Distribution of extracellular adhesins in environmental biofilms and flocs: Reimagining the microbial structure
Bibliographic record
Abstract
Extracellular cellular adhesins facilitate microbial aggregation; however, most of the information about extracellular adhesins is based on pure culture studies. In this study, we characterized the hydrophobic characteristics and distribution of the extracellular adhesins in environmental biofilms and flocs. The hydrophobic characteristics of the extracellular adhesins were studied by sonicating the microbial aggregates to disperse the cells and by fractionating them using the microbial adhesion to the hydrocarbon method. Furthermore, we probed environmental biofilms and flocs using immunohistochemistry coupled with confocal laser scanning microscopy for reimaging the microbial aggregates based on extracellular adhesins. Small flocs have a relatively dispersed distribution of extracellular adhesins (flagella, fimbriae, pili, and amyloid adhesins). The stratified distribution of extracellular adhesins was observed in environmental biofilms. It was observed that the pili and amyloid adhesins were predominantly present in the core of biofilms, whereas flagella and fimbriae were present in the outer layer of the microbial aggregates. The dispersion of microbial aggregates is one of the limiting factors that challenge the sustainable application of wastewater treatment processes. Greater attention to the components of extracellular protein (such as the adhesins) is required to understand the aggregation of dispersible environmental microbial aggregates.
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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".