Development and application of ultra-sensitive tools for the detection of malaria
Bibliographic record
Abstract
The goal to eliminate malaria has been challenged by the lack of accurate diagnostic tools to identify symptomatic, asymptomatic, and drug-resistant malaria carriers. In this dissertation, we have shown the potential of the Loop-mediated Isothermal Amplification (LAMP)-based diagnostic approaches to be a powerful tool available for malaria elimination. We have validated the combination of the Non-instrumented Nucleic Acid (NINA) platform heater (PATH, Seattle) with a commercial LAMP kit (LoopAmp malaria Pan/Pf detection kit), with a view to deploying it in extremely resource-limited settings in the future. An ultrasensitive (US)-LAMP assay was also developed and validated to identify asymptomatic malaria reservoirs. Moreover, a novel strategy for detecting single nucleotide polymorphisms (SNPs) by the LAMP method was designed and deployed for spotting artemisinin resistance in P. falciparum. We conclude that the NINA-LAMP assay can be a convenient test for detecting symptomatic malaria cases with a sensitivity of 100% and specificity of 98.6% compared to the gold standard nested PCR. Additionally, the US-LAMP assay was able to achieve a limit of detection (LOD) between 25 to 100 parasites/mL from dried blood spots. We have also found that the overall prevalence of asymptomatic malaria was 22.1% in the Gambella region of Ethiopia, detected by the US-LAMP assay. The sensitivity and the specificity of the US-LAMP assay were 92.6% and 97.1%, respectively compared to an ultrasensitive quantitative reverse transcriptase PCR. Additionally, the SNP-LAMP assay was 100% sensitive and 97.3% specific to identify the C580Y mutation in the kelch 13 propeller gene, which is known as the major genetic determinant of artemisinin resistance in Southeast Asia. Furthermore, we conclude that artemisinin resistance-linked kelch 13 propeller mutations are absent in the Bangladeshi P. falciparum isolates. However, two cases of the A578S SNP in the kelch 13 propeller gene were found in those P. falciparum isolates, although this SNP was not associated with artemisinin resistance. In conclusion, as the LAMP-based diagnostic approaches are simple, low-cost, and accurate compared to currently available nucleic acid tests, they can be used at different aspects to diagnose malaria and expedite elimination.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| 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".