Using micro-patterned surfaces to inhibit settlement and biofilm formation by <i>Bacillus subtilis</i>
Bibliographic record
Abstract
Biofilm is a biological complex caused by bacteria attachment to the substrates and their subsequent reproduction and secretion. This phenomenon reduces heat transfer efficiency and causes significant losses in treated sewage heat-recovering systems. This paper describes a physical approach to inhibit bacteria settlement and biofilm formation by Bacillus subtilis, which is the dominant species in treated sewage. Here, micro-patterned surfaces with different characteristics (stripe and cube) and dimensions (1-100 μm) were fabricated as surfaces of interest. Model sewage was prepared and a rotating coupon device was used to form the biofilms. Precision balance, scanning electron microscopy, and confocal laser scanning microscopy (CLSM) were employed to investigate the inhibitory effects and the mechanisms of the biofilm-surface interactions. The results have shown that surfaces with small pattern sizes (1 and 2 μm) all reduced biofilm formation significantly. Interestingly, the CLSM images showed that the surfaces do not play a role in "killing" the bacteria. These findings are useful for future development of new process surfaces on which bacteria settlement and biofilm formation can be inhibited or minimized.
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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".