Navigating the Host Cell Response during Entry into Sites of Latent Cytomegalovirus Infection
Bibliographic record
Abstract
The host cell represents a hostile environment that viruses must counter in order to establish infection. Human cytomegalovirus (HCMV) is no different and encodes a multitude of functions aimed at disabling, re-directing or hijacking cellular functions to promulgate infection. However, during the very early stages of infection the virus relies on the outcome of interactions between virion components, cell surface receptors and host signalling pathways to promote an environment that supports infection. In the context of latent infection-where the virus establishes an infection in an absence of many gene products specific for lytic infection-these initial interactions are crucial events. In this review, we will discuss key host responses triggered by viral infection and how, in turn, the virus ameliorates the impact on the establishment of non-lytic infections of cells. We will focus on strategies to evade intrinsic antiviral and innate immune responses and consider their impact on viral infection. Finally, we will consider the hypothesis that the very early events upon viral infection are important for dictating the outcome of infection and consider the possibility that events that occur during entry into non-permissive cells are unique and thus contribute to the establishment of latency.
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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 | 0.001 |
| 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) | 0.003 | 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".