<i>Streptococcus suis</i> Serotype 2 Interactions with Human Brain Microvascular Endothelial Cells
Bibliographic record
Abstract
Streptococcus suis serotype 2 is a worldwide causative agent of many forms of swine infection and is also recognized as a zoonotic agent causing human disease, including meningitis. The pathogenesis of S. suis infections is poorly understood. Bacteria circulate in the bloodstream in the nonimmune host until they come in contact with brain microvascular endothelial cells (BMEC) forming the blood-brain barrier. The bacterial polysaccharide capsule confers antiphagocytic properties. It is known that group B streptococci (GBS) invade and damage BMEC, which may be a primary step in the pathogenesis of neonatal meningitis. Interactions between S. suis and human endothelial cells were studied to determine if they differ from those between GBS and endothelial cells. Invasion assays performed with BMEC and human umbilical vein endothelial cells demonstrated that unlike GBS, S. suis serotype 2 could not invade either type of cell. Adherence assays showed that S. suis adhered only to BMEC, whereas GBS adhered to both types of cell. These interactions were not affected by the presence of a capsule, since acapsular mutants from both bacterial species adhered similarly compared to the wild-type strains. Lactate dehydrogenase release measurements indicated that some S. suis strains were highly cytotoxic for BMEC, even more than GBS, whereas others were not toxic at all. Cell damage was related to suilysin (S. suis hemolysin) production, since only suilysin-producing strains were cytotoxic and cytotoxicity could be inhibited by cholesterol and antisuilysin antibodies. It is possible that hemolysin-positive S. suis strains use adherence and suilysin-induced BMEC injury, as opposed to direct cellular invasion, to proceed from the circulation to the central nervous system.
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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) | 0.003 | 0.001 |
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".