253 research outputs found

    Epigenetic Alterations Are Critical for Fear Memory Consolidation and Synaptic Plasticity in the Lateral Amygdala

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    Epigenetic mechanisms, including histone acetylation and DNA methylation, have been widely implicated in hippocampal-dependent learning paradigms. Here, we have examined the role of epigenetic alterations in amygdala-dependent auditory Pavlovian fear conditioning and associated synaptic plasticity in the lateral nucleus of the amygdala (LA) in the rat. Using Western blotting, we first show that auditory fear conditioning is associated with an increase in histone H3 acetylation and DNMT3A expression in the LA, and that training-related alterations in histone acetylation and DNMT3A expression in the LA are downstream of ERK/MAPK signaling. Next, we show that intra-LA infusion of the histone deacetylase (HDAC) inhibitor TSA increases H3 acetylation and enhances fear memory consolidation; that is, long-term memory (LTM) is enhanced, while short-term memory (STM) is unaffected. Conversely, intra-LA infusion of the DNA methyltransferase (DNMT) inhibitor 5-AZA impairs fear memory consolidation. Further, intra-LA infusion of 5-AZA was observed to impair training-related increases in H3 acetylation, and pre-treatment with TSA was observed to rescue the memory consolidation deficit induced by 5-AZA. In our final series of experiments, we show that bath application of either 5-AZA or TSA to amygdala slices results in significant impairment or enhancement, respectively, of long-term potentiation (LTP) at both thalamic and cortical inputs to the LA. Further, the deficit in LTP following treatment with 5-AZA was observed to be rescued at both inputs by co-application of TSA. Collectively, these findings provide strong support that histone acetylation and DNA methylation work in concert to regulate memory consolidation of auditory fear conditioning and associated synaptic plasticity in the LA

    Activity and regulation by growth factors of calmodulin-dependent protein kinase III (elongation factor 2-kinase) in human breast cancer

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    Calmodulin-dependent protein kinase III (CaM kinase III, elongation factor-2 kinase) is a unique member of the Ca2+/CaM-dependent protein kinase family. Activation of CaM kinase III leads to the selective phosphorylation of elongation factor 2 (eEF-2) and transient inhibition of protein synthesis. Recent cloning and sequencing of CaM kinase III revealed that this enzyme represents a new superfamily of protein kinases. The activity of CaM kinase III is selectively activated in proliferating cells; inhibition of the kinase blocked cells in G0/G1-S and decreased viability. To determine the significance of CaM kinase III in breast cancer, we measured the activity of the kinase in human breast cancer cell lines as well as in fresh surgical specimens. The specific activity of CaM kinase III in human breast cancer cell lines was equal to or greater than that seen in a variety of cell lines with similar rates of proliferation. The specific activity of CaM kinase III was markedly increased in human breast tumour specimens compared with that of normal adjacent breast tissue. The activity of this enzyme was regulated by breast cancer mitogens. In serum-deprived MDA-MB-231 cells, the combination of insulin-like growth factor I (IGF-I) and epidermal growth factor (EGF) stimulated cell proliferation and activated CaM kinase III to activities observed in the presence of 10% serum. Inhibition of enzyme activity blocked cell proliferation induced by growth factors. In MCF-7 cells separated by fluorescence-activated cell sorting, CaM kinase III was increased in S-phase over that of other phases of the cell cycle. In summary, the activity of Ca2+/CaM-dependent protein kinase III is controlled by breast cancer mitogens and appears to be constitutively activated in human breast cancer. These results suggest that CaM kinase III may contribute an important link between growth factor/receptor interactions, protein synthesis and the induction of cellular proliferation in human breast cancer. © 1999 Cancer Research Campaig

    Computational modelling of wound healing insights to develop new treatments

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    About 1% of the population will suffer a severe wound during their life. Thus, it is really important to develop new techniques in order to properly treat these injuries due to the high socioeconomically impact they suppose. Skin substitutes and pressure based therapies are currently the most promising techniques to heal these injuries. Nevertheless, we are still far from finding a definitive skin substitute for the treatment of all chronic wounds. As a first step in developing new tissue engineering tools and treatment techniques for wound healing, in silico models could help in understanding the mechanisms and factors implicated in wound healing. Here, we review mathematical models of wound healing. These models include different tissue and cell types involved in healing, as well as biochemical and mechanical factors which determine this process. Special attention is paid to the contraction mechanism of cells as an answer to the tissue mechanical state. Other cell processes such as differentiation and proliferation are also included in the models together with extracellular matrix production. The results obtained show the dependency of the success of wound healing on tissue composition and the importance of the different biomechanical and biochemical factors. This could help to individuate the adequate concentration of growth factors to accelerate healing and also the best mechanical properties of the new skin substitute depending on the wound location in the body and its size and shape. Thus, the feedback loop of computational models, experimental works and tissue engineering could help to identify the key features in the design of new treatments to heal severe wounds

    Genetic Modulation of Rpd3 Expression Impairs Long-Term Courtship Memory in Drosophila

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    There is increasing evidence that regulation of local chromatin structure is a critical mechanism underlying the consolidation of long-term memory (LTM), however considerably less is understood about the specific mechanisms by which these epigenetic effects are mediated. Furthermore, the importance of histone acetylation in Drosophila memory has not been reported. The histone deacetylase (HDAC) Rpd3 is abundant in the adult fly brain, suggesting a post-mitotic function. Here, we investigated the role of Rpd3 in long-term courtship memory in Drosophila. We found that while modulation of Rpd3 levels predominantly in the adult mushroom body had no observed impact on immediate recall or one-hour memory, 24-hour LTM was severely impaired. Surprisingly, both overexpression as well as RNAi-mediated knockdown of Rpd3 resulted in impairment of long-term courtship memory, suggesting that the dose of Rpd3 is critical for normal LTM

    Mood Induction in Depressive Patients: A Comparative Multidimensional Approach

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    Anhedonia, reduced positive affect and enhanced negative affect are integral characteristics of major depressive disorder (MDD). Emotion dysregulation, e.g. in terms of different emotion processing deficits, has consistently been reported. The aim of the present study was to investigate mood changes in depressive patients using a multidimensional approach for the measurement of emotional reactivity to mood induction procedures. Experimentally, mood states can be altered using various mood induction procedures. The present study aimed at validating two different positive mood induction procedures in patients with MDD and investigating which procedure is more effective and applicable in detecting dysfunctions in MDD. The first procedure relied on the presentation of happy vs. neutral faces, while the second used funny vs. neutral cartoons. Emotional reactivity was assessed in 16 depressed and 16 healthy subjects using self-report measures, measurements of electrodermal activity and standardized analyses of facial responses. Positive mood induction was successful in both procedures according to subjective ratings in patients and controls. In the cartoon condition, however, a discrepancy between reduced facial activity and concurrently enhanced autonomous reactivity was found in patients. Relying on a multidimensional assessment technique, a more comprehensive estimate of dysfunctions in emotional reactivity in MDD was available than by self-report measures alone and this was unsheathed especially by the mood induction procedure relying on cartoons. The divergent facial and autonomic responses in the presence of unaffected subjective reactivity suggest an underlying deficit in the patients' ability to express the felt arousal to funny cartoons. Our results encourage the application of both procedures in functional imaging studies for investigating the neural substrates of emotion dysregulation in MDD patients. Mood induction via cartoons appears to be superior to mood induction via faces and autobiographical material in uncovering specific emotional dysfunctions in MDD

    The multiplex bead array approach to identifying serum biomarkers associated with breast cancer

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    Introduction Breast cancer is the most common type of cancer seen in women in western countries. Thus, diagnostic modalities sensitive to early-stage breast cancer are needed. Antibody-based array platforms of a data-driven type, which are expected to facilitate more rapid and sensitive detection of novel biomarkers, have emerged as a direct, rapid means for profiling cancer-specific signatures using small samples. In line with this concept, our group constructed an antibody bead array panel for 35 analytes that were selected during the discovery step. This study was aimed at testing the performance of this 35-plex array panel in profiling signatures specific for primary non-metastatic breast cancer and validating its diagnostic utility in this independent population. Methods Thirty-five analytes were selected from more than 50 markers through screening steps using a serum bank consisting of 4,500 samples from various types of cancer. An antibody-bead array of 35 markers was constructed using the Luminex (TM) bead array platform. A study population consisting of 98 breast cancer patients and 96 normal subjects was analysed using this panel. Multivariate classification algorithms were used to find discriminating biomarkers and validated with another independent population of 90 breast cancer and 79 healthy controls. Results Serum concentrations of epidermal growth factor, soluble CD40-ligand and proapolipoprotein A1 were increased in breast cancer patients. High-molecular-weight-kininogen, apolipoprotein A1, soluble vascular cell adhesion molecule-1, plasminogen activator inhibitor-1, vitamin-D binding protein and vitronectin were decreased in the cancer group. Multivariate classification algorithms distinguished breast cancer patients from the normal population with high accuracy (91.8% with random forest, 91.5% with support vector machine, 87.6% with linear discriminant analysis). Combinatorial markers also detected breast cancer at an early stage with greater sensitivity. Conclusions The current study demonstrated the usefulness of the antibody-bead array approach in finding signatures specific for primary non-metastatic breast cancer and illustrated the potential for early, high sensitivity detection of breast cancer. 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