Aptamer-Based Affinity Chromatographic Assays for Thrombin
Why this work is in the frame
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Bibliographic record
Abstract
Affinity chromatographic assays for thrombin were developed using two aptamers as affinity ligands. The efficient capture and step elution of thrombin with NaClO4 enabled the determination of thrombin by using either absorbance or fluorescence detection. Preconcentration of thrombin on the affinity column improved the detection limit of thrombin to 0.1 nM. Using an aptamer for the fibrinogen-binding site of thrombin and a second aptamer for the heparin-binding site, a sandwich chromatographic assay was developed, showing improved selectivity of thrombin detection and eliminating the need for labeling thrombin in the sample. The increased local concentration of aptamers immobilized on monolithic columns favored the formation of aptamer-thrombin complexes, resulting in improved retention and detection of thrombin at trace levels.
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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