Quantitative and Multiplex Detection of Extracellular Vesicle‐Derived MicroRNA via Rolling Circle Amplification within Encoded Hydrogel Microparticles
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
Abstract Extracellular vesicle‐derived microRNA (EV‐miRNA) represent a promising cancer biomarker for disease diagnosis and monitoring. However, existing techniques to detect EV‐miRNA rely on complex, bias‐prone strategies, and preprocessing steps, making absolute quantification highly challenging. This work demonstrates the development and application of a method for quantitative and multiplex detection of EV‐miRNA, via rolling circle amplification within encoded hydrogel particles. By a one‐pot extracellular vesicle lysis and microRNA capture step, the bias and losses associated with standard RNA extraction techniques is avoided. The system offers a large dynamic range (3 orders of magnitude), ease of multiplexing, and a limit of detection down to 2.3 zmol (46 × 10 −18 m ), demonstrating its utility in clinical applications based on liquid biopsy tests. Furthermore, orthogonal measurements of EV concentrations coupled with the direct, absolute quantification of miRNA in biological samples results in quantitative measurements of miRNA copy numbers per volume sample, and per extracellular vesicle.
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.
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