Crosstalk between nucleocytoplasmic trafficking and the innate immune response to viral infection
Bibliographic record
Abstract
The nuclear pore complex is the sole gateway connecting the nucleoplasm and cytoplasm. In humans, the nuclear pore complex is one of the largest multiprotein assemblies in the cell, with a molecular mass of ∼110 MDa and consisting of 8 to 64 copies of about 34 different nuclear pore proteins, termed nucleoporins, for a total of 1000 subunits per pore. Trafficking events across the nuclear pore are mediated by nuclear transport receptors and are highly regulated. The nuclear pore complex is also used by several RNA viruses and almost all DNA viruses to access the host cell nucleoplasm for replication. Viruses hijack the nuclear pore complex, and nuclear transport receptors, to access the nucleoplasm where they replicate. In addition, the nuclear pore complex is used by the cell innate immune system, a network of signal transduction pathways that coordinates the first response to foreign invaders, including viruses and other pathogens. Several branches of this response depend on dynamic signaling events that involve the nuclear translocation of downstream signal transducers. Mounting evidence has shown that these signaling cascades, especially those steps that involve nucleocytoplasmic trafficking events, are targeted by viruses so that they can evade the innate immune system. This review summarizes how nuclear pore proteins and nuclear transport receptors contribute to the innate immune response and highlights how viruses manipulate this cellular machinery to favor infection. A comprehensive understanding of nuclear pore proteins in antiviral innate immunity will likely contribute to the development of new antiviral therapeutic strategies.
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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 | 0.002 | 0.002 |
| 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) | 0.003 | 0.002 |
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".