Effect of recombinant Panton–Valentine leukocidin in vitro on apoptosis and cytokine production of human alveolar macrophages
Bibliographic record
Abstract
Panton-Valentine leukocidin (PVL) is associated with rare cases of necrotizing pneumonia that occur in otherwise healthy individuals. Human alveolar macrophages (HAMs) are major effector cells in host defense against infections. However, the impact of PVL on HAMs is uncertain. We evaluated the role of PVL in cytotoxicity and production of inflammatory cytokines secreted by HAMs. HAMs were purified from bronchoalveolar lavage fluid. Recombinant PVL (rPVL) was used in the study to interfere with HAM apoptosis and cytokine production in vitro. Hoechst 33342 fluorescence staining, transmission electron microscopy examination, and flow cytometry indicated that rPVL (10 nmol/L) treatment resulted in HAMs with markedly apoptotic characteristics, and HAMs treated with rPVL at 100 nmol/L showed clear indication of necrosis. A treatment of rPVL at 10 nmol/L elicited the secretion of IL-10 by HAMs relative to untreated control cells, but there was a slight decrease in the constitutive secretion of tumor necrosis factor (TNF)-alpha. Our results indicate that PVL-treated samples decreased HAM viability, leading to apoptosis at low concentrations and necrosis at high concentrations. In addition, PVL-treated cells released increased amounts of IL-10 and decreased amounts of TNF-alpha under apoptosis-inducing concentrations. Therefore, we speculated that PVL could play a negative role in HAM function at lower concentrations.
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) | 0.000 | 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".