Emerging Loop-Mediated Isothermal Amplification-Based Microchip and Microdevice Technologies for Nucleic Acid Detection
Bibliographic record
Abstract
Rapid, sensitive, and selective pathogen detection is of paramount importance in infectious disease diagnosis and treatment monitoring. Currently available diagnostic assays based on polymerase chain reaction (PCR) and enzyme-linked immunosorbent assay (ELISA) are time-consuming, complex, and relatively expensive, thus limiting their utility in resource-limited settings. Loop-mediated isothermal amplification (LAMP) technique has been used extensively in the development of rapid and sensitive diagnostic assays for pathogen detection and nucleic acid analysis and hold great promise for revolutionizing point-of-care molecular diagnostics. Here, we review novel LAMP-based lab-on-a-chip (LOC) diagnostic assays developed for pathogen detection over the past several years. We review various LOC platforms based on their design strategies for pathogen detection and discuss LAMP-based platforms still in development and already in the commercial pipeline. This review is intended as a guide to the use of LAMP techniques in LOC platforms for molecular diagnostics and genomic amplifications.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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".