| 1. |
- Bikos, Vasilis, et al.
(author)
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An Immunogenetic Signature of Ongoing Antigen Interactions in Splenic Marginal Zone Lymphoma Expressing IGHV1-2*04 Receptors
- 2016
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In: Clinical Cancer Research. - 1078-0432 .- 1557-3265. ; 22:8, s. 2032-2040
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Journal article (peer-reviewed)abstract
- Purpose: Prompted by the extensive biases in the immunoglobulin (IG) gene repertoire of splenic marginal-zone lymphoma (SMZL), supporting antigen selection in SMZL ontogeny, we sought to investigate whether antigen involvement is also relevant post-transformation. Experimental Design: We conducted a large-scale subcloning study of the IG rearrangements of 40 SMZL cases aimed at assessing intraclonal diversification (ID) due to ongoing somatic hypermutation (SHM). Results: ID was identified in 17 of 21 (81%) rearrangements using the immunoglobulin heavy variable (IGHV) 1-2*04 gene versus 8 of 19 (40%) rearrangements utilizing other IGHV genes (P = 0.001). ID was also evident in most analyzed IG light chain gene rearrangements, albeit was more limited compared with IG heavy chains. Identical sequence changes were shared by subclones from different patients utilizing the IGHV1-2*04 gene, confirming restricted ongoing SHM profiles. Non-IGHV1-2*04 cases displayed both a lower number of ongoing SHMs and a lack of shared mutations (per group of cases utilizing the same IGHV gene). Conclusions: These findings support ongoing antigen involvement in a sizable portion of SMZL and further argue that IGHV1-2*04 SMZL may represent a distinct molecular subtype of the disease.
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| 2. |
- Byrne, James, et al.
(author)
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A review of cloud computing simulation platforms and related environments
- 2017
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In: Proceedings of the 7th International Conference on Cloud Computing and Services Science. - : SciTePress. - 9789897582431 ; , s. 679-691
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Conference paper (peer-reviewed)abstract
- Recent years have seen an increasing trend towards the development of Discrete Event Simulation (DES) platforms to support cloud computing related decision making and research. The complexity of cloud environments is increasing with scale and heterogeneity posing a challenge for the efficient management of cloud applications and data centre resources. The increasing ubiquity of social media, mobile and cloud computing combined with the Internet of Things and emerging paradigms such as Edge and Fog Computing is exacerbating this complexity. Given the scale, complexity and commercial sensitivity of hyperscale computing environments, the opportunity for experimentation is limited and requires substantial investment of resources both in terms of time and effort. DES provides a low risk technique for providing decision support for complex hyperscale computing scenarios. In recent years, there has been a significant increase in the development and extension of tools to support DES for cloud computing resulting in a wide range of tools which vary in terms of their utility and features. Through a review and analysis of available literature, this paper provides an overview and multi-level feature analysis of 33 DES tools for cloud computing environments. This review updates and extends existing reviews to include not only autonomous simulation platforms, but also on plugins and extensions for specific cloud computing use cases. This review identifies the emergence of CloudSim as a de facto base platform for simulation research and shows a lack of tool support for distributed execution (parallel execution on distributed memory systems).
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| 3. |
- Haage, Mathias, et al.
(author)
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Teaching Assembly by Demonstration using Advanced Human Robot Interaction and a Knowledge Integration Framework
- 2017
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In: Procedia Manufacturing. - : Elsevier BV. - 2351-9789. ; 11, s. 164-173
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Journal article (peer-reviewed)abstract
- Conventional industrial robots are heavily dependent on hard automation that requires pre-specified fixtures and time-consuming (re)programming performed by experienced operators. In this work, teaching by human-only demonstration is used for reducing required time and expertise to setup a robotized assembly station. This is achieved by the proposed framework enhancing the robotic system with advanced perception and cognitive abilities, accessed through a user-friendly Human Robot Interaction interface. The approach is evaluated on a small parts’ assembly use case deployed onto a collaborative industrial robot testbed. Experiments indicate that the proposed approach allows inexperienced users to efficiently teach robots new assembly tasks.
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| 4. |
- Polychronidou, Eleftheria, et al.
(author)
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Automated shape-based clustering of 3D immunoglobulin protein structures in chronic lymphocytic leukemia
- 2018
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In: BMC Bioinformatics. - : Springer Science and Business Media LLC. - 1471-2105. ; 19
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Journal article (peer-reviewed)abstract
- Background: Although the etiology of chronic lymphocytic leukemia (CLL), the most common type of adult leukemia, is still unclear, strong evidence implicates antigen involvement in disease ontogeny and evolution. Primary and 3D structure analysis has been utilised in order to discover indications of antigenic pressure. The latter has been mostly based on the 3D models of the clonotypic B cell receptor immunoglobulin (BcR IG) amino acid sequences. Therefore, their accuracy is directly dependent on the quality of the model construction algorithms and the specific methods used to compare the ensuing models. Thus far, reliable and robust methods that can group the IG 3D models based on their structural characteristics are missing. Results: Here we propose a novel method for clustering a set of proteins based on their 3D structure focusing on 3D structures of BcR IG from a large series of patients with CLL. The method combines techniques from the areas of bioinformatics, 3D object recognition and machine learning. The clustering procedure is based on the extraction of 3D descriptors, encoding various properties of the local and global geometrical structure of the proteins. The descriptors are extracted from aligned pairs of proteins. A combination of individual 3D descriptors is also used as an additional method. The comparison of the automatically generated clusters to manual annotation by experts shows an increased accuracy when using the 3D descriptors compared to plain bioinformatics-based comparison. The accuracy is increased even more when using the combination of 3D descriptors. Conclusions: The experimental results verify that the use of 3D descriptors commonly used for 3D object recognition can be effectively applied to distinguishing structural differences of proteins. The proposed approach can be applied to provide hints for the existence of structural groups in a large set of unannotated BcR IG protein files in both CLL and, by logical extension, other contexts where it is relevant to characterize BcR IG structural similarity. The method does not present any limitations in application and can be extended to other types of proteins.
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| 5. |
- Polychronidou, Eleftheria, et al.
(author)
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Chronic Lymphocytic Leukemia Patient Clustering Based on Somatic Hypermutation (SHM) Analysis
- 2017
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In: GeNeDis 2016. - Cham : Springer. - 9783319562469 - 9783319562452 ; , s. 127-138
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Conference paper (peer-reviewed)abstract
- Somatic Hypermutation (SHM) load in the immunoglobulin heavy variable (IGHV) gene of the clonotypic B cell receptor immunoglobulin (BcR IG) is one of the most important prognostic markers in CLL, segregating patients into two distinct categories, with contrariwise disease course. Over the last years, immunogenetic studies have identified that similar to 30% of CLL patients carry (quasi)identical BcR IG and thus can be assigned to different subsets with distinct clinicobiological profiles. This characterization was achieved by applying rules mainly concerning the diversity of the VH complementarity determining region 3 (CDR3). Following, studies have also identified subset-specific somatic hypermutation further highlighting antigen selection in disease ontogeny and evolution. In this study, an innovative attempt to explore possible associations amongst SHMs in different CLL patients is implemented and also the potential correlations with VH CDR3 stereotypy is examined, leading to a new classification algorithm implicating both SHM and CDR3 patterns. All results are classified to a ground level analysis, focusing on the most frequent SHMs, their paired associated amino acid changes and the formation of subgroups sharing the same VH CDR3 pattern, the latter being used as a similarity metric. In addition, all results are compared to established VH CDR3 patterns of the well-known CLL subsets in order to confirm the validity of our findings.
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| 6. |
- Rousopoulou, Vaia, et al.
(author)
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Cognitive analytics platform with AI solutions for anomaly detection
- 2022
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In: Computers in industry (Print). - : Elsevier BV. - 0166-3615 .- 1872-6194. ; 134, s. 103555-103555
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Journal article (peer-reviewed)abstract
- This work presents a cognitive analytics platform for anomaly detection which is capable to handle, analyze and exploit resourcefully machine data from a shop-floor of factory, so as to support the emerging and growing needs of manufacturing industry. The introduced system contributes to industrial digitization and creation of smart factories by providing a generic platform which is a complete solution supporting standards-based factory connectivity, data management, various AI models training and comparisons, live predictions and real-time visualizations. The proposed system is built on a micro-service architecture, in order to be extendable and adaptive over time, and contains three core modules, the Data Acquisition, the Knowledge Management and the Predictive maintenance, which contribute to machine failure prediction and activate predictive maintenance procedures, to efficient production schemes and decision making, to monitor anomalies and handle unforeseen conditions, to predict future behaviours on time series etc. The proposed platform utilizes continuous re-training mechanisms enabling a self learning approach for the delivery of AI solutions, usable also for various production data, guaranteeing the quality of results without continuous monitoring and human-resources allocation for AI models’ retraining. This cognitive platform is supported by machine learning techniques and deep learning architectures in order to achieve the desired performance in the management of factory processes and needs. All the information generated by the proposed platform is provided to the end user through a user interface that utilizes advanced visualization techniques.
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| 7. |
- Sutton, Lesley-Ann, et al.
(author)
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An entity evolving into a community: defining the common ancestor and evolutionary trajectory of chronic lymphocytic leukemia stereotyped subset #4
- 2014
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In: Molecular Medicine. - : Springer Science and Business Media LLC. - 1076-1551 .- 1528-3658. ; 20:1, s. 720-728
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Journal article (peer-reviewed)abstract
- Patients with chronic lymphocytic leukemia (CLL) assigned to stereotyped subset #4 express highly homologous B-cell receptor immunoglobulin (BcR IG) sequences with intense intraclonal diversification (ID) in the context of ongoing somatic hypermutation (SHM). Their remarkable biological and clinical similarities strongly support derivation from a common ancestor. We here revisited ID in subset #4 CLL in order to reconstruct their evolutionary history as a community of related clones. To this end, using specialized bioinformatics tools we assessed both IGHV-IGHD-IGHJ rearrangements (n=511) and IGKV-IGKJ rearrangements (n=397) derived from 8 subset #4 cases. Due to high sequence relatedness, a number of subclonal clusters from different cases lay very close to one another, forming a core from which clusters exhibiting greater variation stemmed. Minor subclones from individual cases were mutated to such an extent that they now resembled the sequences of another patient. Viewing the entire subset #4 dataset as a single entity branching through diversification, enabled inference of a common sequence representing the putative ancestral BcR IG expressed by their still elusive common progenitor. These results have implications for improved understanding of the ontogeny of CLL subset #4, as well as the design of studies concerning the antigenic specificity of the clonotypic BcR IGs.
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| 8. |
- Xochelli, Aliki, et al.
(author)
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Disease-biased and shared characteristics of the immunoglobulin gene repertoires in marginal zone B cell lymphoproliferations
- 2019
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In: Journal of Pathology. - : WILEY. - 0022-3417 .- 1096-9896. ; 247:4, s. 416-421
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Journal article (peer-reviewed)abstract
- The B cell receptor immunoglobulin (Ig) gene repertoires of marginal zone (MZ) lymphoproliferations were analyzed in order to obtain insight into their ontogenetic relationships. Our cohort included cases with MZ lymphomas (n = 488), i.e. splenic (SMZL), nodal (NMZL) and extranodal (ENMZL), as well as provisional entities (n = 76), according to the WHO classification. The most striking Ig gene repertoire skewing was observed in SMZL. However, restrictions were also identified in all other MZ lymphomas studied, particularly ENMZL, with significantly different Ig gene distributions depending on the primary site of involvement. Cross-entity comparisons of the MZ Ig sequence dataset with a large dataset of Ig sequences (MZ-related or not; n = 65 837) revealed four major clusters of cases sharing homologous ('public') heavy variable complementarity-determining region 3. These clusters included rearrangements from SMZL, ENMZL (gastric, salivary gland, ocular adnexa), chronic lymphocytic leukemia, but also rheumatoid factors and non-malignant splenic MZ cells. In conclusion, different MZ lymphomas display biased immunogenetic signatures indicating distinct antigen exposure histories. The existence of rare public stereotypes raises the intriguing possibility that common, pathogen-triggered, immune-mediated mechanisms may result in diverse B lymphoproliferations due to targeting versatile progenitor B cells and/or operating in particular microenvironments.
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| 9. |
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