Molecular zipper assays: a simple homosandwich with the sensitivity of PCR.
Bibliographic record
Abstract
PURPOSE: The purpose of this study is to develop a simple and inexpensive method for detection of viral load or antigens present in the body fluids as for diagnosis or monitoring of infectious diseases. For example, in case of viral infection, nucleic acid based quantitative PCR/RTPCR are sensitive in measuring viral load to follow the course of therapy or infection. The key limitations of such assays include the need for sample extraction, susceptibility to inhibitors, and high cost. METHODS: A molecular zipper assay based on the simple homosandwich concept for repeated epitopes was developed where the analyte or virus is sandwiched between the same antibodies for detection. A comparative study of the lower limit of detection of M13 model virus was performed with various substrates. RESULT: Homosandwich molecular zipper assay captured the model virus with high avidity resisting multiple rounds of washing. Detection of the virus by enzyme labeled MAb in combination with chemiluminescent substrates provided practical assay sensitivities of 7-15 phages and a theoretical detection sensitivity of one virus particle. CONCLUSION: The significance of our results on the molecular zipper assay relates to the development of ultrasensitive pathogen assays at low cost. Such assays could be developed for pathogenic bacteria and viruses, especially HIV & HCV viruses, which are ravaging impoverished continents of Africa, Asia and Latin America.
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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 | 0.003 | 0.004 |
| 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 | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.004 |
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".