Optimization and clinical evaluation of a 5.8S rRNA quantitative PCR assay for the diagnosis of talaromycosis
Bibliographic record
Abstract
Talaromyces marneffei is a dimorphic fungus endemic in Southeast Asia that causes the invasive fungal disease talaromycosis in immunocompromised individuals. Detection of T. marneffei nucleic acid in blood by PCR has demonstrated potential as a diagnostic tool for talaromycosis, but previously developed assays have limited sensitivity. This study described the optimization of a quantitative PCR (qPCR) assay for the diagnosis of talaromycosis. Our assay performance was maximized by testing different primers, methods of cell lysis and DNA extraction, whole blood vs. plasma, and methods of specimen treatment, using mean quantification cycle (Cq) values to compare performance. Our qPCR assay achieved the highest analytical sensitivity of 1 yeast cell per mL of whole blood, using primers targeting the 5.8S ribosomal DNA, cell lysis by bead beating, and DNA extraction by the MasterPure Yeast Purification Kit. There was no cross-reactivity observed with six Penicillium species and nine clinically related fungal isolates. In a case-control, diagnostic validation study of 138 cases of talaromycosis and 30 controls with other invasive fungal diseases and opportunistic infections, our 5.8S qPCR assay detected T. marneffei in 99.0% (101/102, 95% CI: 94.6%-99.9%) of blood culture-positive and 55.6% (20/37, 95% CI: 38.1%-72%) of blood culture-negative patients. Overall, our 5.8S qPCR assay had significantly higher sensitivity compared to conventional BACTEC blood culture, 87.7% (95% CI: 80.7%-92.5%) vs. 73.9% (95% CI: 65.6%-80.8%, P < .001), and the specificity was 96.7% (95% CI: 80.9%-99.8%). Our 5.8S qPCR assay has potential as a non-invasive and rapid rule-in test for talaromycosis.
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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 | 0.012 | 0.013 |
| 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 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".