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Record W7020750030

Mitochondrial mechanisms in benzo[a]pyrene-induced carcinogenesis and chemoprevention by polyphenols

2018· dissertation· en· W7020750030 on OpenAlexfundno aff

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldMedicine
TopicSirtuins and Resveratrol in Medicine
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaSaskatchewan Health Research Foundation
KeywordsMitochondrionCarcinogenesisResveratrolOxidative stressMitochondrial ROSReactive oxygen speciesNeoplastic transformationSuperoxide
DOInot available

Abstract

fetched live from OpenAlex

Naturally occurring polyphenols in fruits and vegetables have been shown to exhibit anticancer characteristics. Although some roles of polyphenols in cancer prevention have been previously described, an involvement of mitochondrial mechanisms has not been well-studied. Also, while mitochondrial dysfunction has been identified in several cancer cells and is correlated with poor prognosis, less is known about the involvement of mitochondrial changes in carcinogenesis and neoplastic transformation. In an in vitro model of cancer initiation and promotion using Bhas 42 fibroblasts, we investigated the involvement of mitochondrial changes induced by benzo[a]pyrene (B[a]P) and possible roles of different polyphenols in preventing carcinogenesis and neoplastic transformation, through inhibiting oxidative stress, inducing mitochondrial biogenesis, and ameliorating mitochondrial dysfunction. \nBhas 42 mouse fibroblast cells were pre-treated with 5 μM polyphenols (resveratrol, quercetin, catechin, cyanidin, cyanidin-3-glucoside (C3G), and berberine) for 2h for most experiments followed by treatment with 4 μM B[a]P for 12h, 24h and 72h. Different experiments including measuring intracellular reactive oxygen species (ROS), mitochondrial superoxide, gene expression, mitochondrial content, and neoplastic transformation were conducted.\nB[a]P induced oxidative stress by increasing intracellular ROS and mitochondrial superoxide generation, as well as induced UCP2 expression compared to untreated cells. Most of the polyphenols prevented these effects; however, only anthocyanins (cyanidin and C3G) and berberine decreased B[a]P-induced mitochondrial superoxide generation. B[a]P induced neoplastic transformation almost 5-fold while resveratrol and quercetin inhibited this effect and resveratrol had the strongest effect, inhibiting by 75%. B[a]P also decreased mitochondrial content, as well as decreased SIRT1 activity, ERRα expression, and expression of some mitochondrial respiratory subunits (NDUFS8, ATP5A1, and CYB). All polyphenols increased at least one of these factors with different effectiveness. B[a]P exposure also produced mitochondrial dysfunction, decreased mitochondrial membrane potential (MMP) and ATP content by 25% and 28%, respectively, while some polyphenols such as resveratrol and quercetin completely prevented B[a]P-induced mitochondrial dysfunction. The increased mitochondrial biogenesis by resveratrol corresponded with decreased ROS generation and can be suggested as a plausible mechanism by which resveratrol inhibited B[a]P-induced neoplastic transformation more strongly than other studied polyphenols. \nThe study showed that B[a]P impaired mitochondrial biogenesis and induced mitochondrial dysfunction, oxidative stress, and neoplastic transformation, whereas different polyphenols protected against these effects, with resveratrol showing the most robust effects. The results shed new light into mitochondrial mechanisms by which polyphenols may prevent cancer initiation and progression.

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 score0.004

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 head0.010
GPT teacher head0.281
Teacher spread0.271 · 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
Published2018
Admission routes1
Has abstractyes

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