Product-Enhanced Reverse Transcriptase Assay for Replication-Competent Retrovirus and Lentivirus Detection
Bibliographic record
Abstract
The product-enhanced reverse transcriptase (PERT) assay has been used to detect reverse transcriptase (RT) activity associated with retroviruses. Although the PERT assay has been proposed as a method for detection of replication-competent retrovirus (RCR) and lentivirus (RCL), it has not been rigorously compared with existing methods for RCR and RCL detection. We have assessed the PERT assay for detection of RCL and RCR that may contaminate lentiviral and retroviral vectors and compared it with published methods for RCL (p24gag ELISA/gag PCR) and RCR (S+/L-) detection. Our results suggest that the PERT assay is as sensitive as p24gag ELISA and gag PCR for detection of replication-competent HIV-1 in an RCL detection assay. Comparison of detection of replication-competent retroviruses, GALV and RD114, by extended S+/L- and PERT assays indicates that both assays can detect 1 IU of each virus. Our findings suggest that the PERT assay can be used for RCL and RCR testing of a variety of retroviral vectors regardless of the structure, sequence, and envelope of the vectors.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.006 |
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".