19 research outputs found

    A New Strategy to Identify and Annotate Human RPE-Specific Gene Expression

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    Background: To identify and functionally annotate cell type-specific gene expression in the human retinal pigment epithelium (RPE), a key tissue involved in age-related macular degeneration and retinitis pigmentosa. Methodology: RPE, photoreceptor and choroidal cells were isolated from selected freshly frozen healthy human donor eyes using laser microdissection. RNA isolation, amplification and hybridization to 44 k microarrays was carried out according to Agilent specifications. Bioinformatics was carried out using Rosetta Resolver, David and Ingenuity software. Principal Findings: Our previous 22 k analysis of the RPE transcriptome showed that the RPE has high levels of protein synthesis, strong energy demands, is exposed to high levels of oxidative stress and a variable degree of inflammation. We currently use a complementary new strategy aimed at the identification and functional annotation of RPE-specific expressed transcripts. This strategy takes advantage of the multilayered cellular structure of the retina and overcomes a number of limitations of previous studies. In triplicate, we compared the transcriptomes of RPE, photoreceptor and choroidal cells and we deduced RPE specific expression. We identified at least 114 entries with RPE-specific gene expression. Thirty-nine of these 114 genes also show high expression in the RPE, comparison with the literature showed that 85% of these 39 were previously identified to be expressed in the RPE. In the group of 114 RPE specific genes there was an overrepresentation of genes involved in (membrane) transport, vision and ophthalmic disease. More fundamentally, we found RPE-specific involvement in the RAR-activation, retinol metabolism and GABA receptor signaling pathways. Conclusions: In this study we provide a further specification and understanding of the RPE transcriptome by identifying and analyzing genes that are specifically expressed in the RPE

    Self-Compassion, emotion regulation and stress among australian psychologists: Testing an emotion regulation model of self-compassion using structural equation modeling

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    Psychologists tend to report high levels of occupational stress, with serious implications for themselves, their clients, and the discipline as a whole. Recent research suggests that selfcompassion is a promising construct for psychologists in terms of its ability to promote psychological wellbeing and resilience to stress; however, the potential benefits of self-compassion are yet to be thoroughly explored amongst this occupational group. Additionally, while a growing body of research supports self-compassion as a key predictor of psychopathology, understanding of the processes by which self-compassion exerts effects on mental health outcomes is limited. Structural equation modelling (SEM) was used to test an emotion regulation model of self-compassion and stress among psychologists, including postgraduate trainees undertaking clinical work (n = 198). Self-compassion significantly negatively predicted emotion regulation difficulties and stress symptoms. Support was also found for our preliminary explanatory model of self-compassion, which demonstrates the mediating role of emotion regulation difficulties in the self-compassion-stress relationship. The final self-compassion model accounted for 26.2% of variance in stress symptoms. Implications of the findings and limitations of the study are discussed

    Transgenic and knockout mice in the study of neurodegenerative diseases.

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    Accurate animal models are essential for detailed analysis of the mechanisms underlying human neurodegenerative diseases. In addition, they can offer useful paradigms for the development and evaluation of new therapeutic strategies. We review the most popular techniques for modification of the mammalian genome in vivo, and provide a critical evaluation of the available transgenic mouse models for several neurological conditions of humans, including prion diseases, human retroviral diseases, Alzheimer's disease, and motor neuron diseases
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