Biofilm formation by virulent and non-virulent strains of Haemophilus parasuis
Bibliographic record
Abstract
Haemophilus parasuis is a commensal bacterium of the upper respiratory tract of healthy pigs. It is also the etiological agent of Glässer's disease, a systemic disease characterized by polyarthritis, fibrinous polyserositis and meningitis, which causes high morbidity and mortality in piglets. The aim of this study was to evaluate biofilm formation by well-characterized virulent and non-virulent strains of H. parasuis. We observed that non-virulent strains isolated from the nasal cavities of healthy pigs formed significantly (p < 0.05) more biofilms than virulent strains isolated from lesions of pigs with Glässer's disease. These differences were observed when biofilms were formed in microtiter plates under static conditions or formed in the presence of shear force in a drip-flow apparatus or a microfluidic system. Confocal laser scanning microscopy using different fluorescent probes on a representative subset of strains indicated that the biofilm matrix contains poly-N-acetylglucosamine, proteins and eDNA. The biofilm matrix was highly sensitive to degradation by proteinase K. Comparison of transcriptional profiles of biofilm and planktonic cells of the non-virulent H. parasuis F9 strain revealed a significant number of up-regulated membrane-related genes in biofilms, and genes previously identified in Actinobacillus pleuropneumoniae biofilms. Our data indicate that non-virulent strains of H. parasuis have the ability to form robust biofilms in contrast to virulent, systemic strains. Biofilm formation might therefore allow the non-virulent strains to colonize and persist in the upper respiratory tract of pigs. Conversely, the planktonic state of the virulent strains might allow them to disseminate within the host.
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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".