Universally applicable, quantitative PCR method utilizing fluorescent nucleobase analogs
Bibliographic record
Abstract
We herein describe a novel quantitative PCR (qPCR) method, which operates in both signal-off and on manners, by utilizing a unique property of fluorescent nucleobase analogs. The first, signal-off method is developed by designing the primers to contain pyrrolo-dC (PdC), one of the most common fluorescent nucleobase analogs. The specially designed single-stranded primer is extended to form double-stranded DNA during PCR and the fluorescence signal from the PdCs incorporated in the primer is accordingly reduced due to its conformation-dependent fluorescence properties. In addition, the second, signal-on method is devised by designing the primers to contain 5'-overhang sequences complementary to the PdC-incorporated DNA probes. At the initial phase, the PdC-incorporated DNA probes are hybridized to the 5'-overhang sequences of the primer, exhibiting the significantly quenched fluorescence signal, but are detached by either hydrolysis or strand displacement reaction during PCR, leading to the highly enhanced fluorescence signal. This method is more advanced than the first one since it produces signal-on fluorescence response and permits the use of a single PdC-incorporated DNA probe for the detection of multiple target nucleic acids, remarkably decreasing the assay cost. With these novel qPCR methods, we successfully quantified target nucleic acids derived from sexually transmitted disease (STD) pathogens with high accuracy. Importantly, the proposed strategies overcome the major drawbacks in the current SYBR Green and TaqMan probe-based qPCR methods such as low specificity and high assay cost.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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".