Instability of 8E5 calibration standard revealed by digital PCR risks inaccurate quantification of HIV DNA in clinical samples by qPCR
Bibliographic record
Abstract
Abtract Establishing a cure for HIV is hindered by the persistence of latently infected cells which constitute the viral reservoir. Real-time qPCR, used for quantification of this reservoir by measuring HIV DNA, requires external calibration; a common choice of calibrator is the 8E5 cell line, which is assumed to be stable and to contain one HIV provirus per cell. In contrast, digital PCR requires no external calibration and potentially provides ‘absolute’ quantification. We compared the performance of qPCR and dPCR in quantifying HIV DNA in 18 patient samples. HIV DNA was detected in 18 by qPCR and in 15 by dPCR, the difference being due to the smaller sample volume analysed by dPCR. There was good quantitative correlation (R 2 = 0.86) between the techniques but on average dPCR values were only 60% of qPCR values. Surprisingly, investigation revealed that this discrepancy was due to loss of HIV DNA from the 8E5 cell calibrant. 8E5 extracts from two other sources were also shown to have significantly less than one HIV DNA copy per cell and progressive loss of HIV from 8E5 cells during culture was demonstrated. We therefore suggest that the copy number of HIV in 8E5 extracts be established by dPCR prior to use as calibrator.
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 | 0.011 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".