Sixth, most studies included in the systematic review and meta-analysis did not take into account AF duration, which represents an important aspect in the examination of AF pattern. Hypothetically, underlying cardiovascular risk factors, such as diabetes, can be associated with a longer duration of atrial remodelling. In turn, AF duration can be associated with an increased likelihood of non-paroxysmal AF [45]. However, in one of the studies of our systematic review, the association between diabetes and non-paroxysmal AF became stronger and statistically significant after adjustment for AF duration, among other factors [15]. Future studies are needed to provide well characterized data on AF duration.
Model Analysis Of Structures By Ganesan Pdf Downloadl
Our meta-analysis findings suggest that diabetes is associated with increased likelihood of non-paroxysmal AF rather than paroxysmal AF. Our systematic review provides a comprehensive summary of evidence about the association of diabetes with AF types. These insights allowed us to identify current limitations and propose new directions for the improvement of future research about diabetes and AF types. Specifically, future studies should be based on classifying AF types into paroxysmal vs non-paroxysmal AF, properly adjusting for confounders, accounting for incident diabetes using Cox models with time-varying covariates, as well as using standard definitions for diabetes and AF types in accordance with existing recommendations. Further high quality studies are needed to replicate our findings, examine causality, elucidate the exact mechanisms linking diabetes to non-paroxysmal AF, evaluate the potential value of diabetes in predicting non-paroxysmal AF, and assess the role of glycemic control and antidiabetic medications on AF types.
In a complex system, some techniques, such as Analytical Network Process (ANP) and ISM, are available to analyze the interrelationships between variables. The ISM approach is suggested in the current research review framework to analyze the relationship between identified enablers. ISM transforms ambiguous and complex structures into well-defined models and portrays [38, 39]. The situation is much more reliable than the individual factor taken into isolation, defined directly and indirectly among the factors [40]. The schematic flow of the methodology is shown in Fig. 1. ISM begins with the selection of variables that are important for analysis and then progresses with the methodology of analyzing a group problem. It is a type of modeling, where a digraph model represents the basic relationships and overall structure reported by Jacob et al. [43].
By analyzing structural features found in affinity matured antibodies, a database of Modular Antibody Parts (MAPs) analogous to the variable, diversity, and joining genes has been constructed for the prediction of antibody tertiary structures. The database contains 929 parts constructed from an analysis of 1168 human, humanized, chimeric, and mouse antibody structures and encompasses all currently observed structural diversity of antibodies.
Inspired by this paradigm, in this paper we describe the development of a database of human germline Modular Antibody Parts (MAPs) for predicting antibody tertiary structures. Figure 1 illustrates the MAPs workflow, which allows for predicting the structure of any mutated (usually affinity matured) antibody. First, a prototype sequence for the heavy (H) and light (L) chain variable domains is predicted from germline genes. Next, a model structure of the prototype sequence is created by identifying and assembling the closest MAPs structures. As detailed below, the MAPs database has structures for V* (V region Framework Region (FR) 1 to FR3), CDR3, and J* (J region FR4). Finally, the antibody structure is predicted by incorporating the amino acid (AA) changes of the antibody compared to the prototype.
With this established gene assignment protocol, we next turn our attention to determining if antibodies with the same germline genes assume the same structures. Reliable prediction of antibody tertiary structures, modeled from their prototype AA sequences, hinges upon the hypothesis that antibody regions that share the same prototype sequence assume similar structures. We downloaded 1,168 human, humanized, chimeric, and mouse antibody structures from the IMGT/3Dstructure-DB [19, 23] as well as all complete mouse IGH, IGK, and IGL V, D, and J genes from the IMGT/GENE-DB [41]. Prototype sequences were identified for all antibodies, with human genes used for human antibodies and mouse genes used for mouse, chimeric, and humanized antibodies. Note that chimeric antibodies have mouse variable domains and humanized antibodies have mouse CDR attached to human FR. Mouse genes were used for the humanized antibodies so that CDR3 were modeled using the appropriate genes.
With the prototype sequences determined for the antibody structures, a clustering procedure similar to one used in a previous work for just the CDR [32] was used to determine if identical regions give rise to similar structures. At the end of the clustering procedure, the structure with the smallest average backbone atom (N, Cα, C) RMSD with all other structures in a cluster was selected as the model structure. The clustering was carried out so that all members of a cluster have a backbone atom RMSD of no more than 2.0 Å with the model structure. This distance cutoff was also used to assess previous antibody structure prediction methods [24-26].
The MAPs database can be used to model antibody structures as shown in Figure 1. For a target affinity matured antibody with an unknown structure, a prototype sequence is first computationally identified. Next, the V*, CDR3, and J* structures in the MAPs database that have the closest sequence to the prototype are identified. The models are mutated to the prototype sequence using the optimal rotamer selection protocol based on the Iterative Protein Redesign & Optimization (IPRO) method [43, 44] and relaxed using a CHARMM energy minimization [45] step. Finally, mutating the prototype antibody followed by another CHARMM energy minimization generates the predicted structure of the target antibody.
This paper introduced a modular database of antibody parts that can be used in the de novo design of antibodies in an analogous fashion to V-(D)-J recombination. Using the structural diversity encompassed within 1168 experimental antibody structures we compiled the MAPs database that contains 929 parts that can be combined to create 2.3 1010 unique antibodies. The prediction of 260 antibody structures not used in making any of the MAPs database models revealed that this database can be used to reliably predict antibody tertiary structures. In contrast to previous antibody structure prediction methods [24-26], MAPs allows for antibody structure prediction without the need for de novo folding calculations every time. The all-atom, modular nature of the MAPs database allows for the pre-calculation of pairwise structural component interaction energies. The computational savings do not come at the expense of accuracy of prediction as the RMSD of the predicted structures is at least as accurate as earlier methods.
An Orthogonal Polynomial Framework using 3 x 3 mathematical model has been proposed and attempted for the textureanalysis by L.Ganesan and P.Bhattacharyya during 1990. They proposed this frame work which was unified to address both edgeand texture detection. Subsequently, this work has been extended for different applications by them and by different authors overa period of time. Now the Orthogonal Polynomial Framework has been shown effective for larger grid size of (5 x 5) or (7 x 7) orhigher, to analyze textured surfaces. The image region (5 x 5) under consideration is evaluated to be textured or untextured usinga statistical approach. Once the image region is concluded to be textured, it is proposed to be described by a local descriptor,called pro5num, computed by a simple coding scheme on the individual pixels based on their computed significant variances. Thehistogram of all the pro5nums computed over the entire image, called pro5spectrum, is considered to be the global descriptor.The novelty of this scheme is that it can be used for discriminating the region under consideration is micro or macro texture,based on the range of values in the global descriptor. This method works fine for many standard texture images. The works usingthe proposed descriptors for many texture analysis problems with (5 x5) including higher grid size and applications are underprogress 2ff7e9595c
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