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Record W2124551261 · doi:10.1586/ecp.10.16

Strategies for the real-time detection of Ca<sup>2+</sup>channel events of single cells: recent advances and new possibilities

2010· article· en· W2124551261 on OpenAlex
Xiujun Li, Paul CH Li

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

VenueExpert Review of Clinical Pharmacology · 2010
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Neural Engineering
Canadian institutionsSimon Fraser University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMedicine

Abstract

fetched live from OpenAlex

Ca(2+) ion channels play key roles in cell physiology and they are important drug targets. The Ca(2+) channel events are mainly measurable by fluorescent and patch clamp methods. This review summarizes the recent advances of these techniques for the detection of Ca(2+) channel events and the prospect of their new directions in the near future. Conventional bulk fluorescent methods are amenable to high-throughput applications, but they are not real-time single-cell measurements, which provide kinetic data on individual cells and offer unparalleled sensitive data for rare cells. Recent advances on real-time single-cell fluorescent measurements are conducted on microfluidic chips with scalable cell-retention sites, integrated with electrical stimulation and fluorescent measuring features. Patch clamp techniques are real-time measurements conducted on single cells, but the measurements are of low throughput. Recent advances are conducted on microfluidic patch clamp chips for high-throughput applications. Future real-time single-cell Ca(2+) channel event measurements will be conducted in a multiparametric manner in an integrated and automated microfluidic chip.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.420
Threshold uncertainty score0.356

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.096
GPT teacher head0.435
Teacher spread0.338 · 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