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Record W2726533663

Molecular mechanisms of protection by dietary polyphenols against free fatty acid-induced mitochondrial dysfunction and endoplasmic reticulum stress in an in vitro model of non-alcoholic fatty liver disease

2017· dissertation· en· W2726533663 on OpenAlexfundno aff
Hossein Rafiei

Bibliographic record

VenueUniversity Library - University of Saskatchewan (University of Saskatchewan) · 2017
Typedissertation
Languageen
FieldMedicine
TopicLiver Disease Diagnosis and Treatment
Canadian institutionsnot available
FundersSaskatchewan Health Research Foundation
KeywordsEndoplasmic reticulumFatty liverIn vitroFatty acidPolyphenolChemistryMitochondrionBiochemistryDiseaseUnfolded protein responseMedicineInternal medicineAntioxidant
DOInot available

Abstract

fetched live from OpenAlex

Non-alcoholic fatty liver disease (NAFLD) is a public health burden. Steatosis as the “first hit”, and oxidative stress, inflammation, mitochondrial dysfunction, and endoplasmic reticulum stress as the “second hits” are the main contributors of the progression of fatty liver to non-alcoholic steatohepatitis (NASH). Dietary polyphenols have shown promise in protecting the liver against NAFLD. The relative effectiveness and mechanisms of different polyphenols however is mostly unknown. In this thesis HepG2 hepatocytes exposed to oleic or palmitic acid were used as a model system to explore the ability of selected polyphenols (resveratrol, quercetin, catechin, cyanidin, cyanidin-3-glucoside, berberine) from different classes to protect against molecular aspects of NAFLD and NASH. In an investigation of the “first hit” (Chapter 3), different polyphenols protected similarly against oleic acid-induced intracellular lipid accumulation, but differed in their effects on the expression of genes and proteins involved in lipogenesis, fatty acid oxidation, mitochondrial biogenesis, and bioenergetics. In an investigation of “second hits” (Chapter 4), most of the polyphenols decreased reactive oxygen species (ROS), prevented the decrease in uncoupling protein 2 (UCP2) mRNA, prevented the increase in tumor necrosis factor alpha (TNFα) mRNA, reversed decreases in mitochondrial biogenesis and increased expression of mitochondrial respiratory complexes and manganese superoxide dismutase (MnSOD). The anthocyanins were unique in decreasing ROS without inducing mitochondrial biogenesis or Mn-SOD mRNA expression. In investigations with palmitic acid (Chapter 5), exposure of HepG2 cells to palmitic acid induced endoplasmic reticulum (ER) stress evidenced by upregulated mRNA for the ER chaperones glucose-regulated protein 94 and 78 (GRP94, GRP78) and oxygen-regulated protein 150 (ORP150), cochaperone endoplasmic reticulum-localized DnaJ homologue 4 (ERdj4), and proapoptotic CCAAT-enhancer-binding protein homologous protein (CHOP). A few of the polyphenols (quercetin, catechin, cyanidin) protected against these changes. In a comparison of flavonoids with their phenolic breakdown/digestion products (Chapter 6), the polyphenols 2,4,6-trihydroxybenzaldehyde, protocatechuic acid, and caffeic acid protected similarly to quercetin and cyanidin against oleic and palmitic acid-induced steatosis and ROS generation. Moreover, in a short-term 1 h exposure (to limit spontaneous degradation in the medium), only breakdown/digestion products prevented an oleic acid-induced decrease of mitochondrial biogenesis. In conclusion, different classes of dietary polyphenols were all able to protect against steatosis and ROS generation in this in vitro model of NAFLD. Part of the mechanism for some polyphenols was through effects on mitochondrial biogenesis and function, bioenergetics, and ER stress. Phenolic breakdown/digestion products of flavonoids were shown to contribute to the protective effects of parent polyphenols.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.011
GPT teacher head0.190
Teacher spread0.179 · 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 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".

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Citations0
Published2017
Admission routes1
Has abstractno

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