Use of Polymer Micropillar Arrays as Templates for Solid-Phase Immunoassays
Bibliographic record
Abstract
We investigate the use of periodic micropillar arrays produced by high-fidelity microfabrication with cyclic olefin polymers for solid-phase immunoassays. These three-dimensional (3D) templates offer higher surface-to-volume ratios than two-dimensional substrates, making it possible to attach more antibodies and so increase the signal obtained by the assay. Micropillar arrays also provide the capacity to induce wicking, which is used to distribute and confine antibodies on the surface with spatial control. Micropillar array substrates are modified by using oxygen plasma treatment, followed by grafting of (3-aminopropyl)triethoxysilane for binding proteins covalently using glutaraldehyde as a cross-linker. The relationship between microstructure and fluorescence signal was investigated through variation of pitch (10–50 μm), pillar diameter (5–40 μm), and pillar height (5–57 μm). Our findings suggest that signal intensity scales proportionally with the 3D surface area available for performing solid-phase immunoassays. A linear relationship between fluorescence intensity and microscale structure can be maintained even when the aspect ratio and pillar density both become very high, opening the possibility of tuning assay response by design such that desired signal intensity is obtained over a wide dynamic range compatible with different assays, analyte concentrations, and readout instruments. We demonstrate the versatility of the approach by performing the most common immunoassay formats─direct, indirect, and sandwich─in a qualitative fashion by using colorimetric and fluorescence-based detection for a number of clinically relevant protein markers, such as tumor necrosis factor alpha, interferon gamma (IFN-γ), and spike protein of severe acute respiratory syndrome coronavirus 2. We also show quantitative detection of IFN-γ in serum using a fluorescence-based sandwich immunoassay and calibrated samples with spike-in concentrations ranging from 50 pg/mL to 5 μg/mL, yielding an estimated limit of detection of ∼1 pg/mL for arrays with high micropillar density (11561 per mm 2 ) and aspect ratio (1:11.35).
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".