Serum thyroglobulin antibody levels within or near to the reference range may interfere with thyroglobulin measurement

High concentration of thyroglobulin antibodies (TgAb) is a major limiting factor of thyroglobulin measurements in patients with differentiated thyroid cancer. We investigated whether thyroglobulin antibody added to serum samples could interfere with the thyroglobulin assay. Thyroglobulin levels in serum samples with different concentrations of thyroglobulin were measured by electrochemiluminescence immunoassay before and after the addition of increasing concentrations of thyroglobulin antibody using the secondary calibrator solution of the thyroglobulin assay kit containing sheep thyroglobulin antibody to reach thyroglobulin antibody levels within or near to the reference range. Thyroglobulin and thyroglobulin antibody concentrations were also measured in 134 serum samples from 27 patients after thyroid ablation. There was a strong negative association (slope = −1.179) between thyroglobulin antibody and thyroglobulin concentrations in samples with added thyroglobulin antibody (beta = −0.86; P < 0.001). Changes in thyroglobulin concentrations were described mathematically as loss of thyroglobulin% = −0.2408 × Ln(thyroglobulin antibody IU/ml) + 0.1944. Thyroglobulin concentrations were significantly lower than those calculated from experiments with added thyroglobulin antibody in 26/134 samples from patients after thyroid ablation. We conclude that if the same TgAb interference exists in the presence of naturally occurring human TgAb, our observation may prove to be useful during follow-up of patients with differentiated thyroid cancer. However, further studies are needed to explore the clinical relevance of thyroglobulin antibody levels within or near to the reference range in monitoring these patients.     

Exploring computer supported collaborative coordination through social networks

The performance of work groups and in particular geographically distributed ones is negatively affected by communication issues and task dependencies.Contemporary science suggests social link optimization apart from improving the technical aspects to address these issues. In our study, we focus on distributed coordination and project performance. Social network structure and coordination performance variables are described by our framework with regards to distributed coordination during bug fixing process. Based on the model and the literature reviewed, we propose two propositions—(i) the level of interconnectedness has a negative relation with coordination performance; and (ii) centrality social network measures have positive relation with coordination performance variables. We use a sample of 415 Open Source Projects hosted on SourceForge.net. The results suggest that both propositions are correct. Furthermore, in the methods section implementation of an automated process is introduced to build graph definitions in adjacency matrix or NCOL format from thousands of forum threads. We describe the implementation of a novel method to plot sociograms in batch from hundreds of graph definitions automatically and calculate network centrality and density measures for all of them at the same time. Finally, we suggest the implications of this study to software development project management research.     

Complex adaptive information flow and search transfer analysis

Studying information flow between node clusters can be conceptualised as an important challenge for the knowledge management research and practice community. We are confronted with issues related to establishing links between nodes and/or clusters during the process of information flow and search transfer in large distributed networks. In the case of missing socio-technical links, social networks can be instrumental in supporting the communities of practice interested in sharing and transferring knowledge across informal links. A comprehensive review of methodology for detecting missing links is provided. The proportion of common neighbours was selected as best practice to elicit missing links from a large health insurance data set. Weights were based on geographical arrangements of providers and the dollar value of transactions. The core network was elicited based on statistical thresholds. Suspicious, possibly fraudulent, behaviour is highlighted based on social network measures of the core. Our findings are supported by a health insurance industry expert panel.