Use of complementary and alternative medicine and self-tests by coronary heart disease patients

Background: Coronary heart disease patients have to learn to manage their condition to maximise quality of life and prevent recurrence or deterioration. They may develop their own informal methods of self-management in addition to the advice they receive as part of formal cardiac rehabilitation programmes. This study aimed to explore the use of complementary and alternative medicines and therapies (CAM), self-test kits and attitudes towards health of UK patients one year after referral to cardiac rehabilitation. Method: Questionnaire given to 463 patients attending an assessment clinic for 12 month follow up in four West Midlands hospitals. Results: 91.1% completed a questionnaire. 29.1% of patients used CAM and/or self-test kits for self-management but few (8.9%) used both methods. CAM was more often used for treating other illnesses than for CHD management. Self-test kit use (77.2%,) was more common than CAM (31.7%,) with BP monitors being the most prevalent (80.0%). Patients obtained self-test kits from a wide range of sources, for the most part (89.5%) purchased entirely on their own initiative. Predictors of self-management were post revascularisation status and higher scores on 'holism', 'rejection of authority' and 'individual responsibility'. Predictors of self-test kit use were higher `holism' and 'individual responsibility' scores. Conclusion: Patients are independently using new technologies to monitor their cardiovascular health, a role formerly carried out only by healthcare practitioners. Post-rehabilitation patients reported using CAM for self-management less frequently than they reported using self-test kits. Reports of CAM use were less frequent than in previous surveys of similar patient groups. Automatic assumptions cannot be made by clinicians about which CHD patients are most likely to self-manage. In order to increase trust and compliance it is important for doctors to encourage all CHD patients to disclose their self-management practices and to continue to address this in follow up consultations.

The role of metabolism in the toxicity of N-alkylformamides

Using ionspray tandem mass spectrometry the glutathione conjugate SMG was identified as a biliary metabolite of DMF in rats (0.003% of a dose of 5OOmg/kg DMF i.p.). Formation of this metabolite was increased five fold after induction of CYP2E1 by acetone, and was inhibited to 20% of control values following pretreatment with disulfrram. Generation of SMG from DMF in vivo was shown to exhibit a large kinetic deuterium isotope effect (KWKD=10.1 ± 1.3), which most likely represents the product of 2 discrete isotope effects on N-demethylation and formyl oxidation reactions.The industrial solvent N,N-dimethylformamide (DMF) and the investigational anti-tumour agent N-methylformamide (NMF) cause liver damage in rodents and humans. The hepatotoxicity of N-alkylformamides is linked to their metabolism to N-alkylcarbamic acid thioesters. The enzymatic details of this pathway were investigated. Hepatocytes isolated from BALB/c mice which had been pretreated with acetone, an inducer of the cytochrome P-450 isozyme CYP2E1, were incubated with NMF (10mM). NMF caused extensive toxicity (> 90% ) as determined by lactate dehydrogenase (LDH) release, compared to cells from untreated animals. Incubation of liver cells with NMF for 6 hrs caused 60±17% LDH release whilst in the presence of DMSO (10mM), an alternative substrate for CYP2E1, LDH release was reduced to 20±10% . The metabolism of NMF to S-(N-methylcarbamoyl)glutathione (SMG) was measured in incubates with liver microsomes from mice, rats or humans. Metabolism of NMF was elevated in microsomes isolated from rats and mice pretreated with acetone, by 339% and 183% respectively. Pretreatment of animals with 4-methylpyrazole induced the metabolism of NMF to 280% by rat microsomes, but was without effect on NMF metabolism by mouse microsomes. The CYP2E1 inhibitors or alternative substrates diethyl dithiocarbamate (DEDTC), p-nitrophenol (PNP) and dimethyl sulphoxide (DMSO) strongly inhibited the metabolism of NMF in suspensions of rat liver microsomes, at concentrations which did not effect aminopyrine N-demethylation. The rate of metabolism of NMF to SMG in human microsomes correlated (r> 0.8) with the rate of metabolism of chlorzoxazone, a CYP2E1 probe. A polyclonal antibody against rat CYP2E1 (10mg/nmol P-450) inhibited NMF metabolism in microsomes from rats and humans by 75% and 80% , respectively. The amount of immunoblottable enzyme in human microsomes, determined using an anti-rat CYP2E1 antibody, correlated with the rate of NMF metabolism (r> 0.8). Purified rat CYP2E1 catalysed the generation of SMG from NMF. Formation of the DMF metabolite N-hydroxymethyl-N-methylformamide (HMMF) in incubations with rat liver microsomes was elevated by 200% following pretreatment of animals with acetone. Co-incubation with DEDTC (100μM) inhibited HMMF generation from DMF by 88% . Co-incubation of DMF (10mM) with NMF (1mM) inhibited the formation of SMG by 95% . A polyclonal antibody against rat CYP2E1 (10mg/nmol P-450) inhibited generation of HMMF in incubates with rat and human liver microsomes by 68.4% and 67.5% , respectively. Purified rat CYP2E1 catalysed the generation of HMMF from DMF. Using ionspray tandem mass spectrometry the glutathione conjugate SMG was identified as a biliary metabolite of DMF in rats (0.003% of a dose of 5OOmg/kg DMF i.p.). Formation of this metabolite was increased five fold after induction of CYP2E1 by acetone, and was inhibited to 20% of control values following pretreatment with disulfrram. Generation of SMG from DMF in vivo was shown to exhibit a large kinetic deuterium isotope effect (KHKD=10.1 ± 1.3), which most likely represents the product of 2 discrete isotope effects on N-demethylation and formyl oxidation reactions.

Pyrolysis liquids and gases as alternative fuels in internal combustion engines:a review

Liquids and gases produced through biomass pyrolysis have potential as renewable fuels to replace fossil fuels in conventional internal combustion engines. This review compares the properties of pyrolysis fuels, produced from a variety of feedstocks and using different pyrolysis techniques, against those of fossil fuels. High acidity, the presence of solid particles, high water content, high viscosity, storage and thermal instability, and low energy content are typical characteristics of pyrolysis liquids. A survey of combustion, performance and exhaust emission results from the use of pyrolysis liquids (both crude and up-graded) in compression ignition engines is presented. With only a few exceptions, most authors have reported difficulties associated with the adverse properties of pyrolysis liquids, including: corrosion and clogging of the injectors, long ignition delay and short combustion duration, difficulty in engine start-up, unstable operation, coking of the piston and cylinders and subsequent engine seizure. Pyrolysis gas can be used more readily, either in spark ignition or compression ignition engines; however, NO reduction techniques are desirable. Various approaches to improve the properties of pyrolysis liquids are discussed and a comparison of the properties of up-graded vs. crude pyrolysis liquid is included. Further developments in up-gradation techniques, such as hydrocracking and bio-refinery approaches, could lead to the production of green diesel and green gasoline. Modifications required to engines for use with pyrolysis liquids, for example in the fuel supply and injection systems, are discussed. Storage stability and economic issues are also reviewed. Our study presents recent progress and important R&D areas for successful future use of pyrolysis fuels in internal combustion engines.

What to do when K-means clustering fails:a simple yet principled alternative algorithm

The K-means algorithm is one of the most popular clustering algorithms in current use as it is relatively fast yet simple to understand and deploy in practice. Nevertheless, its use entails certain restrictive assumptions about the data, the negative consequences of which are not always immediately apparent, as we demonstrate. While more flexible algorithms have been developed, their widespread use has been hindered by their computational and technical complexity. Motivated by these considerations, we present a flexible alternative to K-means that relaxes most of the assumptions, whilst remaining almost as fast and simple. This novel algorithm which we call MAP-DP (maximum a-posteriori Dirichlet process mixtures), is statistically rigorous as it is based on nonparametric Bayesian Dirichlet process mixture modeling. This approach allows us to overcome most of the limitations imposed by K-means. The number of clusters K is estimated from the data instead of being fixed a-priori as in K-means. In addition, while K-means is restricted to continuous data, the MAP-DP framework can be applied to many kinds of data, for example, binary, count or ordinal data. Also, it can efficiently separate outliers from the data. This additional flexibility does not incur a significant computational overhead compared to K-means with MAP-DP convergence typically achieved in the order of seconds for many practical problems. Finally, in contrast to K-means, since the algorithm is based on an underlying statistical model, the MAP-DP framework can deal with missing data and enables model testing such as cross validation in a principled way. We demonstrate the simplicity and effectiveness of this algorithm on the health informatics problem of clinical sub-typing in a cluster of diseases known as parkinsonism.