Materials Screening for Sol–Gel-Derived High-Density Multi-Kinase 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
Protein microarrays based on pin-printing of sol–gel-entrapped biomolecules have emerged as a potential tool to accelerate drug screening and discovery. However, while materials have recently been identified that are suitable for printing of high-density sol–gel-based microarrays, the ability to print arrays of delicate proteins such as kinases, and to assay their activity and inhibition on-array, has yet to be demonstrated. In this study, we have performed a criteria-based directed screen of sol–gel-based materials to identify compositions that are suitable for the fabrication of high-density, multikinase microarrays. Printable formulations were assessed for their compatibility with a fluorescent, phosphospecific dye used as an end-point indicator for on-array kinase assays, including an assessment of the effects of spot size (100 μm vs 400 μm) and slide surface chemistry on signal reproducibility. The combinations of materials, surfaces, and spot sizes that were found to be compatible with reproducible signal generation were evaluated for their ability to retain the activity of a range of kinases, which were co-entrapped with their respective substrates into the optimal sol–gel materials to produce microarrays. Ultimately, two material/surface combinations, from potentially thousands, were identified, one of which was used to produce a robust, highly active kinase microarray that could be used for qualitative screening as well as quantitative inhibition assays.
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