Evaluation of rapid extraction methods coupled with Recombinase polymerase amplification assay for point-of-need diagnosis of Post-kala-azar-dermal leishmaniasis
Bibliographic record
Abstract
Abstract Introduction Post kala-azar dermal leishmaniasis (PKDL) usually develops as sequelae of visceral leishmaniasis (VL) and can manifest in multiple dermatological forms. Since PKDL patients harbor Leishmania donovani parasites and can potentially trigger inter-epidemic transmission of the disease, the success of kala-azar elimination programme could be jeopardized by these cases. Although several molecular methods with promising diagnostic efficacy have been developed to detect PKDL cases, albeit complicated and expensive DNA extraction methods limit their application in resource poor settings. To address this, in comparison to a reference DNA extraction method (Qiagen), we evaluated two rapid DNA extraction methods and determined their impact on the detection of the parasite DNA using our newly developed recombinase polymerase amplification (RPA) assay.Methods Thirty suspected PKDL cases were enrolled after diagnosis by clinical examination and a positive rk39 strip test. DNA was extracted from three skin biopsy samples using either a spin column-based method (Qiagen) or one of two rapid DNA extraction methods, (Boil & Spin (B&S) and SpeedXtract (SE)). RPA and qPCR were subsequently performed with the extracted samples to detect L. donovani DNA.Results Using DNA extracted by Qiagen method, the qPCR and RPA assays exhibited sensitivities of 86.7% and 93.3% respectively. In contrast, the sensitivity of RPA assay dropped to 76.7% and 63.3%, respectively, when the B&S and SE rapid extraction methods were performed. Despite this compromised sensitivity, B&S-RPA technique yielded an excellent agreement with both Q-qPCR (k = 0.828) and Q-RPA (k =0.831) techniques. Moreover, SE-RPA showed good agreement with Q-qPCR (k = 0.755), Q-RPA (k =0.692) and B&S-RPA (k =0.635) assays. As expected, with all of the three DNA extraction methods, both qPCR and RPA assay showed absolute specificity.Conclusions This study finding substantiates the superior diagnostic efficacy of Qiagen DNA extraction method over B&S and SE method in detecting LD DNA through RPA assay from skin biopsy of PKDL patients. To apply these rapid DNA extraction methods in resource-constrained settings, further methodological refinement is warranted to improve DNA yield and purity through rigorous experiments.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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".