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Record W2415872615 · doi:10.1038/srep19812

Influence of Electric Fields and Conductivity on Pollen Tube Growth assessed via Electrical Lab-on-Chip

2016· article· en· W2415872615 on OpenAlexafffund
Carlos G. Agudelo, Muthukumaran Packirisamy, Anja Geitmann

Bibliographic record

VenueScientific Reports · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and Biological Electrophysiology Studies
Canadian institutionsUniversité de MontréalConcordia University
FundersFonds Québécois de la Recherche sur la Nature et les Technologies
KeywordsPollen tubePollenElectric fieldOvuleGynoeciumElectrical resistivity and conductivityTube (container)SpermBiological systemBiologyBotanyBiophysicsMaterials sciencePhysicsPollinationComposite materialStamen

Abstract

fetched live from OpenAlex

Pollen tubes are polarly growing plant cells that are able to rapidly respond to a combination of chemical, mechanical, and electrical cues. This behavioural feature allows them to invade the flower pistil and deliver the sperm cells in highly targeted manner to receptive ovules in order to accomplish fertilization. How signals are perceived and processed in the pollen tube is still poorly understood. Evidence for electrical guidance in particular is vague and highly contradictory. To generate reproducible experimental conditions for the investigation of the effect of electric fields on pollen tube growth we developed an Electrical Lab-on-Chip (ELoC). Pollen from the species Camellia displayed differential sensitivity to electric fields depending on whether the entire cell or only its growing tip was exposed. The response to DC fields was dramatically higher than that to AC fields of the same strength. However, AC fields were found to restore and even promote pollen growth. Surprisingly, the pollen tube response correlated with the conductivity of the growth medium under different AC frequencies--consistent with the notion that the effect of the field on pollen tube growth may be mediated via its effect on the motion of ions.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.554
Threshold uncertainty score0.219

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.015
GPT teacher head0.215
Teacher spread0.200 · 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

Citations29
Published2016
Admission routes2
Has abstractyes

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