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Record W2735199155 · doi:10.1139/bcb-2017-0062

Kv10.1 potassium channel: from the brain to the tumors

2017· review· en· W2735199155 on OpenAlexvenueno aff
Verna Cázares‐Ordoñez, Luis A. Pardo

Bibliographic record

VenueBiochemistry and Cell Biology · 2017
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicIon channel regulation and function
Canadian institutionsnot available
FundersConsejo Nacional de Ciencia y Tecnología
KeywordsCarcinogenesisIon channelNeurosciencePotassium channelCancerCell biologyBiologyChemistryComputational biologyBioinformaticsGeneticsEndocrinologyReceptor

Abstract

fetched live from OpenAlex

The KCNH1 gene encodes the Kv10.1 (Eag1) ion channel, a member of the EAG (ether-à-go-go) family of voltage-gated potassium channels. Recent studies have demonstrated that KCHN1 mutations are implicated in Temple-Baraitser and Zimmermann-Laband syndromes and other forms of developmental deficits that all present with mental retardation and epilepsy, suggesting that Kv10.1 might be important for cognitive development in humans. Although the Kv10.1 channel is mainly expressed in the mammalian brain, its ectopic expression occurs in 70% of human cancers. Cancer cells and tumors expressing Kv10.1 acquire selective advantages that favor cancer progression through molecular mechanisms that involve several cellular pathways, indicating that protein-protein interactions may be important for Kv10.1 influence in cell proliferation and tumorigenesis. Several studies on transcriptional and post-transcriptional regulation of Kv10.1 expression have shown interesting mechanistic insights about Kv10.1 role in oncogenesis, increasing the importance of identifying the cellular factors that regulate Kv10.1 expression in tumors.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.002

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 head0.034
GPT teacher head0.295
Teacher spread0.260 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations51
Published2017
Admission routes1
Has abstractyes

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