A Pair of DNA Aptamers That Can Selectively Bind to Bilirubin and Biliverdin
Bibliographic record
Abstract
Bilirubin and biliverdin are two important metabolites from the degradation of heme. Development of aptamers for them will not only help with the measurement of their concentrations for diagnosing diseases such as neonatal jaundice and liver dysfunction, but may also aid in developing molecular switches for the regulation of gene expression. In this work, we report the selection of DNA aptamers against bilirubin and biliverdin. For the biliverdin selection, the tightest affinity aptamer has a dissociation costant ( K d ) value of 6 nM determined using isothermal titration calorimetry (ITC), and using a fluorescent strand-displacement assay, a limit of detection of 0.7 nM was achieved. This strand-displacement sensor also showed a response to bilirubin, although with a 10-fold lower affinity. For the bilirubin selection, many sequences obtained were also present in the biliverdin selection, and it was attributed to the oxidation of a fraction of bilirubin to biliverdin by air. This oxidation was confirmed by a visual color change of bilirubin and by UV–vis spectroscopy. The tightest binding bilirubin aptamer has a K d value of 203 nM based on ITC, and a detection limit of 47 nM was achieved using the strand-displacement assay. This pair of aptamers offer insights into molecular recognition of heme breakdown products and may be useful for developing biosensors and intracellular molecular switches.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".