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Record W1985178889 · doi:10.3791/3288

Culturing and Electrophysiology of Cells on NRCC Patch-clamp Chips

2012· article· en· W1985178889 on OpenAlexafffundabout
Christophe Py, Marzia Martina, Robert Monette, Tanya Comas, M. W. Denhoff, Collin Luk, Naweed I. Syed, Geoff Mealing

Bibliographic record

VenueJournal of Visualized Experiments · 2012
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Neural Engineering
Canadian institutionsUniversity of CalgaryHotchkiss Brain InstituteInstitute for Biological SciencesInstitute for Microstructural Sciences
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchAlberta Heritage Foundation for Medical ResearchFondation pour la Recherche Médicale
KeywordsPipettePatch clampMaterials scienceMicrofluidicsMicromanipulatorNanotechnologyMicroelectrodeAperture (computer memory)ElectrophysiologyBiomedical engineeringIon channelOptoelectronicsElectrodeComputer scienceChemistryEngineering

Abstract

fetched live from OpenAlex

Due to its exquisite sensitivity and the ability to monitor and control individual cells at the level of ion channels, patch-clamping is the gold standard of electrophysiology applied to disease models and pharmaceutical screens alike. The method traditionally involves gently contacting a cell with a glass pipette filled by a physiological solution in order to isolate a patch of the membrane under its apex. An electrode inserted in the pipette captures ion-channel activity within the membrane patch or, when ruptured, for the whole cell. In the last decade, patch-clamp chips have been proposed as an alternative: a suspended film separates the physiological medium from the culture medium, and an aperture microfabricated in the film replaces the apex of the pipette. Patch-clamp chips have been integrated in automated systems and commercialized for high-throughput screening. To increase throughput, they include the fluidic delivery of cells from suspension, their positioning on the aperture by suction, and automated routines to detect cell-to-probe seals and enter into whole cell mode. We have reported on the fabrication of a silicon patch-clamp chip with optimized impedance and orifice shape that permits the high-quality recording of action potentials in cultured snail neurons; recently, we have also reported progress towards interrogating mammalian neurons. Our patch-clamp chips are fabricated at the Canadian Photonics Fabrication Centre, a commercial foundry, and are available in large series. We are eager to engage in collaborations with electrophysiologists to validate the use of the NRCC technology in different models. The chips are used according to the general scheme represented in Figure 1: the silicon chip is at the bottom of a Plexiglas culture vial and the back of the aperture is connected to a subterranean channel fitted with tubes at either end of the package. Cells are cultured in the vial and the cell on top of the probe is monitored by a measuring electrode inserted in the channel .The two outside fluidic ports facilitate solution exchange with minimal disturbance to the cell; this is an advantage compared to glass pipettes for intracellular perfusion.

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)0.002
metaresearch head score (Gemma)0.002
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: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0030.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.011

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 head0.050
GPT teacher head0.403
Teacher spread0.353 · 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
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

Citations6
Published2012
Admission routes3
Has abstractyes

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