Rapid one-step construction of a Middle East Respiratory Syndrome (MERS-CoV) infectious clone system by homologous recombination
Bibliographic record
Abstract
BACKGROUND: Viral Infectious clone systems serve as robust platforms to study viral gene or replicative function by reverse genetics, formulate vaccines and adapt a wild type-virus to an animal host. Since the development of the first viral infectious clone system for the poliovirus, novel strategies of viral genome construction have allowed for the assembly of viral genomes across the identified viral families. However, the molecular profiles of some viruses make their genome more difficult to construct than others. Two factors that affect the difficulty of infectious clone construction are genome length and genome complexity. RESULTS: This work examines the available strategies for overcoming the obstacles of assembling the long and complex RNA genomes of coronaviruses and reports one-step construction of an infectious clone system for the Middle East Respiratory Syndrome coronavirus (MERS-CoV) by homologous recombination in S. cerevisiae. CONCLUSIONS: Future use of this methodology will shorten the time between emergence of a novel viral pathogen and construction of an infectious clone system. Completion of a viral infectious clone system facilitates further study of a virus's biology, improvement of diagnostic tests, vaccine production and the screening of antiviral compounds.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".