Investigating Klebsiella pneumoniae biofilm preservation for scanning electron microscopy
Bibliographic record
Abstract
Klebsiella pneumoniae biofilm formation is associated with chronic and relapsing infections. Scanning electron microscopy (SEM) is a powerful tool for characterizing biofilm structure and studying their formation. Reliable visualization of biofilm structure requires careful sample preservation, otherwise there may be loss of non-covalent interactions that are susceptible to damage during the dehydration and washing preparation steps. However, no standard procedure has been adopted in the literature to fix K. pneumoniae biofilm for scanning electron microscopy studies. This lack of standardization makes it challenging to compare results between studies and determine the degree to which native structures have been preserved. To advance this critical area of study, we investigated different scanning electron microscopy fixation methods for K. pneumoniae biofilm preservation. Our study reveals the impact preparation steps can have on retaining in biofilm architecture observed using scanning electron microscopy. Using fixation methods developed through our studies, we show that although species that overproduce capsular extracellular polysaccharides produced more robust biofilms, K. pneumoniae can form a developed biofilm in the absence of capsular polysaccharides.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".