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Record W2896225373 · doi:10.1039/c8an00911b

Monitoring individual cell-signaling activity using combined metal-clad waveguide and surface-enhanced fluorescence imaging

2018· article· en· W2896225373 on OpenAlex
Thomas Söllradl, Kevin Chabot, Ulrike Fröhlich, Michael Canva, Paul G. Charette, Michel Grandbois

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueThe Analyst · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced Biosensing Techniques and Applications
Canadian institutionsUniversité de Sherbrooke
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchFonds Québécois de la Recherche sur la Nature et les Technologies
KeywordsSurface plasmon resonanceMolecular imagingBiophysicsFluorescenceFluorescence-lifetime imaging microscopyIntracellularBiosensorSIGNAL (programming language)ReceptorMaterials scienceNanotechnologyChemistryComputer scienceNanoparticleBiologyIn vivoOpticsPhysicsBiochemistry

Abstract

fetched live from OpenAlex

Evanescent field based biosensing systems such as surface plasmon resonance (SPR), diffraction gratings, or metal-clad waveguides (MCWGs) are powerful tools for label-free real-time monitoring of signaling activity of living cells exposed to hormones, pharmacological agents, and toxins. In particular, MCWG-based imaging is well suited for studying relatively thick objects such as cells due to its greater depth of penetration into the sensing medium, compared to SPR. Label-free methods, however, provide only indirect measurements in that the measured signal arises from local changes in material properties rather than from specific biomolecular targets. In the case of cells, the situation is especially complex as the measured label-free signal may result from a combination of very diverse sources: morphological changes, intra-cellular reorganization, cascaded molecular events, protein expression etc. Consequently, deconvolving the contributions of specific sources to a particular cell response profile can be challenging. In the following, we present a cell imaging platform that combines two distinct sensing modalities, namely label-free MCWG imaging and label-based surface enhanced fluorescence (SEF), designed to facilitate the identification of the underlying molecular and structural contributions to the label-free MCWG images. We demonstrate the bimodal capabilities of this imaging platform in experiments designed to visualize actin cytoskeleton organization in vascular smooth muscle cells. We then monitored the real-time response of HEK293 cells expressing the Angiotensin 1 receptor (AT1R), when stimulated by the receptor agonist Angiotensin II (AngII). The analysis of the simultaneous label-free signal obtained by MCWG and the intracellular calcium signal resulting form AT1R activation, measured by SEF, allows relating label-free signal features to specific markers of receptor activation. Our results show that the intracellular calcium levels normally observed following AT1R activation are not required for the initial burst of cellular activity observed in the MCWG signal but rather indicates signaling activity involving the intracellular kinase ROCK.

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.

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 score0.022
Threshold uncertainty score0.431

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 head0.022
GPT teacher head0.297
Teacher spread0.275 · 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