Chaperoning heat shock proteins: Proteomic analysis and relevance for normal and dystrophin-deficient muscle

Molecular chaperones play a key role in normal muscle function and during physiological adaptations to extensive exercise and numerous forms of cellular stress. The various classes of HSPs and related chaperones are also involved in the molecular pathogenesis of a large number of neuromuscular diseases. Several MS-based proteomic studies have recently shown that the expression levels of molecular chaperones are severely altered in dystrophin-deficient muscles. Dystrophin isoform Dp427 (where Dp427 is dystrophin protein of 427 kDa) is a large membrane cytoskeletal protein and its deficiency is the primary underlying cause of Duchenne muscular dystrophy. Current efforts have focused on the establishment of a comprehensive biomarker signature of dystrophinopathy in order to improve diagnostic methods, establish reliable prognostic factors and identify novel therapeutic targets. Following an introduction into the biology of HSPs and their general role in skeletal muscle, this review outlines the proteomic profiling of molecular chaperones in dystrophinopathy. The focus is especially on the molecular fate of HSPs cardiovascular HSP (HSPB7), αBC (HSPB5), HSP70 (HSPA) and HSP90 (HSPC) in dystrophin-deficient muscles and their involvement in progressive muscular dystrophy. Furthermore, the potential usage of distinct chaperones as disease markers of secondary pathobiochemical changes for the evaluation of novel treatment options is discussed.     

Neuroproteomics and its applications in research on nicotine and other drugs of abuse

The rapidly growing field of neuroproteomics is able to track changes in protein expression and protein modifications underlying various physiological conditions, including the neural diseases related to drug addiction. Thus, it presents great promise in characterizing protein function, biochemical pathways, and networks to understand the mechanisms underlying drug dependence. In this article, we first provide an overview of proteomics technologies and bioinformatics tools available to analyze proteomics data. Then we summarize the recent applications of proteomics to profile the protein expression pattern in animal or human brain tissues after the administration of nicotine, alcohol, amphetamine, butorphanol, cocaine, and morphine. By comparing the protein expression profiles in response to chronic nicotine exposure with those appearing in response to treatment with other drugs of abuse, we identified three biological processes that appears to be regulated by multiple drugs of abuse: energy metabolism, oxidative stress response, and protein degradation and modification. Such similarity indicates that despite the obvious differences among their chemical properties and the receptors with which they interact, different substances of abuse may cause some similar changes in cellular activities and biological processes in neurons.     

Digital-analog hybrid control model for eukaryotic heat shock response illustrating the dynamics of heat shock protein 70 on exposure to thermal stress

We are introducing in this paper a digital-analog hybrid model approach for the study of a complete gene regulatory network; the heat shock response (HSR) network of eukaryotes. HSR is a crucial and widely studied cellular phenomenon occurring due to various stresses on the cell, and is characterised by the induction of heat shock genes resulting in the production of heat shock proteins (HSPs) which restores cellular homeostasis by maintaining protein integrity. We are proposing a model which incorporates simple digital and analog components which mimic the functioning of biological molecules involved in HSR and model their dynamics and behaviour. The simulation result of the circuit for the production of HSP70 has been found to be consistent with published experimental results. The qualitative behaviour of the HSR is expressed through a truth table. Through this novel approach, the authors have tried to develop a level of understanding of the interactions of the parts of the HSR system and of this system as a whole.     

Tumor antigens eliciting autoantibody response in cancer of gingivo-buccal complex

Cancer of the gingivo-buccal complex (GBC) is a major cancer in Indian men. This study reports the identification of tumor antigens, which elicit an antibody response in cancer of GBC using immunoproteomics. Proteins from KB cells separated by 2-D PAGE, were immunoblotted with IgG from sera of 28 cancer patients, 12 patients with leukoplakia, and 28 healthy individuals. Antigens detected by the IgGs from the patient's sera were different among different individuals with presence of any single antigen ranging from 7 to 79%. Several of these antigens have been identified by MS and confirmed by immunostaining. They are three forms of α-enolase, peroxiredoxin-VI, annexin-II, HSP70, pyruvate kinase, α-tubulin, β-tubulin, ATP-synthase, phosphoglycerate mutase (PGM), aldose reductase, triosephosphate isomerase, and cyclophilin-A. Except, HSP70, these antigens are being reported in cancer of GBC for the first time. Pyruvate kinase and aldose reductase have not been reported to elicit autoantibody response in any other cancer earlier. Initial results show that autoantibody response against α-enolase, HSP70, annexin-II, peroxiredoxin-VI, and aldose reductase are also seen in patients with leukoplakia of GBC, which suggest early occurrence of these autoantibodies during the process of oral carcinogenesis. These antigens can be further validated for their use in cancer management by immune intervention.     

Vascular proteomics

The characterization of patients with acute coronary syndromes (ACS) at the molecular and cellular levels provides a novel vision for understanding the pathological and clinical expression of the disease. Recent advances in proteomic technologies permit the evaluation of systematic changes in protein expression in many biological systems and have been extensively applied to cardiovascular diseases (CVD). The cardiovascular system is in permanent intimate contact with blood, making blood-based biomarker discovery a particularly worthwhile approach. Thus, proteomics can potentially yield novel biomarkers reflecting CVD, establish earlier detection strategies, and monitor response to therapy. Here we review the different proteomic strategies used in the study of atherosclerosis and the novel proteins differentially expressed and secreted by atherosclerotic lesions which constitute novel potential biomarkers (HSP-27, Cathepsin D). Special attention is paid to MS-Imaging of atheroma plaque and the generation, for the first time, of 2-D images of lipids, showing the distribution of these molecules in the different areas of the atherosclerotic lesions. In addition new potential biomarkers have been identified in plasma (amyloid A1α, transtherytin), circulating cells (protein profile in monocytes from ACS patients) and individual cells constituents of atheroma plaques (endothelial, VSMC, macrophages) which provide novel insights into vascular pathophysiology.     

Degradative proteomics and disease mechanisms

Protein degradation is a fundamental biological process, which is essential for the maintenance and regulation of normal cellular function. In humans and animals, proteins can be degraded by a number of mechanisms: the ubiquitin-proteasome system, autophagy and intracellular proteases. The advances in contemporary protein analysis means that proteomics is increasingly being used to explore these key pathways and as a means of monitoring protein degradation. The dysfunction of protein degradative pathways has been associated with the development of a number of important diseases including cancer, muscle wasting disorders and neurodegenerative diseases. This review will focus on the role of proteomics to study cellular degradative processes and how these strategies are being applied to understand the molecular basis of diseases arising from disturbances in protein degradation.     

Liver proteins as sensor of human malignancies and inflammation

In this review we would like to highlight the importance of acute-phase proteins as sensor of diseases. Both acute-phase protein levels and glycosylation have been reported to be altered in inflammation and other diseases including cancer. Factors that promote acute-phase protein synthesis and enhance the expression of specific glycosyltransferases, such as sialyltransferases and fucosyltransferases, may be up-regulated in some tumours and would explain the changes in acute-phase protein levels and the specific N-glycosylation modifications of some acute-phase proteins in cancer. However, further studies are required to define the potential clinical application of these acute-phase protein cancer-specific modifications as possible cancer diagnostic or monitoring tools.     

Immune response to chemically modified proteome

Both enzymatic and nonenzymatic PTMs of proteins involve chemical modifications. Some of these modifications are prerequisite for the normal functioning of cell, while other chemical modifications render the proteins as “neo-self” antigens, which are recognized as “non-self” leading to aberrant cellular and humoral immune responses. However, these modifications could be a secondary effect of autoimmune diseases, as in the case of type I diabetes, hyperglycemia leads to protein glycation. The enigma of chemical modifications and immune response is akin to the “chick-and-egg” paradox. Nevertheless, chemical modifications regulate immune response. In some of the well-known autoimmune diseases such as rheumatoid arthritis, systemic lupus erythematosus, and multiple sclerosis, chemically modified proteins act as autoantigens forming immune complexes. In some instances, chemical modifications are also involved in regulating immune response during pathogen infection. Further, the usefulness of proteomic analysis of immune complexes is briefly discussed.     

Proteomics as a research tool in clinical and experimental ophthalmology

It is estimated that 37 million people worldwide suffer from blindness and 124 million people have impaired vision. While the relatively recently developed therapies, antivascular endothelial growth factor inhibitors for the treatment of age-related macular degeneration, and prostaglandin analogues for the treatment of glaucoma are beneficial for some patients, there are many individuals with sight-threatening diseases for whom no effective pharmacological therapy is available. For many of these diseases, the molecular mechanisms remain to be comprehensively elucidated, thus precluding the design of successful therapies against specific pathological targets. The current review summarises recent attempts to elucidate molecular mechanisms of ocular diseases, including diabetic retinal disease, age-related macular degeneration and inherited blindness using proteomic methodologies. A novel hypothesis can be generated from global protein expression analysis of disease tissue, which can then be addressed with cellular and in vivo functional studies. For example, the identification of extracellular carbonic anhydrase from the vitreous of diabetic retinopathy patients using MS based proteomics led to the elucidation of a new pathway involved in intraretinal edema, which could be inhibited by a number of agents targeting different proteins in this pathway in relevant animal models. The potential of protein biomarkers for diagnosis and the identification of novel disease mechanisms are also discussed.     

噪声环境中时延区间CNN网络鲁棒稳定性

由于采用大规模集成电路方法实现细胞神经网络(cellular neural networks,CNN),其 电路所产生的噪声不可避免,实际的网络都是在噪声环境中进行工作的,弄清楚这些随机干扰 是如何影响网络的稳定性,在网络设计时非常关键.利用鞅收敛定理、李雅普诺夫直接法和矩阵 分析的方法,研究了白噪声干扰下时延区间细胞神经网络承受扰动的能力,得到了仅依赖系统 参数的充分性代数判据.所得结果在系统设计时检验较为方便.     

Myofilament proteins: From cardiac disorders to proteomic changes

Myofilament proteins of the cardiac sarcomere house the molecular machinery responsible for generating tension and pressure. Release of intracellular Ca(2+) triggers myofilament tension generation and shortening, but the response to Ca(2+) is modulated by changes in key regulatory proteins. We review how these proteomic changes are essential to adaptive physiological regulation of cardiac output and become maladaptive in cardiac disorders. We also review the essentials of proteomic techniques used to study myofilament protein changes, including degradation, isoform expression, phosphorylation and oxidation. Selected proteomic studies illustrate the applications of these approaches.     

细胞信号网络稳定性的计算机仿真分析

许多疾病的发生、发展与细胞内信号转导密切相关，众多的信号转导途径之间因交互作用和交叉调节而形成了庞大复杂的信号网络，研究这一网络的结构属性、内在组织机制以及信号转导整合的特征，对于认识和理解系统复杂性、生物自适应以及疾病的发病机制，设计与开发新型治疗药物都具有重要的意义。该文根据构建的信号网络模型，采用计算机仿真技术对细胞信号网络对外界攻击的承受能力进行了动力学模拟，仿真结果表明该网络对不同类型的节点所受攻击的承受能力不同。     

Differentially expressed proteins of MCF-7 human breast cancer cells affected by Zilongjin, a complementary Chinese herbal medicine

Purpose : Zilongjin, a complementary Chinese herbal medicine, has been used to alleviate the adverse effects of chemotherapeutic drugs in cancer therapy. However, the mechanisms of anti‐cancer activity of Zilongjin are still largely unkonwn. Experimental design : First, the proteomic approach of combined 2‐DE and ESI‐MS/MS was used to investigate the effect of Zilongjin on the protein expression in MCF‐7 cells. Then, the differential expression of some proteins was confirmed by Western blot, cytoimmunofluoresecnce, and quantitative real‐time RT‐PCR analysis. Results : The identified proteins with differential expression, involved in such events as protein translation, cellular signal transduction, cytoskeleton formation and transportation, include seven downregulating proteins, such as Eukaryotic translation initiation factor 3 subunit I, Eukaryotic translation initiation factor 1A Y‐chromosomal, Ran‐specific GTPase‐activating protein, Ubiquitin‐conjugating enzyme E2 N, Tropomodulin‐3, Macrophage‐capping protein, and Tumor protein D52, as well as two upregulating proteins, HSP β‐1 and keratin18. Moreover, the differential expression of three proteins was confirmed. Conclusions and clinical relevance : (i) These results provide a new insight into the molecular mechanisms of Zilongjin on therapy for breast cancer. (ii) The application of the proteomic approaches will result in the more extended appreciation of Chinese medicine than those known at present.     

Feature extraction of protein expression levels based on classification of functional foods with SOM

We investigated the relations between the physiological activities and protein expression levels of functional foods using a self-organizing map (SOM). The input vectors to the SOM were the protein expression levels and the physiological activity. A competitive node has two kinds of weights: one is for protein expression levels, and the other is for physiological activity. A winner node is decided by the distance between the values of protein expression levels described in the input vector and the corresponding weights only. Then all weights, including those for physiological activity in each node, are updated. Therefore each node has an artificially generated value of physiological activity. Finally, the nodes can be categorized by the abovementioned physiological activity. A well-trained SOM gives us information about the relations between physiological activities and protein expression levels. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

A review of Hidden Markov models and Recurrent Neural Networks for event detection and localization in biomedical signals

Biomedical signals carry signature rhythms of complex physiological processes that control our daily bodily activity. The properties of these rhythms indicate the nature of interaction dynamics among physiological processes that maintain a homeostasis. Abnormalities associated with diseases or disorders usually appear as disruptions in the structure of the rhythms which makes isolating these rhythms and the ability to differentiate between them, indispensable. Computer aided diagnosis systems are ubiquitous nowadays in almost every medical facility and more closely in wearable technology, and rhythm or event detection is the first of many intelligent steps that they perform. How these rhythms are isolated? How to develop a model that can describe the transition between processes in time? Many methods exist in the literature that address these questions and perform the decoding of biomedical signals into separate rhythms. In here, we demystify the most effective methods that are used for detection and isolation of rhythms or events in time series and highlight the way in which they were applied to different biomedical signals and how they contribute to information fusion. The key strengths and limitations of these methods are also discussed as well as the challenges encountered with application in biomedical signals.     

Using psychophysiological techniques to measure user experience with entertainment technologies

Emerging technologies offer exciting new ways of using entertainment technology to create fantastic play experiences and foster interactions between players. Evaluating entertainment technology is challenging because success isn't defined in terms of productivity and performance, but in terms of enjoyment and interaction. Current subjective methods of evaluating entertainment technology aren't sufficiently robust. This paper describes two experiments designed to test the efficacy of physiological measures as evaluators of user experience with entertainment technologies. We found evidence that there is a different physiological response in the body when playing against a computer versus playing against a friend. These physiological results are mirrored in the subjective reports provided by the participants. In addition, we provide guidelines for collecting physiological data for user experience analysis, which were informed by our empirical investigations. This research provides an initial step towards using physiological responses to objectively evaluate a user's experience with entertainment technology.     

Using psychophysiological techniques to measure user experience with entertainment technologies

Emerging technologies offer exciting new ways of using entertainment technology to create fantastic play experiences and foster interactions between players. Evaluating entertainment technology is challenging because success isn't defined in terms of productivity and performance, but in terms of enjoyment and interaction. Current subjective methods of evaluating entertainment technology aren't sufficiently robust. This paper describes two experiments designed to test the efficacy of physiological measures as evaluators of user experience with entertainment technologies. We found evidence that there is a different physiological response in the body when playing against a computer versus playing against a friend. These physiological results are mirrored in the subjective reports provided by the participants. In addition, we provide guidelines for collecting physiological data for user experience analysis, which were informed by our empirical investigations. This research provides an initial step towards using physiological responses to objectively evaluate a user's experience with entertainment technology.     

Adaptive Surface Texture Synthesis Using Round‐Shaped Neighbourhoods

This paper presents a novel surface texture synthesis method, which is capable of producing high‐quality results by performing the synthesis within an effective multi‐resolution scheme using an adaptive texture similarity metric. Compared with related works, our method allows us to directly carry out multi‐resolution synthesis without involving complicated operations such as mesh hierarchy and partitioning on the target surface. Also, the adaptive similarity metric focuses on measuring texture properties at different scales ranging from local to global, allowing for consistency within differently‐sized texture structures. Further, with the introduced round shaped neighbourhoods, we can save considerable amount of computation for the surface texture synthesis over variable texture directions. Experimental results are provided and comparisons are made against other latest works.     

Biomarkers for cardiovascular risk assessment in autoimmune diseases

Autoimmune diseases, such as antiphospholipid syndrome, systemic lupus erythematosus, and rheumatoid arthritis, are characterized by a high prevalence of cardiovascular (CV) disease (CVD), which constitutes the leading causes of morbidity and mortality among such patients. Although such effects are partly explained by a higher prevalence of traditional CV risk factors, many studies indicate that such factors do not fully explain the enhanced CV risk in these patients. In addition, risk stratification algorithms based upon traditional CV risk factors are not as predictive in autoimmune diseases as in the general population. For these reasons, the timely and accurate assessment of CV risk in these high-risk populations still remains an unmet clinical need. An enhanced contribution of different inflammatory components of the immune response, as well as autoimmune elements (e.g. autoantibodies, autoantigens, and cellular response), has been proposed to underlie the incremental CV risk observed in these populations. Recent advances in proteomic tools have contributed to the discovery of proteins involved in CVDs, including some that may be suitable to be used as biological markers. In this review we summarize the main markers in the field of CVDs associated with autoimmunity, as well as the recent advances in proteomic technology and their application for biomarker discovery in autoimmune disease.     

Heat-shock protein-27, -70 and peroxiredoxin-II show molecular chaperone function in sickle red cells: Evidence from transgenic sickle cell mouse model

Sickle cell disease (SCD) is an autosomal recessive genetic red cell disorder characterized by the production of a defective form of hemoglobin, hemoglobin-S, that is worldwide-distributed. The acute clinical manifestations of SCD are related to hemoglobin cyclic-polymerization and to the generation of rigid, dense red blood cells (RBCs). We studied RBCs membrane proteome from human sickle RBCs, fractioned according to density compared to normal RBCs. 2-DE followed by MS analysis was carried out. We identified 65 proteins differently expressed, divided into five major clusters according to their functions: (i) membrane-cytoskeleton proteins; (ii) metabolic enzymes; (iii) ubiquitin-proteasome-system; (iv) flotillins; (v) chaperones. HSP27, HSP70 and peroxiredoxin-II (Prx-II) showed the most relevant changes. They were differently recruited to sickle RBCs membrane in response to in vitro hypoxia. Potential markers were then validated in a transgenic-mouse model for SCD, the SAD mice, exposed to hypoxia mimicking acute SCD vaso-occlusive-crisis (VOCs); we found that HSP70 and HSP27 bound to RBCs membrane respectively after 12?h and 48?h of hypoxia, while Prx-II membrane binding was modulated during hypoxia. Our data indicate that HSP27 and HSP70 play a novel role as RBCs membrane protein protectors and as possibly new markers of severity of RBCs membrane damage during acute VOCs.