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Record W4254432607 · doi:10.1158/1538-7445.am2019-3724

Abstract 3724: Molecular mechanisms of TTField action determined by measurements and modelling of electro-conductive properties of microtubules

2019· article· en· W4254432607 on OpenAlexaff
Aarat P. Kalra, Sahil Patel, Asadullah Bhuiyan, Jordane Preto, Vahid Rezania, John D. Lewis, Karthik Shankar, Jack A. Tuszyński

Bibliographic record

VenueCancer Research · 2019
Typearticle
Languageen
FieldEngineering
TopicMolecular Communication and Nanonetworks
Canadian institutionsMacEwan UniversityUniversity of Alberta
Fundersnot available
KeywordsMicrotubuleTubulinElectrical conductorMitosisMaterials scienceActinBiophysicsChemistryPhysicsBiologyCell biologyComposite material

Abstract

fetched live from OpenAlex

Abstract Biological effects of AC electric fields at frequencies between 100-300 kHz discovered a decade ago are being applied to cancer cells as a therapeutic modality in the treatment of glioblastoma multiforme (GBM). They are called Tumor Treating Fields (TTFields) as they disrupt cell division. Based on our electro-conductive measurements and modeling, we provide an assessment of possible molecular-level mechanisms. Computer simulations and experimental measurements carried out for microtubules and actin filaments are presented. Charge and dipole values for monomers and dimers as well as polymerized forms of these proteins are summarized. Continuum approximations for cable equations describing actin filaments and microtubules compare favorably to measurements in buffer solutions showing soliton waves and transistor-like amplification of ionic signals, respectively. AC Conductivity and capacitance of tubulin and microtubules have been measured and modeled in the range of frequencies between 1 Hz and 1 MHz. A dramatic change in conductivity occurs when tubulin forms microtubules. In living cells, this signals a conductive phase transition coinciding with mitosis in dividing cells. This process is allowed by TTField penetration into the cleavage furrow in dividing cells and provides the most significant mechanistic explanation of the observed effects. We provide estimates of the forces, energies and power involved in the action of TTFields on microtubules and kinesin motors. These calculations are compared and contrasted with typical values experienced at a cell level and provide strong arguments for real physical effects of TTFields in dividing cells. We also show results of DLS and TEM measurements on microtubules and tubulin oligomers in solution, which allow us to quantify these processes under controlled conditions. In conclusion, the most likely candidates to provide a quantitative explanation of these effects are ionic condensation waves around microtubules as well as dielectrophoretic effects on the dipole moments of microtubules. Citation Format: Aarat P. Kalra, Sahil Patel, Asadullah Bhuiyan, Jordane Preto, Vahid Rezania, John D. Lewis, Karthik Shankar, Jack Tuszynski. Molecular mechanisms of TTField action determined by measurements and modelling of electro-conductive properties of microtubules [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 3724.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.013
Threshold uncertainty score0.254

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.149
GPT teacher head0.325
Teacher spread0.176 · 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 teacher head, 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

Citations0
Published2019
Admission routes1
Has abstractyes

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