Automating multi-step paper-based assays using integrated layering of reagents
Bibliographic record
Abstract
We describe a versatile and simple method to perform sequential reactions on paper analytical devices by stacking dry pullulan films on paper, where each film contains one or more reagents or acts as a delay layer. Exposing the films to an aqueous solution of the analyte leads to sequential dissolution of the films in a temporally controlled manner followed by diffusive mixing of the reagents, so that sequential reactions can be performed. The films can be easily arranged for lateral flow assays or for spot tests (reactions take place sequentially in the z-direction). We have tested the general feasibility of the approach using three different model systems to demonstrate different capabilities: 1) pH ramping from low to high and high to low to demonstrate timing control; 2) rapid ready-to-use two-step Simon's assays on paper for detection of drugs of abuse utilizing a 2-layer stack containing two different reagents to demonstrate the ability to perform assays in the z-direction; and 3) sequential cell lysing and colorimetric detection of an intracellular bacterial enzyme, to demonstrate the ability of the method to perform sample preparation and analysis in the form of a spot assay. Overall, these studies demonstrate the potential of stacked pullulan films as useful components to enable multi-step assays on simple paper-based devices.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".