A zinc finger protein array for the visual detection of specific DNA sequences for diagnostic applications
Bibliographic record
Abstract
The visual detection of specific double-stranded DNA sequences possesses great potential for the development of diagnostics. Zinc finger domains provide a powerful scaffold for creating custom DNA-binding proteins that recognize specific DNA sequences. We previously demonstrated sequence-enabled reassembly of TEM-1 β-lactamase (SEER-LAC), a system consisting of two inactive fragments of β-lactamase each linked to engineered zinc finger proteins (ZFPs). Here the SEER-LAC system was applied to develop ZFP arrays that function as simple devices to identify bacterial double-stranded DNA sequences. The ZFP arrays provided a quantitative assay with a detection limit of 50 fmol of target DNA. The method could distinguish target DNA from non-target DNA within 5 min. The ZFP arrays provided sufficient sensitivity and high specificity to recognize specific DNA sequences. These results suggest that ZFP arrays have the potential to be developed into a simple and rapid point-of-care (POC) diagnostic for the multiplexed detection of pathogens.
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How this classification was reachedexpand
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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".