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Record W2159742045

Molecular zipper assays: a simple homosandwich with the sensitivity of PCR.

2004· article· en· W2159742045 on OpenAlexaff
Sujatha Guttikonda, Welson Wang, Mavanur R. Suresh

Bibliographic record

VenuePubMed · 2004
Typearticle
Languageen
FieldEngineering
TopicBiosensors and Analytical Detection
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsVirologyVirusBiologyNucleic acidBiochemistry
DOInot available

Abstract

fetched live from OpenAlex

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.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.003
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.004

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.

Opus teacher head0.007
GPT teacher head0.166
Teacher spread0.159 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreMethods

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".

Quick stats

Citations13
Published2004
Admission routes1
Has abstractyes

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