Encapsulation of curcumin in alginate-chitosan-pluronic composite nanoparticles for delivery to cancer cells

Das, Ratul Kumar; Kasoju, Naresh; Bora, Utpal

doi:10.1016/j.nano.2009.05.009

Cited by 583 publications

(311 citation statements)

References 25 publications

Supporting

Mentioning

281

Contrasting

Unclassified

Order By: Relevance

“…At 1983, Korsmeyer et al provided a relationship in drug release from a polymeric system. To discover the overall mechanism of drug release, first 60% drug release data was fitted in KorsmeyerPeppas model (Dash et al, 2010).…”

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Mathematical modeling of drug release from swellable polymeric nanoparticles

2017

J App Pharma Sci

View full text Add to dashboard Cite

This study aims to provide a comparative mathematical analysis of drug release from swellable polymeric delivery systems to find a general model applicable to multi-mechanistic release. Drug release data from various swellable polymeric nanoparticles extracted from the literatures were applied to the eight conventional models. Coefficient of determination (R 2 ) and absolute percent error (E%) were calculated for each set as well as the overall error (OE), the number of error (NE) and the akaike information criterion (AIC) for all sets. The model has the highest R 2 and the number of the error, as well as both the lowest overall error (OE) and the akaike information criterion, was considered as the best one. Among the models Weibull (W) model produced R 2 and OE values of 0.93 and 8.79, respectively. Also, the AIC value and the number of errors less than 5% for the model was -34.93 and 46.15% of a total number of data sets respectively. Mathematical modeling of drug release from a carrier is often attempted to recognize the main determinants of the drug release rate from the carrier with the final goal of the identification of the ideal set of conditions leading to the desired release profile in vivo.

show abstract

Section: Resultsmentioning

confidence: 99%

“…According to the Korsmeyer-Peppas equation (Dash et al, 2010), 0.45 ≤ n are described with a Fickian diffusion mechanism, 0.45 < n <0.89 with non-Fickian transport, n = 0.89 with Case II transport, and n > 0.89 with super case II transport.…”

Section: Resultsmentioning

confidence: 99%

Mathematical modeling of drug release from swellable polymeric nanoparticles

2017

J App Pharma Sci

View full text Add to dashboard Cite

show abstract

“…This is in agreement with the results found by PIMENTEL (2010) that evaluated the progesterone release from PHBV and PHBV/PCL microparticles and found that during 12h of analysis PHBV released up to 95% of the drug while the blends of PHBV/PCL released up to 77% of the drug in the same period. DAS et al (2010) used FTIR to determine the potential interactions between the components of nanoparticles (alginate, chitosan and pluronic) containing curcumin. SAWANT et al (2010) demonstrated by FTIR spectra that there was no interaction between the drug lidocaine encapsulated in hydrophobic Eudragit polymers, since the spectrum did not presented any changes with respect to the spectra of the components when analyzed isolated.…”

Section: Resultsmentioning

confidence: 99%

Characterization of progesterone loaded biodegradable blend polymeric nanoparticles

et al. 2015

View full text Add to dashboard Cite

The encapsulation of progesterone in poly (hydroxybutirate-co-hydroxyvalerate) (PHBV), poly (ε-caprolactone) (PCL), poly (L-lactic acid) (PLLA) nanoparticles and PHBV/PCL and PHBV RESUMO A encapsulação de progesterona em nanopartículas de poli (hidroxibutirato-co-hidroxivalerato) (PHBV), poli (ε-caprolactona) (PCL), poli (L-ácido lático) (PLLA) e em nanopartículas blenda de PHBV/PCL e PHBV

show abstract

“…Similarly, curcumin encapsulated in liposomes having particle size 100-150 nm also showed increased anticarcinogenic potential against human prostate cancer cells (Thangapazam et al, 2008). Furthermore, encapsulated curcumin having size 100 nm was more accessible to cancer cells and inhibitory concentration reduced to 14.34 µm (Das et al, 2010). In our case EU NEs showed lower inhibitory concentration values against both HB8065 and HTB37 cell lines compared to EU alone.…”

Section: Discussionmentioning

confidence: 48%

Apoptotic Effects of Eugenol-loaded Nanoemulsions in Human Colon and Liver Cancer Cell Lines

Majeed¹,

Antoniou²,

Zhong³

2014

Asian Pacific Journal of Cancer Prevention

View full text Add to dashboard Cite

Background: In this study eugenol (EU) loaded nanoemulsions (NEs) emulsified with modified starch were prepared and their apoptotic potential against liver and colon cancer cells was examined in comparison with bulk EU. Materials and Methods: We prepared stable EU loaded NEs whcih were characterized by dynamic light scattering, centrifugation and gas chromatography. Furthermore, cell viability was determined using MTT assay, and apoptosis and cell cycle analysess by flow cytometry. Results: HB8065 (liver) and HTB37 (colon) cells when treated with EU:CA NEs demonstrated greater apoptotic cells percentages as evidenced by microscopic images and flow cytometric evaluations. It was observed that EU and EU:CA NE induced apoptosis in both cell lines via reactive oxygen species (ROS) generation. Conclusions: The present study demonstrated that ROS plays a critical role in EU and EU:CA NE induced apoptosis in HB8065 and HTB37 cells. This is the first report on the antiproliferative mechanisms of EU loaded NE.

show abstract

Encapsulation of curcumin in alginate-chitosan-pluronic composite nanoparticles for delivery to cancer cells

Cited by 583 publications

References 25 publications

Mathematical modeling of drug release from swellable polymeric nanoparticles

Mathematical modeling of drug release from swellable polymeric nanoparticles

Characterization of progesterone loaded biodegradable blend polymeric nanoparticles

Apoptotic Effects of Eugenol-loaded Nanoemulsions in Human Colon and Liver Cancer Cell Lines

Contact Info

Product

Resources

About