of confocal Raman microspectroscopy (CRM) for the analysis of the structure, composition and development of fully hydrated biofilms. METHODS AND RESULTS: Pseudomonas aeruginosa PAO1 biofilms were cultured in a flow cell in minimal nutrient medium (artificial sea water) and their development was followed for up to 3 weeks. The spectroscopic signature of the biofilm cells and extracellular polymeric substances (EPS) were differentiated and their distribution in biofilm colonies and within water channels was mapped in-plane and -depth. The colonies were initially amorphous, mainly composed of cells with no detectable amount of EPS. They developed rapidly to give round colonies composed of a cellular core enclosed in a sheath of EPS. The EPS continued to increase and spread throughout the biofilm to become the dominating feature of aged colonies. Colonies with a liquid core morphology - characteristic of the seeding dispersal process - were also observed. CONCLUSIONS: This study demonstrated that CRM can be used to monitor the distribution of biofilm components in fully hydrated undisturbed biofilms over time. SIGNIFICANCE AND IMPACT OF THE STUDY: Confocal Raman microspectroscopy facilitates the analysis of hydrated, live bacterial biofilms as a function of space and time, thus making it a suitable technique for investigating the effects of various additives and environmental factors on biofilm growth.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.001 | 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".