In Vitro Selection of a DNA Aptamer Targeting Degraded Protein Fragments for Biosensing
Bibliographic record
Abstract
Protein biomarkers often exist as degradation fragments in biological samples, and affinity agents derived using a purified protein may not recognize them, limiting their value for clinical diagnosis. Herein, we present a method to overcome this issue, by selecting aptamers against a degraded form of the toxin B protein, which is a marker for diagnosing toxigenic Clostridium difficile infections. This approach has led to isolation of a DNA aptamer that recognizes degraded toxin B, fresh toxin B, and toxin B spiked into human stool samples. DNA aptamers selected using intact recombinant toxin B failed to recognize degraded toxin B, which is the form present in stored stool samples. Using this new aptamer, we produced a simple paper-based analytical device for colorimetric detection of toxin B in stool samples, or in the NAP1 strain of Clostridium difficile. The combined aptamer-selection and paper-sensing strategy can expand the practical utility of DNA aptamers in clinical diagnosis.
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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".