Biomedical subjects

Adrian Dunne

Publications and source records attributed to Adrian Dunne.

4 recordsLinked to original sources

PubMed2006

The effects of the fibre content and physical structure of carrots on satiety and subsequent intakes when eaten as part of a mixed meal.

Previous research indicates that vegetables yield relatively high satiety scores, and that fibre content and structure may both contribute to these effects. This study evaluated the effects of the fibre content and physical structure (gross anatomy and cell structure) of carrots on postprandial satiety and subsequent food intakes when consumed as part of a mixed meal. Using a randomised, repeated-measures, within-subject cross-over design, young women consumed a standardised breakfast and test lunches on three occasions, 4 weeks apart. The test lunches (3329 kJ) comprised boiled rice (200 g) with sweet and sour sauce (200 g) that included chicken (200 g) and carrots (200 g) in three conditions: whole carrots (fibre and structure; n 34), blended carrots (fibre but no structure; n 34) or carrot nutrients (no fibre or structure; n 32). The carrot nutrients had the same energy, major nutrients and portion weight as the other two conditions. Post-lunch satiety was assessed by visual analogue scales. Intakes were covertly weighed at a meal eaten ad libitum (3 h later), and for the remainder of the day using food diaries. Compared with the meal with carrot nutrients, meals with whole carrots and blended carrots resulted in significantly (P<0.05) higher satiety. There were significant (P<0.05) differences between conditions in intakes at the meal eaten ad libitum and for the remainder of the day, and intakes consistently decreased in the order: carrot nutrients, blended carrots, whole carrots, indicating that both fibre content and structure played a role in these effects.

Adult↗

PubMed2005

Riboflavin lowers homocysteine in individuals homozygous for the MTHFR 677C->T polymorphism.

BACKGROUND: Meta-analyses predict that a 25% lowering of plasma homocysteine would reduce the risk of coronary heart disease by 11% to 16% and stroke by 19% to 24%. Individuals homozygous for the methylenetetrahydrofolate reductase (MTHFR) 677C-->T polymorphism have reduced MTHFR enzyme activity resulting from the inappropriate loss of the riboflavin cofactor, but it is unknown whether their typically high homocysteine levels are responsive to improved riboflavin status. METHODS AND RESULTS: From a register of 680 healthy adults 18 to 65 years of age of known MTHFR 677C-->T genotype, we identified 35 with the homozygous (TT) genotype and age-matched individuals with heterozygous (CT, n=26) or wild-type (CC, n=28) genotypes to participate in an intervention in which participants were randomized by genotype group to receive 1.6 mg/d riboflavin or placebo for a 12-week period. Supplementation increased riboflavin status to the same extent in all genotype groups (8% to 12% response in erythrocyte glutathione reductase activation coefficient; P<0.01 in each case). However, homocysteine responded only in the TT group, with levels decreasing by as much as 22% overall (from 16.1+/-1.5 to 12.5+/-0.8 micromol/L; P=0.003; n=32) and markedly so (by 40%) in those with lower riboflavin status at baseline (from 22.0+/-2.9 and 13.2+/-1.0 micromol/L; P=0.010; n=16). No homocysteine response was observed in the CC or CT groups despite being preselected for suboptimal riboflavin status. CONCLUSIONS: Although previously overlooked, homocysteine is highly responsive to riboflavin, specifically in individuals with the MTHFR 677 TT genotype. Our findings might explain why this common polymorphism carries an increased risk of coronary heart disease in Europe but not in North America, where riboflavin fortification has existed for >50 years.

Adolescent↗

PubMed2005

Mixed effects versus fixed effects modelling of binary data with inter-subject variability.

The question of whether or not a mixed effects model is required when modelling binary data with inter-subject variability and within subject correlation was reported in this journal by Yano et al. (J. Pharmacokin. Pharmacodyn. 28:389-412 [2001]). That report used simulation experiments to demonstrate that, under certain circumstances, the use of a fixed effects model produced more accurate estimates of the fixed effect parameters than those produced by a mixed effects model. The Laplace approximation to the likelihood was used when fitting the mixed effects model. This paper repeats one of those simulation experiments, with two binary observations recorded for every subject, and uses both the Laplace and the adaptive Gaussian quadrature approximations to the likelihood when fitting the mixed effects model. The results show that the estimates produced using the Laplace approximation include a small number of extreme outliers. This was not the case when using the adaptive Gaussian quadrature approximation. Further examination of these outliers shows that they arise in situations in which the Laplace approximation seriously overestimates the likelihood in an extreme region of the parameter space. It is also demonstrated that when the number of observations per subject is increased from two to three, the estimates based on the Laplace approximation no longer include any extreme outliers. The root mean squared error is a combination of the bias and the variability of the estimates. Increasing the sample size is known to reduce the variability of an estimator with a consequent reduction in its root mean squared error. The estimates based on the fixed effects model are inherently biased and this bias acts as a lower bound for the root mean squared error of these estimates. Consequently, it might be expected that for data sets with a greater number of subjects the estimates based on the mixed effects model would be more accurate than those based on the fixed effects model. This is borne out by the results of a further simulation experiment with an increased number of subjects in each set of data. The difference in the interpretation of the parameters of the fixed and mixed effects models is discussed. It is demonstrated that the mixed effects model and parameter estimates can be used to estimate the parameters of the fixed effects model but not vice versa.

Algorithms↗

PubMed2004

Interpretation and optimization of the dissolution specifications for a modified release product with an in vivo-in vitro correlation (IVIVC).

This article considers the in vivo significance attached to in vitro dissolution testing. Almost invariably, the in vitro dissolution test is interpreted in terms of bioequivalence. The literature that describes methods for setting in vitro dissolution specifications is reviewed. The most common interpretation of these specifications is a deterministic one, that is, those batches passing the dissolution specifications would be bioequivalent with the reference if tested in vivo and those failing the dissolution specifications would not be bioequivalent if tested in vivo. Due to random variation, the deterministic interpretation is not appropriate. Instead, we need to consider the conditional probability that a batch that has passed the in vitro dissolution test would demonstrate bioequivalence if tested in vivo, and that a batch known to have failed the in vitro dissolution test would demonstrate bioinequivalence if tested in vivo. One way to estimate these probabilities is by means of a simulated experiment in which the production and testing (in vivo and in vitro) of a large number of batches is computer simulated. Such a simulation can only be performed if the relationship between the in vitro dissolution characteristics and the in vivo performance of the product has been modeled. These models are generally referred to as in vivo-in vitro correlations (IVIVC). The results of one such experiment are described. The above-mentioned conditional probabilities are shown to depend on the choice of dissolution specifications. This result leads to the notion of optimal dissolution specifications. However, both of the conditional probabilities cannot be maximized simultaneously. The probability of making a correct decision on the basis of the in vitro dissolution test is introduced as a possible optimality criterion. This probability is a linear combination of the two conditional probabilities of interest. Using this criterion, the optimal dissolution specifications can be found by searching over the multidimensional space defined by the half width of each interval used in the specifications to find the combination that maximizes this probability. This process is demonstrated using the Nelder-Mead search routine. The choice of dissolution specifications has profound implications for the routine production of the product because if the specifications were very narrow the probability of a batch passing would be low, resulting in a low hit rate. The same computer program used to perform the simulation experiment can be used to estimate the hit rate. Furthermore, it can be used to explore the magnitude of changes required in the parameters describing the test product (particularly variability) to increase a low hit rate to an acceptable level.

Biological Availability↗