Effect of temperature and a crosslinking promoter on the gamma-radiolysis of a perfluoroelastomer

Methods of promoting the radiation-induced cross linking of poly(tetrafluoro-ethylene-co-perfluoromethyl vinyl ether) (TFE/PMVE) have been investigated. Greater control of the crosslinking and chain-scission reactions was achieved by varying the radiolysis temperature. This was attributed to temperature affecting the mobilities of reactive species such as polymeric free radicals. These reactive species are precursors to radiation-induced cross links and chain-ends. Analysis of the sol/gel behaviour, tensile properties and FTIR indicated that the optimum temperature for the radiation crosslinking of TFE/PMVE, at a dose of 150 kGy, was 263 K. This temperature was 10 K below the glass transition temperature. Incorporation of 1 wt% triallyl isocyanurate (TAIC) greatly amplified the radiation crosslinking of TFE/PMVE, The dose for gelation was decreased by 70%, and the additive imparted superior mechanical properties compared to the neat irradiated TFE/PMVE. Electron spin resonance (ESR) measurements showed higher radical yields at 77 K with the 1 wt% TAIC, indicating that the crosslinking promoter was acting as a radical trap. (C) 1999 Society of Chemical Industry.

Methods for effective fluidization of particulate food materials

Depending on the size and shape of the materials, methods employed to achieve effective fluidization during fluid bed drying varies from use of simple hole distributors for small, light weight materials to special techniques for lager and/or moist materials. This paper reviews common air distributors used in fluidized bed drying of food particulates. Also it reviews special methods of fluidizing larger irregular food particulates.

Methods for prediction of peptide binding to MHC molecules: A comparative study

Background: A variety of methods for prediction of peptide binding to major histocompatibility complex (MHC) have been proposed. These methods are based on binding motifs, binding matrices, hidden Markov models (HMM), or artificial neural networks (ANN). There has been little prior work on the comparative analysis of these methods. Materials and Methods: We performed a comparison of the performance of six methods applied to the prediction of two human MHC class I molecules, including binding matrices and motifs, ANNs, and HMMs. Results: The selection of the optimal prediction method depends on the amount of available data (the number of peptides of known binding affinity to the MHC molecule of interest), the biases in the data set and the intended purpose of the prediction (screening of a single protein versus mass screening). When little or no peptide data are available, binding motifs are the most useful alternative to random guessing or use of a complete overlapping set of peptides for selection of candidate binders. As the number of known peptide binders increases, binding matrices and HMM become more useful predictors. ANN and HMM are the predictive methods of choice for MHC alleles with more than 100 known binding peptides. Conclusion: The ability of bioinformatic methods to reliably predict MHC binding peptides, and thereby potential T-cell epitopes, has major implications for clinical immunology, particularly in the area of vaccine design.

Zygosity Diagnosis in the Absence of Genotypic Data: An Approach Using Latent Class Analysis

For zygosity diagnosis in the absence of genotypic data, or in the recruitment phase of a twin study where only single twins from same-sex pairs are being screened, or to provide a test for sample duplication leading to the false identification of a dizygotic pair as monozygotic, the appropriate analysis of respondents' answers to questions about zygosity is critical. Using data from a young adult Australian twin cohort (N = 2094 complete pairs and 519 singleton twins from same-sex pairs with complete responses to all zygosity items), we show that application of latent class analysis (LCA), fitting a 2-class model, yields results that show good concordance with traditional methods of zygosity diagnosis, but with certain important advantages. These include the ability, in many cases, to assign zygosity with specified probability on the basis of responses of a single informant (advantageous when one zygosity type is being oversampled); and the ability to quantify the probability of misassignment of zygosity, allowing prioritization of cases for genotyping as well as identification of cases of probable laboratory error. Out of 242 twins (from 121 like-sex pairs) where genotypic data were available for zygosity confirmation, only a single case was identified of incorrect zygosity assignment by the latent class algorithm. Zygosity assignment for that single case was identified by the LCA as uncertain (probability of being a monozygotic twin only 76%), and the co-twin's responses clearly identified the pair as dizygotic (probability of being dizygotic 100%). In the absence of genotypic data, or as a safeguard against sample duplication, application of LCA for zygosity assignment or confirmation is strongly recommended.

Discovery, structure and biological activities of the cyclotides

The cyclotides are a family of small disulfide rich proteins that have a cyclic peptide backbone and a cystine knot formed by three conserved disulfide bonds. The combination of these two structural motifs contributes to the exceptional chemical, thermal and enzymatic stability of the cyclotides, which retain bioactivity after boiling. They were initially discovered based on native medicine or screening studies associated with some of their various activities, which include uterotonic action, anti-HIV activity, neurotensin antagonism, and cytotoxicity. They are present in plants from the Rubiaceae, Violaceae and Cucurbitaccae families and their natural function in plants appears to be in host defense: they have potent activity against certain insect pests and they also have antimicrobial activity. There are currently around 50 published sequences of cyclotides and their rate of discovery has been increasing over recent years. Ultimately the family may comprise thousands of members. This article describes the background to the discovery of the cyclotides, their structural characterization, chemical synthesis, genetic origin, biological activities and potential applications in the pharmaceutical and agricultural industries. Their unique topological features make them interesting from a protein folding perspective. Because of their highly stable peptide framework they might make useful templates in drug design programs, and their insecticidal activity opens the possibility of applications in crop protection.

Three cases of Q fever osteomyelitis in children and a review of the literature

Q fever is a common zoonosis worldwide. Awareness of the disease and newer diagnostic modalities have resulted in increasing recognition of unusual manifestations. We report 3 cases of Q fever osteomyelitis in children and review the literature on 11 other reported cases. The cases demonstrate that Coxiella burnetii can cause granulomatous osteomyelitis that presents without systemic symptoms and frequently results in a chronic, relapsing, multifocal clinical course. Optimal selection and duration of antimicrobial therapy and methods of monitoring therapy are currently uncertain.

Application of mixture models to detect differentially expressed genes

An important and common problem in microarray experiments is the detection of genes that are differentially expressed in a given number of classes. As this problem concerns the selection of significant genes from a large pool of candidate genes, it needs to be carried out within the framework of multiple hypothesis testing. In this paper, we focus on the use of mixture models to handle the multiplicity issue. With this approach, a measure of the local FDR (false discovery rate) is provided for each gene. An attractive feature of the mixture model approach is that it provides a framework for the estimation of the prior probability that a gene is not differentially expressed, and this probability can subsequently be used in forming a decision rule. The rule can also be formed to take the false negative rate into account. We apply this approach to a well-known publicly available data set on breast cancer, and discuss our findings with reference to other approaches.

Validity of BMI as a measure of obesity in Australian white Caucasian and Australian Sri lankan children

Background: Body mass index ( BMI) is used to diagnose obesity. However, its ability to predict the percentage fat mass (% FM) reliably is doubtful. Therefore validity of BMI as a diagnostic tool of obesity is questioned. Aim: This study is focused on determining the ability of BMI- based cut- off values in diagnosing obesity among Australian children of white Caucasian and Sri Lankan origin. Subjects and methods: Height and weight was measured and BMI ( W/H-2) calculated. Total body water was determined by deuterium dilution technique and fat free mass and hence fat mass derived using age- and gender- specific constants. A % FM of 30% for girls and 20% for boys was considered as the criterion cut- off level for obesity. BMI- based obesity cut- offs described by the International Obesity Task Force ( IOTF), CDC/ NCHS centile charts and BMI- Z were validated against the criterion method. Results: There were 96 white Caucasian and 42 Sri Lankan children. Of the white Caucasians, 19 ( 36%) girls and 29 ( 66%) boys, and of the Sri Lankans 7 ( 46%) girls and 16 ( 63%) boys, were obese based on % FM. The FM and BMI were closely associated in both Caucasians ( r = 0.81, P < 0.001) and Sri Lankans ( r = 0.92, P< 0.001). Percentage FM and BMI also had a lower but significant association. Obesity cut- off values recommended by IOTF failed to detect a single case of obesity in either group. However, NCHS and BMI- Z cut- offs detected cases of obesity with low sensitivity. Conclusions: BMI is a poor indicator of percentage fat and the commonly used cut- off values were not sensitive enough to detect cases of childhood obesity in this study. In order to improve the diagnosis of obesity, either BMI cut- off values should be revised to increase the sensitivity or the possibility of using other indirect methods of estimating the % FM should be explored.

Inter- and intralaboratory variation of in vitro diffusion cell measurements: An international multicenter study using quasi-standardized methods and materials

In vitro measurements of skin absorption are an increasingly important aspect of regulatory studies, product support claims, and formulation screening. However, such measurements are significantly affected by skin variability. The purpose of this study was to determine inter- and intralaboratory variation in diffusion cell measurements caused by factors other than skin. This was attained through the use of an artificial (silicone rubber) rate-limiting membrane and the provision of materials including a standard penetrant, methyl paraben (MP), and a minimally prescriptive protocol to each of the 18 participating laboratories. Standardized calculations of MP flux were determined from the data submitted by each laboratory by applying a predefined mathematical model. This was deemed necessary to eliminate any interlaboratory variation caused by different methods of flux calculations. Average fluxes of MP calculated and reported by each laboratory (60 +/- 27 mug cm(-2) h(-1), n = 25, range 27-101) were in agreement with the standardized calculations of MP flux (60 +/- 21 mug cm(-2) h(-1), range 19-120). The coefficient of variation between laboratories was approximately 35% and was manifest as a fourfold difference between the lowest and highest average flux values and a sixfold difference between the lowest and highest individual flux values. Intra-laboratory variation was lower, averaging 10% for five individuals using the same equipment within a single laboratory. Further studies should be performed to clarify the exact components responsible for nonskin-related variability in diffusion cell measurements. It is clear that further developments of in vitro methodologies for measuring skin absorption are required. (C) 2005 Wiley-Liss, Inc.

A simple implementation of a normal mixture approach to differential gene expression in multiclass microarrays

Motivation: An important problem in microarray experiments is the detection of genes that are differentially expressed in a given number of classes. We provide a straightforward and easily implemented method for estimating the posterior probability that an individual gene is null. The problem can be expressed in a two-component mixture framework, using an empirical Bayes approach. Current methods of implementing this approach either have some limitations due to the minimal assumptions made or with more specific assumptions are computationally intensive. Results: By converting to a z-score the value of the test statistic used to test the significance of each gene, we propose a simple two-component normal mixture that models adequately the distribution of this score. The usefulness of our approach is demonstrated on three real datasets.

Subtypes of Illicit Drug Users: A Latent Class Analysis of Data From an Australian Twin Sample

This article applies methods of latent class analysis (LCA) to data on lifetime illicit drug use in order to determine whether qualitatively distinct classes of illicit drug users can be identified. Self-report data on lifetime illicit drug use (cannabis, stimulants, hallucinogens, sedatives, inhalants, cocaine, opioids and solvents) collected from a sample of 6265 Australian twins (average age 30 years) were analyzed using LCA. Rates of childhood sexual and physical abuse, lifetime alcohol and tobacco dependence, symptoms of illicit drug abuse/dependence and psychiatric comorbidity were compared across classes using multinomial logistic regression. LCA identified a 5-class model: Class 1 (68.5%) had low risks of the use of all drugs except cannabis; Class 2 (17.8%) had moderate risks of the use of all drugs; Class 3 (6.6%) had high rates of cocaine, other stimulant and hallucinogen use but lower risks for the use of sedatives or opioids. Conversely, Class 4 (3.0%) had relatively low risks of cocaine, other stimulant or hallucinogen use but high rates of sedative and opioid use. Finally, Class 5 (4.2%) had uniformly high probabilities for the use of all drugs. Rates of psychiatric comorbidity were highest in the polydrug class although the sedative/opioid class had elevated rates of depression/suicidal behaviors and exposure to childhood abuse. Aggregation of population-level data may obscure important subgroup differences in patterns of illicit drug use and psychiatric comorbidity. Further exploration of a 'self-medicating' subgroup is needed.

A Research Agenda for Assessing the Potential Contribution of Genomic Medicine to Tobacco Control

This paper identifies research priorities in evaluating the ways in which "genomic medicine"-the use of genetic information to prevent and treat disease-may reduce tobacco-related harm by: (1) assisting more smokers to quit; (2) preventing non-smokers from beginning to smoke tobacco; and (3) reducing the harm caused by tobacco smoking. The method proposed to achieve the first aim is pharmacogenetics", the use of genetic information to optimise the selection of smoking-cessation programmes by screening smokers for polymorphisms that predict responses to different methods of smoking cessation. This method competes with the development of more effective forms of smoking cessation that involve vaccinating smokers against the effects of nicotine and using new pharmaceuticals (such as cannabinoid antagonists and nicotine agonists). The second and third aims are more speculative. They include: screening the population for genetic susceptibility to nicotine dependence and intervening (eg, by vaccinating children and adolescents against the effects of nicotine) to prevent smoking uptake, and screening the population for genetic susceptibility to tobacco-related diseases. A framework is described for future research on these policy options. This includes: epidemiological modelling and economic evaluation to specify the conditions under which these strategies are cost-effective; and social psychological research into the effect of providing genetic information on smokers' preparedness to quit, and the general views of the public on tobacco smoking.