A QuEChERS/LC–MS method for the analysis of ractopamine in pork

The development of rapid, high sample throughput methods is constantly demanded by food analytical laboratories. Several current methods for the analysis of ractopamine deal with time-consuming procedures or complicated sample pretreatment steps. Thus, this study aimed to validate and to optimize a simple method for the extraction of ractopamine from pork using a “Quick, Easy, Cheap, Effective, Rugged and Safe” (QuEChERS) approach. Extraction was carried out with an acetonitrile acidic solution and then sodium chloride was used to promote salting out, increasing the solubility of ractopamine. Anhydrous magnesium sulfate was added to remove water and the clean-up was carried out with C₁₈ and primary/secondary amine. Ractopamine was then determined by liquid chromatography–tandem mass spectrometry (LC–MS/MS) within 4.5 min only, before a single extraction procedure. Full validation was performed in accordance to Commission Decision 2002/657/EC. Additionally, matrix effect, limit of detection (LoD), limit of quantitation (LoQ) and measurement uncertainty were also determined. Linear range was among 2.5–20 μg/kg. LoD and LoQ were set to 1.5 μg/kg and 2.5 μg/kg, respectively, being below the maximum residue limit established by most countries. A high throughput screening and confirmatory tool, combined with a cheap and fast sample pretreatment method was developed. The method proved to be reproducible and sensitive and its applicability was checked on several samples of pork and pork products, with results that ranged from below LoQ to 6.54 μg/kg.     

An efficient,rapid and microwave-accelerated dispersive liquid–liquid microextraction method for extraction and pre-concentration of some organophosphorus pesticide residues from aqueous samples

In this paper, microwave-accelerated dispersive liquid–liquid microextraction has been developed for the extraction/preconcentration of some organophosphorus pesticides from aqueous samples prior to their analysis by gas chromatography–flame ionization detection. In this method, temperature of a high volume of aqueous sample is elevated by a microwave oven and then a mixture of extraction and disperser solvents is rapidly injected into the aqueous phase. After cooling to room temperature, the phase separation is accelerated by centrifuging. The main experimental factors affecting performance of the method including type and volume of the extraction and disperser solvents, temperature, pH, and salt addition were investigated and optimized. Under the optimum extraction conditions, the method resulted in low limits of detection and quantification within the ranges of 0.65–1.3 and 2.2–4.5 μg L⁻¹, respectively. Relative standard deviations were in the range of 2–7% (C = 40 or 100 μg L⁻¹) for intra-day (n = 6) and inter-day (n = 4) precisions. Finally, the proposed method was successfully applied to analysis of the target analytes in surface water and well water and fruit juice samples; diazinon was determined at μg L⁻¹ level in apple juice.     

Exploring gene–gene interaction in family-based data with an unsupervised machine learning method: EPISFA

Gene–gene interaction (G × G) is thought to fill the gap between the estimated heritability of complex diseases and the limited genetic proportion explained by identified single-nucleotide polymorphisms. The current tools for exploring G × G were often developed for case-control designs with less considerations for their applications in families. Family-based studies are robust against bias led from population stratification in genetic studies and helpful in understanding G × G. We proposed a new algorithm epistasis sparse factor analysis (EPISFA) and epistasis sparse factor analysis for linkage disequilibrium (EPISFA-LD) based on unsupervised machine learning to screen G × G. Extensive simulations were performed to compare EPISFA/EPISFA-LD with a classical family-based algorithm FAM-MDR (family-based multifactor dimensionality reduction). The results showed that EPISFA/EPISFA-LD is a tool of both high power and computational efficiency that could be applied in family designs and is applicable within high-dimensionality datasets. Finally, we applied EPISFA/EPISFA-LD to a real dataset drawn from the Fangshan/family-based Ischemic Stroke Study in China. Five pairs of G × G were discovered by EPISFA/EPISFA-LD, including three pairs verified by other algorithms (FAM-MDR and logistic), and an additional two pairs uniquely identified by EPISFA/EPISFA-LD only. The results from EPISFA might offer new insights for understanding the genetic etiology of complex diseases. EPISFA/EPISFA-LD was implemented in R. All relevant source code as well as simulated data could be freely downloaded from https://github.com/doublexism/episfa .     

An analysis of mother–child interaction patterns in prison

In April 2002, there were three hundred and eighty‐six children living in prison with their mothers in South Africa, four of which were inmates of the Pretoria Female Prison. The interaction patterns between these four mothers and their children was investigated by means of individual interviews, observation, field notes and the Marschak Interaction Method. It was found that the mother‐child interaction patterns in prison of the participants in this study are typified by four themes: (1) the experience of the restrictiveness of the prison environment; (2) the in‐exclusivity of the mother‐child attachment process; (3) the mothers' inattention to situations that their children might experience as stressful; and (4) the absence of imaginative play.     

An effective method for videorecording the nasal–dorsal part of a rhinoplasty – a multiple case study

Rhinoplasty is a difficult procedure to record for several reasons which include the narrow, dark and deep surgical field cluttered with many instruments, and the heads and hands of the surgical team often blocking the view. This study discusses 13 rhinoplasty cases that were recorded using the authors’ technique. A three-minute, unedited segment was extracted from the mid-portion of each surgical case, and that footage was evaluated by three specialist examiners. Results indicate that the authors’ technique can offer a effective solution in the video recording of the nasal–dorsal part of a rhinoplasty.     

Bayesian bivariate subgroup analysis for risk–benefit evaluation

Subgroup analysis is a frequently used tool for evaluating heterogeneity of treatment effect and heterogeneity in treatment harm across observed baseline patient characteristics. While treatment efficacy and adverse event measures are often reported separately for each subgroup, analyzing their within-subgroup joint distribution is critical for better informed patient decision-making. In this paper, we describe Bayesian models for performing a subgroup analysis to compare the joint occurrence of a primary endpoint and an adverse event between two treatment arms. Our approach emphasizes estimation of heterogeneity in this joint distribution across subgroups, and our approach directly accommodates subgroups with small numbers of observed primary and adverse event combinations. In addition, we describe several ways in which our models may be used to generate interpretable summary measures of benefit-risk tradeoffs for each subgroup. The methods described here are illustrated throughout using a large cardiovascular trial (\(N = 9361\)) investigating the efficacy of an intervention for reducing systolic blood pressure to a lower-than-usual target.     

Efficient gene–environment interaction tests for large biobank-scale sequencing studies

Complex human diseases are affected by genetic and environmental risk factors and their interactions. Gene–environment interaction (GEI) tests for aggregate genetic variant sets have been developed in recent years. However, existing statistical methods become rate limiting for large biobank-scale sequencing studies with correlated samples. We propose efficient Mixed-model Association tests for GEne–Environment interactions (MAGEE), for testing GEI between an aggregate variant set and environmental exposures on quantitative and binary traits in large-scale sequencing studies with related individuals. Joint tests for the aggregate genetic main effects and GEI effects are also developed. A null generalized linear mixed model adjusting for covariates but without any genetic effects is fit only once in a whole genome GEI analysis, thereby vastly reducing the overall computational burden. Score tests for variant sets are performed as a combination of genetic burden and variance component tests by accounting for the genetic main effects using matrix projections. The computational complexity is dramatically reduced in a whole genome GEI analysis, which makes MAGEE scalable to hundreds of thousands of individuals. We applied MAGEE to the exome sequencing data of 41,144 related individuals from the UK Biobank, and the analysis of 18,970 protein coding genes finished within 10.4 CPU hours.     

Exploring data from genetic association studies using bayesian variable selection and the dirichlet process: application to searching for gene × gene patterns

We construct data exploration tools for recognizing important covariate patterns associated with a phenotype, with particular focus on searching for association with gene-gene patterns. To this end, we propose a new variable selection procedure that employs latent selection weights and compare it to an alternative formulation. The selection procedures are implemented in tandem with a Dirichlet process mixture model for the flexible clustering of genetic and epidemiological profiles. We illustrate our approach with the aid of simulated data and the analysis of a real data set from a genome-wide association study.     

Comparisons of power of statistical methods for gene–environment interaction analyses

Any genome-wide analysis is hampered by reduced statistical power due to multiple comparisons. This is particularly true for interaction analyses, which have lower statistical power than analyses of associations. To assess gene–environment interactions in population settings we have recently proposed a statistical method based on a modified two-step approach, where first genetic loci are selected by their associations with disease and environment, respectively, and subsequently tested for interactions. We have simulated various data sets resembling real world scenarios and compared single-step and two-step approaches with respect to true positive rate (TPR) in 486 scenarios and (study-wide) false positive rate (FPR) in 252 scenarios. Our simulations confirmed that in all two-step methods the two steps are not correlated. In terms of TPR, two-step approaches combining information on gene-disease association and gene–environment association in the first step were superior to all other methods, while preserving a low FPR in over 250 million simulations under the null hypothesis. Our weighted modification yielded the highest power across various degrees of gene–environment association in the controls. An optimal threshold for step 1 depended on the interacting allele frequency and the disease prevalence. In all scenarios, the least powerful method was to proceed directly to an unbiased full interaction model, applying conventional genome-wide significance thresholds. This simulation study confirms the practical advantage of two-step approaches to interaction testing over more conventional one-step designs, at least in the context of dichotomous disease outcomes and other parameters that might apply in real-world settings.     

Can people catastrophize barriers? An exploratory analysis of the association between pain catastrophizing and perceptions of environmental factors

Background

Measurement of the environment is taking on increased importance for understanding variability in participation. Most measures of the environment use subjective ratings, yet little is known about how people appraise the environment.

Association between lipoprotein lipase (LPL) gene and blood lipids: A common variant for a common trait?

S447X, a serine substitution by a stop codon on base 99 of exon 9 of the lipoprotein lipase (LPL) gene, has beneficial effects on blood lipids. Other LPL alleles are associated with lipid levels, but whether one of these variants predominates remains elusive. We performed a systematic survey to identify single-nucleotide polymorphisms (SNPs) in all 10 LPL exons and flanking regions by resequencing the gene in 95 subjects. Of 24 variants, 14 were common (> or = 3%). We assayed the common SNPs in 186 cases with atherogenic lipid profiles (low HDL, high LDL) and 185 nonatherogenic controls (high HDL, low LDL). Only S447X and exons 6 (base +73) and 10 (base -11) were individually associated with case-control status (P<0.05, adjusted for major nongenetic covariates with known lipid effects). There were no significant SNP x gender interactions. In adjusted multi-SNP and haplotypic analyses, S447X was interpretable as the sole predictor, with a 2-3-fold reduction in the odds of being atherogenic vs. nonatherogenic (adjusted OR, 0.39; 95% CI, 0.21-0.73). S447X and base -11 of exon 10 were statistically interchangeable because they are strongly associated (r=0.92, P<0.0001), but we posit that the LPL association with lipid profile is more likely attributable to the functional S447X rather than the nonfunctional exon 10 SNP. It appears that the S447X variant of LPL may be another rare example (like APOE4, factor V-Leiden, and PPAR gamma Pro12Ala) of a common variant predisposing to a common disorder.     

A powerful and data-adaptive test for rare-variant–based gene-environment interaction analysis

As whole-exome/genome sequencing data become increasingly available in genetic epidemiology research consortia, there is emerging interest in testing the interactions between rare genetic variants and environmental exposures that modify the risk of complex diseases. However, testing rare-variant–based gene-by-environment interactions (GxE) is more challenging than testing the genetic main effects due to the difficulty in correctly estimating the latter under the null hypothesis of no GxE effects and the presence of neutral variants. In response, we have developed a family of powerful and data-adaptive GxE tests, called “aGE” tests, in the framework of the adaptive powered score test, originally proposed for testing the genetic main effects. Using extensive simulations, we show that aGE tests can control the type I error rate in the presence of a large number of neutral variants or a nonlinear environmental main effect, and the power is more resilient to the inclusion of neutral variants than that of existing methods. We demonstrate the performance of the proposed aGE tests using Pancreatic Cancer Case-Control Consortium Exome Chip data. An R package “aGE” is available at http://github.com/ytzhong/projects/ .     

Did the Medicaid expansions for children displace private insurance? An analysis using the SIPP

Using data from the 1990 panel of the Survey of Income and Program Participation (SIPP), we address the question: Did the Medicaid expansions for children cause declines in private coverage? We use a multivariate approach that attributes a displacement effect to declines in private coverage for children targeted by the Medicaid expansions exceeding declines for a comparison group of older low-income children. We find that 23% of the movement from private coverage to Medicaid due to the expansions was attributable to displacement. There is no evidence of displacement among those starting uninsured, leading to an overall displacement effect of 4%.     

Death denial: obstacle or instrument for palliative care? An analysis of clinical literature

As a society and as individuals, we have come to recognize ourselves as 'death-denying', a self-characterisation particularly prominent in palliative care discourse and practice. As part of a larger project examining death attitudes in the palliative care setting, a Medline search (1971 to 2001) was performed combining the text words 'deny' and 'denial' with the subject headings 'terminal care', 'palliative care' and 'hospice care'. The 30 articles were analysed using a constant comparison technique and emerging themes regarding the meaning and usage of the words deny and denial were identified. This paper examines the theme of denial as an obstacle to palliative care. In the articles, denial was described as an impediment to open discussion of dying, dying at home, stopping 'futile' treatments, advance care planning and control of symptoms. I suggest that these components of care together constitute what has come to be perceived as a correct 'way to die'. Indeed, the very conceptualisation of denial as an obstacle to these components of care has been integral to building and sustaining the 'way to die' itself. The personal struggle with mortality has become an important instrument in the public problem of managing the dying process.     

A rapid and sensitive method for gas chromatographic analysis of the selective piscicide, “Squaxon”

Squaxon (1,1'methylenedi-2 napthol; bis (2 hydroxy-1-napthyl) methane) was discovered by MacPhee and Ruelle (1968, 1969) to exhibit piscicidal properties that are highly species specific. The chemical is lethal to the Northern (Ptychocheilus oregonensis) and the Umpqua (P. umpquae) squawfish, freshwater cyprinids common to the Pacific Northwest, at water treatment concentrations of less than 100 parts per billion (ppb). Other species of fish, including the more desirable salmonids with which the squawfish competes ecologically, are unaffected until this dosage has been increased severalfold. Because squawfish are widely regarded as undesirable for food or sporting purposes, and because competition from squawfish has severly depleted salmonid populations in some areas (Thompson, 1959; Jeppson and Platts, 1959) the potential use of squaxon for fisheries improvement is quite obvious. Squaxon is currently being tested for this purpose on an experimental basis in selected areas in Idaho, Oregon and Washington, pending federal clearance for more widespread application.Commercially formulated squaxon currently being field tested is dispersed as an ethanolic solution of the monosodium salt. The treatment solution consists of 39.5 per cent (by weight) 1,1 methylene-di-2 napthol dissolved in 60 per cent denatured ethyl alcohol. Traces of sodium hydroxide are also present in the commercial solution (Keating, 1972). We report here an analytical method by which petroleum ether-extracted, brominated squaxon can be quickly and easily detected in water and fish tissue by electron capture gas chromatography.This research was supported under Contract No. 68-02-0552 by the Pesticide Community Studies Division, Pesticides Office Environmental Protection Agency, through the Idaho Department of Health and Welfare.