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Record W2117367753

Analysis of gene expression in EMF research

2004· article· en· W2117367753 on OpenAlexfundno aff
Christian Maercker, Daniel Remondini, R Nylund, Dariusz Leszczyński, Kathrin Schlatterer, R. Fitzner, R Tauber, Sabine Ivancsits, Hugo W. Rüdiger, Francesca Bersani

Bibliographic record

VenueSTM:n Hallinnonalan avoin julkaisuarkisto (Julkari) · 2004
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics, Bioinformatics, and Biomedical Research
Canadian institutionsnot available
FundersMultidisciplinary University Research InitiativeNational Institutes of HealthOld Dominion UniversityAir Force Office of Scientific ResearchCanadian Institutes of Health ResearchLawson Health Research InstituteOntario Innovation TrustU.S. Department of Defense
KeywordsGeneGene expressionGeneticsBiologyExpression (computer science)Computer science
DOInot available

Abstract

fetched live from OpenAlex

Several groups have described experiments in which nonthermal electric field pulses with durations of 10 to 300 ns and magnitudes of 1 to 150 kV/cm cause effects associated with subcellular structures.Field-induced apoptosis is the most striking effect.OBJECTIVES: We are creating progressively more realistic models of cells, such that models contain not only the outer plasma membrane (PM), but also models for subcellular structures such as the nucleus, endoplasmic reticulum and several mitochondria.This provides microdosimetry at the cellular and subcellular level.With suitable biophysical coupling models this also provides estimates of chemical change by predicting molecular and ionic transport within a cell model.METHODS: We use a transport lattice approach (Gowrishankar and Weaver, PNAS, 2003) to create two dimensional (2D) mammalian cell models that include subcellular structures.These models include local models for conductive and dielectric properties of membranes and of the extra-and intracellular electrolytes, with the dielectric properties of electrolytes important for short pulses with high frequency components.The membrane also contains local models for the resting potential and a local nonlinear, hysteretic model for lipid membrane electroporation, which involves solving an ordinary differential equation at ~600 local sites within the cell model (Stewart et al, submitted).We also use a 3 µm X 3 µm membrane planar patch model with a Smoluchowski equation-based model to investigate local electroporation behavior due to pulses of a wide range of durations and amplitudes. RESULTS:The planar patch model shows that supra-electroporation (two to three orders of magnitude more pores per area than conventional electroporation) is expected for the very large, submicrosecond pulses (Vailkoski et al., in preparation), and that only minimum size pores (r ~ 1 nm) are involved in preventing the transmembrane voltage from exceeding ~1.5 V.The 2D cell models show that the PM is supra-electroporated.Both displacement and conductive currents create sufficiently large intracellular fields that the mitochondrial inner membrane is electroporated, with the postpulse, slowly decaying pore population sufficient to create a quasi-voltage clamp of ~0 V (transmembrane voltage).This should open the mitochondrial permeability transition pore (MPTP), one proposed mechanism for initiating apoptosis by a permeability transition (Halestrap et al.Biochimie, 2002; Zamzami and Kroemer, Curr.Biol.2003).A general feature of our models is that supra-electroporation occurs extensively in the PM and less but significant electroporation occurs in membranes of the nucleus, endoplasmic reticulum and both the inner and outer mitochondrial membranes.The small, residual pores have lifetimes of order seconds, which is a mechanism for translating submicrosecond interactions to the physiological time scale of 0.1 ms to seconds.Translocation of membrane components is expected for both conventional (pulses with > 100 microsecond durations and ~ 1 kV/cm magnitudes) and supra-electroporation, and the persistence of translocated phospholipids or proteins generates signals that can last for even longer times.Both molecular and ionic transport of residual pores and signaling by translocated membrane molecules may contribute to diverse and potentially specific intracellular effects that are caused by the exposure of cells and tissues to extremely large, submicrosecond pulses.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.037
GPT teacher head0.350
Teacher spread0.312 · 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 designObservational
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".

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Citations0
Published2004
Admission routes1
Has abstractno

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