Pneumolysin induces release of matrix metalloproteinase-8 and -9 from human neutrophils
Bibliographic record
Abstract
The research question addressed in the current study was: does the pneumococcal pore-forming toxin, pneumolysin, mobilise matrix metalloproteinase (MMP) -8 and -9 from isolated human blood neutrophils at sublytic concentrations of 5, 10 and 20 ng.mL(-1)? MMPs were measured in the supernatants of unstimulated neutrophils and of cells exposed to pneumolysin and the chemoattractant N-formyl-L-methionyl-l-leucyl-l-phenylalanine (f-MLP; 0.1 microM), individually and in combination, using ELISA procedures, and alterations in cytosolic Ca(2+) concentrations were monitored using a fura-2 acetoxymethyl ester (fura-2/AM)-based spectrofluorimetric method. Treatment of neutrophils with pneumolysin alone caused dose-related release of both MMPs, whereas f-MLP caused modest increases; the combination of both activators was, however, most effective. Pneumolysin/f-MLP-activated release of the MMPs from the cells was paralleled by increases in cytosolic Ca(2+). Exposure of human neutrophils to pneumolysin is accompanied by mobilisation of MMPs, which is potentiated by f-MLP. If operative in vivo, pneumolysin-mediated release of MMPs from neutrophils and other cell types may contribute to the pathogenesis of severe pneumococcal disease.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".