<i>Birc1e/Naip5</i>in Macrophage Function and Susceptibility to Infection with<i>Legionella pneumophila</i>
Bibliographic record
Abstract
Genetic analysis in the mouse has been used to identify host genes and proteins that play important roles in natural defences against a broad range of infectious diseases. In mouse, susceptibility to infection with Legionella pneumophila is genetically controlled. Intracellular pathogens have evolved different strategies to inhibit or escape the bacteriostatic or bactericidal defense mechanisms of host macrophages. Electron microscopy studies indicated that Legionella-containing phagosome (LCP) morphology diverges from classic phagosomes: within the first 5 min of infection, LCPs become surrounded by host vesicles; 15 min postinfection, the thickness of the phagosomal membrane resembles that of the endoplasmic reticulum (ER), and 6 h after infection, ribosomes are found attached to the cytoplasmic face of LCPs. Nontransgenic permissive A/J peritoneal and bone marrow-derived macrophages allowed massive L. pneumophila replication over a 72-h infection period (2.8 ± 0.3 and 1.6 ± 0.4 log CFU respectively) compared to macrophages from Birc1e/Naip5-resistant transgenic animals (0.74 ± 0.18 and -0.52 ± 0.26 log CFU respectively). It has been proposed that, like other members of the NLR family, Birc1e/Naip5 may function as an intracellular sensor of L. pneumophila products and may trigger immune responses through inflammatory caspases.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".