Immunization With Recombinant Myelin Oligodendrocyte Glycoprotein Identifies Autoreactive T Cells As A Limiting Factor In Autoreactive Germinal Center Maintenance

Germinal center (GC) responses are responsible for the protection provided by immunizations but can also drive autoimmunity. B and T cells collaborate in the GC to target the same antigen (Ag) to inform B cell differentiation; however, the properties of Ags differ substantially in autoimmunity and foreign-Ag driven immunity. Currently, it is not well understood how properties of the Ag itself influence the initiation or progression of GC responses, limiting our ability to develop effective vaccinations and predict the progression of autoimmune responses. The purpose of this thesis is to assess how GC responses initiate and progress when immunizing with an autoAg relative to a model foreign-Ag. It was hypothesized that autoreactive GCs would be relatively short-lived and less productive than foreign-Ag driven GCs due to limiting properties of the autoAg. To address this hypothesis, we developed a modular protein expression system to purify large amounts of myelin oligodendrocyte glycoprotein (MOG), a commonly targeted autoAg in Multiple Sclerosis (MS), and streamlined the modification of the MOG protein’s properties. Relative to immunization with a model foreign-Ag, immunization with MOG induces a short-lived GC that collapses early forming a large numbers of memory B cells. Memory B cells generated from the MOG-induced GC are capable of participating in secondary GCs, however, these memory cells are short-lived resulting in a short window in which MOG-specific memory B cells can be engaged. The progression of the MOG-induced GC is then shown to be limited by low T cell Ag-affinity. A possible explanation for how Ag-properties affect GC progression, is that Ag-properties influence how B and T cells communicate with each other. To address this hypothesis, reporters capable of monitoring the activation status of B and T cells were generated although, attempts to generate mice carrying these reporters were unsuccessful. Overall, these results confirm that properties of Ags affect the progression of GC responses and that the MOG-induced GC is limited by properties of the MOG autoAg. These results have important implications for future vaccine design but also gives insight into how autoreactive B cells may expand in MS

Laparoscopic versus conventional open appendicectomy: a prospective comparative analytical study in a tertiary care set up

Background: Present study outlines the outcomes of laparoscopic appendicectomy compared to open conventional appendicectomy in a tertiary care set up with aim to validate advantages and shortcomings of both procedures.Methods: A series of 80 cases above 18 years of age with clinical diagnosis of appendicitis having Alvarado score of seven and above were studied prospectively under the two groups after proper written consent: Open appendectomy-40 cases, Laparoscopic appendectomy-40 cases. Both groups were compared on grounds of intra-operative complications, additional diagnostic potential, operative time, postoperative analgesia, post-operative complications, length of hospital stay, subjective cosmesis, and return to routine normal activities. Values obtained were statistically analyzed.Results: The median operative time in Laparoscopic Appendicectomy was 58.22 minutes (range 32.68-85.46 min) as compared to open procedure which took 43.65 minutes (30.36-65.48min) (P<0.05). Conversion to open procedure was done in 10% (n=4) of laparoscopic cases. Mean value of postoperative pain by visual analogue scale was low in Laparoscopic Appendicectomy (LA) compared to Open Appendicectomy (OA) (P<0.05). Mean post-operative stay (3.2±0.34 days versus 2.3±0.24 days) and surgical site infection was recorded in 10 patients (25%) in OA group and 5 (13.9%) in LA group (P<0.05).Conclusions: It can be concluded that laparoscopic surgery is safe with greater diagnostic potential for additional pathologies and better Subjective cosmesis . But all these merits were at the price of longer operating time and a specialized set up needed for laparoscopy

Benchmark Classification of Handwritten Dataset by New Operator

In recent years, many new classifiers and feature extraction algorithms were proposed and tested on various OCR databases and these techniques were used in wide applications. Various systematic papers and inventions in OCR were reported in the literature. We can say that OCR is one of the most important and active research areas in the pattern recognition. Today, research OCR is dealing with diverse a character of complex problems. Important research in OCR includes the text degraded (heavy noise) and analysis/recognition of complex documents (including texts, images, graphs, tables and video documents). In this proposed system we are suing a new operator Recognition of Devnagari handwritten Characters one of the biggest problem in present scenario. Devnagari characters are not recognized efficiently and truthfully by electronic device. Many researchers and algorithm have been proposed for recognizing of characters. For recognizing of characters, many processes have to be performed but no single technique or algorithm can perform that recognition and give more accurate result. objective of this dissertation work is to propose a new operator, the name of this operator is Kirsch Operator and algorithm for getting accurate result

SEARCHING HETEROGENEOUS DOCUMENT IMAGE COLLECTIONS

A decrease in data storage costs and widespread use of scanning devices has led to massive quantities of scanned digital documents in corporations, organizations, and governments around the world. Automatically processing these large heterogeneous collections can be difficult due to considerable variation in resolution, quality, font, layout, noise, and content. In order to make this data available to a wide audience, methods for efficient retrieval and analysis from large collections of document images remain an open and important area of research. In this proposal, we present research in three areas that augment the current state of the art in the retrieval and analysis of large heterogeneous document image collections. First, we explore an efficient approach to document image retrieval, which allows users to perform retrieval against large image collections in a query-by-example manner. Our approach is compared to text retrieval of OCR on a collection of 7 million document images collected from lawsuits against tobacco companies. Next, we present research in document verification and change detection, where one may want to quickly determine if two document images contain any differences (document verification) and if so, to determine precisely what and where changes have occurred (change detection). A motivating example is legal contracts, where scanned images are often e-mailed back and forth and small changes can have severe ramifications. Finally, approaches useful for exploiting the biometric properties of handwriting in order to perform writer identification and retrieval in document images are examined

Meningeal Infiltration of the Spinal Cord by Non-Classically Activated B Cells is Associated with Chronic Disease Course in a Spontaneous B Cell-Dependent Model of CNS Autoimmune Disease

We characterized B cell infiltration of the spinal cord in a B cell-dependent spontaneous model of central nervous system (CNS) autoimmunity that develops in a proportion of mice with mutant T and B cell receptors specific for myelin oligodendrocyte glycoprotein. We found that, while males are more likely to develop disease, females are more likely to have a chronic rather than monophasic disease course. B cell infiltration of the spinal cord was investigated by histology and FACs. CD4+ T cell infiltration was pervasive throughout the white and in some cases gray matter. B cells were almost exclusively restricted to the meninges, often in clusters reminiscent of those described in human multiple sclerosis. These clusters were typically found adjacent to white matter lesions and their presence was associated with a chronic disease course. Extensive investigation of these clusters by histology did not identify features of lymphoid follicles, including organization of T and B cells into separate zones, CD35+ follicular dendritic cells, or germinal centers. The majority of cluster B cells were IgD+ with little evidence of class switch. Consistent with this, B cells isolated from the spinal cord were of the naïve/memory CD38hi CD95lo phenotype. Nevertheless, they were CD62Llo and CD80hi compared to lymph node B cells suggesting that they were at least partly activated and primed to present antigen. Therefore, if meningeal B cells contribute to CNS pathology in autoimmunity, follicular differentiation is not necessary for the pathogenic mechanism

User-Entity Differential Privacy in Learning Natural Language Models

In this paper, we introduce a novel concept of user-entity differential privacy (UeDP) to provide formal privacy protection simultaneously to both sensitive entities in textual data and data owners in learning natural language models (NLMs). To preserve UeDP, we developed a novel algorithm, called UeDP-Alg, optimizing the trade-off between privacy loss and model utility with a tight sensitivity bound derived from seamlessly combining user and sensitive entity sampling processes. An extensive theoretical analysis and evaluation show that our UeDP-Alg outperforms baseline approaches in model utility under the same privacy budget consumption on several NLM tasks, using benchmark datasets.Comment: Accepted at IEEE BigData 202