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Record W2799474486 · doi:10.18433/jpps29726

Functionalized Caprolactone-Polyethylene Glycol Based Thermo-Responsive Hydrogels of Silibinin for the Treatment of Malignant Melanoma

2018· article· en· W2799474486 on OpenAlexafffundvenue
Behzad Sharif Makhmalzadeh, Ommoleila Molavi, Mohammad Reza Vakili, Haifeng Zhang, Amir Solimani, Hoda Soleymani Abyaneh, Raimar Löebenberg, Raymond Lai, Afsaneh Lavasanifar

Bibliographic record

VenueJournal of Pharmacy & Pharmaceutical Sciences · 2018
Typearticle
Languageen
FieldMedicine
TopicSilymarin and Mushroom Poisoning
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaAlberta InnovatesAlberta Innovates - Health Solutions
KeywordsSilibininChemistryCaprolactonePharmacologyMedicinePolymerizationOrganic chemistry

Abstract

fetched live from OpenAlex

PURPOSE: Silibinin, is a natural compound, which has shown anticancer activity in various malignancies. In this study, we evaluated the anticancer effects of silibinin in B16-F10 melanoma cells and developed a novel thermoresponsive hydrogel for local delivery of this compound. METHOD: A thermoresponsive hydrogel loaded with silibinin was prepared using triblock copolymers of poly[(α-benzyl carboxylate-e-caprolactone)-co-(α-carboxyl-e-caprolactone)]ran-b-PEG-b-[(α-benzyl carboxylate-e-caprolactone) -co-(α-carboxyl-e-caprolactone)]ran (PCBCL-b-PEG-b-PCBCL), namely PolyGelTM, and compared with a Pluronic F-127 formulation of silibinin. Sol-gel transition temperature of hydrogels was measured by inverse flow method and modulated differential scanning calorimetry (MDSC). Silibinin loading efficiency was measured by HPLC. The MTT and clonogenic assays were used to assess the cytotoxicity and anti-proliferative effects of silibinin on B16-F10 melanoma cells. Flow cytotmetry was used to quantify the induced level of apoptosis and measure the intracellular level of activated STAT3 (pSTAT3) following silibinin treatment in B16.F10 cells. The effects of silibinin on the activation of oncogenic proteins were also evaluated by western blot. RESULTS: Silibinin inhibited cell proliferation (IC50 = 67 µM), provoked cell cycle arrest, induced apoptosis, suppressed key oncogenic pathways (i.e STAT3 and MEK/ERK), and enhanced the cytotoxic effects of doxorubicin in B16-F10 cells. Both PolyGelTM and Pluronic F-127 hydrogels were effective in loading silibinin. A lower drug release pattern within 24h, fitting first- order release kinetics, was observed for the release of silibinin from both gels compared to free drug. PolyGelTM demonstrated enhanced percutaneous absorption of silibinin through increasing mouse skin intracellular lipid fluidity as documented by DSC of skin following PolyGelTM use. Silibinin loaded in PolyGel TM inhibited the growth of B16-F10 cells (IC50 = 30 µM) and effectively suppressed pSTAT3 activity in B16-F10 cells at 10 µM. CONCLUSION: Our results imply a great potential for PolyGel TM formulations of silibinin for local treatment of malignant melanoma. This article is open to POST-PUBLICATION REVIEW. Registered readers (see "For Readers") may comment by clicking on ABSTRACT on the issue's content page.

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 head0.107
GPT teacher head0.424
Teacher spread0.317 · 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

Citations27
Published2018
Admission routes3
Has abstractyes

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