Antimicrobial Mechanisms of Macrophages and the Immune Evasion Strategies of Staphylococcus aureus
Bibliographic record
Abstract
Habitually professional phagocytes, including macrophages, eradicate microbial invaders from the human body without overt signs of infection. Despite this, there exist select bacteria that are professional pathogens, causing significant morbidity and mortality across the globe and Staphylococcus aureus is no exception. S. aureus is a highly successful pathogen that can infect virtually every tissue that comprises the human body causing a broad spectrum of diseases. The profound pathogenic capacity of S. aureus can be attributed, in part, to its ability to elaborate a profusion of bacterial effectors that circumvent host immunity. Macrophages are important professional phagocytes that contribute to both the innate and adaptive immune response, however from in vitro and in vivo studies, it is evident that they fail to eradicate S. aureus. This review provides an overview of the antimicrobial mechanisms employed by macrophages to combat bacteria and describes the immune evasion strategies and some representative effectors that enable S. aureus to evade macrophage-mediated killing.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".