Development of a rapid, multi-class method for the confirmatory analysis of anti-inflammatory drugs in bovine milk using liquid chromatography tandem mass spectrometry

A rapid liquid chromatography tandem mass spectrometry (LC-MS/MS) method has been developed and validated for the simultaneous identification, confirmation and quantitation of seven licensed anti-inflammatory drugs (AIDS) in bovine milk. The method was validated in accordance with the criteria defined in Commission Decision 2002/657/EC. Two classes of AIDS were investigated, corticosteroids and non-steroidal anti-inflammatory drugs (NSAIDs). The developed method is capable of detecting and confirming dexamethasone (DXM), betamethasone (BTM), prednisolone (FRED), tolfenamic acid (TV), 5-hydroxy flunixin (5-OH-FLU). meloxicam (MLX) and 4-methyl amino antipyrine (4-MAA) at their associated maximum residue limits (MRLs). These compounds represent all the corticosteroids and NSAIDs licensed for use in bovine animals producing milk for human consumption. These compounds have never been analysed before in the same method and also 4-methyl amino antipyrine has never been analysed with the other licensed NSAIDs. The method can be considered rapid as permits the analysis of up to 30 samples in one day. Milk samples are extracted with acetonitrile; sodium chloride is added to aid partition of the milk and acetonitrile mixture. The acetonitrile extract is then subjected to liquid-liquid purification by the addition of hexane. The purified extract is finally evaporated to dryness and reconstituted in a water/acetonitrile mixture and determination is carried out by LC-MS/MS. Decision limit (CC alpha) values and detection capability (CC beta) values have been established for each compound. (C) 2009 Elsevier B.V. All rights reserved.

An empirical analysis of the factors and measures of Enterprise Architecture Management success

Enterprise Architecture Management (EAM) is discussed in academia and industry as a vehicle to guide IT implementations, alignment, compliance assessment, or technology management. Still, a lack of knowledge prevails about how EAM can be successfully used, and how positive impact can be realized from EAM. To determine these factors, we identify EAM success factors and measures through literature reviews and exploratory interviews and propose a theoretical model that explains key factors and measures of EAM success. We test our model with data collected from a cross-sectional survey of 133 EAM practitioners. The results confirm the existence of an impact of four distinct EAM success factors, ‘EAM product quality’, ‘EAM infrastructure quality’, ‘EAM service delivery quality’, and ‘EAM organizational anchoring’, and two important EAM success measures, ‘intentions to use EAM’ and ‘Organizational and Project Benefits’ in a confirmatory analysis of the model. We found the construct ‘EAM organizational anchoring’ to be a core focal concept that mediated the effect of success factors such as ‘EAM infrastructure quality’ and ‘EAM service quality’ on the success measures. We also found that ‘EAM satisfaction’ was irrelevant to determining or measuring success. We discuss implications for theory and EAM practice.

Combining biomarker screening and mass-spectrometric analysis to detect hormone abuse in cattle

Since the introduction of the European ban on hormones in 1989, its implementation has proved to be an enormous challenge to regulatory authorities, because the great economic benefits that result from illegal misuse of growth promoters in animal production encourage their continued use. In efforts to challenge black-market trade in hormones, there have been many analytical advances. Recently, both effect-based bioanalysis for screening to target illegal misuse and improved mass-spectrometry-based confirmatory analysis have greatly increased the likelihood of detecting hormone abuse. This review outlines analytical methods currently used for detecting hormone abuse and presents advances in new approaches based on biological determinants that may complement these techniques in the future. (C) 2009 Elsevier Ltd. All rights reserved.

Analysis of pesticide residues in strawberries and soils by GC-MS/MS, LC-MS/MS and two-dimensional GC-timeof- flight MS comparing organic and integrated pest management farming

This study analysed 22 strawberry and soil samples after their collection over the course of 2 years to compare the residue profiles from organic farming with integrated pest management practices in Portugal. For sample preparation, we used the citrate-buffered version of the quick, easy, cheap, effective, rugged, and safe (QuEChERS) method. We applied three different methods for analysis: (1) 27 pesticides were targeted using LC-MS/MS; (2) 143 were targeted using low pressure GC-tandem mass spectrometry (LP-GC-MS/MS); and (3) more than 600 pesticides were screened in a targeted and untargeted approach using comprehensive, two-dimensional gas chromatography time-of-flight mass spectrometry (GC × GC-TOF-MS). Comparison was made of the analyses using the different methods for the shared samples. The results were similar, thereby providing satisfactory confirmation of both similarly positive and negative findings. No pesticides were found in the organic-farmed samples. In samples from integrated pest management practices, nine pesticides were determined and confirmed to be present, ranging from 2 μg kg−1 for fluazifop-pbutyl to 50 μg kg−1 for fenpropathrin. Concentrations of residues in strawberries were less than European maximum residue limits.

Factor analysis of the North American Spine Society outcome assessment instrument: a study based on a spine registry of patients treated with lumbar and cervical disc arthroplasty.

Background context Studies involving factor analysis (FA) of the items in the North American Spine Society (NASS) outcome assessment instrument have revealed inconsistent factor structures for the individual items. Purpose This study examined whether the factor structure of the NASS varied in relation to the severity of the back/neck problem and differed from that originally recommended by the developers of the questionnaire, by analyzing data before and after surgery in a large series of patients undergoing lumbar or cervical disc arthroplasty. Study design/setting Prospective multicenter observational case series. Patient sample Three hundred ninety-one patients with low back pain and 553 patients with neck pain completed questionnaires preoperatively and again at 3 to 6 and 12 months follow-ups (FUs), in connection with the SWISSspine disc arthroplasty registry. Outcome measures North American Spine Society outcome assessment instrument. Methods First, an exploratory FA without a priori assumptions and subsequently a confirmatory FA were performed on the 17 items of the NASS-lumbar and 19 items of the NASS-cervical collected at each assessment time point. The item-loading invariance was tested in the German version of the questionnaire for baseline and FU. Results Both NASS-lumbar and NASS-cervical factor structures differed between baseline and postoperative data sets. The confirmatory analysis and item-loading invariance showed better fit for a three-factor (3F) structure for NASS-lumbar, containing items on “disability,” “back pain,” and “radiating pain, numbness, and weakness (leg/foot)” and for a 5F structure for NASS-cervical including disability, “neck pain,” “radiating pain and numbness (arm/hand),” “weakness (arm/hand),” and “motor deficit (legs).” Conclusions The best-fitting factor structure at both baseline and FU was selected for both the lumbar- and cervical-NASS questionnaires. It differed from that proposed by the originators of the NASS instruments. Although the NASS questionnaire represents a valid outcome measure for degenerative spine diseases, it is able to distinguish among all major symptom domains (factors) in patients undergoing lumbar and cervical disc arthroplasty; overall, the item structure could be improved. Any potential revision of the NASS should consider its factorial structure; factorial invariance over time should be aimed for, to allow for more precise interpretations of treatment success.

Atitude do Profissional de Contabilidade em relação à fraude: uma abordagem apoiada em cenários

Casos de fraudes têm ocorrido, freqüentemente, no mercado mundial. Diversos são os profissionais envolvidos nestes casos, inclusive os da classe contábil. Os escândalos contábeis, especialmente os mais famosos, como os incididos nas empresas Enron e WordCom, acenderam para uma maior preocupação em relação à conduta ética dos profissionais de contabilidade. Como conseqüência, há uma maior exigência quanto à transparência e a fidedignidade das informações prestadas por estes profissionais. Esta preocupação visa, primordialmente, manter a confiança de empresas, investidores, fornecedores e da sociedade, dentre outras, na responsabilidade ética do contador, denegrida pelo envolvimento nas fraudes detectadas. Desta forma, o presente estudo teve como objetivo verificar a conduta ética dos contadores e técnicos em contabilidade quando, no exercício de suas atividades profissionais, se depararem com questões relacionadas a fraudes. Para tal, são considerados alguns fatores que podem tanto vir a influenciar o processo decisório ético de um indivíduo, demonstrados através do Modelo de tomada de decisão, desenvolvido por Alves, quanto motivar um indivíduo a cometer um ato fraudulento, evidenciados através do Modelo denominado Triângulo da Fraude, desenvolvido por Cressey. Buscando responder a questão norteadora desta pesquisa, executou-se a análise descritiva e estatística dos dados, com a utilização de técnicas não-paramétricas. Para a análise descritiva dos dados foram elaboradas as tabelas de freqüências e calculadas as medidas de posição e dispersão, através do cálculo dos valores da média, moda, mediana e desvio padrão, quando aplicáveis. Em relação à análise estatística dos dados, foram utilizados os testes não-paramétricos de Spearman e a Regressão logística Multivariada. Os resultados demonstraram que a maioria dos profissionais de contabilidade, da amostra pesquisada, reconhece a questão moral inserida nos cenários, discorda dos atos dos agentes de cada cenário e, ainda, classifica esses atos como graves ou muito graves. Entretanto, verificou-se que esses profissionais de contabilidade tendem a ter um posicionamento mais voltado para a teoria teleológica, uma vez que a intenção de agir é influenciada por alguns fatores, como a oportunidade, a racionalização e, principalmente, a pressão. Alguns fatores individuais também apresentaram influência sob o posicionamento ético dos profissionais entrevistados nesta pesquisa.

Imagem de um Conselho Profissional: um estudo utilizando equações estruturais

O estudo e medição da imagem, especialmente de um Conselho Profissional são essenciais para auxiliar os gestores destas instituições a tomarem decisões. Como não há uma escala válida e confiável que permita a medição da imagem corporativa de um Conselho Profissional, o presente trabalho busca confirmar, através do método de Modelagem de Equações Estruturais MEE, o modelo hipotético proposto por Peres (2004) e Carvalho (2009) que tomam por base o estudo de Folland, Peacock e Pelfrey (1991) que conclui que a imagem corporativa é composta por dois fatores e a percepção desta imagem impacta na avaliação de seu desempenho. Os resultados obtidos na pesquisa demonstram, com grande segurança estatística, que o modelo proposto é consistente, tem ótimo ajuste, e pode ser aplicado em futuras amostras semelhantes.

中学生焦虑与其影响因素的关系模型

Anxiety, which is one of common factors influencing mental health of secondary school students, whose occurrence, development, diagnosis, treatment and intervention have been studied in neurophysiology, behavior and cognition process. in the present study, the relationship between anxieties including trait anxiety and test anxiety and their influencing factors in secondary school students had been explored by exploratory analysis, confirmatory analysis and structure equation modeling. The following conclusions were drawn: (1) There were grade-characteristics in development of trait anxiety in secondary school students. Trait anxiety degree increased with grade. On the other hand, test anxiety showed no grade-characteristics. However, gender differences showed test anxiety in female was higher than in male. In a test, test anxiety increased with test coming and reached the maximum height before test and dropped to the minimum that night after test. (2) Influencing factor inventory on trait anxiety whose reliability and validity were good, has been developed, which was composed of 44 items including 8 factors were study pressure, bad influence of society, self-abased, dysadaptation, introversion, bad body, interrelationship, bad parents raising style etc, of which study pressure was the first reason for trait anxiety. (3) Influencing factor inventory on test anxiety, whose reliability and validity were good, has been developed, which was composed of 30 items including 5 factors. 5 factors were worry about bad school achievement, bad objective environment, intervention of emergency, self-abased, worry about consequence etc, of which study pressure played the most important role on test anxiety. (4) Personality and school pressure affected trait anxiety, while personality and school pressure were affected by environment. Furthermore, test anxiety was affected by worry, personality and, while worry and personality was influenced by spot circumstances. At last, both trait anxiety and test anxiety related with bad personality and bad school achievement.

Comparison of porcine urine and bile as matrices to screen for the residues of two sulfonamides using a semi-automated enzyme immunoassay.

Porcine urine enzyme immunoassays for sulfamethazine and sulfadiazine have previously been employed as screening tests to predict the concentrations of the drugs in the corresponding tissues (kidneys), If a urine was found positive (> 800 ng ml(-1)) the corresponding kidney was then analysed by an enzyme immunoassay and, if found positive, a confirmatory analysis by HPLC was performed. Urine was chosen as the screening matrix since sulfonamides are mainly eliminated through this body fluid, However, after obtaining a number of false positive predictions, an investigation was carried out to assess the possibility of using an alternative body fluid which would act as a superior indicator of the presence of sulfonamides in porcine kidney, An initial study indicated that serum, plasma and bile could all be used as screening matrices. From these, bile was chosen as the preferred sample matrix and an extensive study followed to compare the efficiencies of sulfonamide positive bile and urine at predicting sulphonamide positive kidneys, Bile was found to be 17 times more efficient than urine at predicting a sulfamethazine positive kidney and 11 times more efficient at predicting a sulfadiazine positive kidney, With this enhanced performance of the initial screening test, the need for the costly and time consuming kidney enzyme immunoassay, prior to HPLC analysis, was eliminated

Development of a solid-phase extraction coupling chemiluminescent enzyme immunoassay for determination of organophosphorus pesticides in environmental water samples

Solid-phase extraction (SPE) and direct competitive chemiluminescence enzyme immunoassay (dcCL-EIA) were combined for the detection of organophosphorus pesticides (OPs) in environmental water samples. dcCL-EIA based on horseradish peroxidase labeled with a broad-specificity monoclonal antibody against OPs was developed, and the effects of several physicochemical parameters on dcCL-EIA performance were studied. SPE was used for the pretreatment of water samples to remove interfering substances and to concentrate the OP analytes. The coupling of SPE and dcCL-EIA can detect seven OPs (parathion, coumaphos, phoxim, quinalphos, triazophos, dichlofenthion, and azinphos-ethyl) with the limit of quantitation below 0.1 ng/mL. The recoveries of OPs from spiked water samples ranged from 62.5% to 131.7% by SPE-dcCL-EIA and 69.5% to 112.3% by SPE-HPLC-MS/MS. The screening of OP residues in real-world environmental water samples by the developed SPE-dcCL-EIA and their confirmatory analysis using SPE-HPLC-MS/MS demonstrated that the assay is ideally suited as a monitoring method for OP residues prior to chromatographic analysis.

An evaluation of the capability of a biolayer interferometry biosensor to detect low-molecular-weight food contaminants

The safety of our food is an essential requirement of society. One well-recognised threat is that of chemical contamination of our food, where low-molecular-weight compounds such as biotoxins, drug residues and pesticides are present. Low-cost, rapid screening procedures are sought to discriminate the suspect samples from the population, thus selecting only these to be forwarded for confirmatory analysis. Many biosensor assays have been developed as screening tools in food contaminant analysis, but these tend to be electrochemical, fluorescence or surface plasmon resonance based. An alternative approach is the use of biolayer interferometry, which has become established in drug discovery and life science studies but is only now emerging as a potential tool in the analysis of food contaminants. A biolayer interferometry biosensor was assessed using domoic acid as a model compound. Instrument repeatability was tested by simultaneously producing six calibration curves showing replicate repeatability (n = 2) ranging from 0.1 to 6.5 % CV with individual concentration measurements (n = 12) ranging from 4.3 to 9.3 % CV, giving a calibration curve midpoint of 7.5 ng/ml (2.3 % CV (n = 6)). Reproducibility was assessed by producing three calibration curves on different days, giving a midpoint of 7.5 ng/ml (3.4 %CV (n = 3)). It was further shown, using assay development techniques, that the calibration curve midpoint could be adjusted from 10.4 to 1.9 ng/ml by varying assay parameters before the simultaneous construction of three calibration curves in matrix and buffer. Sensitivity of the assay compared favourably with previously published biosensor data for domoic acid. © 2013 Springer-Verlag Berlin Heidelberg.

Validation of an ultra high performance liquid chromatography-tandem mass spectrometry method for detection and quantitation of 19 endocrine disruptors in milk

An endocrine disruptor (ED) is an exogenous compound that interferes with the body's endocrine system. Exposure to EDs may result in adverse health effects such as infertility and cancer. EDs are composed of a vast group of chemicals including compounds of natural origin such as phytoestrogens or mycotoxins and a wide range of man-made chemicals such as pesticides. Synthetic compounds may find their way into the food chain where a number of them can biomagnify. Additionally, processing activities and food contact materials may add further to the already existing pool of food contaminants. Thus, our diet is considered to be one of the main exposure routes to EDs. Some precautionary legislation has already been introduced to control production and/or application of some persistent organic pollutants with ED characteristics. However, newly emerging EDs with bioaccumulative properties have recently been reported to appear at lower tiers of the food chain but have not been monitored at the grander scale. Milk and dairy products are a major component of our diet, thus it is important to monitor them for EDs. However, most methods developed to date are devoted to one group of compounds at a time. The UHPLC-MS/MS method described here has been validated according to EC decision 2002/657/EC and allows simultaneous extraction, detection, quantitation and confirmation of 19 EDs in milk. The method calibration range is between 0.50 and 20.0 μg kg with coefficients of determination above 0.99 for all analytes. Precision varied from 4.7% to 23.4% in repeatability and reproducibility studies. Established CCα and CCβ values (0.11-0.67 μg kg) facilitate fast, reliable, quantitative and confirmatory analysis of sub μg kg levels of a range of EDs in milk.

Conditionally unbiased estimation in phase II/III clinical trials with early stopping for futility

Seamless phase II/III clinical trials combine traditional phases II and III into a single trial that is conducted in two stages, with stage 1 used to answer phase II objectives such as treatment selection and stage 2 used for the confirmatory analysis, which is a phase III objective. Although seamless phase II/III clinical trials are efficient because the confirmatory analysis includes phase II data from stage 1, inference can pose statistical challenges. In this paper, we consider point estimation following seamless phase II/III clinical trials in which stage 1 is used to select the most effective experimental treatment and to decide if, compared with a control, the trial should stop at stage 1 for futility. If the trial is not stopped, then the phase III confirmatory part of the trial involves evaluation of the selected most effective experimental treatment and the control. We have developed two new estimators for the treatment difference between these two treatments with the aim of reducing bias conditional on the treatment selection made and on the fact that the trial continues to stage 2. We have demonstrated the properties of these estimators using simulations

A comparison of methods for constructing confidence intervals after phase II/III clinical trials

Recently, in order to accelerate drug development, trials that use adaptive seamless designs such as phase II/III clinical trials have been proposed. Phase II/III clinical trials combine traditional phases II and III into a single trial that is conducted in two stages. Using stage 1 data, an interim analysis is performed to answer phase II objectives and after collection of stage 2 data, a final confirmatory analysis is performed to answer phase III objectives. In this paper we consider phase II/III clinical trials in which, at stage 1, several experimental treatments are compared to a control and the apparently most effective experimental treatment is selected to continue to stage 2. Although these trials are attractive because the confirmatory analysis includes phase II data from stage 1, the inference methods used for trials that compare a single experimental treatment to a control and do not have an interim analysis are no longer appropriate. Several methods for analysing phase II/III clinical trials have been developed. These methods are recent and so there is little literature on extensive comparisons of their characteristics. In this paper we review and compare the various methods available for constructing confidence intervals after phase II/III clinical trials.

Estimation after subpopulation selection in adaptive seamless trials

During the development of new therapies, it is not uncommon to test whether a new treatment works better than the existing treatment for all patients who suffer from a condition (full population) or for a subset of the full population (subpopulation). One approach that may be used for this objective is to have two separate trials, where in the first trial, data are collected to determine if the new treatment benefits the full population or the subpopulation. The second trial is a confirmatory trial to test the new treatment in the population selected in the first trial. In this paper, we consider the more efficient two-stage adaptive seamless designs (ASDs), where in stage 1, data are collected to select the population to test in stage 2. In stage 2, additional data are collected to perform confirmatory analysis for the selected population. Unlike the approach that uses two separate trials, for ASDs, stage 1 data are also used in the confirmatory analysis. Although ASDs are efficient, using stage 1 data both for selection and confirmatory analysis introduces selection bias and consequently statistical challenges in making inference. We will focus on point estimation for such trials. In this paper, we describe the extent of bias for estimators that ignore multiple hypotheses and selecting the population that is most likely to give positive trial results based on observed stage 1 data. We then derive conditionally unbiased estimators and examine their mean squared errors for different scenarios.