Impact of calcium on salivary α-amylase activity, starch paste apparent viscosity and thickness perception

Thickness perception of starch-thickened products during eating has been linked to starch viscosity and salivary amylase activity. Calcium is an essential cofactor for α-amylase and there is anecdotal evidence that adding extra calcium affects amylase activity in processes like mashing of beer. The aims of this paper were to (1) investigate the role of salivary calcium on α-amylase activity and (2) to measure the effect of calcium concentration on apparent viscosity and thickness perception when interacting with salivary α-amylase in starch-based samples. α-Amylase activity in saliva samples from 28 people was assessed using a typical starch pasting cycle (up to 95 °C). The activity of the enzyme (as measured by the change in starch apparent viscosity) was maintained by the presence of calcium, probably by protecting the enzyme from heat denaturation. Enhancement of α-amylase activity by calcium at 37 °C was also observed although to a smaller extent. Sensory analysis showed a general trend of decreased thickness perception in the presence of calcium, but the result was only significant for one pair of samples, suggesting a limited impact of calcium enhanced enzyme activity on perceived thickness

Association between colony-stimulating factor 1 receptor gene polymorphisms and asthma risk

Colony-stimulating factor 1 receptor (CSF1R) is expressed in monocytes/macrophages and dendritic cells. These cells play important roles in the innate immune response, which is regarded as an important aspect of asthma development. Genetic alterations in the CSF1R gene may contribute to the development of asthma. We investigated whether CSF1R gene polymorphisms were associated with the risk of asthma. Through direct DNA sequencing of the CSF1R gene, we identified 28 single nucleotide polymorphisms (SNPs) and genotyped them in 303 normal controls and 498 asthmatic patients. Expression of CSF1R protein and mRNA were measured on CD14-positive monocytes and neutrophils in peripheral blood of asthmatic patients using flow cytometry and real-time PCR. Among the 28 polymorphisms, two intronic polymorphism (+20511C>T and +22693T>C) were associated with the risk of asthma by logistic regression analysis. The frequencies of the minor allele at CSF1R +20511C>T and +22693T>C were higher in asthmatic subjects than in normal controls (4.6 vs. 7.7%, p = 0.001 in co-dominant and dominant models; 16.4 vs. 25.8%, p = 0.0006 in a recessive model). CSF1R mRNA levels in neutrophils of the asthmatic patients having the +22693CC allele were higher than in those having the +22693TT allele (p = 0.026). Asthmatic patients with the +22693CC allele also showed significantly higher CSF1R expression on CD14-positive monocytes and neutrophils than did those with the +22693TT allele (p = 0.045 and p = 0.044). The +20511C>T SNP had no association with CSF1R mRNA or protein expression. In conclusion, the minor allele at CSF1R +22693T>C may have a susceptibility effect in the development of asthma, via increased CSF1R protein and mRNA expression in inflammatory cells

Quality Assurance Driving Factors as Antecedents of Knowledge Management: a Stakeholder-Focussed Perspective in Higher Education

Similar to many other types of organisations, the successful development of higher education institutions generally depends on proactive multi-stakeholder management strategy. As a social responsibility of universities, quality assurance (QA) of higher education is already an established research domain. However, the issues that serve as driving factors in higher education’s quality are acknowledged in this vast knowledge stream in a dispersed way. An objective of this paper is to provide a quick snapshot of the major QA driving factors in higher education. Another objective here is to discuss the significance of these existing QA driving factors in higher education as prospective antecedents of knowledge management among the key stakeholders in the higher education sector and beyond. An inductive constructivist approach is followed to review the relevant QA driving factors from the extant scholarly views. A number of relevant factors are précised from the literature that would be instrumental to uphold quality in higher education. The discussion demonstrates that these factors are also significant to transfer and share knowledge between the key stakeholders not only for universities, but also for businesses, governments and other organisational stakeholders. The paper proposes a framework of the QA drivers’ application for meaningful knowledge transfer between diverse stakeholders and clarifies the framework’s managerial implications. This conceptual framework specifies different scenarios and perspectives of QA drivers’ application in the global education sector. The academic novelty is based on the inductive approach applied in the paper. QA practitioners will be able to follow these factors as steering phenomena to effectively assure quality, in relation to their multi-stakeholder relationships in higher education and beyond

Dealing with Time in Health Economic Evaluation: Methodological Issues and Recommendations for Practice

Time is an important aspect of health economic evaluation, as the timing and duration of clinical events, healthcare interventions and their consequences all affect estimated costs and effects. These issues should be reflected in the design of health economic models. This article considers three important aspects of time in modelling: (1) which cohorts to simulate and how far into the future to extend the analysis; (2) the simulation of time, including the difference between discrete-time and continuous-time models, cycle lengths, and converting rates and probabilities; and (3) discounting future costs and effects to their present values. We provide a methodological overview of these issues and make recommendations to help inform both the conduct of cost-effectiveness analyses and the interpretation of their results. For choosing which cohorts to simulate and how many, we suggest analysts carefully assess potential reasons for variation in cost effectiveness between cohorts and the feasibility of subgroup-specific recommendations. For the simulation of time, we recommend using short cycles or continuous-time models to avoid biases and the need for half-cycle corrections, and provide advice on the correct conversion of transition probabilities in state transition models. Finally, for discounting, analysts should not only follow current guidance and report how discounting was conducted, especially in the case of differential discounting, but also seek to develop an understanding of its rationale. Our overall recommendations are that analysts explicitly state and justify their modelling choices regarding time and consider how alternative choices may impact on results