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EVALUATION OF IN VITRO ANTI-INFLAMMATORY, ANTI-DIABETIC AND ANTI-LIPOGENIC ACTIVITY OF NATURAL POLYPHENOLIC EXTRACTS AND THEIR PURE CONSTITUENTS

2015· dissertation· en· W1759747590 on OpenAlexfundno aff
Pragati Nahar

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldChemistry
TopicPlant-Derived Bioactive Compounds
Canadian institutionsnot available
FundersNational Institute of General Medical SciencesAgriculture and Agri-Food CanadaNational Institutes of HealthVerdure Sciences
KeywordsNutraceuticalCurcuminPolyphenolHealth benefitsAnti-inflammatoryHuman healthNatural (archaeology)Health promotionTraditional medicineMedicineBiotechnologyPublic healthChemistryBiologyPharmacologyFood scienceBiochemistryEnvironmental healthAntioxidantNursing

Abstract

fetched live from OpenAlex

The long-term goals and objectives of our group are to identify bioactive natural products relevant to human disease prevention and health promotion. To attain this goal, the objective of this thesis was to demonstrate that bioactive polyphenol-rich extracts or preparations exert positive health benefits beyond basic nutrition, thus impacting overall health and wellness. We believe that this project has immense scientific merit from a human health perspective and will be of great public impact given that consumers are seeking natural and organic choices for improving health. In this investigation, we have focused our attention on investigating the biological activities of two novel phenolic-rich preparations derived from curcumin and maple syrup for future nutraceutical applications. The work herein assessed the anti-inflammatory properties of novel standardized curcumin formulation Longvida® and phenolic-enriched maple syrup extract using a well-known in vitro model of inflammation, lipopolysaccharide (LPS)-induced RAW 264.7 murine macrophages. RAW 264.7 cells were co-treated with 50 ng/mL LPS and test extracts for 24 hours and then inflammatory markers were measured using supernatants, gene and protein expression. The activation of nuclear factor-kappa B (NFκB) was measured using luciferase activity. Both polyphenolic extracts were able to alleviate the LPS stimulated inflammation by down-regulating the inflammatory markers via targeting nuclear factor-kappa B (NFκB) (a major pathway modulated in inflammation) transcriptional activity in murine macrophages. Next, the work herein studied the anti-hyperglycemic and anti-lipogenic properties of novel standardized nutraceutical grade phenolic rich extract, MSX. Human HepG2 cells were treated with the MSX for 24 h. Glucose consumption, AMP activated protein kinase (AMPK) activation and its target gluconeogenic gene expression were measured. The glucose levels were reduced by MSX in the hepatocytes though AMPK activation. Subsequently, the anti-lipogenic effect of MSX treatment in mature differentiated 3T3-L1 murine adipocytes and human visceral adipocytes was evaluated. MSX treatment to mature adipocytes decreased lipid accumulation compared to control in both murine and human adipocytes. In 3T3-L1 adipocytes, this effect was associated with downregulation of adipo/lipogenic protein expression (e.g. PPARγ, Srebp1c). We also observed reduced mRNA expression of the pro-inflammatory mediators, namely IL-6, and TNF-α. Taken together, we demonstrated that a novel maple syrup extract exhibited anti-inflammatory, anti-hyperglycemic and anti-lipogenic activities in vitro. The current study adds to the growing body of in vitro and in vivo data supporting the biological effects and potential health benefits of the novel curcumin formulation Longvida® and the natural sweetener, maple syrup.

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 score0.001
Threshold uncertainty score0.003

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 integrity0.0000.000
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 head0.024
GPT teacher head0.282
Teacher spread0.258 · 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".

Quick stats

Citations0
Published2015
Admission routes1
Has abstractyes

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