Centric Analysis Research Articles

Proteomic Heterogeneity of the Extracellular Matrix Identifies Histologic Subtype-Specific Fibroblast in Gastric Cancer

Gastric cancer (GC) is a highly heterogeneous disease regarding histologic features, genotypes, and molecular phenotypes. Here, we investigate extracellular matrix (ECM)-centric analysis, examining its association with histologic subtypes and patient prognosis in human GC. We performed quantitative proteomic analysis of decellularized GC tissues that characterizes tumorous ECM, highlighting proteomic heterogeneity in ECM components. We identified 20 tumor-enriched proteins including four glycoproteins, serpin family H member 1 (SERPINH1), annexin family (ANXA3/4/5/13), S100A family (S100A6/8/9), MMP14, and other matrisome-associated proteins. In addition, histopathological characteristics of GC reveals differential expression in ECM composition, with the poorly cohesive carcinoma-not otherwise specified (PCC-NOS) subtype being distinctly demarcated from other histologic subtypes. Integrating ECM proteomics with single-cell RNA sequencing, we identified crucial molecular markers in the PCC-NOS-specific stroma. PCC-NOS-enriched matrisome proteins and gene expression signatures of adipogenic cancer-associated fibroblasts (CAFadi) are closely linked, both associated with adverse outcomes in GC. Using tumor microarray analysis, we confirmed the CAFadi surface marker, ATP binding cassette subfamily A member 8 (ABCA8), predominantly present in PCC-NOS tumors. Our ECM-focused analysis paves the way for studies to determine their utility as biomarkers for patient stratification, offering valuable insights for linking molecular and histologic features in GC.

Influence of Formal Mechanisms on Irrigation Water Distribution: A Farmer Centric Analysis in Pakistan

Influence of Formal Mechanisms on Irrigation Water Distribution: A Farmer Centric Analysis in Pakistan

National security and migration: A human security centric analysis

National security and migration: A human security centric analysis

On the interpretability of part-prototype based classifiers: a human centric analysis

Part-prototype networks have recently become methods of interest as an interpretable alternative to many of the current black-box image classifiers. However, the interpretability of these methods from the perspective of human users has not been sufficiently explored. In addition, previous works have had major issues with following proper experiment design and task representation that limit their reliability and validity. In this work, we have devised a framework for evaluating the interpretability of part-prototype-based models from a human perspective that solves these issues. The proposed framework consists of three actionable metrics and experiments. The results of these experiments will reveal important and reliable interpretability related properties of such models. To demonstrate the usefulness of our framework, we performed an extensive set of experiments using Amazon Mechanical Turk. They not only show the capability of our framework in assessing the interpretability of various part-prototype-based models, but they also are, to the best of our knowledge, the most comprehensive work on evaluating such methods in a unified framework.

Pathway centric analysis for single-cell RNA-seq and spatial transcriptomics data with GSDensity

Advances in single-cell technology have enabled molecular dissection of heterogeneous biospecimens at unprecedented scales and resolutions. Cluster-centric approaches are widely applied in analyzing single-cell data, however they have limited power in dissecting and interpreting highly heterogenous, dynamically evolving data. Here, we present GSDensity, a graph-modeling approach that allows users to obtain pathway-centric interpretation and dissection of single-cell and spatial transcriptomics (ST) data without performing clustering. Using pathway gene sets, we show that GSDensity can accurately detect biologically distinct cells and reveal novel cell-pathway associations ignored by existing methods. Moreover, GSDensity, combined with trajectory analysis can identify curated pathways that are active at various stages of mouse brain development. Finally, GSDensity can identify spatially relevant pathways in mouse brains and human tumors including those following high-order organizational patterns in the ST data. Particularly, we create a pan-cancer ST map revealing spatially relevant and recurrently active pathways across six different tumor types.

Resource Centric Analysis of RSA and ECC Algorithms on FPGA

The electronics industry’s shadow side is counterfeiting, and the doom is growing. Almost every business in the supply chain is impacted by the issue, including component suppliers, distributors, Electronics Manufacturing Services (EMS) providers, Original Design Manufacturers (ODMs), Original Equipment Manufacturers (OEMs), and their clients. In fact, any electronics firm that wishes to benefit from the cheap costs associated with globalization must be aware that someone along the supply chain may be persuaded to acquire fake items and sell them as genuine. A thorough grasp of chip designs, including partitioning and prioritizing data transit and storage, as well as a range of obfuscation techniques and activity monitoring, is necessary to reduce the danger of future hardware breaches. To battle this problem, we need to enforce various security measures at different levels of the supply chain. The recent methods include implementing cryptographic ciphers into the devices. The commonly used ciphers are the hard ciphers. But owing to the advancements and increase in the number of low power and resource constrained devices, there has been a dire need to design ciphers that support such devices. This paper talks about the advantages of lightweight ciphers, aiming to secure low power devices and other embedded devices. This work mainly compares two algorithms, RSA(hard cipher) and ECC(light cipher) in terms of their device utilization and power consumption on a Kintex-7. The presented results are justified from simulations performed on the Vivado design suite.

Instructional Grouping Theory: Optimizing Classrooms and the Placement of Ranked Students

Two common approaches to grouping students include an approach where students are grouped based on their aptitude and a cross-sectional approach where equal groups are formed and comprised of students of varied aptitudes. Instructional Grouping Theory is the study of how selection strategies impact the learning of group members. Using a non-biased, mathematically centric analysis, we found that a liked-skilled tiered grouping strategy is preferable to a cross-sectional grouping strategy when the goal is to facilitate the learning of all students. In addition, we found that a higher teacher-to-student ratio provides further benefit when analyzing the potential for facilitated learning.

Thethesanproject: Lyman-α emission and transmission during the Epoch of Reionization

ABSTRACTThe visibility of high-redshift Lyman-alpha emitting galaxies (LAEs) provides important constraints on galaxy formation processes and the Epoch of Reionization (EoR). However, predicting realistic and representative statistics for comparison with observations represents a significant challenge in the context of large-volume cosmological simulations. The thesan project offers a unique framework for addressing such limitations by combining state-of-the-art galaxy formation (IllustrisTNG) and dust models with the arepo-rt radiation-magnetohydrodynamics solver. In this initial study, we present Lyman-alpha centric analysis for the flagship simulation that resolves atomic cooling haloes throughout a $(95.5\, \text{cMpc})^3$ region of the Universe. To avoid numerical artefacts, we devise a novel method for accurate frequency-dependent line radiative transfer in the presence of continuous Hubble flow, transferable to broader astrophysical applications as well. Our scalable approach highlights the utility of LAEs and red damping-wing transmission as probes of reionization, which reveal nontrivial trends across different galaxies, sightlines, and frequency bands that can be modelled in the framework of covering fractions. In fact, after accounting for environmental factors influencing large-scale ionized bubble formation such as redshift and UV magnitude, the variation across galaxies and sightlines mainly depends on random processes including peculiar velocities and self-shielded systems that strongly impact unfortunate rays more than others. Throughout the EoR local and cosmological optical depths are often greater than or less than unity such that the exp (− τ) behaviour leads to anisotropic and bimodal transmissivity. Future surveys will benefit by targeting both rare bright objects and Goldilocks zone LAEs to infer the presence of these (un)predictable (dis)advantages.

795. A Bayesian Spatial-temporal Modelling Approach for Prevalence Estimation of a VRE Outbreak in a Tertiary Care Hospital

BackgroundThere was a nosocomial outbreak of vancomycin-resistant enterococci (VRE) in our hospital group from 2018-19. The goals of the study were to describe the prevalence trajectory and explore risk factors associated with putative room colonization during the outbreak. MethodsWe performed a room centric analysis of 12 floors (floors F to R, 264 rooms) of the main bed tower of the hospital, including data on 37’458 patients (23’050 person weeks) over the 104 week period. Patients were assumed to be colonized in the week prior to their first positive test, and thereafter throughout the remainder of their stay until discharge. Poisson Bayesian Hierarchical models were fitted to estimate prevalence per room, including both spatial (conditional autoregressive) and temporal (random walk) random effects terms. Model M1 estimated prevalence for each floor and then used meta-analysis to combine the estimates, whereas model M2 estimated prevalence for “all-floors” simultaneously.ResultsThe oncology department, where the outbreak was thought to have started, experienced slightly higher prevalence (floors O and R; adjusted incidence rate ratio (aIRR) 4.8 [2.6, 8.9], p< 0.001; reference is general medicine; see Figure Panel A), as did both the cardiac surgery (floors G, N, O; aIRR 3.8 [2.0, 7.3], p< 0.001) and abdominal surgery departments (floors H and Q; 3.7 [1.8, 7.6], p< 0.001). There was no discernible difference in prevalence between floors with single and multiple department occupancy. Furthermore, departments spread across multiple floors had similar prevalence on all constituent floors – perhaps indicating transmission by people or devices moving between floors.The “single floor meta-analysis” model (M1) more closely followed the estimated trajectory for the crude prevalence, whereas the “all floors” model (M2) dampened the amplitude of the peaks somewhat, but better estimated periods of low prevalence (Figure Panel B).Figure: Estimates from the Bayesian Hierarchical Models Panel A. Random effect prevalence estimates for each floor (from model M2). Panel B. Crude prevalence (black) and estimates from the “single floor meta-analysis” approach (M1, dashed red) with 95% credible intervals shaded (shaded red), and “all-floors” model (M2, blue ). ConclusionWe applied a room centric approach that took into account spatial and temporal dependencies apparent in the nosocomial VRE outbreak. Despite additional complexity, Bayesian Hierarchical Models provide a more flexible platform for studying transmission dynamics and performing hypothesis testing, compared to more traditional methods.Disclosures All Authors: No reported disclosures

Emotional Intelligence of Post Graduate Students: A Primary Data Centric Analysis

Our emotional intelligence (EI) indicates our capability for learning the various practical skills that are based on its components: self-awareness, managing emotions, maturity, empathy, and social skills &amp; social competencies. Most of the emotions and feelings are well-formed in raising up in the family. Family plays an active role to build constructive emotions. An emotional person is capable to set his/her own goal according to his/her strengths and weaknesses. S/he can also critically evaluate himself/herself. Family helps individuals to maintain a healthy balance between emotions and logic. Generally, children who belong to a joint family, get more opportunities to be familiar with the different emotions. Se/he tries to behave according to their family members. Se/he has to realise others’ point of view too that motivates them to live together.

Resource Allocation in Cloud using Multi Bidding Model with User Centric Behavior Analysis

Background: Number of resource allocation and bidding schemes had been enormously arrived for on demand supply scheme of cloud services. But accessing and presenting the Cloud services depending on the reputation would not produce fair result in cloud computing. Since the cloud users not only looking for the efficient services but in major they look towards the cost. So here there is a way of introducing the bidding option system that includes efficient user centric behavior analysis model to render the cloud services and resource allocation with low cost. Objective: The allocation of resources is not flexible and dynamic for the users in the recent days. This gave me the key idea and generated as a problem statement for my proposed work. Methods: An online auction framework that ensures multi bidding mechanism which utilizes user centric behavioral analysis to produce the efficient and reliable usage of cloud resources according to the user choice. Results: we implement Efficient Resource Allocation using Multi Bidding Model with User Centric Behavior Analysis. Thus the algorithm is implemented and system is designed in such a way to provide better allocation of cloud resources which ensures bidding and user behavior. Conclusion: Thus the algorithm Efficient Resource Allocation using Multi Bidding Model with User Centric Behavior Analysis is implemented &amp; system is designed in such a way to provide better allocation of cloud resources which ensures bidding, user behavior. The user bid data is trained accordingly such that to produce efficient resource utilization. Further the work can be taken towards data analytics and prediction of user behavior while allocating the cloud resources.

Targeting hub genes and pathways of innate immune response in COVID-19: A network biology perspective

The current pandemic of 2019 novel coronavirus disease (COVID-19) caused by a novel virus strain, 2019-nCoV/SARS-CoV-2 have posed a serious threat to global public health and economy. It is largely unknown how the human immune system responds to this infection. A better understanding of the immune response to SARS-CoV-2 will be important to develop therapeutics against COVID-19. Here, we have used transcriptomic profile of human alveolar adenocarcinoma cells (A549) infected with SARS-CoV-2 and employed a network biology approach to generate human-virus interactome. Network topological analysis discovers 15 SARS-CoV-2 targets, which belongs to a subset of interferon (IFN) stimulated genes (ISGs). These ISGs (IFIT1, IFITM1, IRF7, ISG15, MX1, and OAS2) can be considered as potential candidates for drug targets in the treatments of COVID-19. We have identified significant interaction between ISGs and TLR3 agonists, like poly I: C, and imiquimod, and suggests that TLR3 agonists can be considered as a potential drug for drug repurposing in COVID-19. Our network centric analysis suggests that moderating the innate immune response is a valuable approach to target COVID-19.

The EBRD, fail forward neoliberalism and the construction of the European periphery

AbstractThe European Bank for Reconstruction and Development is an institution, a set of programmes and policies designed to mark a number of important reforms not just in the post-Soviet space but in the wider European political economy. It is committed to developing a competitive business environment, foreign investment and private sector activity in the post-communist space. The European Bank for Reconstruction and Development is considered to be a key inter-state mechanism enabling member states to negotiate post-communist reforms. The paper reorients analysis of the European Bank for Reconstruction and Development, claiming that existing framings of the role of the EBRD ignore its tangible neoliberalising pressures. It argues that the EBRD works to fundamentally restructure states in the post-communist space in three ways: (1) the configuration of an ‘appropriately’ neoliberal economic space, (2) the construction of subaltern subjectivities in the regional space, and (3) the persistent dominance of expert knowledge and policy practice external to the state. This restructuring is intended to further neoliberalism in the economic space of the region. By uncoupling the European Bank for Reconstruction and Development from a state centric analysis, the paper reveals how the technical aspects of the European Bank for Reconstruction and Development activities configure particular neoliberal rationalities and competencies not as a putative superstate, but as a key site for the ever-deeper encroachment of neoliberalisation in peripheral European states.

Service Gap In Hospital Industry- A Patient Centric Analysis

This paper is having a major objective of finding out the service gap in hospital industry – A patient centric analysis in Coimbatore District. In the 21st century, Health conscious is very high among the people in Tamil Nadu. Before fifty years, people have limited level of hospitals and other allied health services. But today, increases of public, private, corporate and municipal hospitals providing quality services. Hence patients are expecting high quality services from the service providers. The study reveals that services provided in the hospitals have a positive and strong effect on the satisfaction of the inpatients. But reliability is the factor the hospital administrations have to consider.

Abstract 2282: VIP: A system biology platform for cell line centric integrative analysis of molecular and functional genomics data

Abstract Cancer is a heterogeneous disease that is classified by its tissue of origin or molecular characteristics such as genetic alterations that drive tumorigenesis. Large-scale efforts using loss-of-function genetic screens to systematically identify genes essential for the proliferation and survival of cancer cells provide a powerful approach for studying cancer biology and discovering drug targets. However, cancer cell lines from different lineages or molecular background vary in their dependencies on specific genes or pathways. Functional ablation of a gene may be only lethal in one segment of cancer cell lines harboring certain molecular deficiencies or activation of a specific oncogenic signaling pathway, a phenomenon called synthetic lethality. A key challenge here would be to identify the true synthetic lethal interactions from a combinatorially large number of possible interactions between molecular aberrations and gene-level sensitivity to functional perturbation. With recent advances in large-scale studies such as CCLE and Achilles, genome-wide functional genomics screens using CRISPR-Cas9 or shRNA technologies as well as comprehensive molecular profiles have become available for a large number of cancer cell lines. Here we present the Variant Interpretation Portal (VIP), a system biology tool designed to enable integrative analysis of molecular and functional genomics data in cell lines for identifying synthetic lethal interactions. VIP consists of a command-line pipeline and a web-based user interface. The VIP pipeline rigorously filters out germline events and classifies genomic variants into multiple functional tiers. The VIP web portal provides users with a graphic interface to perform exploratory visual analyses of associations between two variables or multiple variables, where a variable could be a genetic alteration or a gene-level sensitivity profile. VIP also enables systematic search for significant association between one variable, such as the sensitivity profile, vs. a database of variables such as histology or molecular attributes. VIP is optimized to perform real-time analytics and enables the incorporation and analysis of user-provided data. The code can be accessed from https://github.com/juferban/vip. Citation Format: Julio Fernandez, Ying Ding, Zhengyan Kan. VIP: A system biology platform for cell line centric integrative analysis of molecular and functional genomics data [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 2282.

Preemptive data distribution infrastructure for data centric analysis and modelling

The next generation of tokamaks, e.g. ITER, will have extremely large data collection rates significantly larger than those experienced today in present tokamaks, with consequential new challenges in data management, data analysis and integrated modelling. One of these challenges is to ensure that appropriate data is efficiently made available when it is required and where it is consumed. Data volumes with limited network capabilities mean not all data can be distributed in time when a data-object is requested. One possible solution is to preemptively identify and distribute efficiently the data across the storage services before a user or an application requests it. Preemptive data distribution rely on analysis of historical access patterns to identify a set of rules whereby following a data-object request the most probable set of next requests can be inferred. Implementation of these rules requires the inferred sets of data to be moved close to data-object consumer. The work presented will describe the Apache Spark Machine Learning tools, the results of the analysis, and an implementation of the preemptive distribution experimental platform at CCFE, together with plans for its future integration and testing on the upcoming SAGE platform.

Abstract 780: Multi-omic profiling of gliomas reveals distinct DNA methylation changes at tumor recurrence

Abstract Varying possibilities of tumor relapse for lower grade glioma (LGG, WHO grade II and III) and glioblastoma (GBM, WHO grade IV) have led to heterogenous clinical outcomes for patients. Our current study aims to establish a molecular profile of recurrence of matched primary and recurrent LGG (n = 28) and recurrent GBM (n = 24) tumor samples. The Cancer Genome Atlas (TCGA) has comprehensively profiled these matched primary/recurrent tumor sets; whole genomes, coding exomes, methylomes, and transcriptomes have been sequenced, and the samples have undergone targeted profiling of the proteome. While unsupervised analysis techniques have not led to a clear recurrence signature, supervised analysis methods have revealed interesting patterns. Protein profiling has shown that recurrent gliomas retain the overall molecular signature of their primary counterpart, but the DNA damage response, apoptosis and RTK pathways are downregulated in the recurrent gliomas, in contrast to RAS/MAPK, PI3K/AKT, and EMT pathways, which are upregulated. Whole genome sequencing and rearrangement analysis have revealed increased genomic complexity among most recurrent gliomas as well as new fusions of interest in recurrent LGG samples (PTPRZ1-MET and involving ATRX). Using genome-wide Illumina HumanMethylation 450K data we observed that 78.6% of LGGs showed depletion of DNA methylation at recurrence and 50% of GBM tumors showed an enrichment of DNA methylation at recurrence. Patient centric enrichment analysis allowed us to discover a candidate biological subgroup characterized by a subset of LGG recurrences (50%) exhibiting an aberrant CpG methylation loss at inintergenic opensea regions when compared with canonical CpG islands and shores (fold &amp;gt; 1.3 and confidence intervals of 99%). Importantly, inspection of CpG sites significantly hypomethylated at openseas showed that this pronounced epigenetic signature maps to candidate TSS distal and hypomethylated enhancers. The gene-targets of these hypomethylated CpG sites show a corresponding up-regulation of expression. Pathway analysis has demonstrated that these upregulated genes are involved in cellular growth and proliferation, cellular function and maintenance, and cell cycle regulation. Our results provide evidence that DNA methylation may represent a stable signature of glioma recurrence and that the crosstalk between DNA hypomethylation at openseas and chromosomal instability may be involved in glioma recurrence. We plan to further integrate our findings between data types and correlate with treatment and patient clinical outcome. Citation Format: Lindsay C. Stetson, Camila Ferreira de Souza, Tathiane Maistro Malta, Thais Sarraf Sabedot, Quinn Ostrom, Peter Liao, Daniela Pretti da Cunha Tirapelli, Luciano Neder, Carlos Gilberto Carlotti, Rehan Akbani, Sofie Salama, Laila Poisson, Daniel Brat, The Cancer Genome Atlas Network, Houtan Noushmehr, Jill Barnholtz-Sloan. Multi-omic profiling of gliomas reveals distinct DNA methylation changes at tumor recurrence. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 780.

Reconciling Csikszentmihalyi’s Broader Flow Theory: With Meaning and Value in Digital Games

Flow, the concept developed by Mihaly Csikszentmihalyi over the last forty years or so (see Csikszentmihalyi 1975) has been invoked quite often with respect to the way players engage with digital games (e.g. Baron 2012; Cowley et al. 2008; Sweetser and Wyeth 2005; Brathwaite &amp; Schreiber, 2009; Fullerton, Swain, &amp; Hoffman, 2008; Schell, 2008). However, Kubey &amp; Csikszentmihalyi (2002) have argued that ‘video games’ are in fact likely to promote undesirable experiences of a kind Csikszentmihalyi refers to as ‘entropy’ or unstructured and unsatisfying life experiences. This paper explores Csikszentmihalyi’s greater thesis and examines how a broader reading of Flow theory can potentially help us understand Flow like engagements beyond the simple mechanistic view of challenge explicitly introduce personally expressed cultural values into the conditions of Flow. By doing so we can then provide a value centric analysis and design approach, similar to that of Cockton’s (2004; 2012) proposal, to include values in general software design. That is, the very nature of challenges and rewards needs to be considered in order to investigate how overcoming or receiving such challenges would be positively or negatively perceived by individuals, from particular cultures, holding particular values. Thus we hope that we have dealt with the apparent contradiction in using Csikszentmihalyi’s concept in the study of games despite his criticism of such a move, and have provided some indication of how we can deal with unspecified rewards and the differential perception and engagement with potentially equivalent challenges while still supporting the accepted thesis of Flow.

Web-TCGA: an online platform for integrated analysis of molecular cancer data sets.

BackgroundThe Cancer Genome Atlas (TCGA) is a pool of molecular data sets publicly accessible and freely available to cancer researchers anywhere around the world. However, wide spread use is limited since an advanced knowledge of statistics and statistical software is required.ResultsIn order to improve accessibility we created Web-TCGA, a web based, freely accessible online tool, which can also be run in a private instance, for integrated analysis of molecular cancer data sets provided by TCGA. In contrast to already available tools, Web-TCGA utilizes different methods for analysis and visualization of TCGA data, allowing users to generate global molecular profiles across different cancer entities simultaneously. In addition to global molecular profiles, Web-TCGA offers highly detailed gene and tumor entity centric analysis by providing interactive tables and views.ConclusionsAs a supplement to other already available tools, such as cBioPortal (Sci Signal 6:pl1, 2013, Cancer Discov 2:401–4, 2012), Web-TCGA is offering an analysis service, which does not require any installation or configuration, for molecular data sets available at the TCGA. Individual processing requests (queries) are generated by the user for mutation, methylation, expression and copy number variation (CNV) analyses. The user can focus analyses on results from single genes and cancer entities or perform a global analysis (multiple cancer entities and genes simultaneously).Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-016-0917-9) contains supplementary material, which is available to authorized users.

An India Centric Analysis: Providing an Indigenous Approach for Enhancing Education System by Inculcating Moral, Value and Spiritual Education in Pupil Teachers

This paper on Mysore’s Ramakrishna Institute of Moral and Spiritual Education (RIMSE) elucidate various facts about the spiritual, value and moral education in its B.Ed. curriculum and examines the overall training effect of an indigenous integrated approach of this institute (RIMSE) on pupil teachers on psychological, societal and institutional levels. To analyse the data collected and generated; qualitative methodology was vigorously used. For the purpose of this investigation, in-situ case study as a method was applied in a longitudinal format. For collecting data document analysis, participant-observation, interviews, and questionnaire were used in a narrowing funnel approach. In conjunction with qualitative method, data was also analysed by employing appropriate statistical procedures such as frequency distribution, percentage etc. for further validation. Current RIMSE students were inducted as participants (N=79), whom the researcher considered using incidental sampling technique. RIMSE today strives to build a spiritual base for their students for making value education as integral part of their educational programs. This study may play a significant role in making some fundamental changes in other teacher training institution in the country as acknowledged by developmental psychologists across the globe. In fact, findings of this study may also open new horizons in inculcation of such values in various types of institutions at various levels of our psychological, pedagogical arrangements and educational system.