Loop-mediated isothermal amplification (LAMP): An advanced molecular point-of-care technique for the detection of Leishmania infection
Bibliographic record
Abstract
Leishmaniasis, caused by protozoan parasites of the Leishmania genus, represents an important health problem in many regions of the world. Lack of effective point-of-care (POC) diagnostic tests applicable in resources-limited endemic areas is a critical barrier to effective treatment and control of leishmaniasis. The development of the loop-mediated isothermal amplification (LAMP) assay has provided a new tool towards the development of a POC diagnostic test based on the amplification of pathogen DNA. LAMP does not require a thermocycler, is relatively inexpensive, and is simple to perform with high amplification sensitivity and specificity. In this review, we discuss the current technical developments, applications, diagnostic performance, challenges, and future of LAMP for molecular diagnosis and surveillance of Leishmania parasites. Studies employing the LAMP assay to diagnose human leishmaniasis have reported sensitivities of 80% to 100% and specificities of 94% to 100%. These observations suggest that LAMP offers a good molecular POC technique for the diagnosis of leishmaniasis and is also readily applicable to screening at-risk populations and vector sand flies for Leishmania infection in endemic areas.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| 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) | 0.002 | 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".