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Record W6992217986

Lab-On-Chip for Ex-Vivo study of morphogenesis of tip growing cells of pollen tube

2014· dissertation· en· W6992217986 on OpenAlexfundno aff

Bibliographic record

VenueSpectrum Research Repository (Concordia University) · 2014
Typedissertation
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant Reproductive Biology
Canadian institutionsnot available
FundersConcordia University
KeywordsPollen tubePollenMicrochannelMicrofluidicsGametophyteTip growthTube (container)Flow (mathematics)
DOInot available

Abstract

fetched live from OpenAlex

The purpose of the thesis is to develop a microfluidic based lab-on-chip (LOC) platform providing an Ex-Vivotesting environment that is able to mimic certain aspects of the in vivo growth conditions of the pollen tube, a cellular protuberance formed by the male gametophyte in the flowering plants. The thesis focuses on design, fabrication, modeling and testing of various LOC devices for the study of static and dynamic behavior of pollen tubes in response to mechanical stimulation. 
\nTipChip, an LOC platform, was developed to advance both experimentation and phenotyping in cell tip growth research. The platform enabled simultaneous testing of multiple pollen tubes. Using TipChip, we were able to answer several outstanding questions regarding pollen tube biology. We found that contrary to other types of tip growing cells such as root hairs and fungal hyphae, pollen tubes do not have a directional memory. Furthermore, we explored the effect of geometry of the microfluidic cell culture on pollen tube growth. We found that changing the width of the microfluidic channels does not have a significant effect on the pollen tube growth rate, while the growth rate was increased by increasing microchannel depth. 
\nWe modified the original TipChip design to ascertain identical growth conditions for sequentiallyarranged pollen tubes and to ensure even distribution of entrapment probabilities for all microchannels. The effect of different dimensions of the microfluidic network on cell trapping probability was assessed using computational fluid dynamics and verified by experimental testing. The design was optimized based on trapping probability and uniformity of fluid flow conditions within the microchannels. 
\nThis thesis also presents a novel method of fabricating a high aspect ratio horizontal PDMS microcantilever-based flow sensor integrated into a microfluidic device. The performance of the flow sensor was tested by introducing various flow rates into the microfluidic device and measuring the deflection of the cantilever’s tip using an optical microscope.
\nThe thesis addresses the quantification of cellular growth force of Camellia pollen tip growing cells using FlexChip, a flexure integrated LOC on polymer. We quantified the force that pollen tube is able to exert using a microfluidic lab-on-a-chip device integrated with flexural structure. The pollen grain is trapped in the microfluidic network and the growing tube is guided against a flexible microstructure that is monolithically integrated within the microfluidic chip. The invasive growth force of growing pollen tube was calculated from the maximal bending of microstructure modelled by Finite Element Analysis (FEA). 
\nFurthermore, the effect of the mechanical obstacle on the pollen tube's growth dynamics was assessed by quantifying the shift in the peak frequency characterizing the oscillatory behavior of the pollen tube growth rate. Our detailed analysis of the pollen tube growth dynamic before and during the contact with microcantilever revealed that pollen tube growth rate was reduced by 44% during the contact with the microcantilever. Moreover, the peak of oscillation frequency of pollen tube growth rate was reduced more dramatically by 70-75%. This suggests that the pollen tube actively changes its growth pattern to cope with the mechanical obstacle. 
\nOur findings in this thesis are novel in terms of pollen biology, and we believe insights from this research will lead to a better understanding of morphogenesis of a kind of tip growing cells, namely, pollen tube.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.014
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.022
GPT teacher head0.275
Teacher spread0.253 · 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.

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
Published2014
Admission routes1
Has abstractyes

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