Multiplexed Real-Time PCR Assay for Discrimination of <i>Plasmodium</i> Species with Improved Sensitivity for Mixed Infections
Bibliographic record
Abstract
The implementation of real-time PCR for the diagnosis of malaria has been hampered by poor sensitivity for the detection of mixed infections. We have optimized a method that enhances the sensitivity of detection of minor species in mixed infections within a single multiplex reaction. Our assay uses species-specific forward primers in combination with a conserved reverse primer and largely overcomes primer competition for the minor species DNA. With a blind panel of clinical samples, we successfully identified the species in 13/16 mixed infections. This assay was further validated with 91 blood samples and demonstrated a specificity and sensitivity for single infections of 100% compared with nested PCR as the "gold standard." This test has been implemented for routine confirmation of malaria species in Alberta, Canada. In comparison with species identification by microscopy, the real-time PCR test demonstrated greater sensitivity for the identification of species causing low-level and mixed infections and for the discrimination of Plasmodium species other than Plasmodium falciparum. Our experience supports a role for real-time PCR in the identification of malarial species in conjunction with microscopy.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".