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Record W2952921291

IN VITRO STUDIES ON CYANIDIN PROTECTION AGAINST DOXORUBICIN CARDIOMYOCYTE CYTOTOXICITY AND ANTICANCER ACTIVITY

2019· dissertation· en· W2952921291 on OpenAlexfundno aff
Muath Helal

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldChemistry
TopicSynthesis and biological activity
Canadian institutionsnot available
FundersSaskatchewan Health Research Foundation
KeywordsDoxorubicinCytotoxicityIn vitroAnticancer drugPharmacologyChemistryMedicineBiochemistryDrugInternal medicineChemotherapy
DOInot available

Abstract

fetched live from OpenAlex

Mitochondrial reactive oxygen species (ROS) are recognized for their role in several health related problems when produced at excessively high concentrations. Due to their potent antioxidant activity and potential mitochondriotropic behavior, the anthocyanidins may have the potential to lower mitochondrial ROS levels. Nevertheless, the effect of anthocyanidins remains overlooked due to their presumed low stability and bioavailability. In addition, this instability has lead to a general belief that the phenolic degradation products, protocatechuic acid (PCA) and phloroglucinaldehye (PGA), exert the bioactivity rather than the parent compound. \nIn this work, doxorubicin-induced cytotoxicity in differentiated H9c2 cardiomyocytes was initially established as a model in which the mitochondrial antioxidant activity of the selected flavonoids would be examined. First, we delineated the mechanisms by which doxorubicin affected H9c2 cell survival and mitochondrial function. The results showed that the early effects of doxorubicin on mitochondrial superoxide generation led to a delayed effect on cell survival. Using this model, we then revealed the protective ability of cyanidin against doxorubicin-induced cytological damage, showing protection to mitochondria. While cyanidin co-incubation with doxorubicin did not show protection when cell survival was assessed after 24 h, it gave delayed protection after a further 24 h drug-free period. Using the delayed protection model, we also showed that cyanidin had greater bioactivity over other flavonoids tested (quercetin, catechin and cyanidin-3-glucoside (C3G)). The protection by cyanidin also exceeded that of its degradation products (PCA and PGA), suggesting that the parent compound has additional bioactivity. The cytoprotective ability of the flavonoids was related to their ability to lower mitochondrial superoxide at early time points, with cyanidin being the most effective. Experiments on doxorubicin cytotoxicity to HepG2 (liver cancer) and K562 (erythroleukemia) cells showed no protective effect with cyanidin. These results suggest cyanidin protects cardiomyocytes but does not interfere with the cytotoxic activity of doxorubicin in the cancer cell lines. \nInvestigations on the degradation of cyanidin in physiological media, UV-vis, HPLC and MS analytical techniques provided evidence that cyanidin does not degrade immediately to PCA and PGA. Instead, intermediate compounds (hemiketal and chalcone) survived for sufficient periods to exert putative bioactivity. Studies on the influence of different media on the degradation of cyanidin showed that the stability in human serum was significantly higher (t½ 43.2 min at room temperature, 22 ¬± 1°C) compared to phosphate buffered saline and Dulbecco’s Modified Eagle’s Medium with and without 10% fetal bovine serum (t½ 10.2-32.6 min). \nIn conclusion, using differentiated H9c2 cells, our results show an ability of cyanidin to survive long enough in cell culture media, and presumably intracellularly, to exert cytoprotection against doxorubicin which exceeded that of other flavonoids (quercetin, catechin, C3G) and its degradation products (PCA and PGA). The results present cyanidin as a possible antioxidant choice to use in clinical practice to protect the heart from the mitochondrial toxicity of doxorubicin and warrants investigation into this possible therapeutic application.

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 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 score0.018
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.037
GPT teacher head0.295
Teacher spread0.257 · 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
Published2019
Admission routes1
Has abstractyes

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