Flow Cytometry-Assisted Detection of Adenosine in Serum with an Immobilized Aptamer Sensor
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Aptamers are single-stranded nucleic acids that can selectively bind to essentially any molecule of choice. Because of their high stability, low cost, ease of modification, and availability through selection, aptamers hold great promise in addressing key challenges in bioanalytical chemistry. In the past 15 years, many highly sensitive fluorescent aptamer sensors have been reported. However, few such sensors showed high performance in serum samples. Further challenges related to practical applications include detection in a very small sample volume and a low dependence of sensor performance on ionic strength. We report the immobilization of an aptamer sensor on a magnetic microparticle and the use of flow cytometry for detection. Flow cytometry allows the detection of individual particles in a capillary and can effectively reduce the light scattering effect of serum. Since DNA immobilization generated a highly negatively charged surface and caused an enrichment of counterions, the sensor performance showed a lower salt dependence. The detection limits for adenosine are determined to be 178 microM in buffer and 167 microM in 30% serum. Finally, we demonstrated that the detection can be carried out in 10 microL of 90% human blood serum.
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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