Patterning Multiplex Protein Microarrays in a Single Microfluidic Channel
Why this work is in the frame
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Bibliographic record
Abstract
The development of versatile biofunctional surfaces is a fundamental prerequisite in designing Lab on a Chip (LOC) devices for applications in biosensing interfaces and microbioreactors. The current paper presents a rapid combinatorial approach to create multiplex protein patterns in a single microfluidic channel. This approach consists of coupling microcontact printing with microfluidic patterning, where microcontact printing is employed for silanization using (3-Aminopropyl) triethoxysilane (APTES), followed by microfluidic patterning of multiple antibodies. As a result, the biomolecules of choice could be covalently attached to the microchannel surface, thus creating a durable and highly resistant functional interface. Moreover, the experimental procedure was designed to create a microfluidic platform that maintains functionality at high flow rates. The functionalized surfaces were characterized using X-ray photoelectron spectroscopy (XPS) and monitored with fluorescence microscopy at each step of functionalization. To illustrate the possibility of patterning multiple biomolecules along the cross section of a single microfluidic channel, microarrays of five different primary antibodies were patterned onto a single channel and their functionality was evaluated accordingly through a multiplex immunoassay using secondary antibodies specific to each patterned primary antibody. The resulting patterns remained stable at shear stresses of up to 50 dyn/cm(2). The overall findings suggest that the developed multiplex functional interface on a single channel can successfully lead to highly resistant multiplex functional surfaces for high throughput biological assays.
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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 it