Effects of cigarette smoke condensate on pneumococcal biofilm formation and pneumolysin
Bibliographic record
Abstract
Although the well-recognised predisposition of cigarette smokers to the development of severe pneumococcal disease may be attributable to impairment of local host defences, less is known about the direct effects of smoke exposure on airway pathogens, or their virulence factors. In the current study, we have investigated the effects of cigarette smoke condensate (CSC) on biofilm formation by Streptococcus pneumoniae, and on the pore-forming activity of its major toxin, pneumolysin. Biofilm formation following exposure of the pneumococcus to CSC (20-160 μg·mL(-1)) was measured using a crystal violet-based spectrophotometric procedure, while the pore-forming activity of recombinant pneumolysin was determined by a fura-2/acetoxymethyl ester-based spectrofluorimetric procedure to monitor the uptake of extracellular Ca(2+) by isolated human neutrophils. Exposure of the pneumococcus or pneumolysin to CSC resulted in significant dose-related augmentation of biofilm formation (p≤0.05 at 80 and 160 μg·mL(-1)) and substantial attenuation of the pore-forming interactions of pneumolysin, respectively. Augmentation of biofilm formation and inactivation of pneumolysin as a consequence of smoking are likely to favour microbial colonisation and persistence, both being essential precursors of pneumococcal disease.
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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) | 0.002 | 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".