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Record W2000054138 · doi:10.1021/ac9010759

Antibody−Antigen Exchange Equilibria in a Field of an External Force: Design of Reagentless Biosensors

2009· article· en· W2000054138 on OpenAlexaff
Christopher F. Monson, Laura N. Driscoll, Eliot Bennion, Cary J. Miller, Marcin Majda

Bibliographic record

VenueAnalytical Chemistry · 2009
Typearticle
Languageen
FieldPhysics and Astronomy
TopicForce Microscopy Techniques and Applications
Canadian institutionsAbbott (Canada)
FundersDivision of ChemistryNational Science Foundation
KeywordsChemistryAnalyteAntigenBiosensorNanotechnologySuperparamagnetismMicrofluidicsImmunoassayAntibodyChromatographyMagnetic fieldBiochemistry

Abstract

fetched live from OpenAlex

This correspondence presents a new strategy for detecting biological molecules that relies on competitive exchange interactions of an analyte with two-component molecular tethers attaching superparamagnetic microspheres (4 microm in diameter) to a sensor surface. The individual tethers consist of an antibody-antigen complex and are designed to selectively detect antigenic proteins in a sensitive reagentless fashion. In order to impart a driving force to the otherwise free energy neutral antibody-antigen exchange equilibrium, a small mechanical force of approximately 10 pN was applied to stretch the antibody-antigen tethers using a massively parallel magnetic tweezers device. The experimental work was carried out with human cardiac troponin I. This serum heart attack marker was used as an example of analytes of credible relevance to biomedical diagnostics. The initial results illustrate the functioning of a cardiotroponin sensor and offer a preliminary estimate of its sensitivity of 16 pM.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.063
Threshold uncertainty score0.533

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.015
GPT teacher head0.336
Teacher spread0.322 · 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 teacher head, not a consensus.

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

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

Citations9
Published2009
Admission routes1
Has abstractyes

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