MS analysis of rheumatoid arthritic synovial tissue identifies specific citrullination sites on fibrinogen

Purpose : Citrullination is a post‐translational modification of arginine residues to citrulline catalyzed by peptidyl arginine deiminases. Induced expression of citrullinated proteins are frequently detected in various inflammatory states including arthritis; however, direct detection of citrullination in arthritic samples has not been successfully performed in the past. Experimental design : Citrullination of human fibrinogen, a candidate autoantigen in arthritis, was studied. Accurate identification of citrullinated fibrinogen peptides from rheumatoid arthritis synovial tissue specimens was performed using accurate mass and retention time analysis. Results : A peptide with the sequence ESSSHHPGIAEFPSRGK corresponding to amino acids 559–575 of fibrinogen α‐chain was identified to be citrullinated with an occupancy rate between 1.4 and 2.5%. Citrullination of the peptide KREEAPSLRPAPPPISGGGYRARPAK corresponding to amino acids 52–77 of the fibrinogen β‐chain was identified with an occupancy rate of 1.2%. Conclusions and clinical relevance : We report a proof of principle study for the identification of citrullinated proteins and within them, identification of citrullination sites and quantification of their occupancies in synovial tissue from rheumatoid arthritis patients using high‐resolution MS. Detailed studies on which molecules are citrullinated in arthritis can provide information about their role in immune regulation and serve as novel biomarkers and potentially even as therapeutic targets.     

In pursuit of B-cell synovial autoantigens in rheumatoid arthritis: Confirmation of citrullinated fibrinogen, detection of vimentin, and introducing carbonic anhydrase as a possible new synovial autoantigen

We aimed to investigate potential synovial autoantigens in rheumatoid arthritis (RA) that could trigger the induction of B‐cell autoantibodies. Total protein extract of synovial tissue obtained from seven RA patients was pooled and separated by 1‐DE and 2‐DE. The corresponding blots were probed with sera from RA (n = 30) and disease control samples (n = 30). Protein spots showing a sensitivity of >15% were identified by MS. 1‐D immunoblots revealed one protein band with a specificity in RA of 100%, a sensitivity of 43%, which was identified as fibrinogen β chain. 2‐D analysis revealed the subunits of fibrinogen, especially the β and γ chain, as the most prominent synovial autoantigens. We also identified vimentin, the Sa‐antigen and carbonic anhydrase I as a potentially new synovial autoantigen. The protein patterns of these immunoreactive spots were observed as trains. The spots showing the highest autoimmune reactivity occurred at the acidic side of these trains and were recognized by anticitrullinated protein/peptide antibodies positive RA sera. Antimodified citrulline staining of these patterns confirmed protein citrullination. Therefore, PTMs such as citrullination due to alterations of peptidylarginine deiminase activity or generation of RA‐specific epitopes, should be considered as a trigger in tolerance break.     

Proteomics in rheumatology: The beginning of a fairy tale?

One of the major challenges in proteome research is to translate its applications to the setting of human diseases. Proteomics in rheumatology is an area with marked potential including applications ranging from diagnostics, over therapeutic monitoring to discovery of new potential therapeutic targets. Biomarkers will be essential to discriminate between clinical similar rheumatic diseases, to monitor disease-states or to install the best appropriate therapy. Especially in the field of rheumatology, analysis of specific genes and/or their expression products by pharmacogenetics/-genomics or pharmacoproteomics could be necessary to enable an effective, patient-tailored therapy. In rheumatology, direct examination of proteins may be of utmost importance, as it is already known that PTMs, such as citrullination of proteins or peptides, may be involved in certain rheumatic diseases. The discovery and validation of antibodies directed against citrullinated proteins/peptides in rheumatic diseases using proteome analysis approaches has been described. Gel-free methods, SELDI-approaches and classic 2-DE approaches have been deployed on body fluids as well as on target tissues in different rheumatic diseases. Proteomics in rheumatology is on the rise and pilot studies have indicated that the application of proteomics-based technologies in rheumatic diseases appears to be an exciting example of translational research.     

Research progress in protein microarrays: Focussing on cancer research

Although several effective treatment modalities have been developed for cancers, the morbidity and mortality associated with cancer continues to increase every year. As one of the most exciting emerging technologies, protein microarrays represent a powerful tool in the field of cancer research because of their advantages such as high throughput, small sample usage, more flexibility, high sensitivity and direct readout of results. In this review, we focus on the research progress in four types of protein microarrays (proteome microarray, antibody microarray, lectin microarray and reversed protein array) with emphasis on their application in cancer research. Finally, we discuss the current challenges faced by protein microarrays and directions for future developments. We firmly believe that this novel systems biology research tool holds immense potential in cancer research and will become an irreplaceable tool in this field.     

Understanding dendritic cell biology and its role in immunological disorders through proteomic profiling

Dendritic cells (DC) have always been present on the bright spot of immune research. They have been extensively studied for the last 35 years, and much is known about their different phenotypes, stimulatory capacity, and role in the immune system. During the last 15 years, great attention has been given to studies on global gene and protein expression profiles during the differentiation and maturation processes of these cells. It is well understood that studying the proteome, together with information on the role of protein post-translational modifications (PTM), will reveal the real dynamics of a living cell. The rapid increase of proteomic studies during the last decade describing the differentiation and maturation process in DCs, as well as modifications brought by the use of different compounds that either increase or decrease their immunogenicity, reflects the importance of understanding the molecular processes behind the functional properties of these cells. In the present review, we will give an overview of proteomic studies focusing on DCs. Thereby we will concentrate on the importance of these studies in understanding DC behavior from a molecular point of view and how these findings have aided in understanding the differences in functional properties of these cells.     

Proteomic identification of proteins in the human brain: Towards a more comprehensive understanding of neurodegenerative disease

Proteomics has revealed itself as a powerful tool in the identification and determination of proteins and their biological significance. More recently, several groups have taken advantage of the high-throughput nature of proteomics in order to gain a more in-depth understanding of the human brain. In turn, this information has provided researchers with invaluable insight into the potential pathways and mechanisms involved in the pathogenesis of several neurodegenerative disorders, e.g., Alzheimer and Parkinson disease. Furthermore, these findings likely will improve methods to diagnose disease and monitor disease progression as well as generate novel targets for therapeutic intervention. Despite these advances, comprehensive understanding of the human brain proteome remains challenging, and requires development of improved sample enrichment, better instrumentation, and innovative analytic techniques. In this review, we will focus on the most recent progress related to identification of proteins in the human brain under normal as well as pathological conditions, mainly Alzheimer and Parkinson disease, their potential application in biomarker discovery, and discuss current advances in protein identification aimed at providing a more comprehensive understanding of the brain.     

Proteomic analysis of multiple myeloma: current status and future perspectives

Multiple myeloma (MM) is a malignant plasma cell neoplasm that accounts for slightly more than 10% of all hematologic cancers and remains incurable. The major challenge remains the identification of better diagnosis and prognostic biomarkers. The advent of proteomic technologies creates new opportunities and challenges for those seeking to gain greater understanding of MM. Although there is a limited number of proteomic studies to date in MM, those performed highlight the potential impact of these technologies in our understanding of MM pathogenesis and the identification of novel therapeutic targets. In this review, we introduce the proteomic technologies available for the study of MM, summarize results of the published proteomic studies on MM, and discuss the novel developments and applications for the analysis of protein PTM in MM. The application of proteomic technologies will be valuable to better understand the pathogenesis of MM and may in the future open novel avenues in the treatment of MM.     

The role of O-GlcNAc signaling in the pathogenesis of diabetic retinopathy

Diabetic retinopathy is a leading cause of blindness worldwide. Despite laser and surgical treatments, antiangiogenic and other therapies, and strict metabolic control, many patients progress to visual impairment and blindness. New insights are needed into the pathophysiology of diabetic retinopathy in order to develop new methods to improve the detection and treatment of disease and the prevention of blindness. Hyperglycemia and diabetes result in increased flux through the hexosamine biosynthetic pathway, which, in turn, results in increased PTM of Ser/Thr residues of proteins by O-linked β-N-acetylglucosamine (O-GlcNAc). O-GlcNAcylation is involved in regulation of many nuclear and cytoplasmic proteins in a manner similar to protein phosphorylation. Altered O-GlcNAc signaling has been implicated in the pathogenesis of diabetes and may play an important role in the pathogenesis of diabetic retinopathy. The goal of this review is to summarize the biology of the hexosamine biosynthesis pathway and O-GlcNAc signaling, to present the current evidence for the role of O-GlcNAc signaling in diabetes and diabetic retinopathy, and to discuss future directions for research on O-GlcNAc in the pathogenesis of diabetic retinopathy.     

Mass spectrometry imaging for the proteomic study of clinical tissue

Over the last decade, MALDI-MS imaging has been used by researchers to explore areas of proteomics, lipidomics and metabolomics in samples of clinical origin for both targeted and global biomarker analysis. Numerous technological advancements in MS and clinical tissue MS imaging have been accomplished; hence, in this article we aim to critically discuss whether MS imaging has now in fact become a true champion of the ‘Omics Era’. In order to assess the potential for it to be routinely used in the clinical setting, it is pertinent to discuss some of its limitations, and to examine how these have been addressed by researchers. The key limitations of the technique we will discuss in this viewpoint article are as follows: sample throughput; relevance to patients, the availability of validated/standardised techniques; and integration with conventional pathology and other medical imaging techniques. Good progress has been made over the last 5 years in overcoming these limitations that had previously restricted the use of this technology in the clinical setting.     

基于深度学习的数字病理图像分割综述与展望

数字病理图像分析对于乳腺癌、前列腺癌等良恶性分级诊断具有重要意义,其中,组织基元的形态和目标测量是量化分析的重要依据.然而,由于病理数据多样性和复杂性等新特点,其分割任务面临着特征提取困难、实例分割困难等挑战.人工智能辅助病理量化分析将复杂病理数据转化为可挖掘的图像特征,使得自动提取组织基元的定量化信息成为可能.特别是...     

Developing control-theoretic objectives for large-scale brain dynamics and cognitive enhancement

The development of technologies for brain stimulation provides a means for scientists and clinicians to directly actuate the brain and nervous system. Brain stimulation has shown intriguing potential in terms of modifying particular symptom clusters in patients and behavioral characteristics of subjects. The stage is thus set for optimization of these techniques and the pursuit of more nuanced stimulation objectives, including the modification of complex cognitive functions such as memory and attention. Control theory and engineering will play a key role in the development of these methods, guiding computational and algorithmic strategies for stimulation. In particular, realizing this goal will require new development of frameworks that allow for controlling not only brain activity, but also latent dynamics that underlie neural computation and information processing. In the current opinion, we review recent progress in brain stimulation and outline challenges and potential research pathways associated with exogenous control of cognitive function.     

IPv6的DoS／DDoS攻击及防御

IPv6无疑要比IPv4更加安全,但其本身就不是认证加密所能解决,而且就目前来看IPsec的大规模应用还有许多问题需要解决。本文详细分析了IPv6网络的DoS／DDoS攻击并针对IPV6可能面临的各种形式的拒绝服务攻击展开了讨论。     

Is GRP78/BiP a potential salivary biomarker in patients with rheumatoid arthritis?

Purpose : In the last few years, serum and joint synovial fluid have been extensively analyzed for the proteomic research of rheumatoid arthritis (RA) biomarkers. Nonetheless, to date, there have been no studies investigating salivary biomarkers in this condition. Therefore, aim of this study is to investigate the presence of potential biomarkers of RA in human whole saliva. Experimental design : We combined 2‐DE and MS to analyze the whole saliva protein profile of 20 RA patients in comparison with 20 sex‐ and age‐matched healthy subjects. Results : Eight salivary proteins resulted differentially expressed, namely calgranulin A, calgranulin B, apolipoprotein A‐1, 6‐phosphogluconate dehydrogenase, peroxiredoxin 5, epidermal fatty acid‐binding protein, 78 kDa glucose‐regulated protein precursor (GRP78/BiP), and 14‐3‐3 proteins. It is particularly interesting that chaperone GRP78/BiP showed the greatest increase in RA patients. This finding was validated by Western Blot analysis and the over‐expression of GRP78/BiP appear to be distinctive of RA and drugs treatment independent. Conclusions and clinical relevance : This study provides a rationale for further studies aimed at evaluating any correlation between GRP78/BiP and different clinical/serological aspects of the disease in order to improve the diagnostic algorithms of RA.     

Proteomics in paediatric cardiac surgery: Is a personalised approach feasible?

The incidence of congenital cardiac abnormalities remains high. Paediatric patients with congenital cardiac defects often require surgery at a young age. The surgeries are often long and complex, rendering this population particularly vulnerable to the deleterious effects of cardiopulmonary bypass and cardiac surgery. The search for cardioprotective strategies is ongoing in an attempt to reduce the morbidity in this population. In the post-genomic era, it is apparent that simply determining the genomic sequences holds little diagnostic potential and means to determine progression of disease and response to treatment. The field of proteomics is expanding and application of proteomic techniques in the clinical setting holds great potential to advance our understanding of the proteomic changes involved in specific disease stages. This review will assess the application of proteomic techniques in the setting of paediatric cardiac surgery and highlight the need to obtain a clear understanding of the role of various proteins in children with cardiac conditions. The success and challenges of the available proteomic technology will be discussed as well as the future potential of proteomic methods for advancing our understanding of protein changes in children requiring cardiac surgery.     

Phosphoproteomics: A possible route to novel biomarkers of breast cancer

Proteomics is rapidly transforming the way that cancer and other pathologies are investigated. The ability to identify hundreds of proteins and to compare their abundance in different clinical samples presents a unique opportunity for direct identification of novel disease markers. Furthermore, recent advances allow us to analyse and compare PTMs. This gives an additional dimension for defining a new class of protein biomarker based not only on abundance and expression but also on the occurrence of covalent modifications specific to a disease state or therapy response. Such modifications are often a consequence of the activation/inactivation of a particular disease related pathway. In this review we evaluate the available information on breast cancer related protein-phosphorylation events, illustrating the rationale for investigating this PTM as a target for breast cancer research with eventual clinical relevance. We present a critical survey of the published experimental strategies to study protein phosphorylation on a system wide scale and highlight recent specific advances in breast cancer phosphoproteomics. Finally we discuss the feasibility of establishing novel biomarkers for breast cancer based on the detection of patterns of specific protein phosphorylation events.     

Developing proteomics-based biomarkers for colorectal neoplasms for clinical practice: Opportunities and challenges

Colorectal cancer (CRC) arises from the normal colon epithelium through the accumulation of genetic mutations and epigenetic alterations that are associated with progression along the histological adenoma-adenocarcinoma sequence. Elucidating the molecular alterations underlying disease progression will not only provide insight into the behavior of the tumors, but also could lead to the discovery of useful biomarkers for diagnosis, monitoring treatment responsiveness, or predicting disease outcomes. In the past a few years, there have been several evaluating differentially expressed protein biomarkers by employing proteomics technologies coupled with mass spectrometry. In the current review, we will briefly summarize the results from selected recent studies using tissue or serum samples from CRC patients in the past 5 years and discuss the opportunities and challenges in translating these findings from the research setting to clinical practice.     

Quantitative proteomic approaches for biomarker discovery

The rapid advances in proteomic technologies have made possible systematic analysis of hundreds to thousands of proteins in clinical samples with the promise of uncovering novel protein biomarkers for various disease conditions. We will discuss in this review article current MS and protein chip-based quantitative proteomic approaches and their application in biomarker discovery. The emphasis will be placed on new quantification strategies employing stable isotopic labeling coupled with MS/MS, and antibody-based protein chips and nanodevices. The strength and weakness of each technology are briefly highlighted.     

Robust estimation of surface properties and interpolation of shadow/specularity components

The Polynomial Texture Map framework (PTM) extends the simple model of image formation from the Lambertian variant of Photometric Stereo (PST) to more general reflectances and to more complex-shaped surfaces. It forms an alternative method for apprehending object color, albedo, and surface normals. Here we consider solving such a model in a robust version, not to date attempted for PTM, with the upshot that both shadows and specularities are identified automatically without the need for any thresholds. Instead of the linear model used in few-source PST for Lambertian surfaces, PTM adopts a higher degree polynomial model. PTM has two aims: interpolation of images for new lighting directions, and recovery of surface properties. Here we show that a robust approach is a good deal more accurate in recovering surface properties. For new-lighting interpolation, we demonstrate that a simple radial basis function interpolation can accurately interpolate specularities as well as attached and cast shadows even with a medium-sized image set, with no need for reflectance sharing across pixels or extremely large numbers of interpolation coefficients.     

Facial Feature Exaggeration According to Social Psychology of Face Perception

We propose a personality trait exaggeration system emphasizing the impression of human face in images, based on multi‐level features learning and exaggeration. These features are called Personality Trait Model (PTM). Abstract level of PTM is social psychology trait of face perception such as amiable, mean, cute and so on. Concrete level of PTM is shape feature and texture feature. A training phase is presented to learn multi‐level features of faces from different images. Statistical survey is taken to label sample images with people's first impressions. From images with the same labels, we capture not only shape features but also texture features to enhance exaggeration effect. Texture feature is expressed by matrix to reflect depth of facial organs, wrinkles and so on. In application phase, original images will be exaggerated using PTM iteratively. And exaggeration rate for each iteration is constrained to keep likeness with the original face. Experimental results demonstrate that our system can emphasize chosen social psychology traits effectively.