The Provisional Paediatric Rheumatology International Trials Organisation/American College of Rheumatology/European League Against Rheumatism disease activity core set for the evaluation of response to therapy in juvenile dermatomyositis: A prospective validation study

Objective. To validate a core set of outcome measures for the evaluation of response to treatment in patients with juvenile dermatomyositis (DM). Methods. In 2001, a preliminary consensus-derived core set for evaluating response to therapy in juvenile DM was established. In the present study, the core set was validated through an evidence-based, large-scale data collection that led to the enrollment of 294 patients from 36 countries. Consecutive patients with active disease were assessed at baseline and after 6 months. The validation procedures included assessment of feasibility, responsiveness, discriminant and construct ability, concordce in the evaluation of response to therapy between physicians and parents, redundancy, internal consistency, and ability to predict a therapeutic response. Results. The following clinical measures were found to be feasible, and to have good construct validity, discriminative ability, and internal consistency; furthermore, they were not redundant, proved responsive to clinically important changes in disease activity, and were associated strongly with treatment outcome and thus were included in the final core set: 1) physician`s global assessment of disease activity, 2) muscle strength, 3) global disease activity measure, 4) parent`s global assessment of patient`s well-being, 5) functional ability, and 6) health-related quality of life. Conclusion. The members of the Paediatric Rheumatology International Trials Organisation, with the endorsement of the American College of Rheumatology and the European Leauge Against Rheumatism, propose a core set of criteria for the evaluation of response of therapy that is scientifically and clinically relevant and statistically validated. The core set will help standardize the conduct and reporting of clinical trials and assist practitioners in deciding whether a child with juvenile DM has responded adequately to therapy.

Synchronization of EEG: bivariate and multivariate measures.

Synchronization behavior of electroencephalographic (EEG) signals is important for decoding information processing in the human brain. Modern multichannel EEG allows a transition from traditional measurements of synchronization in pairs of EEG signals to whole-brain synchronization maps. The latter can be based on bivariate measures (BM) via averaging over pair-wise values or, alternatively, on multivariate measures (MM), which directly ascribe a single value to the synchronization in a group. In order to compare BM versus MM, we applied nine different estimators to simulated multivariate time series with known parameters and to real EEGs.We found widespread correlations between BM and MM, which were almost frequency-independent for all the measures except coherence. The analysis of the behavior of synchronization measures in simulated settings with variable coupling strength, connection probability, and parameter mismatch showed that some of them, including S-estimator, S-Renyi, omega, and coherence, aremore sensitive to linear interdependences,while others, like mutual information and phase locking value, are more responsive to nonlinear effects. Onemust consider these properties together with the fact thatMM are computationally less expensive and, therefore, more efficient for the large-scale data sets than BM while choosing a synchronization measure for EEG analysis.

Common variants near MC4R are associated with fat mass, weight and risk of obesity.

To identify common variants influencing body mass index (BMI), we analyzed genome-wide association data from 16,876 individuals of European descent. After previously reported variants in FTO, the strongest association signal (rs17782313, P = 2.9 x 10(-6)) mapped 188 kb downstream of MC4R (melanocortin-4 receptor), mutations of which are the leading cause of monogenic severe childhood-onset obesity. We confirmed the BMI association in 60,352 adults (per-allele effect = 0.05 Z-score units; P = 2.8 x 10(-15)) and 5,988 children aged 7-11 (0.13 Z-score units; P = 1.5 x 10(-8)). In case-control analyses (n = 10,583), the odds for severe childhood obesity reached 1.30 (P = 8.0 x 10(-11)). Furthermore, we observed overtransmission of the risk allele to obese offspring in 660 families (P (pedigree disequilibrium test average; PDT-avg) = 2.4 x 10(-4)). The SNP location and patterns of phenotypic associations are consistent with effects mediated through altered MC4R function. Our findings establish that common variants near MC4R influence fat mass, weight and obesity risk at the population level and reinforce the need for large-scale data integration to identify variants influencing continuous biomedical traits.

Comparative modular analysis of gene expression in vertebrate development

The focus of my PhD research was the concept of modularity. In the last 15 years, modularity has become a classic term in different fields of biology. On the conceptual level, a module is a set of interacting elements that remain mostly independent from the elements outside of the module. I used modular analysis techniques to study gene expression evolution in vertebrates. In particular, I identified ``natural'' modules of gene expression in mouse and human, and I showed that expression of organ-specific and system-specific genes tends to be conserved between such distance vertebrates as mammals and fishes. Also with a modular approach, I studied patterns of developmental constraints on transcriptome evolution. I showed that none of the two commonly accepted models of the evolution of embryonic development (``evo-devo'') are exclusively valid. In particular, I found that the conservation of the sequences of regulatory regions is highest during mid-development of zebrafish, and thus it supports the ``hourglass model''. In contrast, events of gene duplication and new gene introduction are most rare in early development, which supports the ``early conservation model''. In addition to the biological insights on transcriptome evolution, I have also discussed in detail the advantages of modular approaches in large-scale data analysis. Moreover, I re-analyzed several studies (published in high-ranking journals), and showed that their conclusions do not hold out under a detailed analysis. This demonstrates that complex analysis of high-throughput data requires a co-operation between biologists, bioinformaticians, and statisticians.

The consensus molecular subtypes of colorectal cancer.

Colorectal cancer (CRC) is a frequently lethal disease with heterogeneous outcomes and drug responses. To resolve inconsistencies among the reported gene expression-based CRC classifications and facilitate clinical translation, we formed an international consortium dedicated to large-scale data sharing and analytics across expert groups. We show marked interconnectivity between six independent classification systems coalescing into four consensus molecular subtypes (CMSs) with distinguishing features: CMS1 (microsatellite instability immune, 14%), hypermutated, microsatellite unstable and strong immune activation; CMS2 (canonical, 37%), epithelial, marked WNT and MYC signaling activation; CMS3 (metabolic, 13%), epithelial and evident metabolic dysregulation; and CMS4 (mesenchymal, 23%), prominent transforming growth factor-β activation, stromal invasion and angiogenesis. Samples with mixed features (13%) possibly represent a transition phenotype or intratumoral heterogeneity. We consider the CMS groups the most robust classification system currently available for CRC-with clear biological interpretability-and the basis for future clinical stratification and subtype-based targeted interventions.

The legitimacy of foreign investors: individual attitudes toward the impact of multinational enterprises

Purpose – This article aims to analyze individual attitudes toward the impact of multinational enterprises (MNEs) on local businesses. These individual attitudes are important in understanding voters' preferences, which studies show to affect governmental policies. MNEs' market entry location decisions are conditioned by the host's political environment. Moreover, MNEs' attempts to attain legitimacy in their host contexts ultimately affect their bottom line, so how the public perceive MNEs matters. Design/methodology/approach – Using a large-scale data set, the paper carefully delineates between a set of potential mechanisms influencing individual attitudes to globalization in the context of individuals' attitudes toward the impact of MNEs on local businesses. Findings – The article demonstrates that there is remarkable heterogeneity and complexity in individual attitudes toward the impact of MNEs on local businesses and that these attitudes differ across regions and across countries. It is found that better educated individuals, those employed in the private sector, and those who do not have nationalistic tendencies are more likely to consider that MNEs are not harming local firms, while the opposite holds for those who are employed in “less skilled” occupations, such as those working in plants or in elementary occupations. The article also provides evidence that individuals' attitudes are determined by more than the labor market calculations these individuals might have. In fact, the socializing influence of education and the socializing impact of the individuals' type/sector of occupation also significantly determine the individual attitudes under study. Originality/value – This area of research remains substantially under-developed in the literature that analyzes individual attitudes toward globalization, which focuses on individual attitudes toward trade and immigration. Thus, the article not only aims to broaden the work on individual attitudes toward globalization, but it also aims to facilitate further discussion on the specific topic of individual attitudes toward MNEs.

A single-column model ensemble approach applied to the TWP-ICE experiment

Single-column models (SCM) are useful test beds for investigating the parameterization schemes of numerical weather prediction and climate models. The usefulness of SCM simulations are limited, however, by the accuracy of the best estimate large-scale observations prescribed. Errors estimating the observations will result in uncertainty in modeled simulations. One method to address the modeled uncertainty is to simulate an ensemble where the ensemble members span observational uncertainty. This study first derives an ensemble of large-scale data for the Tropical Warm Pool International Cloud Experiment (TWP-ICE) based on an estimate of a possible source of error in the best estimate product. These data are then used to carry out simulations with 11 SCM and two cloud-resolving models (CRM). Best estimate simulations are also performed. All models show that moisture-related variables are close to observations and there are limited differences between the best estimate and ensemble mean values. The models, however, show different sensitivities to changes in the forcing particularly when weakly forced. The ensemble simulations highlight important differences in the surface evaporation term of the moisture budget between the SCM and CRM. Differences are also apparent between the models in the ensemble mean vertical structure of cloud variables, while for each model, cloud properties are relatively insensitive to forcing. The ensemble is further used to investigate cloud variables and precipitation and identifies differences between CRM and SCM particularly for relationships involving ice. This study highlights the additional analysis that can be performed using ensemble simulations and hence enables a more complete model investigation compared to using the more traditional single best estimate simulation only.

A scalable expressive ensemble learning using Random Prism: a MapReduce approach

The induction of classification rules from previously unseen examples is one of the most important data mining tasks in science as well as commercial applications. In order to reduce the influence of noise in the data, ensemble learners are often applied. However, most ensemble learners are based on decision tree classifiers which are affected by noise. The Random Prism classifier has recently been proposed as an alternative to the popular Random Forests classifier, which is based on decision trees. Random Prism is based on the Prism family of algorithms, which is more robust to noise. However, like most ensemble classification approaches, Random Prism also does not scale well on large training data. This paper presents a thorough discussion of Random Prism and a recently proposed parallel version of it called Parallel Random Prism. Parallel Random Prism is based on the MapReduce programming paradigm. The paper provides, for the first time, novel theoretical analysis of the proposed technique and in-depth experimental study that show that Parallel Random Prism scales well on a large number of training examples, a large number of data features and a large number of processors. Expressiveness of decision rules that our technique produces makes it a natural choice for Big Data applications where informed decision making increases the user’s trust in the system.

Metrics for Association Rule Clustering Assessment

Issues related to association mining have received attention, especially the ones aiming to discover and facilitate the search for interesting patterns. A promising approach, in this context, is the application of clustering in the pre-processing step. In this paper, eleven metrics are proposed to provide an assessment procedure in order to support the evaluation of this kind of approach. To propose the metrics, a subjective evaluation was done. The metrics are important since they provide criteria to: (a) analyze the methodologies, (b) identify their positive and negative aspects, (c) carry out comparisons among them and, therefore, (d) help the users to select the most suitable solution for their problems. Besides, the metrics do the users think about aspects related to the problems and provide a flexible way to solve them. Some experiments were done in order to present how the metrics can be used and their usefulness.

ExperNet: An Intelligent Multiagent System for WAN Management

This paper describes ExperNet, an intelligent multi-agent system that was developed under an EU funded project to assist in the management of a large-scale data network. ExperNet assists network operators at various nodes of a WAN to detect and diagnose hardware failures and network traffic problems and suggests the most feasible solution, through a web-based interface. ExperNet is composed by intelligent agents, capable of both local problem solving and social interaction among them for coordinating problem diagnosis and repair. The current network state is captured and maintained by conventional network management and monitoring software components, which have been smoothly integrated into the system through sophisticated information exchange interfaces. For the implementation of the agents, a distributed Prolog system enhanced with networking facilities was developed. The agents’ knowledge base is developed in an extensible and reactive knowledge base system capable of handling multiple types of knowledge representation. ExperNet has been developed, installed and tested successfully in an experimental network zone of Ukraine.

Establishment of a confluent monolayer model with human primary trophoblast cells: novel insights into placental glucose transport

STUDY HYPOTHESIS Using optimized conditions, primary trophoblast cells isolated from human term placenta can develop a confluent monolayer in vitro, which morphologically and functionally resembles the microvilli structure found in vivo. STUDY FINDING We report the successful establishment of a confluent human primary trophoblast monolayer using pre-coated polycarbonate inserts, where the integrity and functionality was validated by cell morphology, biophysical features, cellular marker expression and secretion, and asymmetric glucose transport. WHAT IS KNOWN ALREADY Human trophoblast cells form the initial barrier between maternal and fetal blood to regulate materno-fetal exchange processes. Although the method for isolating pure human cytotrophoblast cells was developed almost 30 years ago, a functional in vitro model with primary trophoblasts forming a confluent monolayer is still lacking. STUDY DESIGN, SAMPLES/MATERIALS, METHODS Human term cytotrophoblasts were isolated by enzymatic digestion and density gradient separation. The purity of the primary cells was evaluated by flow cytometry using the trophoblast-specific marker cytokeratin 7, and vimentin as an indicator for potentially contaminating cells. We screened different coating matrices for high cell viability to optimize the growth conditions for primary trophoblasts on polycarbonate inserts. During culture, cell confluency and polarity were monitored daily by determining transepithelial electrical resistance (TEER) and permeability properties of florescent dyes. The time course of syncytia-related gene expression and hCG secretion during syncytialization were assessed by quantitative RT-PCR and enzyme-linked immunosorbent assay, respectively. The morphology of cultured trophoblasts after 5 days was determined by light microscopy, scanning electron microscopy (SEM) and transmission electron microscopy (TEM). Membrane makers were visualized using confocal microscopy. Additionally, glucose transport studies were performed on the polarized trophoblasts in the same system. MAIN RESULTS AND THE ROLE OF CHANCE During 5-day culture, the highly pure trophoblasts were cultured on inserts coated with reconstituted basement membrane matrix . They exhibited a confluent polarized monolayer, with a modest TEER and a size-dependent apparent permeability coefficient (Papp) to fluorescently labeled compounds (MW ∼400-70 000 Da). The syncytialization progress was characterized by gradually increasing mRNA levels of fusogen genes and elevating hCG secretion. SEM analyses confirmed a confluent trophoblast layer with numerous microvilli, and TEM revealed a monolayer with tight junctions. Immunocytochemistry on the confluent trophoblasts showed positivity for the cell-cell adhesion molecule E-cadherin, the tight junction protein 1 (ZO-1) and the membrane proteins ATP-binding cassette transporter A1 (ABCA1) and glucose transporter 1 (GLUT1). Applying this model to study the bidirectional transport of a non-metabolizable glucose derivative indicated a carrier-mediated placental glucose transport mechanism with asymmetric kinetics. LIMITATIONS, REASONS FOR CAUTION The current study is only focused on primary trophoblast cells isolated from healthy placentas delivered at term. It remains to be evaluated whether this system can be extended to pathological trophoblasts isolated from diverse gestational diseases. WIDER IMPLICATIONS OF THE FINDINGS These findings confirmed the physiological properties of the newly developed human trophoblast barrier, which can be applied to study the exchange of endobiotics and xenobiotics between the maternal and fetal compartment, as well as intracellular metabolism, paracellular contributions and regulatory mechanisms influencing the vectorial transport of molecules. LARGE-SCALE DATA Not applicable. STUDY FUNDING AND COMPETING INTERESTS This study was supported by the Swiss National Center of Competence in Research, NCCR TransCure, University of Bern, Switzerland, and the Swiss National Science Foundation (grant no. 310030_149958, C.A.). All authors declare that their participation in the study did not involve factual or potential conflicts of interests.

Systematic proteomic strategies to map the human signaling landscape

Thesis (Ph.D.)--University of Washington, 2016-05

Empirical studies of corporate governance in China

The thesis aims to provide empirical studies towards Chinese corporate governance. Since China initially established its stock exchange system in the 1990s, it has gone through different stages of changes to become a more market-oriented system. Extensive studies have been conducted in Chinese corporate governance, however, many were theoretical discussion focusing on the early stages and there‘s a general lack of empirical analysis. This paper provides three empirical analysis of the Chinese corporate governance: the overall market discipline efficiency, the impact of capital structure on agency costs, the status of 2005- 2006 reform that substantially modified ownership structure of Chinese listed firms and separated ownership and control of listed firms. The three empirical studies were selected to reflect four key issues that need answering: the first empirical study, using event study to detect market discipline on a collective level. This study filled a gap in the Chinese stock market literature for being the first one ever using cross-market data to test market discipline. The second empirical study endeavoured to contribute to the existing corporate governance literature regarding capital structure and agency costs. Two conclusions can be made through this study: 1) for Chinese listed firms, higher gearing means higher asset turnover ratios and ROE, i.e. more debts seem to reduce agency costs; 2) concentration level of shares appears to be irrelevant with company performance, controlling shareholders didn‘t seem to commit to the improvement of corporate assets utilization or contribute to reducing agency costs. This study addressed a key issue in Chinese corporate governance since the state has significant shareholding in most big listed companies. The discussion of corporate governance in the Chinese context would be completely meaningless without discussing the state‘s role in corporate governance, given that about 2/3 of the almost all shares were non-circulating shares controlled by the state before the 2005-2006 overhaul ownership reform. The third study focused on the 2005-2006 reform of ownership of Chinese listed firms. By collecting large-scale data covering all 64 groups of Chinese listed companies went through the reform by the end of 2006 (accounting for about 97.86% and 96.76% of the total market value of Shanghai (SSE) and Shenzhen Stock Exchange (SZSE) respectively), a comprehensive study about the ownership reform was conducted. This would be first and most comprehensive empirical study in this area. The study of separated ownership and control of listed firm is the first study conducted using the ultimate ownership concept in Chinese context.

HomeBank: An Online Repository of Daylong Child-Centered Audio Recordings.

HomeBank is introduced here. It is a public, permanent, extensible, online database of daylong audio recorded in naturalistic environments. HomeBank serves two primary purposes. First, it is a repository for raw audio and associated files: one database requires special permissions, and another redacted database allows unrestricted public access. Associated files include metadata such as participant demographics and clinical diagnostics, automated annotations, and human-generated transcriptions and annotations. Many recordings use the child-perspective LENA recorders (LENA Research Foundation, Boulder, Colorado, United States), but various recordings and metadata can be accommodated. The HomeBank database can have both vetted and unvetted recordings, with different levels of accessibility. Additionally, HomeBank is an open repository for processing and analysis tools for HomeBank or similar data sets. HomeBank is flexible for users and contributors, making primary data available to researchers, especially those in child development, linguistics, and audio engineering. HomeBank facilitates researchers' access to large-scale data and tools, linking the acoustic, auditory, and linguistic characteristics of children's environments with a variety of variables including socioeconomic status, family characteristics, language trajectories, and disorders. Automated processing applied to daylong home audio recordings is now becoming widely used in early intervention initiatives, helping parents to provide richer speech input to at-risk children.

Flexible modeling and estimation for high-dimensional graphs

Thesis (Ph.D.)--University of Washington, 2016-08