Direct DNA Analysis with Paper-Based Ion Concentration Polarization
Bibliographic record
Abstract
DNA analysis is essential for diagnosis and monitoring of many diseases. Conventional DNA testing is generally limited to the laboratory. Increasing access to relevant technologies can improve patient care and outcomes in both developed and developing regions. Here, we demonstrate direct DNA analysis in paper-based devices, uniquely enabled by ion concentration polarization at the interface of patterned nanoporous membranes in paper (paper-based ICP). Hepatitis B virus DNA targets in human serum are simultaneously preconcentrated, separated, and detected in a single 10 min operation. A limit of detection of 150 copies/mL is achieved without prior viral load amplification, sufficient for early diagnosis of hepatitis B. We clinically assess the DNA integrity of sperm cells in raw human semen samples. The percent DNA fragmentation results from the paper-based ICP devices strongly correlate (R(2) = 0.98) with the sperm chromatin structure assay. In all cases, agreement was 100% with respect to the clinical decision. Paper-based ICP can provide inexpensive and accessible advanced molecular diagnostics.
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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 | 0.002 |
| 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) | 0.002 | 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".