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Record W2624528266 · doi:10.1038/s41598-017-03846-y

Electrophoresis assisted time-of-flow mass spectrometry using hollow nanomechanical resonators

2017· article· en· W2624528266 on OpenAlexafffund
Swathi Chaudhari, Kamalesh Chaudhari, Seokbeom Kim, Faheem Khan, Jungchul Lee, Thomas Thundat

Bibliographic record

VenueScientific Reports · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMechanical and Optical Resonators
Canadian institutionsUniversity of Alberta
FundersIndian Institute of Technology MadrasCanada Research ChairsNational Research Foundation of KoreaCanada Excellence Research Chairs, Government of CanadaDepartment of Science and Technology, Ministry of Science and Technology, IndiaNational Research FoundationUniversity of Alberta
KeywordsMass spectrometryCapillary electrophoresisElectrophoresisAnalytical Chemistry (journal)AnalyteResonatorChemistryChromatographyCapillary actionFree-flow electrophoresisMaterials scienceOptoelectronicsPolyacrylamide gel electrophoresisGel electrophoresis of proteins

Abstract

fetched live from OpenAlex

This report discusses the first demonstration of electrophoresis assisted time-of-flow mass spectrometry using 'U' shaped hollow nanomechanical resonators (HNR). Capillary electrophoresis was coupled with the HNR based mass detection to overcome low ionic conductivity of channels embedded in the HNR preventing direct in-situ electrophoretic separation. The flow of analytes through the HNR was achieved by balancing the hydrodynamic pressure to override the electromotive force and inhibit the motion of analytes towards the anode for capillary electrophoresis. The resonance frequency shifts of the HNR vibrating around 1.5 MHz were correlated with the time of the passage of the protein bands to construct the mass spectrum. The proposed concept was demonstrated by constructing a mass spectrum of egg white proteins in the molecular weight range of 14-250 kDa. When compared to regular polyacrylamide gel electrophoresis, our method not only provides a precise and fast readout but also avoids the use of chemical staining. This study paves a new route for low-cost and on-chip mass spectrometers with ultra-miniaturized dimensions.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.270
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.019
GPT teacher head0.266
Teacher spread0.248 · 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.

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

Citations7
Published2017
Admission routes2
Has abstractyes

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