Synthesis and Translation of Viral mRNA in Reovirus-Infected Cells: Progress and Remaining Questions
Bibliographic record
Abstract
At the end of my doctoral studies, in 1988, I published a review article on the major steps of transcription and translation during the mammalian reovirus multiplication cycle, a topic that still fascinates me 30 years later. It is in the nature of scientific research to generate further questioning as new knowledge emerges. Our understanding of these fascinating viruses thus remains incomplete but it seemed appropriate at this moment to look back and reflect on our progress and most important questions that still puzzle us. It is also essential of being careful about concepts that seem so well established, but could still be better validated using new approaches. I hope that the few reflections presented here will stimulate discussions and maybe attract new investigators into the field of reovirus research. Many other aspects of the viral multiplication cycle would merit our attention. However, I will essentially limit my discussion to these central aspects of the viral cycle that are transcription of viral genes and their phenotypic expression through the host cell translational machinery. The objective here is not to review every aspect but to put more emphasis on important progress and challenges in the field.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".