The pros and cons of nucleic acid-amplified immunoassays—a comparative study on the quantitation of prostate-specific antigen with and without rolling circle amplification
Bibliographic record
Abstract
Integrating isothermal nucleic acid amplification strategies into immunoassays can significantly decrease analytical limits of detection (LODs). On the other hand, an amplification step adds time, complication, reagents, and costs to the assay format. To evaluate the pros and cons in the context of heterogeneous multistep immunoassays, we quantified prostate-specific antigen (PSA) with and without rolling circle amplification (RCA). In addition, we compared time-gated (TG) with continuous-wave (CW) photoluminescence (PL) detection using a terbium complex and a fluorescein dye, respectively. For both direct (non-amplified) and amplified assays, TG PL detection provided circa four- to eightfold lower LODs, illustrating the importance of autofluorescence background suppression even for multi-wash assay formats. Amplified assays required an approximately 2.4 h longer assay time but led to almost 100-fold lower LODs down to 1.3 pg/mL of PSA. Implementation of TG-FRET (using a Tb-Cy5.5 donor-acceptor pair) into the RCA immunoassay resulted in a slightly higher LOD (3.0 pg/mL), but the ratiometric detection format provided important benefits, such as higher reproducibility, lower standard deviations, and multiplexing capability. Overall, our direct comparison demonstrated the importance of biological background suppression even in heterogeneous assays and the potential of using isothermal RCA for strongly decreasing analytical LODs, making such assays viable alternatives to conventional enzyme-linked immunosorbent assays (ELISAs).
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".