Optimization of Sol−Gel Formulations and Surface Treatments for the Development of Pin-Printed Protein Microarrays
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We report on the development and optimization of a sol−gel-based method for the preparation of protein microarrays that has the potential to allow pin-spotting of active proteins for high throughput multianalyte biosensing and screening of protein−small molecule interactions. Microarrays were printed onto bare and chemically modified surfaces using the commercially available sol−gel precursors tetraethyl orthosilicate and sodium silicate and the newly developed biocompatible sol−gel precursors monosorbitol silane and diglyceryl silane. Parameters such as the type and level of the buffer, the water-to-silane ratio, and the solution pH were also varied to assess the factors that controlled the production of optimal microarrays. Such factors included the ability to pin-print without clogging of the pins, the adhesion of the sol−gel spot to the substrate, the dimensions of the microspot, and the stability of both the microspot and the entrapped protein. The microarraying of active antibodies was successfully demonstrated using an optimized combination of parameters, and such arrays were shown to have significantly higher signal-to-background levels than conventional arrays formed by covalent immobilization of antibodies on chemically derivatized surfaces.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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