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Record W2972548204 · doi:10.1080/19336950.2019.1666455

Voltage gated sodium channels in cancer and their potential mechanisms of action

2019· article· en· W2972548204 on OpenAlexaff
Madeline Angus, Peter C. Ruben

Bibliographic record

VenueChannels · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicIon channel regulation and function
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsInvadopodiaSodium channelCancer cellDepolarizationMetastasisCell biologyIon channelChemistryCancerSodiumCalciumCancer researchBiophysicsBiologyBiochemistryMedicineInternal medicine

Abstract

fetched live from OpenAlex

Voltage gated sodium channels (VGSC) are implicated in cancer cell invasion and metastasis. However, the mechanism by which VGSC increase cell invasiveness and probability of metastasis is still unknown. In this review we outline lesser known functions of VGSC outside of action potential propagation, and the current understanding of the effects of VGSC in cancer. Finally, we discuss possible downstream effects of VGSC activation in cancer cells. After extensive review of the literature, the most likely role of VGSC in cancer is in the invadopodia, the leading edge of metastatic cancer cells. Sodium gradients are used to drive many biological processes in the body, and invadopodia may be similar. The function of the sodium hydrogen exchanger (NHE) and sodium calcium exchanger (NCX) are driven by sodium gradients. Voltage gated calcium channels, activated by membrane depolarization, are also capable of becoming activated in response to VGSC activity. Changes to hydrogen ion exchange or calcium handling have functional consequences for invadopodia and would explain the relationship between VGSC expression and invasiveness of cancer 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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.016
GPT teacher head0.250
Teacher spread0.234 · 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

Citations73
Published2019
Admission routes1
Has abstractyes

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