Dymanics of Neisseria meningitidis interactions with human cellular barriers and immune effectors
Bibliographic record
Abstract
Neisseria meningitidis outer membrane (OM) adhesins, Opa and Opc are known to exert significant influence on bacterial adhesion and invasion properties. They are also likely to affect the dynamics of cellular barrier penetration as they target human receptors that are subject to upregulation under inflammatory conditions. As some of the targeted receptors are also expressed on immune cells, it is possible that the OM proteins, when presented on bacteria or in OM vesicle vaccines, have the additional capacity to modulate host immune responses. In our recent studies, in vitro model systems were used to further explore these possibilities. The studies illustrated that the major human receptors targeted by Opa and Opc, i.e. CEACAMs and integrins, when upregulated by inflammatory cytokines, encourage enhanced cellular adhesion, invasion and barrier traversal. Tissue infiltration by fully capsulate bacteria via Opa proteins was also observed for piliated Opa+ meningococci. Other studies indicate that Opc increases meningococcal resistance to serum-mediated killing by binding to the complement regulatory molecule vitronectin. In addition, although adverse immunomodulatory effects have been reported for Opa-expressing gonococci and meningococcal OMVs, our studies indicate that interactions with CD4+ T cell expressed CEACAM1 does not offer immunomodulatory properties to meningococci.
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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".