Entry of the bacterial pathogen Listeria monocytogenes into mammalian cells
Bibliographic record
Abstract
The bacterial pathogen Listeria monocytogenes causes food-borne illnesses leading to meningitis or abortion. Listeria provokes its internalization ('entry') into mammalian cells that are normally non-phagocytic, such as intestinal epithelial cells and hepatocytes. Entry provides access to a nutrient-rich cytosol and allows translocation across anatomical barriers. Here I discuss the two major internalization pathways used by Listeria. These pathways are initiated by binding of the bacterial surface proteins InlA or InlB to their respective host receptors, E-cadherin or Met. InlA mediates traversal of the intestinal barrier, whereas InlB promotes infection of the liver. At the cellular level, both InlA- and InlB-dependent entry require host signalling that promotes cytoskeletal rearrangements and pathogen engulfment. However, many of the specific signalling proteins in the two entry routes differ. InlA-mediated uptake uses components of adherens junctions that are coupled to F-actin and myosin, whereas InlB-dependent entry involves cytosolic adaptors that bridge Met to regulators of F-actin, including phosphoinositide 3-kinase and activators of the Arp2/3 complex. Unexpectedly, entry directed by InlB also involves endocytic components. Future work on InlA and InlB will lead to a better understanding of virulence, and may also provide novel insights into the normal biological functions of E-cadherin and Met.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.004 | 0.007 |
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".