Coreferentiality: A New Method for the Hypothesis-Based Analysis of Phenotypes Characterized by Multivariate Data

Many multifactorial biologic effects, particularly in the context of complex human diseases, are still poorly understood. At the same time, the systematic acquisition of multivariate data has become increasingly easy. The use of such data to analyze and model complex phenotypes, however, remains a challenge. Here, a new analytic approach is described, termed coreferentiality, together with an appropriate statistical test. Coreferentiality is the indirect relation of two variables of functional interest in respect to whether they parallel each other in their respective relatedness to multivariate reference data, which can be informative for a complex effect or phenotype. It is shown that the power of coreferentiality testing is comparable to multiple regression analysis, sufficient even when reference data are informative only to a relatively small extent of 2.5%, and clearly exceeding the power of simple bivariate correlation testing. Thus, coreferentiality testing uses the increased power of multivariate analysis, however, in order to address a more straightforward interpretable bivariate relatedness. Systematic application of this approach could substantially improve the analysis and modeling of complex phenotypes, particularly in the context of human study where addressing functional hypotheses by direct experimentation is often difficult.

Exploring Multi-Component Superconducting Compounds by a High-Pressure Method and Ceramic Combinatorial Chemistry

In this short review, we provide some new insights into the material synthesis and characterization of modern multi-component superconducting oxides. Two different approaches such as the high-pressure, high-temperature method and ceramic combinatorial chemistry will be reported with application to several typical examples. First, we highlight the key role of the extreme conditions in the growth of Fe-based superconductors, where a careful control of the composition-structure relation is vital for understanding the microscopic physics. The availability of high-quality LnFeAsO (Ln = lanthanide) single crystals with substitution of O by F, Sm by Th, Fe by Co, and As by P allowed us to measure intrinsic and anisotropic superconducting properties such as Hc2, Jc. Furthermore, we demonstrate that combinatorial ceramic chemistry is an efficient way to search for new superconducting compounds. A single-sample synthesis concept based on multi-element ceramic mixtures can produce a variety of local products. Such a system needs local probe analyses and separation techniques to identify compounds of interest. We present the results obtained from random mixtures of Ca, Sr, Ba, La, Zr, Pb, Tl, Y, Bi, and Cu oxides reacted at different conditions. By adding Zr but removing Tl, Y, and Bi, the bulk state superconductivity got enhanced up to about 122 K.

Ultrasound Mapping of Nerve Stimulator Response during Sciatic Nerve Blockade and Relation to Postoperative Pain Scores

1.1 Background and Purpose: Ultrasound guided sciatic nerve blockade has rapid onset but at 24 hours pain is greater than nerve stimulator techniques. Injection of the nerve branches or trunk and sub-sheath blockade increase success and reduce onset times but risk injury. This study mapped needle coordinates for sciatic nerve blockade with nerve stimulation and its relation to postoperative pain scores. 1.2 Method: Angle and distance of the needle tip and infusion catheter from the popliteal sciatic nerve at which stimulated plantar flexion occurred were measured. Pain scores at postanesthesia unit discharge and 24 hours were recorded. 1.3 Results: 81% of opioid naïve patients reported immediate analgesia and 20.8% at 24 hours. In opioid tolerant patients 56.8% reported immediate analgesia and 9.1% at 24 hours. Plantar flexion was observed with the needle in the posterior medial quadrant near the sciatic nerve. Opioid tolerant patients reported adequate analgesia when the needle was located more medially and proximally to the sciatic nerve. 1.4 Conclusion: Stimulated plantar flexion is isolated to a narrow angular range in the posterior medial quadrant adjacent to the sciatic nerve. Opioid tolerant patients report adequate analgesia if the needle and catheter are more medial and proximal to the nerve surface.

Relation between cell disruption conditions, cell debris particle size, and inclusion body release

The efficiency of physical separation of inclusion bodies from cell debris is related to cell debris size and inclusion body release and both factors should be taken into account when designing a process. In this work, cell disruption by enzymatic treatment with lysozyme and cellulase, by homogenization, and by homogenization with ammonia pretreatment is discussed. These disruption methods are compared on the basis of inclusion body release, operating costs, and cell debris particle size. The latter was measured with cumulative sedimentation analysis in combination with membrane-associated protein quantification by SDS-PAGE and a spectrophotometric pepticloglycan quantification method. Comparison of the results obtained with these two cell debris quantification methods shows that enzymatic treatment yields cell debris particles with varying chemical composition, while this is not the case with the other disruption methods that were investigated. Furthermore, the experiments show that ammonia pretreatment with homogenization increases inclusion body release compared to homogenization without pretreatment and that this pretreatment may be used to control the cell debris size to some extent. The enzymatic disruption process gives a higher product release than homogenization with or without ammonia pretreatment at lower operating costs, but it also yields a much smaller cell debris size than the other disruption process. This is unfavorable for centrifugal inclusion body purification in this case, where cell debris is the component going to the sediment and the inclusion body is the floating component. Nevertheless, calculations show that centrifugal separation of inclusion bodies from the enzymatically treated cells gives a high inclusion body yield and purity. (C) 2004 Wiley Periodicals, Inc.

Greene Climacteric Scale: norms in an Australian population in relation to age and menopausal status

Objectives The aim of this study was two-fold: to assess climacteric symptoms and provide normative data for the Greene Climacteric Scale during the menopause transition, and to investigate the prevalence of climacteric symptoms in a representative sample of postmenopausal Australian women. Method A cohort of 500 premenopausal, perimenopausal and postmenopausal women aged 40-80 years participated in the Longitudinal Study of Ageing in Women (LAW study) at the Royal Brisbane and Women's Hospital, Brisbane, Australia. In year 1 of the study (2001), all participants completed the Greene Climacteric Scale and information regarding their menopausal status and the use of hormone therapy (HT) was obtained through a clinical interview with a qualified medical practitioner. Results The 50-59-year age group achieved the highest scores on the vasomotor and the depression scales in comparison to other age groups. Significant differences were also evident on the vasomotor and the depression scales on the basis of menopausal status, especially in perimenopausal women. Approximately 10% of women in the 60-79-year age group continued to experience vasomotor symptoms. Conclusion Vasomotor symptoms, as assessed by the Greene Climacteric Scale, are common during the menopause transition and remain elevated for some years in a minority of older postmenopausal women. The norms presented in this study are appropriate for use in an Australian population.

Development of an oligonucleotide-based SNP detection method on lateral flow strips using hexapet tages

Detection of point mutations or single nucleotide polymorphisms (SNPs) is important in relation to disease susceptibility or detection in pathogens of mutations determining drug resistance or host range. There is an emergent need for rapid detection methods amenable to point-of-care applications. The purpose of this study was to reduce to practice a novel method for SNP detection and to demonstrate that this technology can be used downstream of nucleic acid amplification. The authors used a model system to develop an oligonucleotide-based SNP detection system on nitrocellulose lateral flow strips. To optimize the assay they used cloned sequences of the herpes simplex virus-1 (HSV-1) DNA polymerase gene into which they introduced a point mutation. The assay system uses chimeric polymerase chain reaction (PCR) primers that incorporate hexameric repeat tags ("hexapet tags"). The chimeric sequences allow capture of amplified products to predefined positions on a lateral flow strip. These "hexapet" sequences have minimal cross-reactivity and allow specific hybridization-based capture of the PCR products at room temperature onto lateral flow strips that have been striped with complementary hexapet tags. The allele-specific amplification was carried out with both mutant and wild-type primer sets present in the PCR mix ("competitive" format). The resulting PCR products carried a hexapet tag that corresponded with either a wild-type or mutant sequence. The lateral flow strips are dropped into the PCR reaction tube, and mutant sequence and wild-type sequences diffuse along the strip and are captured at the corresponding position on the strip. A red line indicative of a positive reaction is visible after 1 minute. Unlike other systems that require separate reactions and strips for each target sequence, this system allows multiplex PCR reactions and multiplex detection on a single strip or other suitable substrates. Unambiguous visual discrimination of a point mutation under room temperature hybridization conditions was achieved with this model system in 10 minutes after PCR. The authors have developed a capture-based hybridization method for the detection and discrimination of HSV-1 DNA polymerase genes that contain a single nucleotide change. It has been demonstrated that the hexapet oligonucleotides can be adapted for hybridization on the lateral flow strip platform for discrimination of SNPs. This is the first step in demonstrating SNP detection on lateral flow using the hexapet oligonucleotide capture system. It is anticipated that this novel system can be widely used in point-of-care settings.

Customer information system data pre-processing with feature selection techniques for non-technical losses prediction in an electricity market

Non-technical losses (NTL) identification and prediction are important tasks for many utilities. Data from customer information system (CIS) can be used for NTL analysis. However, in order to accurately and efficiently perform NTL analysis, the original data from CIS need to be pre-processed before any detailed NTL analysis can be carried out. In this paper, we propose a feature selection based method for CIS data pre-processing in order to extract the most relevant information for further analysis such as clustering and classifications. By removing irrelevant and redundant features, feature selection is an essential step in data mining process in finding optimal subset of features to improve the quality of result by giving faster time processing, higher accuracy and simpler results with fewer features. Detailed feature selection analysis is presented in the paper. Both time-domain and load shape data are compared based on the accuracy, consistency and statistical dependencies between features.

Implementing an adaptive sending rate by exploiting SNR in relation to throughput over Wireless Mesh Networks

Wireless Mesh Networks (WMNs) have emerged as a key technology for the next generation of wireless networking. Instead ofbeing another type of ad-hoc networking, WMNs diversify the capabilities of ad-hoc networks. There are many kinds of protocols that work over WMNs, such as IEEE 802.11a/b/g, 802.15 and 802.16. To bring about a high throughput under varying conditions, these protocols have to adapt their transmission rate. While transmission rate is a significant part, only a few algorithms such as Auto Rate Fallback (ARF) or Receiver Based Auto Rate (RBAR) have been published. In this paper we will show MAC, packet loss and physical layer conditions play important role for having good channel condition. Also we perform rate adaption along with multiple packet transmission for better throughput. By allowing for dynamically monitored, multiple packet transmission and adaptation to changes in channel quality by adjusting the packet transmission rates according to certain optimization criteria improvements in performance can be obtained. The proposed method is the detection of channel congestion by measuring the fluctuation of signal to the standard deviation of and the detection of packet loss before channel performance diminishes. We will show that the use of such techniques in WMN can significantly improve performance. The effectiveness of the proposed method is presented in an experimental wireless network testbed via packet-level simulation. Our simulation results show that regardless of the channel condition we were to improve the performance in the throughput.

Customer-driven innovation within U.S. business services and its impact on firm performance

This thesis examines the innovative performance of 206 U.S. business service firms. Undeniably, a need exists for better comprehension of the service sector of developed economies. This research takes a unique view by applying a synthesis approach to studying innovation and attempts to build under a proposed strategic innovation paradigm. A quantitative method is utilised via questionnaire in which all major types of innovation are under examination including: product and service, organisational, and technology-driven innovations. Essential ideas for this conceptual framework encapsulate a new mode of understanding service innovation. Basically, the structure of this analysis encompasses the likelihood of innovation and determining the extent of innovation, while also attempting to shed light on the factors which determine the impact of innovation on performance among service firms. What differentiates this research is its focus on customer-driven service firms in addition to other external linkages. A synopsis of the findings suggest that external linkages, particularly with customers, suppliers and strategic alliances or joint ventures, significantly affect innovation performance with regard to the introduction of new services. Service firms which incorporate formal and informal R&D experience significant increases in the extent of new-to-market and new-to-firm innovations. Additionally, the results show that customer-driven service firms experience greater productivity and growth. Furthermore, the findings suggest that external linkages assist service firm performance.

Synchronization processes in nonlinear systems and their relation to cortical oscillatory dynamics

This thesis was focused on theoretical models of synchronization to cortical dynamics as measured by magnetoencephalography (MEG). Dynamical systems theory was used in both identifying relevant variables for brain coordination and also in devising methods for their quantification. We presented a method for studying interactions of linear and chaotic neuronal sources using MEG beamforming techniques. We showed that such sources can be accurately reconstructed in terms of their location, temporal dynamics and possible interactions. Synchronization in low-dimensional nonlinear systems was studied to explore specific correlates of functional integration and segregation. In the case of interacting dissimilar systems, relevant coordination phenomena involved generalized and phase synchronization, which were often intermittent. Spatially-extended systems were then studied. For locally-coupled dissimilar systems, as in the case of cortical columns, clustering behaviour occurred. Synchronized clusters emerged at different frequencies and their boundaries were marked through oscillation death. The macroscopic mean field revealed sharp spectral peaks at the frequencies of the clusters and broader spectral drops at their boundaries. These results question existing models of Event Related Synchronization and Desynchronization. We re-examined the concept of the steady-state evoked response following an AM stimulus. We showed that very little variability in the AM following response could be accounted by system noise. We presented a methodology for detecting local and global nonlinear interactions from MEG data in order to account for residual variability. We found crosshemispheric nonlinear interactions of ongoing cortical rhythms concurrent with the stimulus and interactions of these rhythms with the following AM responses. Finally, we hypothesized that holistic spatial stimuli would be accompanied by the emergence of clusters in primary visual cortex resulting in frequency-specific MEG oscillations. Indeed, we found different frequency distributions in induced gamma oscillations for different spatial stimuli, which was suggestive of temporal coding of these spatial stimuli. Further, we addressed the bursting character of these oscillations, which was suggestive of intermittent nonlinear dynamics. However, we did not observe the characteristic-3/2 power-law scaling in the distribution of interburst intervals. Further, this distribution was only seldom significantly different to the one obtained in surrogate data, where nonlinear structure was destroyed. In conclusion, the work presented in this thesis suggests that advances in dynamical systems theory in conjunction with developments in magnetoencephalography may facilitate a mapping between levels of description int he brain. this may potentially represent a major advancement in neuroscience.

Automated assessment of visual fields and their inter-relation to evoked potentials in visual disorders

The Octopus Automated Perimeter was validated in a comparative study and found to offer many advantages in the assessment of the visual field. The visual evoked potential was investigated in an extensive study using a variety of stimulus parameters to simulate hemianopia and central visual field defects. The scalp topography was recorded topographically and a technique to compute the source derivation of the scalp potential was developed. This enabled clarification of the expected scalp distribution to half field stimulation using different electrode montages. The visual evoked potential following full field stimulation was found to be asymmetrical around the midline with a bias over the left occiput particularly when the foveal polar projections of the occipital cortex were preferentially stimulated. The half field response reflected the distribution asymmetry. Masking of the central 3° resulted in a response which was approximately symmetrical around the midline but there was no evidence of the PNP-complex. A method for visual field quantification was developed based on the neural representation of visual space (Drasdo and Peaston 1982) in an attempt to relate visual field depravation with the resultant visual evoked potentials. There was no form of simple, diffuse summation between the scalp potential and the cortical generators. It was, however, possible to quantify the degree of scalp potential attenuation for M-scaled full field stimuli. The results obtained from patients exhibiting pre-chiasmal lesions suggested that the PNP-complex is not scotomatous in nature but confirmed that it is most likely to be related to specific diseases (Harding and Crews 1982). There was a strong correlation between the percentage information loss of the visual field and the diagnostic value of the visual evoked potential in patients exhibiting chiasmal lesions.

Statin use in rheumatoid arthritis in relation to actual cardiovascular risk:evidence for substantial undertreatment of lipid-associated cardiovascular risk?

Background Cardiovascular disease (CVD) is partially attributed to traditional cardiovascular risk factors, which can be identified and managed based on risk stratification algorithms (Framingham Risk Score, National Cholesterol Education Program, Systematic Cardiovascular Risk Evaluation and Reynolds Risk Score). We aimed to (a) identify the proportion of at risk patients with rheumatoid arthritis (RA) requiring statin therapy identified by conventional risk calculators, and (b) assess whether patients at risk were receiving statins. Methods Patients at high CVD risk (excluding patients with established CVD or diabetes) were identified from a cohort of 400 well characterised patients with RA, by applying risk calculators with or without a ×1.5 multiplier in specific patient subgroups. Actual statin use versus numbers eligible for statins was also calculated. Results The percentage of patients identified as being at risk ranged significantly depending on the method, from 1.6% (for 20% threshold global CVD risk) to 15.5% (for CVD and cerebrovascular morbidity and mortality) to 21.8% (for 10% global CVD risk) and 25.9% (for 5% CVD mortality), with the majority of them (58.1% to 94.8%) not receiving statins. The application of a 1.5 multiplier identified 17% to 78% more at risk patients. Conclusions Depending on the risk stratification method, 2% to 26% of patients with RA without CVD have sufficiently high risk to require statin therapy, yet most of them remain untreated. To address this issue, we would recommend annual systematic screening using the nationally applicable risk calculator, combined with regular audit of whether treatment targets have been achieved.

The role of the sales employee in securing customer satisfaction

Purpose: Previous research has emphasized the pivotal role that salespeople play in customer satisfaction. In this regard, the relationship between salespeople's attitudes, skills, and characteristics, and customer satisfaction remains an area of interest. The paper aims to make three contributions: first, it seeks to examine the impact of salespeople's satisfaction, adaptive selling, and dominance on customer satisfaction. Second, this research aims to use dyadic data, which is a better test of the relationships between constructs since it avoids common method variance. Finally, in contrast to previous research, it aims to test all of the customers of salespeople rather than customers selected by salespeople. Design/methodology/approach: The study employs multilevel analysis to examine the relationship between salespeople's satisfaction with the firm on customer satisfaction, using a dyadic, matched business-to-business sample of a large European financial service provider that comprises 188 customers and 18 employees. Findings: The paper finds that customers' evaluation of service quality, product quality, and value influence customer satisfaction. The analysis at the selling firm's employee level shows that adaptive selling and employee satisfaction positively impact customer satisfaction, while dominance is negatively related to customer satisfaction. Practical implications: Research shows that customer-focus is a key driver in the success of service companies. Customer satisfaction is regarded as a prerequisite for establishing long-term, profitable relations between company and customer, and customer contact employees are key to nurturing this relationship. The role of salespeople's attitudes, skills, and characteristics in the customer satisfaction process are highlighted in this paper. Originality/value: The use of dyadic, multilevel studies to assess the nature of the relationship between employees and customers is, to date, surprisingly limited. The paper examines the link between employee attitudes, skills, and characteristics, and customer satisfaction in a business-to-business setting in the financial service sector, differentiating between customer- and employee-level drivers of business customer satisfaction.

Relation discovery from web data for competency management

In current organizations, valuable enterprise knowledge is often buried under rapidly expanding huge amount of unstructured information in the form of web pages, blogs, and other forms of human text communications. We present a novel unsupervised machine learning method called CORDER (COmmunity Relation Discovery by named Entity Recognition) to turn these unstructured data into structured information for knowledge management in these organizations. CORDER exploits named entity recognition and co-occurrence data to associate individuals in an organization with their expertise and associates. We discuss the problems associated with evaluating unsupervised learners and report our initial evaluation experiments in an expert evaluation, a quantitative benchmarking, and an application of CORDER in a social networking tool called BuddyFinder.

Community relation discovery by named entities

Discovering who works with whom, on which projects and with which customers is a key task in knowledge management. Although most organizations keep models of organizational structures, these models do not necessarily accurately reflect the reality on the ground. In this paper we present a text mining method called CORDER which first recognizes named entities (NEs) of various types from Web pages, and then discovers relations from a target NE to other NEs which co-occur with it. We evaluated the method on our departmental Website. We used the CORDER method to first find related NEs of four types (organizations, people, projects, and research areas) from Web pages on the Website and then rank them according to their co-occurrence with each of the people in our department. 20 representative people were selected and each of them was presented with ranked lists of each type of NE. Each person specified whether these NEs were related to him/her and changed or confirmed their rankings. Our results indicate that the method can find the NEs with which these people are closely related and provide accurate rankings.