Impact of Lectin biotinylation for surface plasmon resonance and enzyme-linked Lectin assays for protein glycosylation
Bibliographic record
Abstract
Lectins are widely employed for the assessment of protein glycosylation as their carbohydrate binding specificities have been well characterized. In glycosylation assays, lectins are often conjugated with biotin tags, which interact with streptavidin to functionalize biosensing surfaces or recruit signal generating molecules, depending on the assay configuration. We here demonstrate that a high degree of biotin conjugation can limit total capture to streptavidin functionalized SPR surfaces due to multipoint binding, and can additionally bias the reported kinetic evaluations when measuring the interaction between lectins and glycoproteins by SPR. For microplate assays using different configurations, high biotinylation ratios can effectively amplify the signal obtained when using Streptavidin conjugates for detection, in some cases significantly lowering the limit of detection. The cumulative results express the importance of customizing the ligand biotinylation ratios for different assay configurations, as commercially obtained pre-biotinylated lectins are not necessarily optimized for different assay configurations.
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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".