Analysis of herpes simplex virus type I nuclear particles by flow cytometry
Bibliographic record
Abstract
Flow cytometry has been instrumental to characterize cell populations and examine their inner molecules and processes. In most instances, whole cells are analyzed, and hence, particle size is not an issue. Viruses are 2-3 orders of magnitude smaller than cells so flow cytometry has typically been used to study viral markers within whole infected cells. However, the ability to separate and purify viral particles representing different maturation stages within a viral life cycle would be a useful tool to analyze them in details and characterize the host proteins they associate with. Herpes simplex virus Type 1 is a 250 nm enveloped DNA virus that replicates in the nucleus where it assembles new viral particles called capsids. These capsids eventually travel to the cell surface and are modified along the way, producing several intermediate particles. In the nucleus, three types of stable nonenveloped 125 nm nuclear capsids exist that differ in protein composition and genome content. This includes so-called nuclear C-capsids that are the precursors of mature extracellular virions. We report that we can apply flow cytometry to sort these nuclear C-capsid intermediates by labeling the viral genome with Syto 13, a fluorescent marker that binds to nucleic acids. This is the first time flow cytometry has been used not only to detect but also to purify an intracellular viral maturation intermediate. This opens new research avenues in virology to study capsid assembly, maturation and egress, analyze mutant phenotypes, and define host factors associated with specific viral intermediates.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".