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Ion Channel and Neurotransmitter Modulators as Electroceutical Approaches to the Control of Cancer

2017· review· en· W2617459439 on OpenAlex

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.

Bibliographic record

VenueCurrent Pharmaceutical Design · 2017
Typereview
Languageen
FieldNeuroscience
TopicPhotoreceptor and optogenetics research
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsNeurotransmitterNeuroscienceCancer cellSerotonergicCancerBiologyCarcinogenesisIon channelMetastasisCell biologyCentral nervous systemSerotoninReceptorBiochemistryGenetics

Abstract

fetched live from OpenAlex

The activities of individual cells must be tightly coordinated in order to build and maintain complex 3- dimensional body structures during embryogenesis and regeneration. Thus, one way to view cancer is within systems biology as a network disorder affecting the ability of cells to properly interact with a morphodynamic field of instructive signals that keeps proliferation and migration orchestrated toward the anatomical needs of the host organism. One layer of this set of instructive microenvironmental cues is bioelectrical. Voltage gradients among all somatic cells (not just excitable nerve and muscle) control cell behavior, and the ionic coupling of cells into networks via electrochemical synapses allows them to implement tissue-level patterning decisions. These gradients have been increasingly implicated in the induction and suppression of tumorigenesis and metastasis, in the emerging links between developmental bioelectricity to the cancer problem. Consistent with the well-known role of neurotransmitter molecules in transducing electrical activity to downstream cascades in the brain, serotonergic signaling has likewise been implicated in cancer. Here, we review these recent data and propose new approaches for manipulating bioelectric and neurotransmitter pathways in cancer biology based on a bioelectric view of cancer. To support this methodology, we present new data on the effects of the SSRI Prozac and its analog (ZINC ID = ZINC06811610) on survival of both cancer (MCF7) and normal (MCF10A) breast cells exposed to these compounds. We found an IC50 concentration (25 µM for Prozac and 100 µM for the Prozac analog) at which these compounds inhibited tumor cell survival and proliferation. Additionally, at these concentrations, we did not observe alterations in a non-tumoral cell line. This constitutes a proof-of-concept demonstration for our hypothesis that the use of both existing and novel drugs as electroceuticals could serve as an alternative to highly toxic chemotherapy strategies replacing or augmenting them with less toxic alternatives. We believe this new approach forms an exciting roadmap for future biomedical advances.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.995
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.711
GPT teacher head0.515
Teacher spread0.196 · 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