Differential protein expression and subcellular distribution of TGFβ1, β2 and β3 in cardiomyocytes during pressure overload-induced hypertrophy

The transforming growth factorβ(TGFβ) superfamily plays an important role in the myocardial response to hypertrophy. We have investigated the protein expression of TGFβ1,β2andβ3in left ventricular tissue, and determined their subcellular distribution in myocytes by immunoblotting and immunocytochemistry during the development of left ventricular hypertrophy (LVH), using isoform specific antibodies to TGFβ1,β2andβ3. LVH was produced in rats by aortic constriction (AC) and LV tissue was obtained at days (d)0, 1, 3, 7, 14, 21 and 42 following operation. Compared with age matched sham-operated controls (SH), TGFβ1levels in LV tissue of AC rats increased significantly from d1–d14 (P<0.03) concomitant with the adaptive growth of LV tissue. In contrast, TGFβ3levels decreased in LV tissue of AC rats from d3 post-operation (significant from d14–d42,P<0.03). No significant difference in TGFβ2levels were observed from SH and AC rats after operation. Antibodies to TGFβ1stained intercalated disks, sarcolemmal membranes and cytoplasm, but not nuclei, of cardiomyocytes on LV sections from untreated and SH rats. However, a trans-localisation of TGFβ1to the nuclei of cardiomyocytes was observed in AC hearts. Antibodies to TGFβ3stained T tubules, cytoplasm and the nuclei of cardiomyocytes from untreated and SH rats. However, by d7 post-AC operation, TGFβ3expression was lost rapidly from nuclei of cardiomyocytes followed by a reduction in total TGFβ3immunofluorescence in myocytes. Antibodies to TGFβ2stained sarcolemmal membranes of cardiomyocytes from both SH and AC rats without significant difference between groups. Thus, the differential pattern of protein expression and subcellular distribution of TGFβ1,β2andβ3in myocytes during the development of LVH suggests that these molecules play different roles in the response of cardiomyocytes to LVH.

Operator Theory and Its Applications: In Memory of V. B. Lidskii (1924-2008)

This book is a collection of articles devoted to the theory of linear operators in Hilbert spaces and its applications. The subjects covered range from the abstract theory of Toeplitz operators to the analysis of very specific differential operators arising in quantum mechanics, electromagnetism, and the theory of elasticity; the stability of numerical methods is also discussed. Many of the articles deal with spectral problems for not necessarily selfadjoint operators. Some of the articles are surveys outlining the current state of the subject and presenting open problems.

Electronic properties of 4,4 ',5,5 '-tetramethyl-2,2 '-biphosphinine (tmbp) in the redox series fac-[Mn(Br)(CO)(3)(tmbp)], [Mn(CO)(3)(tmbp)](2), and [Mn(CO)(3)(tmbp)](-): crystallographic, spectroelectrochemical, and DFT computational study

Stepwise electrochemical reduction of the complex fac-[Mn(Br)(CO)(3)(tmbp)] (tmbp = 4,4',5,5'-tetramethyl-2,2'-biphosphinine) produces the dimer [Mn(CO)(3)(tmbp)](2) and the five-coordinate anion [Mn(CO)(3)(tmbp)](-). All three members of the redox series have been characterized by single-crystal X-ray diffraction. The crystallographic data provide valuable insight into the localization of the added electrons on the (carbonyl)manganese and tmbp centers. In particular, the formulation of the two-electron-reduced anion as [Mn-0(CO)(3)(tmbp(-))](-) also agrees with the analysis of its IR nu(CO) wavenumbers and with the results of density functional theoretical (DFT) MO calculations on this compound. The strongly delocalized pi-bonding in the anion stabilizes its five-coordinate geometry and results in the appearance of several mixed Mn-to-tmbp charge-transfer/IL(tmbp) transitions in the near-UV-vis spectral region. A thorough voltammetric and UV-vis/IR spectroelectrochemical study of the reduction path provided evidence for a direct formation of [Mn(CO)(3)(tmbp)](-) via a two-electron ECE mechanism involving the [Mn(CO)(3)(tmbp)](.) radical transient. At ambient temperature [Mn(CO)(3)(tmbp)](-) reacts rapidly with nonreduced fac-[Mn(Br)(CO)(3)(tmbp)] to produce [Mn(CO)(3)(tmbp)](2). Comparison with the analogous 2,2'-bipyridine complexes has revealed striking similarity in the bonding properties and reactivity, despite the stronger pi-acceptor character of the tmbp ligand.

Automated organizational network analysis for enterprise 2.0

Social Networking Sites have recently become a mainstream communications technology for many people around the world. Major IT vendors are releasing social software designed for use in a business/commercial context. These Enterprise 2.0 technologies have impressive collaboration and information sharing functionality, but so far they do not have any organizational network analysis (ONA) features that reveal any patterns of connectivity within business units. This paper shows the impact of organizational network analysis techniques and social networks on organizational performance, we also give an overview on current enterprise social software, and most importantly, we highlight how Enterprise 2.0 can help automate an organizational network analysis.

Insulin receptor substrate-2 gene variants in subjects with metabolic syndrome: association with plasma fatty acid levels and insulin resistance

Several insulin receptor substrate-2 (IRS-2) polymorphisms have been studied in relation to insulin resistance and type 2 diabetes. To examine whether the genetic variability at the IRS-2 gene locus was associated with the degree of insulin resistance and plasma fatty acid levels in metabolic syndrome (MetS) subjects. Methods and results: Insulin sensitivity, insulin secretion, glucose effectiveness, plasma fatty acid composition and three IRS-2 tag-single nucleotide polymorphisms (SNPs) were determined in 452 MetS subjects. Among subjects with the lowest level of monounsaturated (MUFA) (below the median), the rs2289046 A/A genotype was associated with lower glucose effectiveness (p<0.038), higher fasting insulin concentrations (p<0.028) and higher HOMA IR (p<0.038) as compared to subjects carrying the minor G-allele (A/G and G/G). In contrast, among subjects with the highest level of MUFA (above the median), the A/A genotype was associated with lower fasting insulin concentrations and HOMA-IR, whereas individuals carrying the G allele and with the highest level of ω-3 polyunsaturated fatty acids (above the median) showed lower fasting insulin (p<0.01) and HOMA-IR (p<0.02) as compared with A/A subjects. Conclusion: The rs2289046 polymorphism at the IRS2 gene locus may influence insulin sensitivity by interacting with certain plasma fatty acids in MetS subjects.

FACSGen 2.0 animation software: generating three-dimensional FACS-valid facial expressions for emotion research

In this article, we present FACSGen 2.0, new animation software for creating static and dynamic threedimensional facial expressions on the basis of the Facial Action Coding System (FACS). FACSGen permits total control over the action units (AUs), which can be animated at all levels of intensity and applied alone or in combination to an infinite number of faces. In two studies, we tested the validity of the software for the AU appearance defined in the FACS manual and the conveyed emotionality of FACSGen expressions. In Experiment 1, four FACS-certified coders evaluated the complete set of 35 single AUs and 54 AU combinations for AU presence or absence, appearance quality, intensity, and asymmetry. In Experiment 2, lay participants performed a recognition task on emotional expressions created with FACSGen software and rated the similarity of expressions displayed by human and FACSGen faces. Results showed good to excellent classification levels for all AUs by the four FACS coders, suggesting that the AUs are valid exemplars of FACS specifications. Lay participants’ recognition rates for nine emotions were high, and comparisons of human and FACSGen expressions were very similar. The findings demonstrate the effectiveness of the software in producing reliable and emotionally valid expressions, and suggest its application in numerous scientific areas, including perception, emotion, and clinical and euroscience research.

An investigation into the viability of LibraryThing for promotional and user engagement purposes in libraries

Structured abstract: Purpose: LibraryThing is a Web 2.0 tool allowing users to catalogue books using data drawn from sources such as Amazon and the Library of Congress and has facilities such as tagging and interest groups. This study evaluates whether LibraryThing is a valuable tool for libraries to use for promotional and user engagement purposes. Methodology: This study used a sequential mixed methods 3 phase design: (1) the identification of LibraryThing features for user engagement or promotional purposes, (2) exploratory semi-structured interviews (3) a questionnaire. Findings: Several uses of LibraryThing for promotional and user engagement purposes were identified. The most popular reason libraries used LibraryThing was to promote the library or library stock, with most respondents using it specifically to highlight collections of books. Monitoring of patron usage was low and many respondents had not received any feedback. LibraryThing was commonly reported as being easy to use, remotely accessible, and having low cost, whilst its main drawbacks were the 200 book limit for free accounts, and it being a third-party site. The majority of respondents felt LibraryThing was a useful tool for libraries. Practical implications: LibraryThing has most value as a promotional tool for libraries. Libraries should actively monitor patron usage of their LibraryThing account or request user feedback to ensure that LibraryThing provides a truly valuable service for their library. Orginality : There is little research on the value of LibraryThing for libraries, or librarians perceptions of LibraryThing as a Web 2.0 tool.

Complex extreme learning machine applications in terahertz pulsed signals feature sets

This paper presents a novel approach to the automatic classification of very large data sets composed of terahertz pulse transient signals, highlighting their potential use in biochemical, biomedical, pharmaceutical and security applications. Two different types of THz spectra are considered in the classification process. Firstly a binary classification study of poly-A and poly-C ribonucleic acid samples is performed. This is then contrasted with a difficult multi-class classification problem of spectra from six different powder samples that although have fairly indistinguishable features in the optical spectrum, they also possess a few discernable spectral features in the terahertz part of the spectrum. Classification is performed using a complex-valued extreme learning machine algorithm that takes into account features in both the amplitude as well as the phase of the recorded spectra. Classification speed and accuracy are contrasted with that achieved using a support vector machine classifier. The study systematically compares the classifier performance achieved after adopting different Gaussian kernels when separating amplitude and phase signatures. The two signatures are presented as feature vectors for both training and testing purposes. The study confirms the utility of complex-valued extreme learning machine algorithms for classification of the very large data sets generated with current terahertz imaging spectrometers. The classifier can take into consideration heterogeneous layers within an object as would be required within a tomographic setting and is sufficiently robust to detect patterns hidden inside noisy terahertz data sets. The proposed study opens up the opportunity for the establishment of complex-valued extreme learning machine algorithms as new chemometric tools that will assist the wider proliferation of terahertz sensing technology for chemical sensing, quality control, security screening and clinic diagnosis. Furthermore, the proposed algorithm should also be very useful in other applications requiring the classification of very large datasets.

Image retrieval techniques for THz applications in cultural heritage

Techniques to retrieve reliable images from complicated objects are described, overcoming problems introduced by uneven surfaces, giving enhanced depth resolution and improving image contrast. The techniques are illustrated with application to THz imaging of concealed wall paintings.

Simultaneous mobile sink allocation in home environments with applications in mobile consumer robotics

This paper presents a novel mobile sink area allocation scheme for consumer based mobile robotic devices with a proven application to robotic vacuum cleaners. In the home or office environment, rooms are physically separated by walls and an automated robotic cleaner cannot make a decision about which room to move to and perform the cleaning task. Likewise, state of the art cleaning robots do not move to other rooms without direct human interference. In a smart home monitoring system, sensor nodes may be deployed to monitor each separate room. In this work, a quad tree based data gathering scheme is proposed whereby the mobile sink physically moves through every room and logically links all separated sub-networks together. The proposed scheme sequentially collects data from the monitoring environment and transmits the information back to a base station. According to the sensor nodes information, the base station can command a cleaning robot to move to a specific location in the home environment. The quad tree based data gathering scheme minimizes the data gathering tour length and time through the efficient allocation of data gathering areas. A calculated shortest path data gathering tour can efficiently be allocated to the robotic cleaner to complete the cleaning task within a minimum time period. Simulation results show that the proposed scheme can effectively allocate and control the cleaning area to the robot vacuum cleaner without any direct interference from the consumer. The performance of the proposed scheme is then validated with a set of practical sequential data gathering tours in a typical office/home environment.

The Met Office Global Coupled model 2.0 (GC2) configuration

The latest coupled configuration of the Met Office Unified Model (Global Coupled configuration 2, GC2) is presented. This paper documents the model components which make up the configuration (although the scientific description of these components is detailed elsewhere) and provides a description of the coupling between the components. The performance of GC2 in terms of its systematic errors is assessed using a variety of diagnostic techniques. The configuration is intended to be used by the Met Office and collaborating institutes across a range of timescales, with the seasonal forecast system (GloSea5) and climate projection system (HadGEM) being the initial users. In this paper GC2 is compared against the model currently used operationally in those two systems. Overall GC2 is shown to be an improvement on the configurations used currently, particularly in terms of modes of variability (e.g. mid-latitude and tropical cyclone intensities, the Madden–Julian Oscillation and El Niño Southern Oscillation). A number of outstanding errors are identified with the most significant being a considerable warm bias over the Southern Ocean and a dry precipitation bias in the Indian and West African summer monsoons. Research to address these is ongoing.

Targeting medication non-adherence behavior in selected autoimmune diseases: a systematic approach to digital health program development

Background 29 autoimmune diseases, including Rheumatoid Arthritis, gout, Crohn’s Disease, and Systematic Lupus Erythematosus affect 7.6-9.4% of the population. While effective therapy is available, many patients do not follow treatment or use medications as directed. Digital health and Web 2.0 interventions have demonstrated much promise in increasing medication and treatment adherence, but to date many Internet tools have proven disappointing. In fact, most digital interventions continue to suffer from high attrition in patient populations, are burdensome for healthcare professionals, and have relatively short life spans. Objective Digital health tools have traditionally centered on the transformation of existing interventions (such as diaries, trackers, stage-based or cognitive behavioral therapy programs, coupons, or symptom checklists) to electronic format. Advanced digital interventions have also incorporated attributes of Web 2.0 such as social networking, text messaging, and the use of video. Despite these efforts, there has not been little measurable impact in non-adherence for illnesses that require medical interventions, and research must look to other strategies or development methodologies. As a first step in investigating the feasibility of developing such a tool, the objective of the current study is to systematically rate factors of non-adherence that have been reported in past research studies. Methods Grounded Theory, recognized as a rigorous method that facilitates the emergence of new themes through systematic analysis, data collection and coding, was used to analyze quantitative, qualitative and mixed method studies addressing the following autoimmune diseases: Rheumatoid Arthritis, gout, Crohn’s Disease, Systematic Lupus Erythematosus, and inflammatory bowel disease. Studies were only included if they contained primary data addressing the relationship with non-adherence. Results Out of the 27 studies, four non-modifiable and 11 modifiable risk factors were discovered. Over one third of articles identified the following risk factors as common contributors to medication non-adherence (percent of studies reporting): patients not understanding treatment (44%), side effects (41%), age (37%), dose regimen (33%), and perceived medication ineffectiveness (33%). An unanticipated finding that emerged was the need for risk stratification tools (81%) with patient-centric approaches (67%). Conclusions This study systematically identifies and categorizes medication non-adherence risk factors in select autoimmune diseases. Findings indicate that patients understanding of their disease and the role of medication are paramount. An unexpected finding was that the majority of research articles called for the creation of tailored, patient-centric interventions that dispel personal misconceptions about disease, pharmacotherapy, and how the body responds to treatment. To our knowledge, these interventions do not yet exist in digital format. Rather than adopting a systems level approach, digital health programs should focus on cohorts with heterogeneous needs, and develop tailored interventions based on individual non-adherence patterns.