Capsid Integrity qPCR—An Azo-Dye Based and Culture-Independent Approach to Estimate Adenovirus Infectivity after Disinfection and in the Aquatic Environment
Bibliographic record
Abstract
Recreational, reclaimed and drinking source waters worldwide are under increasing anthropogenic pressure, and often contain waterborne enteric bacterial, protozoan, and viral pathogens originating from non-point source fecal contamination. Recently, the capsid integrity (ci)-qPCR, utilizing the azo-dyes propidium monoazide (PMA) or ethidium monoazide (EMA), has been shown to reduce false-positive signals under laboratory conditions as well as in food safety applications, thus improving the qPCR estimation of virions of public health significance. The compatibility of two widely used human adenovirus (HAdV) qPCR protocols was evaluated with the addition of a PMA/EMA pretreatment using a range of spiked and environmental samples. Stock suspensions of HAdV were inactivated using heat, UV, and chlorine before being quantified by cell culture, qPCR, and ci-qPCR. Apparent inactivation of virions was detected for heat and chlorine treated HAdV while there was no significant difference between ci-qPCR and qPCR protocols after disinfection by UV. In a follow-up comparative analysis under more complex matrix conditions, 51 surface and 24 wastewater samples pre/post UV treatment were assessed for enteric waterborne HAdV to evaluate the ability of ci-qPCR to reduce the number of false-positive results when compared to conventional qPCR and cell culture. Azo-dye pretreatment of non-UV inactivated samples was shown to improve the ability of molecular HAdV quantification by reducing signals from virions with an accessible genome, thereby increasing the relevance of qPCR results for public health purposes, particularly suited to resource-limited low and middle-income settings.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".