Colorimetric Polymerase Chain Reaction Enabled by a Fast Light-Activated Substrate Chromogenic Detection Platform
Bibliographic record
Abstract
Miniaturization of nucleic acid tests (NATs) into portable, inexpensive detection platforms may aid disease diagnosis in point-of-care (POC) settings. Colorimetric signals are ideal readouts for portable NATs, and it remains of high demand to develop color readouts that are simple, quantitative, and versatile. Thus motivated, we report a fast light-activated substrate chromogenic polymerase chain reaction (FLASH PCR) that uses DNA intercalating dyes (DIDs) to enable colorimetric nucleic acid detection and quantification. The FLASH system is established on our finding that DID-DNA intercalation can promote the rapid photooxidation of chromogenic substrates through light-induced production of singlet oxygen. Using this principle, we have successfully converted DID-based fluorescent PCR assays into colorimetric FLASH PCR. To demonstrate the practical applicability of FLASH PCR to POC diagnosis, we also fabricated two readout platforms, including a portable electronic FLASH reader and a paper-based FLASH strip. Using the FLASH reader, we were able to detect as low as 60 copies of DNA standards, a limit of detection (LOD) comparable with commercial quantitative PCR. The FLASH strip further enables the reader-free detection of PCR amplicons by converting the colorimetric signal into the visual measurement of distance as a readout. Finally, the practical applicability of the FLASH PCR was demonstrated by the detection and/or quantification of nucleic acid markers in diverse clinical and biological samples.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".