Loss of ACTN3 gene function alters mouse muscle metabolism and shows evidence of positive selection in humans

More than a billion humans worldwide are predicted to be completely deficient in the fast skeletal muscle fiber protein alpha-actinin-3 owing to homozygosity for a premature stop codon polymorphism, R577X, in the ACTN3 gene. The R577X polymorphism is associated with elite athlete status and human muscle performance, suggesting that alpha-actinin-3 deficiency influences the function of fast muscle fibers. Here we show that loss of alpha-actinin-3 expression in a knockout mouse model results in a shift in muscle metabolism toward the more efficient aerobic pathway and an increase in intrinsic endurance performance. In addition, we demonstrate that the genomic region surrounding the 577X null allele shows low levels of genetic variation and recombination in individuals of European and East Asian descent, consistent with strong, recent positive selection. We propose that the 577X allele has been positively selected in some human populations owing to its effect on skeletal muscle metabolism.     

Research and Reflection: Potential Impact on the Professional Development of Undergraduate Occupational Therapy Students

In occupational therapy education in South Africa, community service (CS) focuses learning opportunities during fieldwork placements. CS therefore enabled the researcher to utilise successive small scale research projects to guide learning of students during fieldwork while simultaneously developing the occupational therapy service at a residential care facility. This community setting provided a powerful environment through which research, in combination with opportunities for reflection, contributed to nurturing skills needed by these future health professionals. A technical action research (AR) approach incorporated AR cycles and opportunities for structured reflection. Therefore situations were created for the students to embrace experiential learning. Experiential learning in the form of anticipatory reflection, reflection-in-action, reflection on reflection and retrospective reflection impacted on the quality of the students’ work. Besides encouraging unique leaning opportunities for students when engaging in research during their fieldwork placement, engagement in AR cycles simultaneously improved service delivery to residents in the facility. Key benefits of this investigation were that fieldwork education utilising AR cycles within a CS situation promoted students to identify voids in their theoretical background as well as practice skills; to apply reflective practice that could contribute to their personal and professional development; and to utilize learning opportunities optimally. Despite positive gains showed by this study, the role of power relations between the researcher as fieldwork educator and the students prohibited the AR cycles from being more emancipatory in nature and should be addressed in follow-up studies.     

Clustering patents using non-exhaustive overlaps

Patent documents are unique external sources of information that reveal the core technology underlying new inventions.Patents also serve as a strategic data source that can be mined to discover state-of-the-art technical development and subsequently help guide R&D investments.This research incorporates an ontology schema to extract and represent patent concepts.A clustering algorithm with non-exhaustive overlaps is proposed to overcome deficiencies with exhaustive clustering methods used in patent mining and technology discovery.The non-exhaustive clustering approach allows for the clustering of patent documents with overlapping technical findings and claims,a feature that enables the grouping of patents that define related key innovations.Legal advisors can use this approach to study potential cases of patent infringement or devise strategies to avoid litigation.The case study demonstrates the use of non-exhaustive overlaps algorithm by clustering US and Japan radio frequency identification (RFID) patents and by analyzing the legal implications of automated discovery of patent infringement.     

Decentralized Bezout Identity and a Parametrization of Decentralized Controllers for Singular Systems

1　 IntroductionConsider a singular decentralized control system of the formEx(t) =Ax(t) ∑Ni=1Biui(t)yi =Cix(t) ,i∈ N ={ 1 ,2 ,… ,N}(1 )where x(t)∈ Rn is the state vector,ui(t)∈ Rmi and yi(t)∈ Rpi are respectively the localcontrol input and measure outputvectors of the ith control channel.The matrix E may besingular,i.e.,rank(E) 相似文献   

1998-based national population projections for the United Kingdom and constituent countries

The 1998-based national population projections, carried out by the Government Actuary in consultation with the Registrars General, show the population of the United Kingdom rising from 59.2 million in 1998 to over 63.5 million by 2021. Longer-term projections suggest the population will peak around 2036 and then gradually start to fall. The population will become gradually older with the median age expected to rise from 36.9 years in 1998 to nearly 42 years by 2021. In 1998, there were 1.4 million (13 per cent) more children aged under 16, than people of pensionable age. However, by 2008, the population of pensionable age is projected to exceed the number of children.     

Automatic patent document summarization for collaborative knowledge systems and services

Engineering and research teams often develop new products and technologies by referring to inventions described in patent databases. Efficient patent analysis builds R&D knowledge, reduces new product development time, increases market success, and reduces potential patent infringement. Thus, it is beneficial to automatically and systematically extract information from patent documents in order to improve knowledge sharing and collaboration among R&D team members. In this research, patents are summarized using a combined ontology based and TF-IDF concept clustering approach. The ontology captures the general knowledge and core meaning of patents in a given domain. Then, the proposed methodology extracts, clusters, and integrates the content of a patent to derive a summary and a cluster tree diagram of key terms. Patents from the International Patent Classification (IPC) codes B25C, B25D, B25F (categories for power hand tools) and B24B, C09G and H011 (categories for chemical mechanical polishing) are used as case studies to evaluate the compression ratio, retention ratio, and classification accuracy of the summarization results. The evaluation uses statistics to represent the summary generation and its compression ratio, the ontology based keyword extraction retention ratio, and the summary classification accuracy. The results show that the ontology based approach yields about the same compression ratio as previous non-ontology based research but yields on average an 11% improvement for the retention ratio and a 14% improvement for classification accuracy.     

A multiple intelligent agent system for credit risk prediction via an optimization of localized generalization error with diversity

Company bankruptcies cost billions of dollars in losses to banks each year. Thus credit risk prediction is a critical part of a bank＇s loan approval decision process. Traditional financial models for credit risk prediction are no longer adequate for describing today＇s complex relationship between the financial health and potential bankruptcy of a company. In this work, a multiple classifier system （embedded in a multiple intelligent agent system） is proposed to predict the financial health of a company. In our model, each individual agent （classifier） makes a prediction on the likelihood of credit risk based on only partial information of the company. Each of the agents is an expert, but has limited knowledge （represented by features） about the company. The decisions of all agents are combined together to form a final credit risk prediction. Experiments show that our model out-performs other existing methods using the benchmarking Compustat American Corporations dataset.     

Alzheimer’s disease: the impact of age-related changes in reproductive hormones

No Abstract.  .     

Phosphodiesterase: overview of protein structures, potential therapeutic applications and recent progress in drug development

Phosphodiesterases (PDEs) are essential regulators of cyclic nucleotide signaling with diverse physiological functions. Because of their great market potential and therapeutic importance, PDE inhibitors became recognized as important therapeutic agents in the treatment of various diseases. Currently, there are seven PDE inhibitors on the market, and the pharmacological and safety evaluations of many drug candidates are in progress. Three-dimensional (3D) structures of catalytic domains of PDE 1, -3, -4, -5 and -9 in the presence of their inhibitors are now available, and can be utilized for rational drug design. Recent advances in molecular pharmacology of PDE isoenzymes resulted in identification of new potential applications of PDE inhibitors in various therapeutic areas, including dementia, depression and schizophrenia. This review will describe the latest advances in PDE research on 3D structural studies, the potential of therapeutic applications and the development of drug candidates.Received 30 November 2004; received after revision 24 January 2005; accepted 5 February 2005