Neuregulins with an Ig-like domain are essential for mouse myocardial and neuronal development.

Neuregulins are ligands for the erbB family of receptor tyrosine kinases and mediate growth and differentiation of neural crest, muscle, breast cancer, and Schwann cells. Neuregulins contain an epidermal growth factor-like domain located C-terminally to either an Ig-like domain or a cysteine-rich domain specific to the sensory and motor neuron-derived isoform. Here it is shown that elimination of the Ig-like domain-containing neuregulins by homologous recombination results in embryonic lethality associated with a deficiency of ventricular myocardial trabeculation and impairment of cranial ganglion development. The erbB receptors are expressed in myocardial cells and presumably mediate the neuregulin signal originating from endocardial cells. The trigeminal ganglion is reduced in size and lacks projections toward the brain stem and mandible. We conclude that IgL-domain-containing neuregulins play a major role in cardiac and neuronal development.

Phage display selection of ligand residues important for Src homology 3 domain binding specificity.

The Src homology 3 (SH3) domain is a 50-aa modular unit present in many cellular proteins involved in intracellular signal transduction. It functions to direct protein-protein interactions through the recognition of proline-rich motifs on associated proteins. SH3 domains are important regulatory elements that have been demonstrated to specify distinct regulatory pathways important for cell growth, migration, differentiation, and responses to the external milieu. By the use of synthetic peptides, ligands have been shown to consist of a minimum core sequence and to bind to SH3 domains in one of two pseudosymmetrical orientations, class I and class II. The class I sites have the consensus sequence ZP(L/P)PP psi P whereas the class II consensus is PP psi PPZ (where psi is a hydrophobic residue and Z is a SH3 domain-specific residue). We previously showed by M13 phage display that the Src, Fyn, Lyn, and phosphatidylinositol 3-kinase (PI3K) SH3 domains preferred the same class I-type core binding sequence, RPLPP psi P. These results failed to explain the specificity for cellular proteins displayed by SH3 domains in cells. In the current study, class I and class II core ligand sequences were displayed on the surface of bacteriophage M13 with five random residues placed either N- or C-terminal of core ligand residues. These libraries were screened for binding to the Src, Fyn, Lyn, Yes, and PI3K SH3 domains. By this approach, additional ligand residue preferences were identified that can increase the affinity of SH3 peptide ligands at least 20-fold compared with core peptides. The amino acids selected in the flanking sequences were similar for Src, Fyn, and Yes SH3 domains; however, Lyn and PI3K SH3 domains showed distinct binding specificities. These results indicate that residues that flank the core binding sequences shared by many SH3 domains are important determinants of SH3 binding affinity and selectivity.

A protein-binding domain, EH, identified in the receptor tyrosine kinase substrate Eps15 and conserved in evolution.

In this report we structurally and functionally define a binding domain that is involved in protein association and that we have designated EH (for Eps15 homology domain). This domain was identified in the tyrosine kinase substrate Eps15 on the basis of regional conservation with several heterogeneous proteins of yeast and nematode. The EH domain spans about 70 amino acids and shows approximately 60% overall amino acid conservation. We demonstrated the ability of the EH domain to specifically bind cytosolic proteins in normal and malignant cells of mesenchymal, epithelial, and hematopoietic origin. These observations prompted our search for additional EH-containing proteins in mammalian cells. Using an EH domain-specific probe derived from the eps15 cDNA, we cloned and characterized a cDNA encoding an EH-containing protein with overall similarity to Eps15; we designated this protein Eps15r (for Eps15-related). Structural comparison of Eps15 and Eps15r defines a family of signal transducers possessing extensive networking abilities including EH-mediated binding and association with Src homology 3-containing proteins.

A new algorithm to accelerate harmonic analysis of time series

The Lomb periodogram has been traditionally a tool that allows us to elucidate if a frequency turns out to be important for explaining the behaviour of a given time series. Many linear and nonlinear reiterative harmonic processes that are used for studying the spectral content of a time series take into account this periodogram in order to avoid including spurious frequencies in their models due to the leakage problem of energy from one frequency to others. However, the estimation of the periodogram requires long computation time that makes the harmonic analysis slower when we deal with certain time series. Here we propose an algorithm that accelerates the extraction of the most remarkable frequencies from the periodogram, avoiding its whole estimation of the harmonic process at each iteration. This algorithm allows the user to perform a specific analysis of a given scalar time series. As a result, we obtain a functional model made of (1) a trend component, (2) a linear combination of Fourier terms, and (3) the so-called mixed secular terms by reducing the computation time of the estimation of the periodogram.

Domain Globalization: Using Languages to Support Technical and Social Coordination

When a project is realized in a globalized environment, multiple stakeholders from different organizations work on the same system. Depending on the stakeholders and their organizations, various (possibly overlapping) concerns are raised in the development of the system. In this context a Domain Specific Language (DSL) supports the work of a group of stakeholders who are responsible for addressing a specific set of concerns. This chapter identifies the open challenges arising from the coordination of globalized domain-specific languages. We identify two types of coordination: technical coordination and social coordination. After presenting an overview of the current state of the art, we discuss first the open challenges arising from the composition of multiple DSLs, and then the open challenges associated to the collaboration in a globalized environment.

GIS-Based Suitability Analysis and Planning of Green Infrastructure: A Case of the PPCOD, Capitol Hill

Thesis (Master's)--University of Washington, 2016-06

Hodgkin's lymphoma cell lines express a fusion protein encoded by intergenically spliced mRNA for the multilectin receptor DEC-205 (CD205) and a novel C-type lectin receptor DCL-1

Classic Hodgkin's lymphoma (HL) tissue contains a small population of morphologically distinct malignant cells called Hodgkin and Reed-Sternberg (HRS) cells, associated with the development of HL. Using 3'-rapid amplification of cDNA ends ( RACE) we identified an alternative mRNA for the DEC-205 multilectin receptor in the HRS cell line L428. Sequence analysis revealed that the mRNA encodes a fusion protein between DEC-205 and a novel C-type lectin DCL-1. Although the 7.5-kb DEC-205 and 4.2-kb DCL-1 mRNA were expressed independently in myeloid and B lymphoid cell lines, the DEC-205/DCL-1 fusion mRNA (9.5 kb) predominated in the HRS cell lines ( L428, KM-H2, and HDLM-2). The DEC-205 and DCL-1 genes comprising 35 and 6 exons, respectively, are juxtaposed on chromosome band 2q24 and separated by only 5.4 kb. We determined the DCL-1 transcription initiation site within the intervening sequence by 5'-RACE, confirming that DCL-1 is an independent gene. Two DEC-205/DCL-1 fusion mRNA variants may result from cotranscription of DEC-205 and DCL-1, followed by splicing DEC-205 exon 35 or 34-35 along with DCL-1 exon 1. The resulting reading frames encode the DEC-205 ectodomain plus the DCL-1 ectodomain, the transmembrane, and the cytoplasmic domain. Using DCL-1 cytoplasmic domain-specific polyclonal and DEC-205 monoclonal antibodies for immunoprecipitation/Western blot analysis, we showed that the fusion mRNA is translated into a DEC-205/DCL-1 fusion protein, expressed in the HRS cell lines. These results imply an unusual transcriptional control mechanism in HRS cells, which cotranscribe an mRNA containing DEC-205 and DCL-1 prior to generating the intergenically spliced mRNA to produce a DEC-205/DCL-1 fusion protein.

Analysis of oxidized and chlorinated lipids by mass spectrometry and relevance to signalling

Oxidized and chlorinated phospholipids are generated under inflammatory conditions and are increasingly understood to play important roles in diseases involving oxidative stress. MS is a sensitive and informative technique for monitoring phospholipid oxidation that can provide structural information and simultaneously detect a wide variety of oxidation products, including chain-shortened and -chlorinated phospholipids. MSn technologies involve fragmentation of the compounds to yield diagnostic fragment ions and thus assist in identification. Advanced methods such as neutral loss and precursor ion scanning can facilitate the analysis of specific oxidation products in complex biological samples. This is essential for determining the contributions of different phospholipid oxidation products in disease. While many pro-inflammatory signalling effects of oxPLs (oxidized phospholipids) have been reported, it has more recently become clear that they can also have anti-inflammatory effects in conditions such as infection and endotoxaemia. In contrast with free radical-generated oxPLs, the signalling effects of chlorinated lipids are much less well understood, but they appear to demonstrate mainly pro-inflammatory effects. Specific analysis of oxidized and chlorinated lipids and the determination of their molecular effects are crucial to understanding their role in disease pathology.

Extracting interactions between proteins from the literature

During the last decade, biomedicine has witnessed a tremendous development. Large amounts of experimental and computational biomedical data have been generated along with new discoveries, which are accompanied by an exponential increase in the number of biomedical publications describing these discoveries. In the meantime, there has been a great interest with scientific communities in text mining tools to find knowledge such as protein-protein interactions, which is most relevant and useful for specific analysis tasks. This paper provides a outline of the various information extraction methods in biomedical domain, especially for discovery of protein-protein interactions. It surveys methodologies involved in plain texts analyzing and processing, categorizes current work in biomedical information extraction, and provides examples of these methods. Challenges in the field are also presented and possible solutions are discussed.

From biomedical literature to knowledge:mining protein-protein interactions

To date, more than 16 million citations of published articles in biomedical domain are available in the MEDLINE database. These articles describe the new discoveries which accompany a tremendous development in biomedicine during the last decade. It is crucial for biomedical researchers to retrieve and mine some specific knowledge from the huge quantity of published articles with high efficiency. Researchers have been engaged in the development of text mining tools to find knowledge such as protein-protein interactions, which are most relevant and useful for specific analysis tasks. This chapter provides a road map to the various information extraction methods in biomedical domain, such as protein name recognition and discovery of protein-protein interactions. Disciplines involved in analyzing and processing unstructured-text are summarized. Current work in biomedical information extracting is categorized. Challenges in the field are also presented and possible solutions are discussed.

Self-explanation in adaptive systems based on runtime goal-based models

The behaviour of self adaptive systems can be emergent, which means that the system’s behaviour may be seen as unexpected by its customers and its developers. Therefore, a self-adaptive system needs to garner confidence in its customers and it also needs to resolve any surprise on the part of the developer during testing and maintenance. We believe that these two functions can only be achieved if a self-adaptive system is also capable of self-explanation. We argue a self-adaptive system’s behaviour needs to be explained in terms of satisfaction of its requirements. Since self-adaptive system requirements may themselves be emergent, we propose the use of goal-based requirements models at runtime to offer self-explanation of how a system is meeting its requirements. We demonstrate the analysis of run-time requirements models to yield a self-explanation codified in a domain specific language, and discuss possible future work.

Statistical dialog management for health interventions

Research endeavors on spoken dialogue systems in the 1990s and 2000s have led to the deployment of commercial spoken dialogue systems (SDS) in microdomains such as customer service automation, reservation/booking and question answering systems. Recent research in SDS has been focused on the development of applications in different domains (e.g. virtual counseling, personal coaches, social companions) which requires more sophistication than the previous generation of commercial SDS. The focus of this research project is the delivery of behavior change interventions based on the brief intervention counseling style via spoken dialogue systems. ^ Brief interventions (BI) are evidence-based, short, well structured, one-on-one counseling sessions. Many challenges are involved in delivering BIs to people in need, such as finding the time to administer them in busy doctors' offices, obtaining the extra training that helps staff become comfortable providing these interventions, and managing the cost of delivering the interventions. Fortunately, recent developments in spoken dialogue systems make the development of systems that can deliver brief interventions possible. ^ The overall objective of this research is to develop a data-driven, adaptable dialogue system for brief interventions for problematic drinking behavior, based on reinforcement learning methods. The implications of this research project includes, but are not limited to, assessing the feasibility of delivering structured brief health interventions with a data-driven spoken dialogue system. Furthermore, while the experimental system focuses on harmful alcohol drinking as a target behavior in this project, the produced knowledge and experience may also lead to implementation of similarly structured health interventions and assessments other than the alcohol domain (e.g. obesity, drug use, lack of exercise), using statistical machine learning approaches. ^ In addition to designing a dialog system, the semantic and emotional meanings of user utterances have high impact on interaction. To perform domain specific reasoning and recognize concepts in user utterances, a named-entity recognizer and an ontology are designed and evaluated. To understand affective information conveyed through text, lexicons and sentiment analysis module are developed and tested.^

ArchWiSeN: uma estratégia baseada em modelos para desenvolvimento de aplicações para redes de sensores e atuadores sem fio

Wireless Sensor and Actuator Networks (WSAN) are a key component in Ubiquitous Computing Systems and have many applications in different knowledge domains. Programming for such networks is very hard and requires developers to know the available sensor platforms specificities, increasing the learning curve for developing WSAN applications. In this work, an MDA (Model-Driven Architecture) approach for WSAN applications development called ArchWiSeN is proposed. The goal of such approach is to facilitate the development task by providing: (i) A WSAN domain-specific language, (ii) a methodology for WSAN application development; and (iii) an MDA infrastructure composed of several software artifacts (PIM, PSMs and transformations). ArchWiSeN allows the direct contribution of domain experts in the WSAN application development without the need of specialized knowledge on WSAN platforms and, at the same time, allows network experts to manage the application requirements without the need for specific knowledge of the application domain. Furthermore, this approach also aims to enable developers to express and validate functional and non-functional requirements of the application, incorporate services offered by WSAN middleware platforms and promote reuse of the developed software artifacts. In this sense, this Thesis proposes an approach that includes all WSAN development stages for current and emerging scenarios through the proposed MDA infrastructure. An evaluation of the proposal was performed by: (i) a proof of concept encompassing three different scenarios performed with the usage of the MDA infrastructure to describe the WSAN development process using the application engineering process, (ii) a controlled experiment to assess the use of the proposed approach compared to traditional method of WSAN application development, (iii) the analysis of ArchWiSeN support of middleware services to ensure that WSAN applications using such services can achieve their requirements ; and (iv) systematic analysis of ArchWiSeN in terms of desired characteristics for MDA tool when compared with other existing MDA tools for WSAN.

Characterisation of an ubiquitin binding CUE domain in presenilin-1

The presenilins are the catalytic component of the gamma-secretase protease complex, involved in the regulated intramembrane proteolysis of numerous type-1 transmembrane proteins, including Amyloid precursor protein (APP) and Notch. In addition to their role in the γ-secretase complex the presenilins are involved in a number of γ-secretase independent functions such as calcium homeostasis, apoptosis, inflammation and protein trafficking. Presenilin function is known to be regulated through posttranslational modifications like endoproteolysis, phosphorylation and ubiquitination. Using a bioinformatics and protein sequence analysis approach this lab has identified a putative ubiquitin binding CUE domain in the presenilins. The aim of this project was to characterise the function of the presenilin CUE domains. Firstly, the presenilins are shown to contain a functional ubiquitin-binding CUE domain that preferentially binds to K63-linked polyubiquitin chains. The PS1 CUE domain is shown to be dispensable for PS1 endoproteolysis and γ-secretase mediated cleavage of APP, Notch and IL-1R1. This suggests the PS1 CUE domain is involved in a γ-secretase independent PS1 function. Our hypothesis is that the PS1 CUE domain is involved in regulating PS1’s intermolecular protein-protein interactions or intramolecular PS1:PS1 interactions. Here the PS1 CUE domain is shown to be dispensable for the interaction of PS1 and the K63-linked polyubiquitinated PS1 interacting proteins P75NTR, IL-1R1, TRAF6, TRAF2 and RIP1. To further investigate PS1 CUE domain function a mass spectrometry proteomics based approach is used to identify PS1 CUE domain interacting proteins. This proteomics approach demonstrated that the PS1 CUE domain is not required for PS1 dimerization. Instead a number of proteins thatinteract with the PS1 CUE domain are identified as well as proteins whose interaction with PS1 is downregulated by the presence of the PS1 CUE domain. Bioinformatic analysis of these proteins suggests possible roles for the PS1 CUE domain in regulating cell signalling, ubiquitination or cellular trafficking.

Statistical Dialog Management for Health Interventions

Research endeavors on spoken dialogue systems in the 1990s and 2000s have led to the deployment of commercial spoken dialogue systems (SDS) in microdomains such as customer service automation, reservation/booking and question answering systems. Recent research in SDS has been focused on the development of applications in different domains (e.g. virtual counseling, personal coaches, social companions) which requires more sophistication than the previous generation of commercial SDS. The focus of this research project is the delivery of behavior change interventions based on the brief intervention counseling style via spoken dialogue systems. Brief interventions (BI) are evidence-based, short, well structured, one-on-one counseling sessions. Many challenges are involved in delivering BIs to people in need, such as finding the time to administer them in busy doctors' offices, obtaining the extra training that helps staff become comfortable providing these interventions, and managing the cost of delivering the interventions. Fortunately, recent developments in spoken dialogue systems make the development of systems that can deliver brief interventions possible. The overall objective of this research is to develop a data-driven, adaptable dialogue system for brief interventions for problematic drinking behavior, based on reinforcement learning methods. The implications of this research project includes, but are not limited to, assessing the feasibility of delivering structured brief health interventions with a data-driven spoken dialogue system. Furthermore, while the experimental system focuses on harmful alcohol drinking as a target behavior in this project, the produced knowledge and experience may also lead to implementation of similarly structured health interventions and assessments other than the alcohol domain (e.g. obesity, drug use, lack of exercise), using statistical machine learning approaches. In addition to designing a dialog system, the semantic and emotional meanings of user utterances have high impact on interaction. To perform domain specific reasoning and recognize concepts in user utterances, a named-entity recognizer and an ontology are designed and evaluated. To understand affective information conveyed through text, lexicons and sentiment analysis module are developed and tested.