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Record W91790983

Biochemical, Molecular and Pharmacological Studies of the Wheat (Triticum aestivum L) Flavone, Tricin

2012· dissertation· en· W91790983 on OpenAlexaboutno aff
Amira Moheb

Bibliographic record

VenueSpectrum Research Repository (Concordia University) · 2012
Typedissertation
Languageen
FieldMedicine
TopicPhytochemicals and Antioxidant Activities
Canadian institutionsnot available
Fundersnot available
KeywordsTricinCropCommon wheatAbiotic stressAbiotic componentAgronomyBiologyChemistryBotanyAntioxidantFlavonoidBiochemistryGene
DOInot available

Abstract

fetched live from OpenAlex

Biochemical, Molecular and Pharmacological Studies of the Wheat (Triticum aestivum L) Flavone, Tricin
\n 
\nAmira Moheb, Ph.D. 
\nConcordia University, 2012
\n
\nTricin (5,7,4'-trihyroxy-3',5'-dimethoxyflavone), a naturally occurring compound, is a characteristic constituent of the grass family, including cereal grain plants, and has been isolated from rice, oat, maize, and wheat. Apart from being a powerful antioxidant, antimutagenic, and anti-inflammatory agent, tricin has been considered as an efficient chemopreventive agent in growth inhibition of human malignant breast tumour cells and colon cancer cells. However, its high commercial price as a pure compound may hinder further experimentation. Wheat is considered one of the main staple foods in Canada and worldwide, and is the most widely adapted crop to abiotic stresses. The main aim of this study is to investigate the effects of abiotic stress factors, such as cold, drought, and salt treatments, among others, on the biosynthesis and accumulation of tricin in different parts of wheat (Triticum aestivum L), with aim of defining an optimum source for tricin production in this important crop. This thesis consists of four research chapters.
\nThe first chapter focuses on an investigation of the phenolic profile of two varieties of wheat (Triticum aestivum L) leaves grown under normal and cold stress conditions. The leaf ‘phenolomes’ were established for two varieties: the winter wheat (Triticum aestivum L. var Claire) and spring wheat (Triticum aestivum L. var, Bounty) using a combination of HPLC-ESI-MS techniques. Phenolic compounds accumulated at a higher level in the Claire than in the Bounty variety, and detected in significant amounts in the apoplast compartment. The accumulation of a mixture of beneficial flavonoids in cold-acclimated wheat leaves attests to its potential use as an inexpensive supplement of a health-promoting component to the human diet. 
\n The second chapter describes the distribution of tricin in different parts of wheat with the aim to designate a rich source for its utilization. Winter wheat husk was identified as the most valuable part. Its tricin content is considered the highest in any plant materials suggesting the use of winter wheat husk as a good source of tricin. Moreover, the potential anticancer effect of tricin on two cancer cell lines was evaluated where it was revealed to have a selective anticancer effect. 
\n In the third chapter, the selective anticancer effect of several methylated phenolic and flavonoids compounds were tested in vitro on cell cultures, using a LDH-spectrophotometer method to assess the viability of the cell lines. Several candidates were found to possess a remarkable antitumor activity on these malignant cell lines, such as trimethyltricetin, a tricin derivative that exhibited a superior selective activity against human adenocarcinomic alveolar basal epithelial cells (A-549). 
\n In the last chapter, the biosynthesis of tricin is discussed. The expression and the enzyme activity of TaOMT2, the enzyme that catalyzes the methylation of tricetin to tricin, were measured at different wheat developmental stages and in response to different abiotic stresses such as cold, salt and drought. The significant accumulation of tricin in the inflorescences suggests that tricin may play a role in protecting the seeds against biotic and abiotic stresses.

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 score0.032
Threshold uncertainty score0.894

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.043
GPT teacher head0.333
Teacher spread0.290 · 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

Citations2
Published2012
Admission routes1
Has abstractyes

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