[Reverse genetics in reovirus study: advances, difficulties and perspectives].
Bibliographic record
Abstract
In "classical" genetics, examination of a phenotype leads to the study of the gene(s) involved in its obtention. Reverse genetics is a powerful experimental approach in which, on the contrary, the genetic material is modified and used to reconstruct a complete organism in order to study the result of these modifications. This approach is especially well adapted to the study of viruses, considering their relative simplicity and small size of their genomes; the main obstacle remains to recover infectious viruses from cloned viral genomes. Over the years, this exploit has been achieved with representatives of almost all families of mammalian viruses. Until recently, the Reoviridae, viruses with segmented double-stranded RNA genome, were an exception. In this review, the progress accomplished toward the development of such an approach for the Orthoreovirus will thus be discussed. Reverse genetics could have a major impact for the optimization of novel virus strains for their use in therapy as oncolytic viruses and for the development of vaccines in the case of Rotavirus and Orbivirus. However, current works stress the limitations of the approach, the need for careful analysis of the results obtained, as well as the necessity to develop more efficient and polyvalent systems.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| 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".