Capillary-Scale Monolithic Immunoaffinity Columns for Immunoextraction with In-Line Laser-Induced Fluorescence Detection
Bibliographic record
Abstract
A bimodal meso/macroporous monolithic silica capillary column containing an entrapped antibody was prepared by a biocompatible sol-gel process and used for nanoflow immunoaffinity chromatography and immunoextraction studies. Stationary phases were prepared by combining the protein-compatible silane precursor diglycerylsilane with an aqueous solution containing 10,000 Da poly(ethylene glycol) and the antibody. An analytical method was developed that was capable of determining both the dissociation constant and binding site content for the anti-fluorescein antibody within the stationary phase. The assay showed that while the antibody residing in macropores was easily removed, approximately 20% of initially loaded antibody remained active and accessible after several washes, consistent with the antibody being entrapped within the mesopores of the sol-gel matrix. The dissociation constants for fluorescein binding to the anti-fluorescein antibody were similar in solution and in the meso/macroporous silica, indicating that the entrapped antibody retained its native conformation within such a matrix. The mixture was loaded into a 250-microm-i.d. fused-silica capillary where the polymer phase separated from the silica followed by gelation of the silica. The capillary-scale immunoaffinity columns could be operated at low back pressure using a syringe pump and were capable of performing chromatographic separations that were dependent on the presence of the antibody within the stationary phase. Such columns could also be operated using in-line laser-induced fluorescence detection. The use of the capillary-scale monolithic columns for on-column immunoextraction and preconcentration is also demonstrated.
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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".