MétaCan
Menu
Back to cohort

Human neural stem cells: electrophysiological properties of voltage-gated ion channels

2002· article· en· W1967675581 on OpenAlexaff
T. Cho, Jae-Han Bae, Hyun B. Choi, Sung‐Soo Kim, James G. McLarnon, Haeyoung Suh‐Kim, S. U. Kim, Churl K. Min

Bibliographic record

VenueNeuroreport · 2002
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Neural Engineering
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsNeural stem cellNeuroDNestinStem cellPatch clampTransfectionBiologyCell biologyCell cultureEmbryonic stem cellElectrophysiologyChemistryMolecular biologyCellular differentiationNeuroscienceBiochemistryGeneticsGene

Abstract

fetched live from OpenAlex

We have characterized the profile of membrane currents in an immortalized human neural stem cell line, HB1.F3 cells, using whole-cell patch clamp technique. Human neural stem cell line generated from primary cell cultures of embryonic human telencephalon using a replication-incompetent retroviral vector containing v-myc expresses nestin, a cell type-specific marker for neural stem cells. The human neural stem cells expressed both outward and inward K(+) currents with no evidence for Na(+) currents. The density of the outward, delayed rectifying type K(+) current was 1.8 +/- 0.015 nA/pF, and that of the inwardly rectifying K(+) current was 0.37 +/- 0.012 nA/pF (at 30 mM of [K(+)](o)). In order to induce neuronal differentiation of the neural stem cells, a full-length coding region of NeuroD, a neurogenic transcription factor, was transfected into HB1.F3 cells. Introduction of NeuroD induced expression of Na(+) currents with the current density of 0.042 +/- 0.011 nA/pF. The presence of two types of K(+) currents and expression of Na(+) currents induced by NeuroD appear to reflect the characteristic physiological features of human neural stem cells.

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)0.000
metaresearch head score (Gemma)0.000
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: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.001

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 head0.091
GPT teacher head0.246
Teacher spread0.154 · 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

Citations116
Published2002
Admission routes1
Has abstractyes

Explore more

Same venueNeuroreportSame topicNeuroscience and Neural EngineeringFrench-language works237,207