Sliding-strip microfluidic device enables ELISA on paper
Bibliographic record
Abstract
This article describes a 3D microfluidic paper-based analytical device that can be used to conduct an enzyme-linked immunosorbent assay (ELISA). The device comprises two parts: a sliding strip (which contains the active sensing area) and a structure surrounding the sliding strip (which holds stored reagents—buffers, antibodies, and enzymatic substrate—and distributes fluid). Running an ELISA involves adding sample (e.g. blood) and water, moving the sliding strip at scheduled times, and analyzing the resulting color in the sensing area visually or using a flatbed scanner. We demonstrate that this device can be used to detect C-reactive protein (CRP)—a biomarker for neonatal sepsis, pelvic inflammatory disease, and inflammatory bowel diseases—at a concentration range of 1–100 ng/mL in 1000-fold diluted blood (1–100 µg/mL in undiluted blood). The accuracy of the device (as characterized by the area under the receiver operator characteristics curve) is 89% and 83% for cut-offs of 10 ng/mL (for neonatal sepsis and pelvic inflammatory disease) and 30 ng/mL (for inflammatory bowel diseases) CRP in 1000-fold diluted blood respectively. In resource-limited settings, the device can be used as a part of a kit (containing the device, a fixed-volume capillary, a pre-filled tube, a syringe, and a dropper); this kit would cost ~ $0.50 when produced in large scale (>100,000 devices/week). This kit has the technical characteristics to be employed as a pre-screening tool, when combined with other data such as patient history and clinical signs. • 3D microfluidic paper-based analytical device performs ELISA with colorimetric results. • Two components enable separation of reagents in the device: a sliding-strip and a functional dock. • All required reagents (antibodies, enzyme, substrate, buffers) are stored in the device. • User only needs to add sample and water using the provided kit. • Device can detect C-reactive protein for possible pre-screening of neonatal sepsis, pelvic inflammatory disease, or inflammatory bowel diseases.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".