Measurement of ionic calcium, pH and soluble divalent cations in milk at high temperature

Dialysis and ultrafiltration were investigated as methods for measuring pH and ionic calcium and partitioning of divalent cations of milk at high temperatures. It was found that ionic calcium, pH, and total soluble divalent cations decreased as temperature increased between 20 and 80°C in both dialysates and ultrafiltration permeates. Between 90 and 110°C, ionic calcium and pH in dialysates continued to decrease as temperature increased, and the relationship between ionic calcium and temperature was linear. The permeabilities of hydrogen and calcium ions through the dialysis tubing were not changed after the tubing was sterilized for 1h at 120°C. There were no significant differences in pH and ionic calcium between dialysates from raw milk and those from a range of heat-treated milks. The effects of calcium chloride addition on pH and ionic calcium were measured in milk at 20°C and in dialysates collected at 110°C. Heat coagulation at 110°C occurred with addition of calcium chloride at 5.4mM, where pH and ionic calcium of the dialysate were 6.00 and 0.43mM, respectively. Corresponding values at 20°C were pH 6.66 and 2.10mM.

The effects of environmental perturbation and measurement error on estimates of the shape parameter in the theta-logistic model of population regulation

The theta-logistic is a widely used generalisation of the logistic model of regulated biological processes which is used in particular to model population regulation. Then the parameter theta gives the shape of the relationship between per-capita population growth rate and population size. Estimation of theta from population counts is however subject to bias, particularly when there are measurement errors. Here we identify factors disposing towards accurate estimation of theta by simulation of populations regulated according to the theta-logistic model. Factors investigated were measurement error, environmental perturbation and length of time series. Large measurement errors bias estimates of theta towards zero. Where estimated theta is close to zero, the estimated annual return rate may help resolve whether this is due to bias. Environmental perturbations help yield unbiased estimates of theta. Where environmental perturbations are large, estimates of theta are likely to be reliable even when measurement errors are also large. By contrast where the environment is relatively constant, unbiased estimates of theta can only be obtained if populations are counted precisely Our results have practical conclusions for the design of long-term population surveys. Estimation of the precision of population counts would be valuable, and could be achieved in practice by repeating counts in at least some years. Increasing the length of time series beyond ten or 20 years yields only small benefits. if populations are measured with appropriate accuracy, given the level of environmental perturbation, unbiased estimates can be obtained from relatively short censuses. These conclusions are optimistic for estimation of theta. (C) 2008 Elsevier B.V All rights reserved.

Forkhead (FOX) transcription factors and the cell cycle: measurement of DNA binding by FoxO and FoxM transcription factors

Certain forkhead (FOX) transcription factors have been shown to play an intrinsic role in controlling cell cycle progression. In particular, the FoxO subclass has been shown to regulate cell cycle entry and exit, whereas the expression and activity of FoxM1 is important for the correct coupling of DNA synthesis to mitosis. In this chapter, I describe a method for measuring FoxO and FoxM1 transcription factor DNA binding in nuclear extracts from mammalian cells.

The measurement of maternal plasma corticotropin-releasing factor (CRF) and CRF-binding protein improves the early prediction of preeclampsia

In the present study we measured maternal plasma concentrations of two placental neurohormones, corticotropin-releasing factor (CRF) and CRF-binding protein (CRF-BP), in 58 at-risk pregnant women consecutively enrolled between 28 and 29 wk of pregnancy to evaluate whether their evaluation may predict third trimester-onset preeclampsia ( PE). The statistical significance was assessed by t test. The cut-off points for defining altered CRF and CRF-BP levels for prediction of PE were chosen by receiving operator characteristics curve analysis, and the probability of developing PE was calculated for several combinations of hormone testing results. CRF and CRF-BP levels were significantly ( both P < 0.0001) higher and lower, respectively, in the patients (n = 20) who later developed PE than in those who did not present PE at follow-up. CRF at the cut-off 425.95 pmol/liter achieved a sensitivity of 94.8% and a specificity of 96.9%, whereas CRF-BP at the cut-off 125.8 nmol/liter combined a sensitivity of 92.5% and a specificity of 82.5% as single markers for prediction of PE. The probability of PE was 34.5% in the whole study population, 93.75% when both CRF and CRF-BP levels were changed, and 0% if both hormone markers were unaltered. The measurement of CRF and CRF-BP levels may add significant prognostic information for predicting PE in at-risk pregnant women.

Preparation of nanomagnetic absorbent for partition coefficient measurement

In this paper, we report a new method based on supercritical carbon dioxide (scCO(2)) to fill and distribute the porous magnetic nanoparticles with n-octanol in a homogeneous manner. The high solubility of n-octanol in scCO(2) and high diffusivity and permeability of the fluid allow efficient delivery of n-octanol into the porous magnetic nanoparticles. Thus, the n-octanol-loaded magnetic nanoparticles can be readily dispersed into aqueous buffer (pH 7.40) to form a homogenous suspension consisting of nano-sized n-octanol droplets. We refer this suspension as the n-octanol stock solution. The n-octanol stock solution is then mixed with bulk aqueous phase (pH 7.40) containing an organic compound prior to magnetic separation. The small-size of the particles and the efficient mixing enable a rapid establishment of the partition equilibrium of the organic compound between the solid supported n-octanol nano-droplets and the bulk aqueous phase. UV-vis spectrophotometry is then applied to determine the concentration of the organic compound in the aqueous phase both before and after partitioning (after magnetic separation). As a result, log D values of organic compounds of pharmaceutical interest determined by this modified method are found to be in excellent agreement with the literature data. (c) 2006 Elsevier B.V. All rights reserved.

Key performance indicators (KPIs) and priority setting in using the multi-attribute approach for assessing sustainable intelligent buildings

The main objectives of this paper are to: firstly, identify key issues related to sustainable intelligent buildings (environmental, social, economic and technological factors); develop a conceptual model for the selection of the appropriate KPIs; secondly, test critically stakeholder's perceptions and values of selected KPIs intelligent buildings; and thirdly develop a new model for measuring the level of sustainability for sustainable intelligent buildings. This paper uses a consensus-based model (Sustainable Built Environment Tool- SuBETool), which is analysed using the analytical hierarchical process (AHP) for multi-criteria decision-making. The use of the multi-attribute model for priority setting in the sustainability assessment of intelligent buildings is introduced. The paper commences by reviewing the literature on sustainable intelligent buildings research and presents a pilot-study investigating the problems of complexity and subjectivity. This study is based upon a survey perceptions held by selected stakeholders and the value they attribute to selected KPIs. It is argued that the benefit of the new proposed model (SuBETool) is a ‘tool’ for ‘comparative’ rather than an absolute measurement. It has the potential to provide useful lessons from current sustainability assessment methods for strategic future of sustainable intelligent buildings in order to improve a building's performance and to deliver objective outcomes. Findings of this survey enrich the field of intelligent buildings in two ways. Firstly, it gives a detailed insight into the selection of sustainable building indicators, as well as their degree of importance. Secondly, it tesst critically stakeholder's perceptions and values of selected KPIs intelligent buildings. It is concluded that the priority levels for selected criteria is largely dependent on the integrated design team, which includes the client, architects, engineers and facilities managers.