Versican processing by a disintegrin-like and metalloproteinase domain with thrombospondin-1 repeats proteinases-5 and -15 facilitates myoblast fusion

Skeletal muscle development and regeneration requires the fusion of myoblasts into multinucleated myotubes. Because the enzymatic proteolysis of a hyaluronan and versican-rich matrix by ADAMTS versicanases is required for developmental morphogenesis, we hypothesized that the clearance of versican may facilitate the fusion of myoblasts during myogenesis. Here, we used transgenic mice and an in vitro model of myoblast fusion, C2C12 cells, to determine a potential role for ADAMTS versicanases. Versican processing was observed during in vivo myogenesis at the time when myoblasts were fusing to form multinucleated myotubes. Relevant ADAMTS genes, chief among them Adamts5 and Adamts15, were expressed both in developing embryonic muscle and differentiating C2C12 cells. Reducing the levels of Adamts5 mRNA in vitro impaired myoblast fusion, which could be rescued with catalytically active but not the inactive forms of ADAMTS5 or ADAMTS15. The addition of inactive ADAMTS5, ADAMTS15, or full-length V1 versican effectively impaired myoblast fusion. Finally, the expansion of a hyaluronan and versican-rich matrix was observed upon reducing the levels of Adamts5 mRNA in myoblasts. These data indicate that these ADAMTS proteinases contribute to the formation of multinucleated myotubes such as is necessary for both skeletal muscle development and during regeneration, by remodeling a versican-rich pericellular matrix of myoblasts. Our study identifies a possible pathway to target for the improvement of myogenesis in a plethora of diseases including cancer cachexia, sarcopenia, and muscular dystrophy.

Biosynthesis and expression of a disintegrin-like and metalloproteinase domain with thrombospondin-1 repeats-15

Background
ADAMTS proteoglycanases show proteolytic activity toward versican and other proteoglycans.

Results
ADAMTS15, which cleaves versican, is expressed during early cardiac development and during musculoskeletal development.

Conclusion
With unique and overlapping biological properties, ADAMTS15 is likely to have cooperative roles with other members of the ADAMTS proteoglycanase clade.

Significance
Versican cleavage has profound effects on developmental morphogenesis and regulates cancer cell behavior.

Potassium channel modulation by a toxin domain in matrix metalloprotease

Peptide toxins found in a wide array of venoms block K+ channels, causing profound physiological and pathological effects. Here we describe the first functional K+ channel-blocking toxin domain in a mammalian protein. MMP23 (matrix metalloprotease 23) contains a domain (MMP23TxD) that is evolutionarily related to peptide toxins from sea anemones. MMP23TxD shows close structural similarity to the sea anemone toxins BgK and ShK. Moreover, this domain blocks K+ channels in the nanomolar to low micromolar range (Kv1.6 > Kv1.3 > Kv1.1 = Kv3.2 > Kv1.4, in decreasing order of potency) while sparing other K+ channels (Kv1.2, Kv1.5, Kv1.7, and KCa3.1). Full-length MMP23 suppresses K+ channels by co-localizing with and trapping MMP23TxD-sensitive channels in the ER. Our results provide clues to the structure and function of the vast family of proteins that contain domains related to sea anemone toxins. Evolutionary pressure to maintain a channel-modulatory function may contribute to the conservation of this domain throughout the plant and animal kingdoms.

Acquisition of domain ontology from relational schemes based on reverse engineering

Acquisition of domain ontology from database has been of catholic concern. This paper, taking relational schemes as example, analyzes how to identify the information about the structure of relational schemes in legacy systems. Then, it presents twelve extraction rules, which facilitate the obtaining of terms and relations from the relational schemes. Finally, it uses the EER diagram to further obtain semantic information from relational schemes for refining ontology model. The development method of domain ontology based on reverse engineering is a supplement to forward engineering. The union of the two development methods is certainly beneficial for the designers of domain ontology. © 2009 IEEE.

Total and domain-specific sitting time among employees in desk-based work settings in Australia

Objective: To describe the total and domain-specific daily sitting time among a sample of Australian office-based employees. Methods: In April 2010, paper-based surveys were provided to desk-based employees (n=801) in Victoria, Australia. Total daily and domain-specific (work, leisure-time and transport-related) sitting time (minutes/day) were assessed by validated questionnaires. Differences in sitting time were examined across socio-demographic (age, sex, occupational status) and lifestyle characteristics (physical activity levels, body mass index [BMI]) using multiple linear regression analyses. Results: The median (95% confidence interval [CI]) of total daily sitting time was 540 (531-557) minutes/day. Insufficiently active adults (median=578 minutes/day, [95%CI: 564-602]), younger adults aged 18-29 years (median=561 minutes/day, [95%CI: 540-577]) reported the highest total daily sitting times. Occupational sitting time accounted for almost 60% of total daily sitting time. In multivariate analyses, total daily sitting time was negatively associated with age (unstandardised regression coefficient [B]=-1.58, p<0.001) and overall physical activity (minutes/week) (B=-0.03, p<0.001) and positively associated with BMI (B=1.53, p=0.038). Conclusions: Desk-based employees reported that more than half of their total daily sitting time was accrued in the work setting. Implications: Given the high contribution of occupational sitting to total daily sitting time among desk-based employees, interventions should focus on the work setting.

An online transfer learning RBF neural network for cross domain data classification

In this paper, a Radial Basis Function Network (RBFN) trained with the Dynamic Decay Adjustment (DDA) algorithm (i.e., RBFNDDA) is deployed as an incremental learning model for tackling transfer learning problems. An online learning strategy is exploited to allow the RBFNDDA model to transfer knowledge from one domain and applied to classification tasks in a different yet related domain. An experimental study is carried out to evaluate the effectiveness of the online RBFNDDA model using a benchmark data set obtained from a public domain. The results are analyzed and compared with those from other methods. The outcomes positively reveal the potentials of the online RBFNDDA model in handling transfer learning tasks. © 2014 The authors and IOS Press. All rights reserved.

Frequency-domain beamformers using conjugate gradient techniques for speech enhancement

A multiple-iteration constrained conjugate gradient (MICCG) algorithm and a single-iteration constrained conjugate gradient (SICCG) algorithm are proposed to realize the widely used frequency-domain minimum-variance-distortionless-response (MVDR) beamformers and the resulting algorithms are applied to speech enhancement. The algorithms are derived based on the Lagrange method and the conjugate gradient techniques. The implementations of the algorithms avoid any form of explicit or implicit autocorrelation matrix inversion. Theoretical analysis establishes formal convergence of the algorithms. Specifically, the MICCG algorithm is developed based on a block adaptation approach and it generates a finite sequence of estimates that converge to the MVDR solution. For limited data records, the estimates of the MICCG algorithm are better than the conventional estimators and equivalent to the auxiliary vector algorithms. The SICCG algorithm is developed based on a continuous adaptation approach with a sample-by-sample updating procedure and the estimates asymptotically converge to the MVDR solution. An illustrative example using synthetic data from a uniform linear array is studied and an evaluation on real data recorded by an acoustic vector sensor array is demonstrated. Performance of the MICCG algorithm and the SICCG algorithm are compared with the state-of-the-art approaches.

A stochastic time-domain model for burst data aggregation in IEEE 802.15.4 wireless sensor networks

In many network applications, the nature of traffic is of burst type. Often, the transient response of network to such traffics is the result of a series of interdependant events whose occurrence prediction is not a trivial task. The previous efforts in IEEE 802.15.4 networks often followed top-down approaches to model those sequences of events, i.e., through making top-view models of the whole network, they tried to track the transient response of network to burst packet arrivals. The problem with such approaches was that they were unable to give station-level views of network response and were usually complex. In this paper, we propose a non-stationary analytical model for the IEEE 802.15.4 slotted CSMA/CA medium access control (MAC) protocol under burst traffic arrival assumption and without the optional acknowledgements. We develop a station-level stochastic time-domain method from which the network-level metrics are extracted. Our bottom-up approach makes finding station-level details such as delay, collision and failure distributions possible. Moreover, network-level metrics like the average packet loss or transmission success rate can be extracted from the model. Compared to the previous models, our model is proven to be of lower memory and computational complexity order and also supports contention window sizes of greater than one. We have carried out extensive and comparative simulations to show the high accuracy of our model.

HorusCML: context-aware domain-specific visual languages designer

The objective behind building domain-specific visual languages (DSVLs) is to provide users with the most appropriate concepts and notations that best fit with their domain and experience. However, the existing DSVL designers do not support integrating environment and user context information when modeling, editing or viewing DSVL models at different locations, permissions, devices, etc. In this paper, we introduce HorusCML, a context-aware DSVL designer, which supports DSVL experts in integrating necessary context details within their DSVLs. The resultant DSVLs can reflect different facets, layouts, and behaviours according to context it is used in. We show a case study on developing a context-aware data flow diagram DSVL tool using HorusCML.