Evidence map›Paper›PMID 23569859›Full record

ArticleAsian Pacific journal of tropical biomedicine2012

Preparation and characterization of curcumin-piperine dual drug loaded nanoparticles.

C Moorthi, Kiran Krishnan, R Manavalan, K Kathiresan

Abstract read
In one paragraph

Article in Asian Pacific journal of tropical biomedicine, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

22 citing papers in PubMed.

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  16. Future directions in the prevention of prostate cancer.Nature reviews. Clinical oncology · 2014
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

C MoorthiDepartment of Pharmacy, Annamalai University, Annamalai Nagar, Chidambaram, Tamil Nadu, India.
Kiran Krishnan
R Manavalan
K Kathiresan

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo prepare curcumin-piperine (Cu-Pi) nanoparticles by various methods and to study the effect of various manufacturing parameters on Cu-Pi nanoparticles and to identify a suitable method for the preparation of Cu-Pi nanoparticles to overcome oral bioavailability and cancer cell targeting limitations in the treatment of cancer.

methodsCu-Pi nanoparticles were prepared by thin film hydration method, solid dispersion method, emulsion polymerization method and Fessi method. Optimization was carried out to study the effect of various manufacturing parameter on the Cu-Pi nanoparticles.

resultsOut of four methods, Fessi method produced a minimum average particle size of 85.43 nm with a polydispersity index of 0.183 and zeta potential of 29.7 mV. Change of organic solvent (acetone or ethanol) did not have any significant effect on Cu-Pi nanoparticles. However, increase in sonication time, stirring speed, viscosity, use of 1:10:10 ratio of drug/polymer/surfactant, and use of anionic surfactant or combination of anionic surfactant with cationic polymer or combination of non-ionic surfactant with cationic polymer had a significant effect on Cu-Pi nanoparticles.

conclusionsCu-Pi nanoparticles coated with PEG containing copolymer produced by Fessi method had a minimum average particle size, excellent polydispersity index and optimal zeta potential which fall within the acceptable limits of the study. This dual nanoparticulate drug delivery system appears to be promising to overcome oral bioavailability and cancer cell targeting limitations in the treatment of cancer.

Indexed as

AlkaloidsAntineoplastic AgentsBenzodioxolesCurcuminDrug CarriersDrug CombinationsNanoparticlesParticle SizePiperidinesPolyunsaturated AlkamidesAlkaloidsAntineoplastic AgentsBenzodioxolesCurcuminDrug CarriersDrug CombinationsPiperidinespiperinePolyunsaturated AlkamidesCancer treatmentCurcuminNanoparticlesPiperinePolymeric nanoparticles

Identifiers

PMID23569859
PMCPMC3609247

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.