Analysis of biofilm expansion rate of <i>Bacillus subtilis</i> (MTC871) on agar substrates with different stiffness
Bibliographic record
Abstract
The surface morphology of mature biofilms is heterogeneous and can be divided into concentric rings wrinkles (I), labyrinthine networks wrinkles (II), radial ridges wrinkles (III), and branches wrinkles (IV), according to surface wrinkle structure and distribution characteristics. Due to the wrinkle structures, channels are formed between the biofilm and substrate and transport nutrients, water, metabolic products, etc. We find that expansion rate variations of biofilms growing on substrates with high and low agar concentrations (1.5, 2.0, 2.5 wt.%) are not in the same phase. In the first 3 days' growth, the interaction stress between biofilm and each agar substrate increases, which makes the biofilm expansion rate decreases before wrinkle pattern IV (branches) comes up. After 3 days, in the later growth stage after wrinkle pattern IV appears, the biofilm has larger expansion rate growing on 2.0 wt.% agar concentration, which has the larger wrinkle distance in wrinkle pattern IV reducing energy consumption. Our study shows that the stiff substrate does not always inhibit the biofilm expansion, although it does in the earlier stage; after that, mature biofilms acquire larger expansion rate by adjusting the growth mode through the wrinkle evolution even in nutrient extremely depletion.
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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) | 0.001 | 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".