Bibliographic record
Abstract
DNA viruses undertake their replication within the cell nucleus, and therefore they must first deliver their genome into the nucleus of their host cells. Thus, trafficking across the nuclear envelope is at the basis of DNA virus infections. Nuclear transport of molecules with diameters up to 39 nm is a tightly regulated process that occurs through the nuclear pore complex (NPC). Due to the enormous diversity of virus size and structure, each virus has developed its own strategy for entering the nucleus of their host cells, with no two strategies alike. For example, baculoviruses target their DNA-containing capsid to the NPC and subsequently enter the nucleus intact, while the hepatitis B virus capsid crosses the NPC but disassembles at the nuclear side of the NPC. For other viruses such as herpes simplex virus and adenovirus, although both dock at the NPC, they have each developed a distinct mechanism for the subsequent delivery of their genome into the nucleus. Remarkably, other DNA viruses, such as parvoviruses and human papillomaviruses, access the nucleus through an NPC-independent mechanism. This review discusses our current understanding of the mechanisms used by DNA viruses to deliver their genome into the nucleus, and further presents the experimental evidence for such mechanisms.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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".