Neuropsychological outcomes of nocturnal asthma

Lung disease as a determinant of cognitive decline and dementia

Almost 40 million people currently live with dementia but this is estimated to double over the next 20 years; despite this, research identifying modifiable risk factors is scarce. There is increasing evidence that cognitive impairment is more frequent in those with chronic lung disease than those without. Chronic obstructive pulmonary disease affects 210 million people, with cognitive impairment present in 60% of certain populations. Co-morbid cognitive dysfunction also appears to impact on important outcomes such as quality of life, hospitalisation and survival. This review summarises the evidence of an association between cognition, impaired lung function and obstructive lung disease. It goes on to examine the contribution of neuro-imaging to our understanding of the underlying pathophysiology. While the mechanisms of brain pathology and cognitive impairment are likely to be complex and multi-factorial, there is evidence to suggest a key role for occult cerebrovascular damage independent of traditional vascular risk factors, including smoking.

Hydrophilic matrices: application of Placket-Burman screening design to model the effect of POLYOX-carbopol blends on drug release

The aim of the present study was to screen the effect of seven factors--POLYOX molecular weight (X(1)) and amount (X(2)); carbopol (X(3)), lactose (X(4)), sodium chloride (X(5)), citric acid (X(6)); compression pressure (X(7))--on (1) the release of theophylline from hydrophilic matrices, demonstrated by changes in dissolution rate, and (2) their impact on the release exponent [n] indicative of the drug transport mechanism through the diffusion matrix. This objective was accomplished utilizing the Placket-Burman screening design. Theophylline tablets were prepared according to a 7-factor-12-run statistical model and subjected to a 24-h dissolution study in phosphate buffer at pH 7.2. The primary response variable, Y(4), was the cumulative percent of theophylline dissolved in 12h. The regression equation for the response was Y(4)=66.2167 - 17.5833X(1) - 3.3833X(2) - 9.366X(3) - 1.1166X(4) - 0.6166X(5) + 2.6X(6) - 2.783X(7). This polynomial model was validated by the ANOVA and residual analysis. The results showed that only two factors (X(2) and X(3)) had significant effect (p-value<0.10) on theophylline release from the hydrophilic polymer matrix. Factors (X(2) and X(7)) had significant effect (p-value<0.10) on [n], the exponent.