10 research outputs found

    Identification of Single- and Multiple-Class Specific Signature Genes from Gene Expression Profiles by Group Marker Index

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    Informative genes from microarray data can be used to construct prediction model and investigate biological mechanisms. Differentially expressed genes, the main targets of most gene selection methods, can be classified as single- and multiple-class specific signature genes. Here, we present a novel gene selection algorithm based on a Group Marker Index (GMI), which is intuitive, of low-computational complexity, and efficient in identification of both types of genes. Most gene selection methods identify only single-class specific signature genes and cannot identify multiple-class specific signature genes easily. Our algorithm can detect de novo certain conditions of multiple-class specificity of a gene and makes use of a novel non-parametric indicator to assess the discrimination ability between classes. Our method is effective even when the sample size is small as well as when the class sizes are significantly different. To compare the effectiveness and robustness we formulate an intuitive template-based method and use four well-known datasets. We demonstrate that our algorithm outperforms the template-based method in difficult cases with unbalanced distribution. Moreover, the multiple-class specific genes are good biomarkers and play important roles in biological pathways. Our literature survey supports that the proposed method identifies unique multiple-class specific marker genes (not reported earlier to be related to cancer) in the Central Nervous System data. It also discovers unique biomarkers indicating the intrinsic difference between subtypes of lung cancer. We also associate the pathway information with the multiple-class specific signature genes and cross-reference to published studies. We find that the identified genes participate in the pathways directly involved in cancer development in leukemia data. Our method gives a promising way to find genes that can involve in pathways of multiple diseases and hence opens up the possibility of using an existing drug on other diseases as well as designing a single drug for multiple diseases

    CYP3A5 Mediates Effects of Cocaine on Human Neocorticogenesis: Studies using an In Vitro 3D Self-Organized hPSC Model with a Single Cortex-Like Unit

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    Because of unavoidable confounding variables in the direct study of human subjects, it has been difficult to unravel the effects of prenatal cocaine exposure on the human fetal brain, as well as the cellular and biochemical mechanisms involved. Here, we propose a novel approach using a human pluripotent stem cell (hPSC)-based 3D neocortical organoid model. This model retains essential features of human neocortical development by encompassing a single self-organized neocortical structure, without including an animal-derived gelatinous matrix. We reported previously that prenatal cocaine exposure to rats during the most active period of neural progenitor proliferation induces cytoarchitectural changes in the embryonic neocortex. We also identified a role of CYP450 and consequent oxidative ER stress signaling in these effects. However, because of differences between humans and rodents in neocorticogenesis and brain CYP metabolism, translation of the research findings from the rodent model to human brain development is uncertain. Using hPSC 3D neocortical organoids, we demonstrate that the effects of cocaine are mediated through CYP3A5-induced generation of reactive oxygen species, inhibition of neocortical progenitor cell proliferation, induction of premature neuronal differentiation, and interruption of neural tissue development. Furthermore, knockdown of CYP3A5 reversed these cocaine-induced pathological phenotypes, suggesting CYP3A5 as a therapeutic target to mitigate the deleterious neurodevelopmental effects of prenatal cocaine exposure in humans. Moreover, 3D organoid methodology provides an innovative platform for identifying adverse effects of abused psychostimulants and pharmaceutical agents, and can be adapted for use in neurodevelopmental disorders with genetic etiologies

    A Dry Powder Formulation of Liposome-Encapsulated Recombinant Secretory Leukocyte Protease Inhibitor (rSLPI) for Inhalation: Preparation and Characterisation

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    Inhaled recombinant secretory leukocyte protease inhibitor (rSLPI) has shown potential for the treatment of inflammatory lung conditions. Rapid inactivation of rSLPI by cathepsin L (Cat L) and rapid clearance from the lungs has limited clinical efficacy to date. Previous studies by us have shown that encapsulation of rSLPI within1,2-dioleoyl-sn-glycero-3-[phospho-L-serine]/cholesterol (DOPS/Chol) liposomes protects rSLPI against Cat L inactivation in vitro. Liquid DOPS–rSLPI preparations were found to be unstable upon long-term storage and nebulisation. The aim of this study was therefore to develop a method of manufacture for preparing DOPS–rSLPI liposomes as a dry powder for inhalation. DOPS–rSLPI dry powders were lyophilised and subsequently micronised with a novel micronisation aid. The effects of formulation and processing on rSLPI stability, activity, and uniformity of content within the powders were characterised. Using D-mannitol as the micronisation aid, dry powder particles in the inhalable size range (<5 μm) were prepared. By optimising process parameters, up to 54% of rSLPI was recovered after micronisation, of which there was no significant loss in anti-neutrophil elastase activity and no detectable evidence of protein degradation. Aerosolisation was achieved using a dry powder inhaler, and mass median aerodynamic diameter (MMAD) was evaluated after collection in a cascade impactor. Aerosolisation of the DOPS–rSLPI dry powder yielded 38% emitted dose, with 2.44 μm MMAD. When challenged with Cat L post-aerosolisation, DOPS–rSLPI dry powder was significantly better at retaining a protective function against Cat L-induced rSLPI inactivation compared to the aqueous DOPS–rSLPI liposome dispersion and was also more stable under storage
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