Improvement of in vivo efficacy of recombinant human erythropoietin by encapsulation in PEG&amp;ndash;PLA micelle

Shi, Yanan; Huang, Wan; Liang, Rongcai; Sun, Kaoxiang; Zhang, Fangxi; Liu, Wanhui; Li, Youxin

doi:10.2147/ijn.s38648

Cited by 13 publications

(10 citation statements)

References 44 publications

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“…These differentially expressed miRNAs can be further used in developing effective diagnostic tools. Recently, few studies are carried out to identify differentially expressed miRNAs [ 4 ]‐[ 9 ]. However, absence of robust method makes it an open problem.…”

Section: Introductionmentioning

confidence: 99%

“…Given a data set with discretized attribute values, it is possible to find a subset of the original attributes using rough set theory that are the most informative; all other attributes can be removed from the data set with minimal information loss. The theory of rough sets has also been successfully applied to microarray data analysis in [ 9 , 24 ]‐[ 35 ].…”

Section: Introductionmentioning

confidence: 99%

“…However, the real life high dimensional microarray data set may contain a number of irrelevant and insignificant miRNAs [ 9 ]. The presence of such miRNAs may lead to a reduction in useful information and degrade the prediction capability.…”

Section: Introductionmentioning

confidence: 99%

“…Such miRNAs are expected to be able to predict the classes of the samples. Accordingly, a measure is required that can assess the effectiveness of a miRNA set [ 9 ].…”

Section: Introductionmentioning

confidence: 99%

“…In microarray data, the class labels of samples are represented by discrete symbols, while the expression values of miRNAs are continuous. Hence, to measure both relevance and significance of miRNAs using rough set theory, the continuous expression values of a miRNA have to be divided into several discrete partitions to generate equivalence classes [ 9 ]. However, the inherent error that exists in discretization process is of major concern in the computation of the dependency of real valued features.…”

Section: Introductionmentioning

confidence: 99%

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μHEM for identification of differentially expressed miRNAs using hypercuboid equivalence partition matrix

Paul

Maji

2013

BMC Bioinformatics

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BackgroundThe miRNAs, a class of short approximately 22‐nucleotide non‐coding RNAs, often act post‐transcriptionally to inhibit mRNA expression. In effect, they control gene expression by targeting mRNA. They also help in carrying out normal functioning of a cell as they play an important role in various cellular processes. However, dysregulation of miRNAs is found to be a major cause of a disease. It has been demonstrated that miRNA expression is altered in many human cancers, suggesting that they may play an important role as disease biomarkers. Multiple reports have also noted the utility of miRNAs for the diagnosis of cancer. Among the large number of miRNAs present in a microarray data, a modest number might be sufficient to classify human cancers. Hence, the identification of differentially expressed miRNAs is an important problem particularly for the data sets with large number of miRNAs and small number of samples.ResultsIn this regard, a new miRNA selection algorithm, called μHEM, is presented based on rough hypercuboid approach. It selects a set of miRNAs from a microarray data by maximizing both relevance and significance of the selected miRNAs. The degree of dependency of sample categories on miRNAs is defined, based on the concept of hypercuboid equivalence partition matrix, to measure both relevance and significance of miRNAs. The effectiveness of the new approach is demonstrated on six publicly available miRNA expression data sets using support vector machine. The.632+ bootstrap error estimate is used to minimize the variability and biasedness of the derived results.ConclusionsAn important finding is that the μHEM algorithm achieves lowest B.632+ error rate of support vector machine with a reduced set of differentially expressed miRNAs on four expression data sets compare to some existing machine learning and statistical methods, while for other two data sets, the error rate of the μHEM algorithm is comparable with the existing techniques. The results on several microarray data sets demonstrate that the proposed method can bring a remarkable improvement on miRNA selection problem. The method is a potentially useful tool for exploration of miRNA expression data and identification of differentially expressed miRNAs worth further investigation.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…Such miRNAs are expected to be able to predict the classes of the samples. Accordingly, a measure is required that can assess the effectiveness of a miRNA set [ 9 ].…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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μHEM for identification of differentially expressed miRNAs using hypercuboid equivalence partition matrix

Paul

Maji

2013

BMC Bioinformatics

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Cationic micelle delivery of a multi‐epitope vaccine candidate derived from tumor‐associated antigens, causing regression in established CT26 colorectal tumors in mice

Sabzehei,

Taromchi,

Ramazani

et al. 2023

J Biomedical Materials Res

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Among all the cancers, colorectal cancer (CRC) has the third mortality rank in both genders. Cancer vaccines have shown promising results in boosting patients' immune systems to fight cancer. Using the IEDB database, we predicted mouse MHC‐I (H2‐Ld) binding epitopes from four tumor‐associated antigens (APC, KRAS, TP53, and PIK3CA) and designed a multi‐epitope vaccine. We expressed the candidate vaccine and encapsulated it into the cationic micelle with polyethyleneimine conjugated to oleic acid as its building blocks. We studied tumor inhibition effect, cytokine production, and lymphocyte proliferation in the mouse CRC model after vaccination. Our finding illustrated significant tumor growth inhibition in mouse models treated with the candidate nanovaccine. Besides the significant release of IFN‐γ and IL‐4 by immunized mouse spleen T‐lymphocytes, T‐cell proliferation assay results confirmed effective immune response after the vaccination. These results demonstrate the potential therapeutic effects of nanovaccines and could be a possible approach to CRC immunotherapy.

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Current status of in vivo bioanalysis of nano drug delivery systems

Wang

Zhang

Sun

et al. 2020

Journal of Pharmaceutical Analysis

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Improvement of in vivo efficacy of recombinant human erythropoietin by encapsulation in PEG–PLA micelle

Cited by 13 publications

References 44 publications

μHEM for identification of differentially expressed miRNAs using hypercuboid equivalence partition matrix

μHEM for identification of differentially expressed miRNAs using hypercuboid equivalence partition matrix

Cationic micelle delivery of a multi‐epitope vaccine candidate derived from tumor‐associated antigens, causing regression in established CT26 colorectal tumors in mice

Current status of in vivo bioanalysis of nano drug delivery systems

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