Microfluidic chip for fast bioassays��evaluation of binding parameters

A seven channel polystyrene (PS) microchip has been constructed using a micromilling machine and a high-temperature assembling. Protein A (PA) has been immobilized by a passive sorption on the microchannel walls. Two bioaffinity assays with human immunoglobulin G (hIgG) as a ligand have been carried out. (i) PA as the receptor and fluorescently labeled hIgG (FITC-hIgG) as the ligand, (ii) PA as the receptor with hIgG as the quantified ligand and fluorescently labeled goat anti-human IgG (FITC-gIgG) as the secondary ligand. One incubation step of the assays took only 5 min instead of hours typical for enzyme-linked immunosorbent assay applications. Calibration curves of the dependence of a fluorescence signal on the hIgG concentration in a sample have been obtained in one step due to a parallel arrangement of microchannels. A mathematical model of the PA-FITC-hIgG complex formation in the chip has been developed. The values of the kinetic constant of the PA-FITC-hIgG binding (k_on=5.5 m³ mol⁻¹ s⁻¹) and the equilibrium dissociation constant of the formed complex (K_d≤3×10⁻⁶ mol m⁻³) have been obtained by fitting to experimental data. The proposed microchip enables fast evaluation of kinetic and equilibrium constants of ligand-receptor bioaffinity pairs and the ligand quantification. As the use of microfluidic chips for immunoassays is often limited by price, we used procedures and chemicals that allow for an inexpensive construction and operation of the microdevice, e.g., temperature assembling as a fabrication technique, detection via an ordinary digital camera, nonspecific polystyrene as a substrate, passive sorption of biomolecules as an immobilization technique, etc.     

Hemolysis from a nurses’ standpoint – survey from four Croatian hospitals

Introduction

Hemolysis can occur during sample collection, handling and transport. It is more frequent when the non-laboratory staff performs sampling. The aim of this study was to assess nurses’ knowledge on the causes of hemolysis and consequential impact on the laboratory tests results. Additionally, the differences in knowledge, related to work experience, professional degree and previous education about hemolysis were explored.

Materials and methods

An anonymus survey, containing 11 questions on demographics, causes of hemolysis, its impact on biochemical parameters and nurses’ attitude towards additional education in preanalytics, was conducted in four Croatian hospitals. The answers were compared by Chi-squared and Fischer exact test.

Results

In total, 562 survey results were collected. Majority of nurses declared familiarity with the term “hemolysis” (99.6%). There were 77% of correct answers regarding questions about the causes of hemolysis, but only 50% when it comes to questions about interference in biochemical tests. The percentage of correct answers about causes was significantly lower (P = 0.029) among more experienced nurses, and higher (P = 0.027) in those with higher professional degree, while influence of previous education was not significant. Also, higher percentage of correct answers about interferences was encountered in nurses with longer work experience (P = 0.039). More than 70% of nurses declared that additional education about preanalytical factors would be beneficial.

Conclusion

Croatian nurses are familiar with the definition of hemolysis, but a lack of knowledge about causes and influence on laboratory test results is evident. Nurses are eager to improve their knowledge in this field of preanalytical phase.Key words: hemolysis, nurses, survey, preanalytical phase     

Application of association and decision rules on intellectual capital

Intellectual capital (IC), leading to sustainable competitiveness shapes the patterns of business reality nowadays. IC disclosure has become a critical necessity in this new framework. Being a novel interdisciplinary study, the aim of this paper was to examine IC disclosure by Greek publicly traded firms implementing association and decision rules. Firms were divided into three classes (low, medium and high) according to their IC disclosure, measured by the content analysis methodology. The association rules of each class were specified, highlighting IC reporting profile and focus of the firms belonging to each class. Firms in the high class were shown to have strongly realised the crucial need for a reporting change. Teamwork, corporate culture and extra-firm potential appeared to be underlined. Applying the decision tree methodology, the paper succeeded in proving the remuneration–incentive system, R&D and business collaborations items as the IC reporting-related factors differentiating classes.     

Knowledge development and advice networks in professional organizations

In this paper, social network analysis techniques and regression models are used to explain the impact of the level of knowledge development on ego-network redundancy in a community of hospital physicians. Our findings document that the level of knowledge development and the extent to which knowledge is homogeneously distributed amongst collaborating physicians are related to the redundancy of their advice networks, albeit with opposite effects. Our results highlight also that the impact of these relationships on network redundancy is moderated based on whether partnering individuals belong to different professional groups. Our results provide valuable input for the management of knowledge networks within professional organizations.     

Embedded knowledge management: towards improved managerial relevance

Despite the large volume of research and managerial literature on knowledge management, many practitioners seem to find it difficult to appreciate its added value for their managerial work. This paper aims to understand and elaborate the added value that knowledge management as a managerial approach can bring to the management of knowledge-intensive organizations. This study explores empirically the actual management practices of a knowledge-intensive organization and examines how knowledge-related phenomena are managed as embedded aspects of management. This paper makes a contribution to prior discussions concerning the relevance of knowledge management and the role of knowledge management as an embedded management practice. The findings of this study should be useful in explaining practitioners the nature, relevance and value of knowledge management.     

Knowledge management systems: the hallmark of SMEs

This paper provides an overview of the knowledge management systems (KMSs) adopted by small and medium enterprises (SMEs). KMSs are divided into two categories: knowledge management tools (KM-Tools) and knowledge management practices (KM-Practices). On the basis of the analysis of the literature, two research questions (RQs) were identified and addressed through semi-structured interviews carried out in a sample of 35 SMEs operating in high-tech industries. The first RQ concerns the degree of adoption of KMSs by SMEs. The second RQ regards the relationship between KM-Tools and KM-Practices. As far as the degree of adoption of KMSs, the paper highlights that SMEs are not a homogeneous world but there are a variety of approaches and behaviours. As far as the relationship between the degree of adoption of KM-Tools and KM-Practices, the paper identifies three groups of SMEs that seem to point out the stages of the process of adoption of KMSs: Introduction, SMEs that deal with the process of knowledge management exploiting practices and tools that are already known; Growth, SMEs that adopt specialist practices of knowledge management acquiring new organisational and managerial competence in the field of knowledge management; Maturity, SMEs that invest in new technology and that acquire new technological competence in the field of knowledge management. This categorisation paves the way for further theoretical and practical implications for both managers and policy makers.     

Integrierte Entwicklung von Automotive-Software mit AutoFocus

Zur Beherrschung der komplexen vernetzten und verteilten Funktionen von Automotive-Software ist eine Beschreibung des zu erstellenden Systems auf verschiedenen Abstraktionsebenen und schrittweise überg?nge zwischen diesen Ebenen notwendig. Neben der Definition geeigneter Ebenen werden zur Unterstützung echtzeitkritischer Systemanteile ein einheitliches Berechnungsmodell, ebenenspezifische Beschreibungstechniken, sowie methodische Regeln für diese Abstraktionsebenen eingeführt und in den Werkzeugprototypen AutoFocus integriert.     

Dimensions of variability in embedded operating systems

Design, implementation, and re-engineering of operating systems are still an ambitious undertaking. Despite, or even because, of the long history of theory and practice in this field, adapting existing systems to environments of different conditions and requirements as originally specified or assumed, in terms of functional and/or non-functional respects, is anything but simple. Especially this is true for the embedded systems domain which, on the one hand, calls for highly specialized and application-aware system abstractions and, on the other hand, cares a great deal for easily reusable implementations of these abstractions. The latter aspect becomes more and more important as embedded systems technology is faced with an innovation cycle decreasing in length. Software for embedded systems needs to be designed for variability, and this is in particular true for the operating systems of this domain. The paper discusses dimensions of variability that need to be considered in the development of embedded operating systems and presents approaches that aid construction and maintenance of evolutionary operating systems. CR subject classification  C.3; D.2.11; D.2.13; D.4.7     

Efficient reverse k-nearest neighbor estimation

The reverse k-nearest neighbor (RkNN) problem, i.e. finding all objects in a data set the k-nearest neighbors of which include a specified query object, has received increasing attention recently. Many industrial and scientific applications call for solutions of the RkNN problem in arbitrary metric spaces where the data objects are not Euclidean and only a metric distance function is given for specifying object similarity. Usually, these applications need a solution for the generalized problem where the value of k is not known in advance and may change from query to query. In addition, many applications require a fast approximate answer of RkNN-queries. For these scenarios, it is important to generate a fast answer with high recall. In this paper, we propose the first approach for efficient approximative RkNN search in arbitrary metric spaces where the value of k is specified at query time. Our approach uses the advantages of existing metric index structures but proposes to use an approximation of the nearest-neighbor-distances in order to prune the search space. We show that our method scales significantly better than existing non-approximative approaches while producing an approximation of the true query result with a high recall.